From e88b022cd475d09d2a610b0575fd6a1e8f56f080 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 25 Feb 2022 12:07:09 +0100 Subject: [PATCH 001/592] Version bump 2022.2 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 54cecbec2..e7d2dbf1b 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.1' +__version__ = '2022.2' if __version__ == 'develop': From f9d10a7fadea7d6bfb7564e8804993bed51fa1bd Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 26 Feb 2022 08:35:50 +0100 Subject: [PATCH 002/592] Version bump 2022.2.1 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index e7d2dbf1b..90f5dab78 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.2' +__version__ = '2022.2.1' if __version__ == 'develop': From e90e3cead063535e32476c8ef91d5fe1ffb91307 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 9 Mar 2022 17:35:41 +0100 Subject: [PATCH 003/592] Map usdt fiat to correct coingecko fiat --- freqtrade/rpc/fiat_convert.py | 1 + 1 file changed, 1 insertion(+) diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py index 82a6a4778..70f3647b6 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -23,6 +23,7 @@ coingecko_mapping = { 'eth': 'ethereum', 'bnb': 'binancecoin', 'sol': 'solana', + 'usdt': 'tether', } From 4d8d30ea39b4fe8d5e5953d87efc5d5f93404cab Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 21 Mar 2022 06:34:33 +0100 Subject: [PATCH 004/592] Version bump to 2022.2.2 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 90f5dab78..f047d98b4 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.2.1' +__version__ = '2022.2.2' if __version__ == 'develop': From fe6c62e144fb525f37b234ab125940c86cc8500a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 27 Mar 2022 15:09:16 +0200 Subject: [PATCH 005/592] Version bump 2022.3 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index f6a9caa0e..349c1def1 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.2.2' +__version__ = '2022.3' if 'dev' in __version__: try: From 7615c4e904759b08960fb49abc9d5b287c046a7a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 1 May 2022 11:19:32 +0200 Subject: [PATCH 006/592] Version bump 2022.4 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 349c1def1..42ab285d7 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.3' +__version__ = '2022.4' if 'dev' in __version__: try: From e7f5252074c2cd0d4d89875143701a11e3f8aaed Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 1 May 2022 16:49:11 +0200 Subject: [PATCH 007/592] Version bump 2022.4.1 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 42ab285d7..60ae39670 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.4' +__version__ = '2022.4.1' if 'dev' in __version__: try: From 2c750fdb09379cd4bde489b97479346af1801def Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 3 May 2022 19:42:17 +0200 Subject: [PATCH 008/592] Reduce no stake amount verbosity closes #6768 --- freqtrade/freqtradebot.py | 1 - 1 file changed, 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index b6f0daeed..c20c14861 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -599,7 +599,6 @@ class FreqtradeBot(LoggingMixin): pair, price, stake_amount, trade_side, enter_tag, trade) if not stake_amount: - logger.info(f"No stake amount to enter a trade for {pair}.") return False if pos_adjust: From 5b76ae452f5aa2599d0e9ab53348f25155319780 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 3 May 2022 18:03:45 +0200 Subject: [PATCH 009/592] Fix fee handling for futures trades --- freqtrade/exchange/exchange.py | 7 +++++-- tests/exchange/test_exchange.py | 24 ++++++++++++++++++------ 2 files changed, 23 insertions(+), 8 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 82dcacb51..b300156b5 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1613,7 +1613,9 @@ class Exchange: order['fee']['cost'] / safe_value_fallback2(order, order, 'filled', 'amount'), 8) elif fee_curr in self.get_pair_quote_currency(order['symbol']): # Quote currency - divide by cost - return round(order['fee']['cost'] / order['cost'], 8) if order['cost'] else None + return round(self._contracts_to_amount( + order['symbol'], order['fee']['cost']) / order['cost'], + 8) if order['cost'] else None else: # If Fee currency is a different currency if not order['cost']: @@ -1628,7 +1630,8 @@ class Exchange: fee_to_quote_rate = self._config['exchange'].get('unknown_fee_rate', None) if not fee_to_quote_rate: return None - return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8) + return round((self._contracts_to_amount( + order['symbol'], order['fee']['cost']) * fee_to_quote_rate) / order['cost'], 8) def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]: """ diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 689ffa4ce..9faf404cd 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4151,7 +4151,10 @@ def test__order_contracts_to_amount( 'cost': 60.0, 'filled': None, 'remaining': 30.0, - 'fee': 0.06, + 'fee': { + 'currency': 'USDT', + 'cost': 0.06, + }, 'fees': [{ 'currency': 'USDT', 'cost': 0.06, @@ -4178,7 +4181,10 @@ def test__order_contracts_to_amount( 'cost': 80.0, 'filled': None, 'remaining': 40.0, - 'fee': 0.08, + 'fee': { + 'currency': 'USDT', + 'cost': 0.08, + }, 'fees': [{ 'currency': 'USDT', 'cost': 0.08, @@ -4212,12 +4218,18 @@ def test__order_contracts_to_amount( 'info': {}, }, ] + order1_bef = orders[0] + order2_bef = orders[1] + order1 = exchange._order_contracts_to_amount(deepcopy(order1_bef)) + order2 = exchange._order_contracts_to_amount(deepcopy(order2_bef)) + assert order1['amount'] == order1_bef['amount'] * contract_size + assert order1['cost'] == order1_bef['cost'] * contract_size - order1 = exchange._order_contracts_to_amount(orders[0]) - order2 = exchange._order_contracts_to_amount(orders[1]) + assert order2['amount'] == order2_bef['amount'] * contract_size + assert order2['cost'] == order2_bef['cost'] * contract_size + + # Don't fail exchange._order_contracts_to_amount(orders[2]) - assert order1['amount'] == 30.0 * contract_size - assert order2['amount'] == 40.0 * contract_size @pytest.mark.parametrize('pair,contract_size,trading_mode', [ From 851c5dad309345516da2fd485b7e45d68eb79acb Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 3 May 2022 20:37:29 +0200 Subject: [PATCH 010/592] Version bump 2022.4.2 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 60ae39670..e7f2f9d6f 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.4.1' +__version__ = '2022.4.2' if 'dev' in __version__: try: From fab197edf284ddb843d96fb238bde6510d6377b6 Mon Sep 17 00:00:00 2001 From: DJCrashdummy Date: Tue, 10 May 2022 10:33:04 +0000 Subject: [PATCH 011/592] corrected minor "typo" in formatting --- docs/includes/pairlists.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md index cec5ceb19..5b5e285fe 100644 --- a/docs/includes/pairlists.md +++ b/docs/includes/pairlists.md @@ -44,7 +44,7 @@ It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklis ```json "pairlists": [ {"method": "StaticPairList"} - ], +], ``` By default, only currently enabled pairs are allowed. From a1d54f5ae0b2e7e2a9a303f64ef88b905512cfb9 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 28 May 2022 09:49:58 +0200 Subject: [PATCH 012/592] Version bump 2022.5 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index e7f2f9d6f..29506905b 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.4.2' +__version__ = '2022.5' if 'dev' in __version__: try: From c57db0a33063049b60fd009b31bd6d9798dd0fb2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 1 Jun 2022 06:34:28 +0200 Subject: [PATCH 013/592] Version bump 2022.5.1 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 29506905b..4a7da02b0 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.5' +__version__ = '2022.5.1' if 'dev' in __version__: try: From c1d407851825c4565996860843e669f3b7184353 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 3 Jul 2022 15:04:38 +0200 Subject: [PATCH 014/592] Version bump to 2022.6 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 4a7da02b0..253e7d7ce 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.5.1' +__version__ = '2022.6' if 'dev' in __version__: try: From 28b4773083c705c77d24f649a0c51ab42e99e780 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 30 Jul 2022 09:21:29 +0200 Subject: [PATCH 015/592] Version bump 2022.7 --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 253e7d7ce..21054a723 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.6' +__version__ = '2022.7' if 'dev' in __version__: try: From 8bf056ca3916cd4365cdd45966e3f6897b48a2b7 Mon Sep 17 00:00:00 2001 From: OGSK <53548542+Jetsukda@users.noreply.github.com> Date: Fri, 5 Aug 2022 00:28:28 +0700 Subject: [PATCH 016/592] Edit Typo Custom-stake-amount Edit Custom-stake-amount to `custom_stake_amount` --- docs/strategy_migration.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md index 471ffa601..042c2494f 100644 --- a/docs/strategy_migration.md +++ b/docs/strategy_migration.md @@ -192,7 +192,7 @@ class AwesomeStrategy(IStrategy): return False ``` -### Custom-stake-amount +### `custom_stake_amount` New string argument `side` - which can be either `"long"` or `"short"`. From c3d06257bee4ae71236103cc02ff4f4b9d9b755e Mon Sep 17 00:00:00 2001 From: OGSK <53548542+Jetsukda@users.noreply.github.com> Date: Fri, 5 Aug 2022 09:36:26 +0700 Subject: [PATCH 017/592] Edit index of `custom_stake_amount` --- docs/strategy_migration.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md index 042c2494f..064e7a59d 100644 --- a/docs/strategy_migration.md +++ b/docs/strategy_migration.md @@ -18,7 +18,7 @@ Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `fo * [`check_buy_timeout()` -> `check_entry_timeout()`](#custom_entry_timeout) * [`check_sell_timeout()` -> `check_exit_timeout()`](#custom_entry_timeout) * New `side` argument to callbacks without trade object - * [`custom_stake_amount`](#custom-stake-amount) + * [`custom_stake_amount`](#custom_stake_amount) * [`confirm_trade_entry`](#confirm_trade_entry) * [`custom_entry_price`](#custom_entry_price) * [Changed argument name in `confirm_trade_exit`](#confirm_trade_exit) From 0c34104e45f4fbeae66036452ade47fff13ff058 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 17 Aug 2022 15:18:44 +0200 Subject: [PATCH 018/592] extract download-data from freqai to prepare for future async changes --- freqtrade/freqai/data_kitchen.py | 102 ++++++++++++++++++++------- freqtrade/freqai/freqai_interface.py | 12 ++-- freqtrade/strategy/interface.py | 13 +++- 3 files changed, 94 insertions(+), 33 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 35f51baed..4554a5c1a 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -816,7 +816,7 @@ class FreqaiDataKitchen: return False def check_if_new_training_required( - self, trained_timestamp: int + self, trained_timestamp: int = 0 ) -> Tuple[bool, TimeRange, TimeRange]: time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() @@ -889,31 +889,6 @@ class FreqaiDataKitchen: self.model_filename = f"cb_{coin.lower()}_{int(trained_timerange.stopts)}" - def download_all_data_for_training(self, timerange: TimeRange, dp: DataProvider) -> None: - """ - Called only once upon start of bot to download the necessary data for - populating indicators and training the model. - :param timerange: TimeRange = The full data timerange for populating the indicators - and training the model. - :param dp: DataProvider instance attached to the strategy - """ - new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) - if not dp._exchange: - # Not realistic - this is only called in live mode. - raise OperationalException("Dataprovider did not have an exchange attached.") - refresh_backtest_ohlcv_data( - dp._exchange, - pairs=self.all_pairs, - timeframes=self.freqai_config["feature_parameters"].get("include_timeframes"), - datadir=self.config["datadir"], - timerange=timerange, - new_pairs_days=new_pairs_days, - erase=False, - data_format=self.config.get("dataformat_ohlcv", "json"), - trading_mode=self.config.get("trading_mode", "spot"), - prepend=self.config.get("prepend_data", False), - ) - def set_all_pairs(self) -> None: self.all_pairs = copy.deepcopy( @@ -1027,3 +1002,78 @@ class FreqaiDataKitchen: if self.unique_classes: for label in self.unique_classes: self.unique_class_list += list(self.unique_classes[label]) + +# Methods called by interface.py (load_freqai_model()) + + +def download_all_data_for_training(timerange: TimeRange, + dp: DataProvider, config: dict) -> None: + """ + Called only once upon start of bot to download the necessary data for + populating indicators and training the model. + :param timerange: TimeRange = The full data timerange for populating the indicators + and training the model. + :param dp: DataProvider instance attached to the strategy + """ + all_pairs = copy.deepcopy( + config["freqai"]["feature_parameters"].get("include_corr_pairlist", []) + ) + for pair in config.get("exchange", "").get("pair_whitelist"): + if pair not in all_pairs: + all_pairs.append(pair) + + new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) + if not dp._exchange: + # Not realistic - this is only called in live mode. + raise OperationalException("Dataprovider did not have an exchange attached.") + refresh_backtest_ohlcv_data( + dp._exchange, + pairs=all_pairs, + timeframes=config["freqai"]["feature_parameters"].get("include_timeframes"), + datadir=config["datadir"], + timerange=timerange, + new_pairs_days=new_pairs_days, + erase=False, + data_format=config.get("dataformat_ohlcv", "json"), + trading_mode=config.get("trading_mode", "spot"), + prepend=config.get("prepend_data", False), + ) + + +def get_required_data_timerange( + config: dict +) -> TimeRange: + """ + Used by interface.py to pre-download necessary data for FreqAI + user. + """ + time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() + trained_timerange = TimeRange() + data_load_timerange = TimeRange() + + timeframes = config["freqai"]["feature_parameters"].get("include_timeframes") + + max_tf_seconds = 0 + for tf in timeframes: + secs = timeframe_to_seconds(tf) + if secs > max_tf_seconds: + max_tf_seconds = secs + + max_period = config["freqai"]["feature_parameters"].get( + "indicator_max_period_candles", 20 + ) * 2 + additional_seconds = max_period * max_tf_seconds + + trained_timerange.startts = int( + time - config["freqai"].get("train_period_days", 0) * SECONDS_IN_DAY + ) + trained_timerange.stopts = int(time) + + data_load_timerange.startts = int( + time + - config["freqai"].get("train_period_days", 0) * SECONDS_IN_DAY + - additional_seconds + ) + data_load_timerange.stopts = int(time) + + return data_load_timerange diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 49e4ce5c3..5d85cc225 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -278,12 +278,12 @@ class IFreqaiModel(ABC): # download candle history if it is not already in memory if not self.dd.historic_data: - logger.info( - "Downloading all training data for all pairs in whitelist and " - "corr_pairlist, this may take a while if you do not have the " - "data saved" - ) - dk.download_all_data_for_training(data_load_timerange, strategy.dp) + # logger.info( + # "Downloading all training data for all pairs in whitelist and " + # "corr_pairlist, this may take a while if you do not have the " + # "data saved" + # ) + # dk.download_all_data_for_training(data_load_timerange, strategy.dp) self.dd.load_all_pair_histories(data_load_timerange, dk) if not self.scanning: diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 79dbd4c69..20a35ac3e 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -149,9 +149,20 @@ class IStrategy(ABC, HyperStrategyMixin): if self.config.get('freqai', {}).get('enabled', False): # Import here to avoid importing this if freqAI is disabled from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver - + from freqtrade.freqai.data_kitchen import (get_required_data_timerange, + download_all_data_for_training) self.freqai = FreqaiModelResolver.load_freqaimodel(self.config) self.freqai_info = self.config["freqai"] + + # download the desired data in dry/live + if self.config.get('runmode') in (RunMode.DRY_RUN, RunMode.LIVE): + logger.info( + "Downloading all training data for all pairs in whitelist and " + "corr_pairlist, this may take a while if you do not have the " + "data saved" + ) + data_load_timerange = get_required_data_timerange(self.config) + download_all_data_for_training(data_load_timerange, self.dp, self.config) else: # Gracious failures if freqAI is disabled but "start" is called. class DummyClass(): From 5155afb4e7adb62b219fab65df86ac29524e405a Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 17 Aug 2022 15:22:48 +0200 Subject: [PATCH 019/592] clean up code remnants --- freqtrade/freqai/data_kitchen.py | 2 +- freqtrade/freqai/freqai_interface.py | 8 +------- 2 files changed, 2 insertions(+), 8 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 4554a5c1a..6541261eb 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -816,7 +816,7 @@ class FreqaiDataKitchen: return False def check_if_new_training_required( - self, trained_timestamp: int = 0 + self, trained_timestamp: int ) -> Tuple[bool, TimeRange, TimeRange]: time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 5d85cc225..1a9e549f6 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -276,14 +276,8 @@ class IFreqaiModel(ABC): ) dk.set_paths(metadata["pair"], new_trained_timerange.stopts) - # download candle history if it is not already in memory + # load candle history into memory if it is not yet. if not self.dd.historic_data: - # logger.info( - # "Downloading all training data for all pairs in whitelist and " - # "corr_pairlist, this may take a while if you do not have the " - # "data saved" - # ) - # dk.download_all_data_for_training(data_load_timerange, strategy.dp) self.dd.load_all_pair_histories(data_load_timerange, dk) if not self.scanning: From 88dd9920ea9dd66c17a55fad4d6fb69cacefb8c2 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 17 Aug 2022 16:38:09 +0200 Subject: [PATCH 020/592] sort imports for isort --- freqtrade/strategy/interface.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 20a35ac3e..1e51701f7 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -148,9 +148,9 @@ class IStrategy(ABC, HyperStrategyMixin): def load_freqAI_model(self) -> None: if self.config.get('freqai', {}).get('enabled', False): # Import here to avoid importing this if freqAI is disabled + from freqtrade.freqai.data_kitchen import (download_all_data_for_training, + get_required_data_timerange) from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver - from freqtrade.freqai.data_kitchen import (get_required_data_timerange, - download_all_data_for_training) self.freqai = FreqaiModelResolver.load_freqaimodel(self.config) self.freqai_info = self.config["freqai"] From 9f6bba40af1a407f190a89f5c0c8b4e3f528ba46 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 18 Aug 2022 10:39:20 -0600 Subject: [PATCH 021/592] initial concept for replicate, basic leader and follower logic --- .gitignore | 2 + freqtrade/__init__.py | 2 +- freqtrade/constants.py | 28 + freqtrade/enums/__init__.py | 1 + freqtrade/enums/replicate.py | 11 + freqtrade/enums/rpcmessagetype.py | 2 + freqtrade/rpc/api_server/webserver.py | 8 +- freqtrade/rpc/replicate/__init__.py | 385 ++++++++++++++ freqtrade/rpc/replicate/channel.py | 106 ++++ freqtrade/rpc/replicate/proxy.py | 60 +++ freqtrade/rpc/replicate/serializer.py | 42 ++ freqtrade/rpc/replicate/thread_queue.py | 650 ++++++++++++++++++++++++ freqtrade/rpc/replicate/types.py | 9 + freqtrade/rpc/replicate/utils.py | 10 + freqtrade/rpc/rpc_manager.py | 13 + requirements-replicate.txt | 5 + 16 files changed, 1330 insertions(+), 4 deletions(-) create mode 100644 freqtrade/enums/replicate.py create mode 100644 freqtrade/rpc/replicate/__init__.py create mode 100644 freqtrade/rpc/replicate/channel.py create mode 100644 freqtrade/rpc/replicate/proxy.py create mode 100644 freqtrade/rpc/replicate/serializer.py create mode 100644 freqtrade/rpc/replicate/thread_queue.py create mode 100644 freqtrade/rpc/replicate/types.py create mode 100644 freqtrade/rpc/replicate/utils.py create mode 100644 requirements-replicate.txt diff --git a/.gitignore b/.gitignore index e400c01f5..df2121990 100644 --- a/.gitignore +++ b/.gitignore @@ -113,3 +113,5 @@ target/ !config_examples/config_full.example.json !config_examples/config_kraken.example.json !config_examples/config_freqai.example.json + +*-config.json diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 2572c03f1..9e022b2d9 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.8.dev' +__version__ = '2022.8.1+pubsub' # Metadata 1.2 mandates PEP 440 version, but 'develop' is not if 'dev' in __version__: try: diff --git a/freqtrade/constants.py b/freqtrade/constants.py index ddbc84fa9..416b4646f 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -60,6 +60,8 @@ USERPATH_FREQAIMODELS = 'freqaimodels' TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent'] WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw'] +FOLLOWER_MODE_OPTIONS = ['follower', 'leader'] + ENV_VAR_PREFIX = 'FREQTRADE__' NON_OPEN_EXCHANGE_STATES = ('cancelled', 'canceled', 'closed', 'expired') @@ -242,6 +244,7 @@ CONF_SCHEMA = { 'exchange': {'$ref': '#/definitions/exchange'}, 'edge': {'$ref': '#/definitions/edge'}, 'freqai': {'$ref': '#/definitions/freqai'}, + 'replicate': {'$ref': '#/definitions/replicate'}, 'experimental': { 'type': 'object', 'properties': { @@ -483,6 +486,31 @@ CONF_SCHEMA = { }, 'required': ['process_throttle_secs', 'allowed_risk'] }, + 'replicate': { + 'type': 'object', + 'properties': { + 'enabled': {'type': 'boolean', 'default': False}, + 'mode': { + 'type': 'string', + 'enum': FOLLOWER_MODE_OPTIONS + }, + 'api_key': {'type': 'string', 'default': ''}, + 'leaders': { + 'type': 'array', + 'items': { + 'type': 'object', + 'properties': { + 'url': {'type': 'string', 'default': ''}, + 'token': {'type': 'string', 'default': ''}, + } + } + }, + 'follower_reply_timeout': {'type': 'integer'}, + 'follower_sleep_time': {'type': 'integer'}, + 'follower_ping_timeout': {'type': 'integer'}, + }, + 'required': ['mode'] + }, "freqai": { "type": "object", "properties": { diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index e50ebc4a4..e1057208a 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -5,6 +5,7 @@ from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues +from freqtrade.enums.replicate import LeaderMessageType, ReplicateModeType from freqtrade.enums.rpcmessagetype import RPCMessageType from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType diff --git a/freqtrade/enums/replicate.py b/freqtrade/enums/replicate.py new file mode 100644 index 000000000..d55d45b45 --- /dev/null +++ b/freqtrade/enums/replicate.py @@ -0,0 +1,11 @@ +from enum import Enum + + +class ReplicateModeType(str, Enum): + leader = "leader" + follower = "follower" + + +class LeaderMessageType(str, Enum): + Pairlist = "pairlist" + Dataframe = "dataframe" diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index 415d8f18c..d5b3ce89c 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -19,6 +19,8 @@ class RPCMessageType(Enum): STRATEGY_MSG = 'strategy_msg' + EMIT_DATA = 'emit_data' + def __repr__(self): return self.value diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 0da129583..c98fb9fd4 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -54,7 +54,11 @@ class ApiServer(RPCHandler): ApiServer.__initialized = False return ApiServer.__instance - def __init__(self, config: Dict[str, Any], standalone: bool = False) -> None: + def __init__( + self, + config: Dict[str, Any], + standalone: bool = False, + ) -> None: ApiServer._config = config if self.__initialized and (standalone or self._standalone): return @@ -71,8 +75,6 @@ class ApiServer(RPCHandler): ) self.configure_app(self.app, self._config) - self.start_api() - def add_rpc_handler(self, rpc: RPC): """ Attach rpc handler diff --git a/freqtrade/rpc/replicate/__init__.py b/freqtrade/rpc/replicate/__init__.py new file mode 100644 index 000000000..d725a4a90 --- /dev/null +++ b/freqtrade/rpc/replicate/__init__.py @@ -0,0 +1,385 @@ +""" +This module manages replicate mode communication +""" +import asyncio +import logging +import secrets +import socket +from threading import Thread +from typing import Any, Coroutine, Dict, Union + +import websockets +from fastapi import Depends +from fastapi import WebSocket as FastAPIWebSocket +from fastapi import WebSocketDisconnect, status + +from freqtrade.enums import LeaderMessageType, ReplicateModeType, RPCMessageType +from freqtrade.rpc import RPC, RPCHandler +from freqtrade.rpc.replicate.channel import ChannelManager +from freqtrade.rpc.replicate.thread_queue import Queue as ThreadedQueue +from freqtrade.rpc.replicate.utils import is_websocket_alive + + +logger = logging.getLogger(__name__) + + +class ReplicateController(RPCHandler): + """ This class handles all websocket communication """ + + def __init__( + self, + rpc: RPC, + config: Dict[str, Any], + api_server: Union[Any, None] = None + ) -> None: + """ + Init the ReplicateRPC class, and init the super class RPCHandler + :param rpc: instance of RPC Helper class + :param config: Configuration object + :return: None + """ + super().__init__(rpc, config) + + self.api_server = api_server + + if not self.api_server: + raise RuntimeError("The API server must be enabled for replicate to work") + + self._loop = None + self._running = False + self._thread = None + self._queue = None + + self.channel_manager = ChannelManager() + + self.replicate_config = config.get('replicate', {}) + + # What the config should look like + # "replicate": { + # "enabled": true, + # "mode": "follower", + # "leaders": [ + # { + # "url": "ws://localhost:8080/replicate/ws", + # "token": "test" + # } + # ] + # } + + # "replicate": { + # "enabled": true, + # "mode": "leader", + # "api_key": "test" + # } + + self.mode = ReplicateModeType[self.replicate_config.get('mode', 'leader').lower()] + + self.leaders_list = self.replicate_config.get('leaders', []) + self.push_throttle_secs = self.replicate_config.get('push_throttle_secs', 1) + + self.reply_timeout = self.replicate_config.get('follower_reply_timeout', 10) + self.ping_timeout = self.replicate_config.get('follower_ping_timeout', 2) + self.sleep_time = self.replicate_config.get('follower_sleep_time', 1) + + if self.mode == ReplicateModeType.follower and len(self.leaders_list) == 0: + raise ValueError("You must specify at least 1 leader in follower mode.") + + # This is only used by the leader, the followers use the tokens specified + # in each of the leaders + # If you do not specify an API key in the config, one will be randomly + # generated and logged on startup + default_api_key = secrets.token_urlsafe(16) + self.secret_api_key = self.replicate_config.get('api_key', default_api_key) + + self.start_threaded_loop() + + if self.mode == ReplicateModeType.follower: + self.start_follower_mode() + elif self.mode == ReplicateModeType.leader: + self.start_leader_mode() + + def start_threaded_loop(self): + """ + Start the main internal loop in another thread to run coroutines + """ + self._loop = asyncio.new_event_loop() + + if not self._thread: + self._thread = Thread(target=self._loop.run_forever) + self._thread.start() + self._running = True + else: + raise RuntimeError("A loop is already running") + + def submit_coroutine(self, coroutine: Coroutine): + """ + Submit a coroutine to the threaded loop + """ + if not self._running: + raise RuntimeError("Cannot schedule new futures after shutdown") + + if not self._loop or not self._loop.is_running(): + raise RuntimeError("Loop must be started before any function can" + " be submitted") + + logger.debug(f"Running coroutine {repr(coroutine)} in loop") + try: + return asyncio.run_coroutine_threadsafe(coroutine, self._loop) + except Exception as e: + logger.error(f"Error running coroutine - {str(e)}") + return None + + def cleanup(self) -> None: + """ + Cleanup pending module resources. + """ + if self._thread: + if self._loop.is_running(): + + self._running = False + + # Tell all coroutines submitted to the loop they're cancelled + pending = asyncio.all_tasks(loop=self._loop) + for task in pending: + task.cancel() + + self._loop.call_soon_threadsafe(self.channel_manager.disconnect_all) + # This must be called threadsafe, otherwise would not work + self._loop.call_soon_threadsafe(self._loop.stop) + + self._thread.join() + + def send_msg(self, msg: Dict[str, Any]) -> None: + """ Push message through """ + + if msg["type"] == RPCMessageType.EMIT_DATA: + self._send_message( + { + "type": msg["data_type"], + "content": msg["data"] + } + ) + + # ----------------------- LEADER LOGIC ------------------------------ + + def start_leader_mode(self): + """ + Register the endpoint and start the leader loop + """ + + logger.info("Running rpc.replicate in Leader mode") + logger.info("-" * 15) + logger.info(f"API_KEY: {self.secret_api_key}") + logger.info("-" * 15) + + self.register_leader_endpoint() + self.submit_coroutine(self.leader_loop()) + + async def leader_loop(self): + """ + Main leader coroutine + At the moment this just broadcasts data that's in the queue to the followers + """ + try: + await self._broadcast_queue_data() + except Exception as e: + logger.error("Exception occurred in leader loop: ") + logger.exception(e) + + def _send_message(self, data: Dict[Any, Any]): + """ + Add data to the internal queue to be broadcasted. This func will block + if the queue is full. This is meant to be called in the main thread. + """ + + if self._queue: + self._queue.put(data) + else: + logger.warning("Can not send data, leader loop has not started yet!") + + async def _broadcast_queue_data(self): + """ + Loop over queue data and broadcast it + """ + # Instantiate the queue in this coroutine so it's attached to our loop + self._queue = ThreadedQueue() + async_queue = self._queue.async_q + + try: + while self._running: + # Get data from queue + data = await async_queue.get() + + # Broadcast it to everyone + await self.channel_manager.broadcast(data) + + # Sleep + await asyncio.sleep(self.push_throttle_secs) + except asyncio.CancelledError: + # Silently stop + pass + + async def get_api_token( + self, + websocket: FastAPIWebSocket, + token: Union[str, None] = None + ): + """ + Extract the API key from query param. Must match the + set secret_api_key or the websocket connection will be closed. + """ + if token == self.secret_api_key: + return token + else: + logger.info("Denying websocket request...") + await websocket.close(code=status.WS_1008_POLICY_VIOLATION) + + def register_leader_endpoint(self, path: str = "/replicate/ws"): + """ + Attach and start the main leader loop to the ApiServer + + :param path: The endpoint path + """ + + if not self.api_server: + raise RuntimeError("The leader needs the ApiServer to be active") + + # The endpoint function for running the main leader loop + @self.api_server.app.websocket(path) + async def leader_endpoint( + websocket: FastAPIWebSocket, + api_key: str = Depends(self.get_api_token) + ): + await self.leader_endpoint_loop(websocket) + + async def leader_endpoint_loop(self, websocket: FastAPIWebSocket): + """ + The WebSocket endpoint served by the ApiServer. This handles connections, + and adding them to the channel manager. + """ + try: + if is_websocket_alive(websocket): + logger.info(f"Follower connected - {websocket.client}") + channel = await self.channel_manager.on_connect(websocket) + + # Send initial data here + + # Keep connection open until explicitly closed, and sleep + try: + while not channel.is_closed(): + await channel.recv() + + except WebSocketDisconnect: + # Handle client disconnects + logger.info(f"Follower disconnected - {websocket.client}") + await self.channel_manager.on_disconnect(websocket) + except Exception as e: + logger.info(f"Follower connection failed - {websocket.client}") + logger.exception(e) + # Handle cases like - + # RuntimeError('Cannot call "send" once a closed message has been sent') + await self.channel_manager.on_disconnect(websocket) + + except Exception: + logger.error(f"Failed to serve - {websocket.client}") + await self.channel_manager.on_disconnect(websocket) + + # -------------------------------FOLLOWER LOGIC---------------------------- + + def start_follower_mode(self): + """ + Start the ReplicateController in Follower mode + """ + logger.info("Starting rpc.replicate in Follower mode") + + self.submit_coroutine(self.follower_loop()) + + async def follower_loop(self): + """ + Main follower coroutine + + This starts all of the leader connection coros + """ + try: + await self._connect_to_leaders() + except Exception as e: + logger.error("Exception occurred in follower loop: ") + logger.exception(e) + + async def _connect_to_leaders(self): + rpc_lock = asyncio.Lock() + + logger.info("Starting connections to Leaders...") + await asyncio.wait( + [ + self._handle_leader_connection(leader, rpc_lock) + for leader in self.leaders_list + ] + ) + + async def _handle_leader_connection(self, leader, lock): + """ + Given a leader, connect and wait on data. If connection is lost, + it will attempt to reconnect. + """ + url, token = leader["url"], leader["token"] + + websocket_url = f"{url}?token={token}" + + logger.info(f"Attempting to connect to leader at: {url}") + # TODO: limit the amount of connection retries + while True: + try: + async with websockets.connect(websocket_url) as ws: + channel = await self.channel_manager.on_connect(ws) + while True: + try: + data = await asyncio.wait_for( + channel.recv(), + timeout=self.reply_timeout + ) + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Just check the connection and continue. + try: + # ping + ping = await channel.ping() + await asyncio.wait_for(ping, timeout=self.ping_timeout) + logger.info(f"Connection to {url} still alive...") + continue + except Exception: + logger.info(f"Ping error {url} - retrying in {self.sleep_time}s") + asyncio.sleep(self.sleep_time) + break + + with lock: + # Should we have a lock here? + await self._handle_leader_message(data) + + except socket.gaierror: + logger.info(f"Socket error - retrying connection in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + continue + except ConnectionRefusedError: + logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + continue + + async def _handle_leader_message(self, message): + type = message.get("type") + + message_type_handlers = { + LeaderMessageType.Pairlist.value: self._handle_pairlist_message, + LeaderMessageType.Dataframe.value: self._handle_dataframe_message + } + + handler = message_type_handlers.get(type, self._handle_default_message) + return await handler(message) + + async def _handle_default_message(self, message): + logger.info(f"Default message handled: {message}") + + async def _handle_pairlist_message(self, message): + logger.info(f"Pairlist message handled: {message}") + + async def _handle_dataframe_message(self, message): + logger.info(f"Dataframe message handled: {message}") diff --git a/freqtrade/rpc/replicate/channel.py b/freqtrade/rpc/replicate/channel.py new file mode 100644 index 000000000..9950742da --- /dev/null +++ b/freqtrade/rpc/replicate/channel.py @@ -0,0 +1,106 @@ +from typing import Type + +from freqtrade.rpc.replicate.proxy import WebSocketProxy +from freqtrade.rpc.replicate.serializer import JSONWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.replicate.types import WebSocketType + + +class WebSocketChannel: + """ + Object to help facilitate managing a websocket connection + """ + + def __init__( + self, + websocket: WebSocketType, + serializer_cls: Type[WebSocketSerializer] = JSONWebSocketSerializer + ): + # The WebSocket object + self._websocket = WebSocketProxy(websocket) + # The Serializing class for the WebSocket object + self._serializer_cls = serializer_cls + + # Internal event to signify a closed websocket + self._closed = False + + # Wrap the WebSocket in the Serializing class + self._wrapped_ws = self._serializer_cls(self._websocket) + + async def send(self, data): + """ + Send data on the wrapped websocket + """ + await self._wrapped_ws.send(data) + + async def recv(self): + """ + Receive data on the wrapped websocket + """ + return await self._wrapped_ws.recv() + + async def ping(self): + """ + Ping the websocket + """ + return await self._websocket.ping() + + async def close(self): + """ + Close the WebSocketChannel + """ + + self._closed = True + + def is_closed(self): + return self._closed + + +class ChannelManager: + def __init__(self): + self.channels = dict() + + async def on_connect(self, websocket: WebSocketType): + """ + Wrap websocket connection into Channel and add to list + + :param websocket: The WebSocket object to attach to the Channel + """ + if hasattr(websocket, "accept"): + try: + await websocket.accept() + except RuntimeError: + # The connection was closed before we could accept it + return + + ws_channel = WebSocketChannel(websocket) + self.channels[websocket] = ws_channel + + return ws_channel + + async def on_disconnect(self, websocket: WebSocketType): + """ + Call close on the channel if it's not, and remove from channel list + + :param websocket: The WebSocket objet attached to the Channel + """ + if websocket in self.channels.keys(): + channel = self.channels[websocket] + if not channel.is_closed(): + await channel.close() + del channel + + async def disconnect_all(self): + """ + Disconnect all Channels + """ + for websocket in self.channels.keys(): + await self.on_disconnect(websocket) + + async def broadcast(self, data): + """ + Broadcast data on all Channels + + :param data: The data to send + """ + for channel in self.channels.values(): + await channel.send(data) diff --git a/freqtrade/rpc/replicate/proxy.py b/freqtrade/rpc/replicate/proxy.py new file mode 100644 index 000000000..b2173670b --- /dev/null +++ b/freqtrade/rpc/replicate/proxy.py @@ -0,0 +1,60 @@ +from typing import TYPE_CHECKING, Union + +from fastapi import WebSocket as FastAPIWebSocket +from websockets import WebSocketClientProtocol as WebSocket + + +if TYPE_CHECKING: + from freqtrade.rpc.replicate.types import WebSocketType + + +class WebSocketProxy: + """ + WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol + under the same API + """ + + def __init__(self, websocket: WebSocketType): + self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket + + async def send(self, data): + """ + Send data on the wrapped websocket + """ + if hasattr(self._websocket, "send_bytes"): + await self._websocket.send_bytes(data) + else: + await self._websocket.send(data) + + async def recv(self): + """ + Receive data on the wrapped websocket + """ + if hasattr(self._websocket, "receive_bytes"): + return await self._websocket.receive_bytes() + else: + return await self._websocket.recv() + + async def ping(self): + """ + Ping the websocket, not supported by FastAPI WebSockets + """ + if hasattr(self._websocket, "ping"): + return await self._websocket.ping() + return False + + async def close(self, code: int = 1000): + """ + Close the websocket connection, only supported by FastAPI WebSockets + """ + if hasattr(self._websocket, "close"): + return await self._websocket.close(code) + pass + + async def accept(self): + """ + Accept the WebSocket connection, only support by FastAPI WebSockets + """ + if hasattr(self._websocket, "accept"): + return await self._websocket.accept() + pass diff --git a/freqtrade/rpc/replicate/serializer.py b/freqtrade/rpc/replicate/serializer.py new file mode 100644 index 000000000..ae5e57b95 --- /dev/null +++ b/freqtrade/rpc/replicate/serializer.py @@ -0,0 +1,42 @@ +import json +from abc import ABC, abstractmethod + +from freqtrade.rpc.replicate.proxy import WebSocketProxy + + +class WebSocketSerializer(ABC): + def __init__(self, websocket: WebSocketProxy): + self._websocket: WebSocketProxy = websocket + + @abstractmethod + def _serialize(self, data): + raise NotImplementedError() + + @abstractmethod + def _deserialize(self, data): + raise NotImplementedError() + + async def send(self, data: bytes): + await self._websocket.send(self._serialize(data)) + + async def recv(self) -> bytes: + data = await self._websocket.recv() + + return self._deserialize(data) + + async def close(self, code: int = 1000): + await self._websocket.close(code) + +# Going to explore using MsgPack as the serialization, +# as that might be the best method for sending pandas +# dataframes over the wire + + +class JSONWebSocketSerializer(WebSocketSerializer): + def _serialize(self, data: bytes) -> bytes: + # json expects string not bytes + return json.dumps(data.decode()).encode() + + def _deserialize(self, data: bytes) -> bytes: + # The WebSocketSerializer gives bytes not string + return json.loads(data).encode() diff --git a/freqtrade/rpc/replicate/thread_queue.py b/freqtrade/rpc/replicate/thread_queue.py new file mode 100644 index 000000000..88321321b --- /dev/null +++ b/freqtrade/rpc/replicate/thread_queue.py @@ -0,0 +1,650 @@ +import asyncio +import sys +import threading +from asyncio import QueueEmpty as AsyncQueueEmpty +from asyncio import QueueFull as AsyncQueueFull +from collections import deque +from heapq import heappop, heappush +from queue import Empty as SyncQueueEmpty +from queue import Full as SyncQueueFull +from typing import Any, Callable, Deque, Generic, List, Optional, Set, TypeVar + +from typing_extensions import Protocol + + +__version__ = "1.0.0" +__all__ = ( + "Queue", + "PriorityQueue", + "LifoQueue", + "SyncQueue", + "AsyncQueue", + "BaseQueue", +) + + +T = TypeVar("T") +OptFloat = Optional[float] + + +class BaseQueue(Protocol[T]): + @property + def maxsize(self) -> int: + ... + + @property + def closed(self) -> bool: + ... + + def task_done(self) -> None: + ... + + def qsize(self) -> int: + ... + + @property + def unfinished_tasks(self) -> int: + ... + + def empty(self) -> bool: + ... + + def full(self) -> bool: + ... + + def put_nowait(self, item: T) -> None: + ... + + def get_nowait(self) -> T: + ... + + +class SyncQueue(BaseQueue[T], Protocol[T]): + @property + def maxsize(self) -> int: + ... + + @property + def closed(self) -> bool: + ... + + def task_done(self) -> None: + ... + + def qsize(self) -> int: + ... + + @property + def unfinished_tasks(self) -> int: + ... + + def empty(self) -> bool: + ... + + def full(self) -> bool: + ... + + def put_nowait(self, item: T) -> None: + ... + + def get_nowait(self) -> T: + ... + + def put(self, item: T, block: bool = True, timeout: OptFloat = None) -> None: + ... + + def get(self, block: bool = True, timeout: OptFloat = None) -> T: + ... + + def join(self) -> None: + ... + + +class AsyncQueue(BaseQueue[T], Protocol[T]): + async def put(self, item: T) -> None: + ... + + async def get(self) -> T: + ... + + async def join(self) -> None: + ... + + +class Queue(Generic[T]): + def __init__(self, maxsize: int = 0) -> None: + self._loop = asyncio.get_running_loop() + self._maxsize = maxsize + + self._init(maxsize) + + self._unfinished_tasks = 0 + + self._sync_mutex = threading.Lock() + self._sync_not_empty = threading.Condition(self._sync_mutex) + self._sync_not_full = threading.Condition(self._sync_mutex) + self._all_tasks_done = threading.Condition(self._sync_mutex) + + self._async_mutex = asyncio.Lock() + if sys.version_info[:3] == (3, 10, 0): + # Workaround for Python 3.10 bug, see #358: + getattr(self._async_mutex, "_get_loop", lambda: None)() + self._async_not_empty = asyncio.Condition(self._async_mutex) + self._async_not_full = asyncio.Condition(self._async_mutex) + self._finished = asyncio.Event() + self._finished.set() + + self._closing = False + self._pending = set() # type: Set[asyncio.Future[Any]] + + def checked_call_soon_threadsafe( + callback: Callable[..., None], *args: Any + ) -> None: + try: + self._loop.call_soon_threadsafe(callback, *args) + except RuntimeError: + # swallowing agreed in #2 + pass + + self._call_soon_threadsafe = checked_call_soon_threadsafe + + def checked_call_soon(callback: Callable[..., None], *args: Any) -> None: + if not self._loop.is_closed(): + self._loop.call_soon(callback, *args) + + self._call_soon = checked_call_soon + + self._sync_queue = _SyncQueueProxy(self) + self._async_queue = _AsyncQueueProxy(self) + + def close(self) -> None: + with self._sync_mutex: + self._closing = True + for fut in self._pending: + fut.cancel() + self._finished.set() # unblocks all async_q.join() + self._all_tasks_done.notify_all() # unblocks all sync_q.join() + + async def wait_closed(self) -> None: + # should be called from loop after close(). + # Nobody should put/get at this point, + # so lock acquiring is not required + if not self._closing: + raise RuntimeError("Waiting for non-closed queue") + # give execution chances for the task-done callbacks + # of async tasks created inside + # _notify_async_not_empty, _notify_async_not_full + # methods. + await asyncio.sleep(0) + if not self._pending: + return + await asyncio.wait(self._pending) + + @property + def closed(self) -> bool: + return self._closing and not self._pending + + @property + def maxsize(self) -> int: + return self._maxsize + + @property + def sync_q(self) -> "_SyncQueueProxy[T]": + return self._sync_queue + + @property + def async_q(self) -> "_AsyncQueueProxy[T]": + return self._async_queue + + # Override these methods to implement other queue organizations + # (e.g. stack or priority queue). + # These will only be called with appropriate locks held + + def _init(self, maxsize: int) -> None: + self._queue = deque() # type: Deque[T] + + def _qsize(self) -> int: + return len(self._queue) + + # Put a new item in the queue + def _put(self, item: T) -> None: + self._queue.append(item) + + # Get an item from the queue + def _get(self) -> T: + return self._queue.popleft() + + def _put_internal(self, item: T) -> None: + self._put(item) + self._unfinished_tasks += 1 + self._finished.clear() + + def _notify_sync_not_empty(self) -> None: + def f() -> None: + with self._sync_mutex: + self._sync_not_empty.notify() + + self._loop.run_in_executor(None, f) + + def _notify_sync_not_full(self) -> None: + def f() -> None: + with self._sync_mutex: + self._sync_not_full.notify() + + fut = asyncio.ensure_future(self._loop.run_in_executor(None, f)) + fut.add_done_callback(self._pending.discard) + self._pending.add(fut) + + def _notify_async_not_empty(self, *, threadsafe: bool) -> None: + async def f() -> None: + async with self._async_mutex: + self._async_not_empty.notify() + + def task_maker() -> None: + task = self._loop.create_task(f()) + task.add_done_callback(self._pending.discard) + self._pending.add(task) + + if threadsafe: + self._call_soon_threadsafe(task_maker) + else: + self._call_soon(task_maker) + + def _notify_async_not_full(self, *, threadsafe: bool) -> None: + async def f() -> None: + async with self._async_mutex: + self._async_not_full.notify() + + def task_maker() -> None: + task = self._loop.create_task(f()) + task.add_done_callback(self._pending.discard) + self._pending.add(task) + + if threadsafe: + self._call_soon_threadsafe(task_maker) + else: + self._call_soon(task_maker) + + def _check_closing(self) -> None: + if self._closing: + raise RuntimeError("Operation on the closed queue is forbidden") + + +class _SyncQueueProxy(SyncQueue[T]): + """Create a queue object with a given maximum size. + + If maxsize is <= 0, the queue size is infinite. + """ + + def __init__(self, parent: Queue[T]): + self._parent = parent + + @property + def maxsize(self) -> int: + return self._parent._maxsize + + @property + def closed(self) -> bool: + return self._parent.closed + + def task_done(self) -> None: + """Indicate that a formerly enqueued task is complete. + + Used by Queue consumer threads. For each get() used to fetch a task, + a subsequent call to task_done() tells the queue that the processing + on the task is complete. + + If a join() is currently blocking, it will resume when all items + have been processed (meaning that a task_done() call was received + for every item that had been put() into the queue). + + Raises a ValueError if called more times than there were items + placed in the queue. + """ + self._parent._check_closing() + with self._parent._all_tasks_done: + unfinished = self._parent._unfinished_tasks - 1 + if unfinished <= 0: + if unfinished < 0: + raise ValueError("task_done() called too many times") + self._parent._all_tasks_done.notify_all() + self._parent._loop.call_soon_threadsafe(self._parent._finished.set) + self._parent._unfinished_tasks = unfinished + + def join(self) -> None: + """Blocks until all items in the Queue have been gotten and processed. + + The count of unfinished tasks goes up whenever an item is added to the + queue. The count goes down whenever a consumer thread calls task_done() + to indicate the item was retrieved and all work on it is complete. + + When the count of unfinished tasks drops to zero, join() unblocks. + """ + self._parent._check_closing() + with self._parent._all_tasks_done: + while self._parent._unfinished_tasks: + self._parent._all_tasks_done.wait() + self._parent._check_closing() + + def qsize(self) -> int: + """Return the approximate size of the queue (not reliable!).""" + return self._parent._qsize() + + @property + def unfinished_tasks(self) -> int: + """Return the number of unfinished tasks.""" + return self._parent._unfinished_tasks + + def empty(self) -> bool: + """Return True if the queue is empty, False otherwise (not reliable!). + + This method is likely to be removed at some point. Use qsize() == 0 + as a direct substitute, but be aware that either approach risks a race + condition where a queue can grow before the result of empty() or + qsize() can be used. + + To create code that needs to wait for all queued tasks to be + completed, the preferred technique is to use the join() method. + """ + return not self._parent._qsize() + + def full(self) -> bool: + """Return True if the queue is full, False otherwise (not reliable!). + + This method is likely to be removed at some point. Use qsize() >= n + as a direct substitute, but be aware that either approach risks a race + condition where a queue can shrink before the result of full() or + qsize() can be used. + """ + return 0 < self._parent._maxsize <= self._parent._qsize() + + def put(self, item: T, block: bool = True, timeout: OptFloat = None) -> None: + """Put an item into the queue. + + If optional args 'block' is true and 'timeout' is None (the default), + block if necessary until a free slot is available. If 'timeout' is + a non-negative number, it blocks at most 'timeout' seconds and raises + the Full exception if no free slot was available within that time. + Otherwise ('block' is false), put an item on the queue if a free slot + is immediately available, else raise the Full exception ('timeout' + is ignored in that case). + """ + self._parent._check_closing() + with self._parent._sync_not_full: + if self._parent._maxsize > 0: + if not block: + if self._parent._qsize() >= self._parent._maxsize: + raise SyncQueueFull + elif timeout is None: + while self._parent._qsize() >= self._parent._maxsize: + self._parent._sync_not_full.wait() + elif timeout < 0: + raise ValueError("'timeout' must be a non-negative number") + else: + time = self._parent._loop.time + endtime = time() + timeout + while self._parent._qsize() >= self._parent._maxsize: + remaining = endtime - time() + if remaining <= 0.0: + raise SyncQueueFull + self._parent._sync_not_full.wait(remaining) + self._parent._put_internal(item) + self._parent._sync_not_empty.notify() + self._parent._notify_async_not_empty(threadsafe=True) + + def get(self, block: bool = True, timeout: OptFloat = None) -> T: + """Remove and return an item from the queue. + + If optional args 'block' is true and 'timeout' is None (the default), + block if necessary until an item is available. If 'timeout' is + a non-negative number, it blocks at most 'timeout' seconds and raises + the Empty exception if no item was available within that time. + Otherwise ('block' is false), return an item if one is immediately + available, else raise the Empty exception ('timeout' is ignored + in that case). + """ + self._parent._check_closing() + with self._parent._sync_not_empty: + if not block: + if not self._parent._qsize(): + raise SyncQueueEmpty + elif timeout is None: + while not self._parent._qsize(): + self._parent._sync_not_empty.wait() + elif timeout < 0: + raise ValueError("'timeout' must be a non-negative number") + else: + time = self._parent._loop.time + endtime = time() + timeout + while not self._parent._qsize(): + remaining = endtime - time() + if remaining <= 0.0: + raise SyncQueueEmpty + self._parent._sync_not_empty.wait(remaining) + item = self._parent._get() + self._parent._sync_not_full.notify() + self._parent._notify_async_not_full(threadsafe=True) + return item + + def put_nowait(self, item: T) -> None: + """Put an item into the queue without blocking. + + Only enqueue the item if a free slot is immediately available. + Otherwise raise the Full exception. + """ + return self.put(item, block=False) + + def get_nowait(self) -> T: + """Remove and return an item from the queue without blocking. + + Only get an item if one is immediately available. Otherwise + raise the Empty exception. + """ + return self.get(block=False) + + +class _AsyncQueueProxy(AsyncQueue[T]): + """Create a queue object with a given maximum size. + + If maxsize is <= 0, the queue size is infinite. + """ + + def __init__(self, parent: Queue[T]): + self._parent = parent + + @property + def closed(self) -> bool: + return self._parent.closed + + def qsize(self) -> int: + """Number of items in the queue.""" + return self._parent._qsize() + + @property + def unfinished_tasks(self) -> int: + """Return the number of unfinished tasks.""" + return self._parent._unfinished_tasks + + @property + def maxsize(self) -> int: + """Number of items allowed in the queue.""" + return self._parent._maxsize + + def empty(self) -> bool: + """Return True if the queue is empty, False otherwise.""" + return self.qsize() == 0 + + def full(self) -> bool: + """Return True if there are maxsize items in the queue. + + Note: if the Queue was initialized with maxsize=0 (the default), + then full() is never True. + """ + if self._parent._maxsize <= 0: + return False + else: + return self.qsize() >= self._parent._maxsize + + async def put(self, item: T) -> None: + """Put an item into the queue. + + Put an item into the queue. If the queue is full, wait until a free + slot is available before adding item. + + This method is a coroutine. + """ + self._parent._check_closing() + async with self._parent._async_not_full: + self._parent._sync_mutex.acquire() + locked = True + try: + if self._parent._maxsize > 0: + do_wait = True + while do_wait: + do_wait = self._parent._qsize() >= self._parent._maxsize + if do_wait: + locked = False + self._parent._sync_mutex.release() + await self._parent._async_not_full.wait() + self._parent._sync_mutex.acquire() + locked = True + + self._parent._put_internal(item) + self._parent._async_not_empty.notify() + self._parent._notify_sync_not_empty() + finally: + if locked: + self._parent._sync_mutex.release() + + def put_nowait(self, item: T) -> None: + """Put an item into the queue without blocking. + + If no free slot is immediately available, raise QueueFull. + """ + self._parent._check_closing() + with self._parent._sync_mutex: + if self._parent._maxsize > 0: + if self._parent._qsize() >= self._parent._maxsize: + raise AsyncQueueFull + + self._parent._put_internal(item) + self._parent._notify_async_not_empty(threadsafe=False) + self._parent._notify_sync_not_empty() + + async def get(self) -> T: + """Remove and return an item from the queue. + + If queue is empty, wait until an item is available. + + This method is a coroutine. + """ + self._parent._check_closing() + async with self._parent._async_not_empty: + self._parent._sync_mutex.acquire() + locked = True + try: + do_wait = True + while do_wait: + do_wait = self._parent._qsize() == 0 + + if do_wait: + locked = False + self._parent._sync_mutex.release() + await self._parent._async_not_empty.wait() + self._parent._sync_mutex.acquire() + locked = True + + item = self._parent._get() + self._parent._async_not_full.notify() + self._parent._notify_sync_not_full() + return item + finally: + if locked: + self._parent._sync_mutex.release() + + def get_nowait(self) -> T: + """Remove and return an item from the queue. + + Return an item if one is immediately available, else raise QueueEmpty. + """ + self._parent._check_closing() + with self._parent._sync_mutex: + if self._parent._qsize() == 0: + raise AsyncQueueEmpty + + item = self._parent._get() + self._parent._notify_async_not_full(threadsafe=False) + self._parent._notify_sync_not_full() + return item + + def task_done(self) -> None: + """Indicate that a formerly enqueued task is complete. + + Used by queue consumers. For each get() used to fetch a task, + a subsequent call to task_done() tells the queue that the processing + on the task is complete. + + If a join() is currently blocking, it will resume when all items have + been processed (meaning that a task_done() call was received for every + item that had been put() into the queue). + + Raises ValueError if called more times than there were items placed in + the queue. + """ + self._parent._check_closing() + with self._parent._all_tasks_done: + if self._parent._unfinished_tasks <= 0: + raise ValueError("task_done() called too many times") + self._parent._unfinished_tasks -= 1 + if self._parent._unfinished_tasks == 0: + self._parent._finished.set() + self._parent._all_tasks_done.notify_all() + + async def join(self) -> None: + """Block until all items in the queue have been gotten and processed. + + The count of unfinished tasks goes up whenever an item is added to the + queue. The count goes down whenever a consumer calls task_done() to + indicate that the item was retrieved and all work on it is complete. + When the count of unfinished tasks drops to zero, join() unblocks. + """ + while True: + with self._parent._sync_mutex: + self._parent._check_closing() + if self._parent._unfinished_tasks == 0: + break + await self._parent._finished.wait() + + +class PriorityQueue(Queue[T]): + """Variant of Queue that retrieves open entries in priority order + (lowest first). + + Entries are typically tuples of the form: (priority number, data). + + """ + + def _init(self, maxsize: int) -> None: + self._heap_queue = [] # type: List[T] + + def _qsize(self) -> int: + return len(self._heap_queue) + + def _put(self, item: T) -> None: + heappush(self._heap_queue, item) + + def _get(self) -> T: + return heappop(self._heap_queue) + + +class LifoQueue(Queue[T]): + """Variant of Queue that retrieves most recently added entries first.""" + + def _qsize(self) -> int: + return len(self._queue) + + def _put(self, item: T) -> None: + self._queue.append(item) + + def _get(self) -> T: + return self._queue.pop() diff --git a/freqtrade/rpc/replicate/types.py b/freqtrade/rpc/replicate/types.py new file mode 100644 index 000000000..5d8c158bd --- /dev/null +++ b/freqtrade/rpc/replicate/types.py @@ -0,0 +1,9 @@ +from typing import TypeVar + +from fastapi import WebSocket as FastAPIWebSocket +from websockets import WebSocketClientProtocol as WebSocket + +from freqtrade.rpc.replicate.channel import WebSocketProxy + + +WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket, WebSocketProxy) diff --git a/freqtrade/rpc/replicate/utils.py b/freqtrade/rpc/replicate/utils.py new file mode 100644 index 000000000..7b703810e --- /dev/null +++ b/freqtrade/rpc/replicate/utils.py @@ -0,0 +1,10 @@ +from starlette.websockets import WebSocket, WebSocketState + + +async def is_websocket_alive(ws: WebSocket) -> bool: + if ( + ws.application_state == WebSocketState.CONNECTED and + ws.client_state == WebSocketState.CONNECTED + ): + return True + return False diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 3ccf23228..140431586 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -44,10 +44,23 @@ class RPCManager: if config.get('api_server', {}).get('enabled', False): logger.info('Enabling rpc.api_server') from freqtrade.rpc.api_server import ApiServer + + # Pass replicate_rpc as param or defer starting api_server + # until we register the replicate rpc enpoint? apiserver = ApiServer(config) apiserver.add_rpc_handler(self._rpc) self.registered_modules.append(apiserver) + # Enable Replicate mode + # For this to be enabled, the API server must also be enabled + if config.get('replicate', {}).get('enabled', False): + logger.info('Enabling rpc.replicate') + from freqtrade.rpc.replicate import ReplicateController + replicate_rpc = ReplicateController(self._rpc, config, apiserver) + self.registered_modules.append(replicate_rpc) + + apiserver.start_api() + def cleanup(self) -> None: """ Stops all enabled rpc modules """ logger.info('Cleaning up rpc modules ...') diff --git a/requirements-replicate.txt b/requirements-replicate.txt new file mode 100644 index 000000000..7ee351d9d --- /dev/null +++ b/requirements-replicate.txt @@ -0,0 +1,5 @@ +# Include all requirements to run the bot. +-r requirements.txt + +# Required for follower +websockets From 6834db11f3ec4d0b9d9a6540633e1b363c11c889 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 19 Aug 2022 00:06:19 -0600 Subject: [PATCH 022/592] minor improvements and pairlist data transmission --- freqtrade/enums/replicate.py | 3 +- freqtrade/freqtradebot.py | 13 + .../plugins/pairlist/ExternalPairList.py | 59 +++++ freqtrade/rpc/replicate/__init__.py | 236 ++++++++++-------- freqtrade/rpc/replicate/channel.py | 23 +- freqtrade/rpc/replicate/proxy.py | 9 +- freqtrade/rpc/replicate/serializer.py | 8 +- freqtrade/rpc/replicate/types.py | 4 +- freqtrade/rpc/rpc_manager.py | 3 + 9 files changed, 243 insertions(+), 115 deletions(-) create mode 100644 freqtrade/plugins/pairlist/ExternalPairList.py diff --git a/freqtrade/enums/replicate.py b/freqtrade/enums/replicate.py index d55d45b45..501d119f3 100644 --- a/freqtrade/enums/replicate.py +++ b/freqtrade/enums/replicate.py @@ -7,5 +7,4 @@ class ReplicateModeType(str, Enum): class LeaderMessageType(str, Enum): - Pairlist = "pairlist" - Dataframe = "dataframe" + whitelist = "whitelist" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 4e3af64ea..ac6a998c5 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -75,6 +75,8 @@ class FreqtradeBot(LoggingMixin): PairLocks.timeframe = self.config['timeframe'] + self.replicate_controller = None + # RPC runs in separate threads, can start handling external commands just after # initialization, even before Freqtradebot has a chance to start its throttling, # so anything in the Freqtradebot instance should be ready (initialized), including @@ -264,6 +266,17 @@ class FreqtradeBot(LoggingMixin): # Extend active-pair whitelist with pairs of open trades # It ensures that candle (OHLCV) data are downloaded for open trades as well _whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist]) + + # If replicate leader, broadcast whitelist data + if self.replicate_controller: + if self.replicate_controller.is_leader(): + self.replicate_controller.send_message( + { + "data_type": "whitelist", + "data": _whitelist + } + ) + return _whitelist def get_free_open_trades(self) -> int: diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py new file mode 100644 index 000000000..832c3d5eb --- /dev/null +++ b/freqtrade/plugins/pairlist/ExternalPairList.py @@ -0,0 +1,59 @@ +""" +External Pair List provider + +Provides pair list from Leader data +""" +import logging +from typing import Any, Dict, List + +from freqtrade.plugins.pairlist.IPairList import IPairList + + +logger = logging.getLogger(__name__) + + +class ExternalPairList(IPairList): + + def __init__(self, exchange, pairlistmanager, + config: Dict[str, Any], pairlistconfig: Dict[str, Any], + pairlist_pos: int) -> None: + super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) + + self._num_assets = self._pairlistconfig.get('num_assets') + self._allow_inactive = self._pairlistconfig.get('allow_inactive', False) + + self._leader_pairs: List[str] = [] + + @property + def needstickers(self) -> bool: + """ + Boolean property defining if tickers are necessary. + If no Pairlist requires tickers, an empty Dict is passed + as tickers argument to filter_pairlist + """ + return False + + def short_desc(self) -> str: + """ + Short whitelist method description - used for startup-messages + -> Please overwrite in subclasses + """ + return f"{self.name}" + + def gen_pairlist(self, tickers: Dict) -> List[str]: + """ + Generate the pairlist + :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :return: List of pairs + """ + pass + + def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + """ + Filters and sorts pairlist and returns the whitelist again. + Called on each bot iteration - please use internal caching if necessary + :param pairlist: pairlist to filter or sort + :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :return: new whitelist + """ + pass diff --git a/freqtrade/rpc/replicate/__init__.py b/freqtrade/rpc/replicate/__init__.py index d725a4a90..80ac0836c 100644 --- a/freqtrade/rpc/replicate/__init__.py +++ b/freqtrade/rpc/replicate/__init__.py @@ -5,7 +5,7 @@ import asyncio import logging import secrets import socket -from threading import Thread +from threading import Event, Thread from typing import Any, Coroutine, Dict, Union import websockets @@ -50,6 +50,9 @@ class ReplicateController(RPCHandler): self._thread = None self._queue = None + self._stop_event = Event() + self._follower_tasks = None + self.channel_manager = ChannelManager() self.replicate_config = config.get('replicate', {}) @@ -93,10 +96,7 @@ class ReplicateController(RPCHandler): self.start_threaded_loop() - if self.mode == ReplicateModeType.follower: - self.start_follower_mode() - elif self.mode == ReplicateModeType.leader: - self.start_leader_mode() + self.start() def start_threaded_loop(self): """ @@ -129,6 +129,29 @@ class ReplicateController(RPCHandler): logger.error(f"Error running coroutine - {str(e)}") return None + async def main_loop(self): + """ + Main loop coro + + Start the loop based on what mode we're in + """ + try: + if self.mode == ReplicateModeType.leader: + await self.leader_loop() + elif self.mode == ReplicateModeType.follower: + await self.follower_loop() + + except asyncio.CancelledError: + pass + finally: + self._loop.stop() + + def start(self): + """ + Start the controller main loop + """ + self.submit_coroutine(self.main_loop()) + def cleanup(self) -> None: """ Cleanup pending module resources. @@ -144,27 +167,62 @@ class ReplicateController(RPCHandler): task.cancel() self._loop.call_soon_threadsafe(self.channel_manager.disconnect_all) - # This must be called threadsafe, otherwise would not work - self._loop.call_soon_threadsafe(self._loop.stop) self._thread.join() def send_msg(self, msg: Dict[str, Any]) -> None: - """ Push message through """ - + """ + Support RPC calls + """ if msg["type"] == RPCMessageType.EMIT_DATA: - self._send_message( + self.send_message( { - "type": msg["data_type"], - "content": msg["data"] + "data_type": msg.get("data_type"), + "data": msg.get("data") } ) + def send_message(self, msg: Dict[str, Any]) -> None: + """ Push message through """ + + if self.channel_manager.has_channels(): + self._send_message(msg) + else: + logger.debug("No listening followers, skipping...") + pass + + def _send_message(self, msg: Dict[Any, Any]): + """ + Add data to the internal queue to be broadcasted. This func will block + if the queue is full. This is meant to be called in the main thread. + """ + + if self._queue: + queue = self._queue.sync_q + queue.put(msg) + else: + logger.warning("Can not send data, leader loop has not started yet!") + + def is_leader(self): + """ + Leader flag + """ + return self.enabled() and self.mode == ReplicateModeType.leader + + def enabled(self): + """ + Enabled flag + """ + return self.replicate_config.get('enabled', False) + # ----------------------- LEADER LOGIC ------------------------------ - def start_leader_mode(self): + async def leader_loop(self): """ - Register the endpoint and start the leader loop + Main leader coroutine + + This starts all of the leader coros and registers the endpoint on + the ApiServer """ logger.info("Running rpc.replicate in Leader mode") @@ -173,30 +231,13 @@ class ReplicateController(RPCHandler): logger.info("-" * 15) self.register_leader_endpoint() - self.submit_coroutine(self.leader_loop()) - async def leader_loop(self): - """ - Main leader coroutine - At the moment this just broadcasts data that's in the queue to the followers - """ try: await self._broadcast_queue_data() except Exception as e: logger.error("Exception occurred in leader loop: ") logger.exception(e) - def _send_message(self, data: Dict[Any, Any]): - """ - Add data to the internal queue to be broadcasted. This func will block - if the queue is full. This is meant to be called in the main thread. - """ - - if self._queue: - self._queue.put(data) - else: - logger.warning("Can not send data, leader loop has not started yet!") - async def _broadcast_queue_data(self): """ Loop over queue data and broadcast it @@ -210,6 +251,8 @@ class ReplicateController(RPCHandler): # Get data from queue data = await async_queue.get() + logger.info(f"Found data - broadcasting: {data}") + # Broadcast it to everyone await self.channel_manager.broadcast(data) @@ -263,6 +306,9 @@ class ReplicateController(RPCHandler): channel = await self.channel_manager.on_connect(websocket) # Send initial data here + # Data is being broadcasted right away as soon as startup, + # we may not have to send initial data at all. Further testing + # required. # Keep connection open until explicitly closed, and sleep try: @@ -286,20 +332,15 @@ class ReplicateController(RPCHandler): # -------------------------------FOLLOWER LOGIC---------------------------- - def start_follower_mode(self): - """ - Start the ReplicateController in Follower mode - """ - logger.info("Starting rpc.replicate in Follower mode") - - self.submit_coroutine(self.follower_loop()) - async def follower_loop(self): """ Main follower coroutine - This starts all of the leader connection coros + This starts all of the follower connection coros """ + + logger.info("Starting rpc.replicate in Follower mode") + try: await self._connect_to_leaders() except Exception as e: @@ -307,79 +348,76 @@ class ReplicateController(RPCHandler): logger.exception(e) async def _connect_to_leaders(self): + """ + For each leader in `self.leaders_list` create a connection and + listen for data. + """ rpc_lock = asyncio.Lock() logger.info("Starting connections to Leaders...") - await asyncio.wait( - [ - self._handle_leader_connection(leader, rpc_lock) - for leader in self.leaders_list - ] - ) + + self.follower_tasks = [ + self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) + for leader in self.leaders_list + ] + return await asyncio.gather(*self.follower_tasks, return_exceptions=True) async def _handle_leader_connection(self, leader, lock): """ Given a leader, connect and wait on data. If connection is lost, it will attempt to reconnect. """ - url, token = leader["url"], leader["token"] + try: + url, token = leader["url"], leader["token"] - websocket_url = f"{url}?token={token}" + websocket_url = f"{url}?token={token}" - logger.info(f"Attempting to connect to leader at: {url}") - # TODO: limit the amount of connection retries - while True: - try: - async with websockets.connect(websocket_url) as ws: - channel = await self.channel_manager.on_connect(ws) - while True: - try: - data = await asyncio.wait_for( - channel.recv(), - timeout=self.reply_timeout - ) - except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): - # We haven't received data yet. Just check the connection and continue. + logger.info(f"Attempting to connect to leader at: {url}") + # TODO: limit the amount of connection retries + while True: + try: + async with websockets.connect(websocket_url) as ws: + channel = await self.channel_manager.on_connect(ws) + while True: try: - # ping - ping = await channel.ping() - await asyncio.wait_for(ping, timeout=self.ping_timeout) - logger.info(f"Connection to {url} still alive...") - continue - except Exception: - logger.info(f"Ping error {url} - retrying in {self.sleep_time}s") - asyncio.sleep(self.sleep_time) - break + data = await asyncio.wait_for( + channel.recv(), + timeout=self.reply_timeout + ) + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Check the connection and continue. + try: + # ping + ping = await channel.ping() + await asyncio.wait_for(ping, timeout=self.ping_timeout) + logger.debug(f"Connection to {url} still alive...") + continue + except Exception: + logger.info( + f"Ping error {url} - retrying in {self.sleep_time}s") + asyncio.sleep(self.sleep_time) + break - with lock: - # Should we have a lock here? - await self._handle_leader_message(data) + async with lock: + # Acquire lock so only 1 coro handling at a time + # as we might call the RPC module in the main thread + await self._handle_leader_message(data) - except socket.gaierror: - logger.info(f"Socket error - retrying connection in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - continue - except ConnectionRefusedError: - logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - continue + except socket.gaierror: + logger.info(f"Socket error - retrying connection in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + continue + except ConnectionRefusedError: + logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + continue + + except asyncio.CancelledError: + pass async def _handle_leader_message(self, message): - type = message.get("type") + type = message.get('data_type') + data = message.get('data') - message_type_handlers = { - LeaderMessageType.Pairlist.value: self._handle_pairlist_message, - LeaderMessageType.Dataframe.value: self._handle_dataframe_message - } - - handler = message_type_handlers.get(type, self._handle_default_message) - return await handler(message) - - async def _handle_default_message(self, message): - logger.info(f"Default message handled: {message}") - - async def _handle_pairlist_message(self, message): - logger.info(f"Pairlist message handled: {message}") - - async def _handle_dataframe_message(self, message): - logger.info(f"Dataframe message handled: {message}") + if type == LeaderMessageType.whitelist: + logger.info(f"Received whitelist from Leader: {data}") diff --git a/freqtrade/rpc/replicate/channel.py b/freqtrade/rpc/replicate/channel.py index 9950742da..7aa316ff5 100644 --- a/freqtrade/rpc/replicate/channel.py +++ b/freqtrade/rpc/replicate/channel.py @@ -1,3 +1,4 @@ +import logging from typing import Type from freqtrade.rpc.replicate.proxy import WebSocketProxy @@ -5,6 +6,9 @@ from freqtrade.rpc.replicate.serializer import JSONWebSocketSerializer, WebSocke from freqtrade.rpc.replicate.types import WebSocketType +logger = logging.getLogger(__name__) + + class WebSocketChannel: """ Object to help facilitate managing a websocket connection @@ -85,9 +89,12 @@ class ChannelManager: """ if websocket in self.channels.keys(): channel = self.channels[websocket] + + logger.debug(f"Disconnecting channel - {channel}") + if not channel.is_closed(): await channel.close() - del channel + del self.channels[websocket] async def disconnect_all(self): """ @@ -102,5 +109,15 @@ class ChannelManager: :param data: The data to send """ - for channel in self.channels.values(): - await channel.send(data) + for websocket, channel in self.channels.items(): + try: + await channel.send(data) + except RuntimeError: + # Handle cannot send after close cases + await self.on_disconnect(websocket) + + def has_channels(self): + """ + Flag for more than 0 channels + """ + return len(self.channels) > 0 diff --git a/freqtrade/rpc/replicate/proxy.py b/freqtrade/rpc/replicate/proxy.py index b2173670b..aae536b6d 100644 --- a/freqtrade/rpc/replicate/proxy.py +++ b/freqtrade/rpc/replicate/proxy.py @@ -1,11 +1,9 @@ -from typing import TYPE_CHECKING, Union +from typing import Union from fastapi import WebSocket as FastAPIWebSocket from websockets import WebSocketClientProtocol as WebSocket - -if TYPE_CHECKING: - from freqtrade.rpc.replicate.types import WebSocketType +from freqtrade.rpc.replicate.types import WebSocketType class WebSocketProxy: @@ -21,6 +19,9 @@ class WebSocketProxy: """ Send data on the wrapped websocket """ + if isinstance(data, str): + data = data.encode() + if hasattr(self._websocket, "send_bytes"): await self._websocket.send_bytes(data) else: diff --git a/freqtrade/rpc/replicate/serializer.py b/freqtrade/rpc/replicate/serializer.py index ae5e57b95..717458f09 100644 --- a/freqtrade/rpc/replicate/serializer.py +++ b/freqtrade/rpc/replicate/serializer.py @@ -33,10 +33,10 @@ class WebSocketSerializer(ABC): class JSONWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data: bytes) -> bytes: + def _serialize(self, data): # json expects string not bytes - return json.dumps(data.decode()).encode() + return json.dumps(data) - def _deserialize(self, data: bytes) -> bytes: + def _deserialize(self, data): # The WebSocketSerializer gives bytes not string - return json.loads(data).encode() + return json.loads(data) diff --git a/freqtrade/rpc/replicate/types.py b/freqtrade/rpc/replicate/types.py index 5d8c158bd..763147196 100644 --- a/freqtrade/rpc/replicate/types.py +++ b/freqtrade/rpc/replicate/types.py @@ -3,7 +3,5 @@ from typing import TypeVar from fastapi import WebSocket as FastAPIWebSocket from websockets import WebSocketClientProtocol as WebSocket -from freqtrade.rpc.replicate.channel import WebSocketProxy - -WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket, WebSocketProxy) +WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 140431586..8eaec21ea 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -59,6 +59,9 @@ class RPCManager: replicate_rpc = ReplicateController(self._rpc, config, apiserver) self.registered_modules.append(replicate_rpc) + # Attach the controller to FreqTrade + freqtrade.replicate_controller = replicate_rpc + apiserver.start_api() def cleanup(self) -> None: From 1c6f96657974f69fbf97ea135740f180393d0239 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:03:03 +0200 Subject: [PATCH 023/592] Hyperopt: simplify parameter "can_optimize" handling --- freqtrade/strategy/parameters.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/freqtrade/strategy/parameters.py b/freqtrade/strategy/parameters.py index 83dd41de9..e64a1e4c0 100644 --- a/freqtrade/strategy/parameters.py +++ b/freqtrade/strategy/parameters.py @@ -57,6 +57,12 @@ class BaseParameter(ABC): Get-space - will be used by Hyperopt to get the hyperopt Space """ + def can_optimize(self): + return ( + self.in_space + and self.optimize + ) + class NumericParameter(BaseParameter): """ Internal parameter used for Numeric purposes """ @@ -133,7 +139,7 @@ class IntParameter(NumericParameter): Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid calculating 100ds of indicators. """ - if self.in_space and self.optimize: + if self.can_optimize(): # Scikit-optimize ranges are "inclusive", while python's "range" is exclusive return range(self.low, self.high + 1) else: @@ -212,7 +218,7 @@ class DecimalParameter(NumericParameter): Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid calculating 100ds of indicators. """ - if self.in_space and self.optimize: + if self.can_optimize(): low = int(self.low * pow(10, self._decimals)) high = int(self.high * pow(10, self._decimals)) + 1 return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)] @@ -261,7 +267,7 @@ class CategoricalParameter(BaseParameter): Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid calculating 100ds of indicators. """ - if self.in_space and self.optimize: + if self.can_optimize(): return self.opt_range else: return [self.value] From 08ef5ad2d8f12100e17beec5c4c23d26d5e51434 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:11:43 +0200 Subject: [PATCH 024/592] Add HyperoptState enum and container class --- freqtrade/enums/__init__.py | 1 + freqtrade/enums/hyperoptstate.py | 12 ++++++++++++ freqtrade/optimize/hyperopt_tools.py | 15 +++++++++++++++ 3 files changed, 28 insertions(+) create mode 100644 freqtrade/enums/hyperoptstate.py diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index e50ebc4a4..d2f5474fc 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -3,6 +3,7 @@ from freqtrade.enums.backteststate import BacktestState from freqtrade.enums.candletype import CandleType from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType +from freqtrade.enums.hyperoptstate import HyperoptState from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues from freqtrade.enums.rpcmessagetype import RPCMessageType diff --git a/freqtrade/enums/hyperoptstate.py b/freqtrade/enums/hyperoptstate.py new file mode 100644 index 000000000..332b3354d --- /dev/null +++ b/freqtrade/enums/hyperoptstate.py @@ -0,0 +1,12 @@ +from enum import Enum + + +class HyperoptState(Enum): + """ Hyperopt states """ + STARTUP = 1 + DATALOAD = 2 + INDICATORS = 3 + OPTIMIZE = 0 + + def __str__(self): + return f"{self.name.lower()}" diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py index ab6ef013b..7f339eec1 100755 --- a/freqtrade/optimize/hyperopt_tools.py +++ b/freqtrade/optimize/hyperopt_tools.py @@ -13,6 +13,7 @@ from colorama import Fore, Style from pandas import isna, json_normalize from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES +from freqtrade.enums import HyperoptState from freqtrade.exceptions import OperationalException from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2 from freqtrade.optimize.hyperopt_epoch_filters import hyperopt_filter_epochs @@ -32,6 +33,20 @@ def hyperopt_serializer(x): return str(x) +class HyperoptStateContainer(): + """ Singleton class to track state of hyperopt""" + __state = HyperoptState.OPTIMIZE + + @classmethod + def set_state(cls, value: HyperoptState): + cls.__state = value + + @classmethod + @property + def state(cls) -> HyperoptState: + return cls.__state + + class HyperoptTools(): @staticmethod From 09f8904545b35454534cf2866216ec4e656c4381 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:12:55 +0200 Subject: [PATCH 025/592] Extract analysis to separate method --- freqtrade/optimize/hyperopt.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index cbcf39131..ebeb7eb25 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -406,6 +406,14 @@ class Hyperopt: def _set_random_state(self, random_state: Optional[int]) -> int: return random_state or random.randint(1, 2**16 - 1) + def advise_and_trim(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]: + preprocessed = self.backtesting.strategy.advise_all_indicators(data) + + # Trim startup period from analyzed dataframe to get correct dates for output. + processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) + self.min_date, self.max_date = get_timerange(processed) + return processed + def prepare_hyperopt_data(self) -> None: data, timerange = self.backtesting.load_bt_data() self.backtesting.load_bt_data_detail() @@ -413,9 +421,7 @@ class Hyperopt: preprocessed = self.backtesting.strategy.advise_all_indicators(data) - # Trim startup period from analyzed dataframe to get correct dates for output. - processed = trim_dataframes(preprocessed, timerange, self.backtesting.required_startup) - self.min_date, self.max_date = get_timerange(processed) + preprocessed = self.advise_and_trim(data) logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} ' f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} ' From bc359675a2bebf55e79e72d3e6c5c54bf519e159 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:19:43 +0200 Subject: [PATCH 026/592] Add --analyze-per-epoch - moving populate_analysis to the epoch process --- docs/hyperopt.md | 10 +++++-- freqtrade/commands/arguments.py | 2 +- freqtrade/commands/cli_options.py | 7 +++++ freqtrade/configuration/configuration.py | 3 +++ freqtrade/optimize/hyperopt.py | 34 +++++++++++++++++------- freqtrade/strategy/parameters.py | 4 +++ 6 files changed, 48 insertions(+), 12 deletions(-) diff --git a/docs/hyperopt.md b/docs/hyperopt.md index c9ec30056..a07bab9de 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -40,7 +40,8 @@ pip install -r requirements-hyperopt.txt ``` usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-s NAME] [--strategy-path PATH] - [--recursive-strategy-search] [-i TIMEFRAME] + [--recursive-strategy-search] [--freqaimodel NAME] + [--freqaimodel-path PATH] [-i TIMEFRAME] [--timerange TIMERANGE] [--data-format-ohlcv {json,jsongz,hdf5}] [--max-open-trades INT] @@ -53,7 +54,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--print-all] [--no-color] [--print-json] [-j JOBS] [--random-state INT] [--min-trades INT] [--hyperopt-loss NAME] [--disable-param-export] - [--ignore-missing-spaces] + [--ignore-missing-spaces] [--analyze-per-epoch] optional arguments: -h, --help show this help message and exit @@ -129,6 +130,7 @@ optional arguments: --ignore-missing-spaces, --ignore-unparameterized-spaces Suppress errors for any requested Hyperopt spaces that do not contain any parameters. + --analyze-per-epoch Run populate_indicators once per epoch. Common arguments: -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). @@ -154,6 +156,10 @@ Strategy arguments: --recursive-strategy-search Recursively search for a strategy in the strategies folder. + --freqaimodel NAME Specify a custom freqaimodels. + --freqaimodel-path PATH + Specify additional lookup path for freqaimodels. + ``` ### Hyperopt checklist diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index 48a423be4..05a6a2ca3 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -34,7 +34,7 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path", "print_colorized", "print_json", "hyperopt_jobs", "hyperopt_random_state", "hyperopt_min_trades", "hyperopt_loss", "disableparamexport", - "hyperopt_ignore_missing_space"] + "hyperopt_ignore_missing_space", "analyze_per_epoch"] ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"] diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index f85b75af1..51a501d7c 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -255,6 +255,13 @@ AVAILABLE_CLI_OPTIONS = { nargs='+', default='default', ), + "analyze_per_epoch": Arg( + '--analyze-per-epoch', + help='Run populate_indicators once per epoch.', + action='store_true', + default=False, + ), + "print_all": Arg( '--print-all', help='Print all results, not only the best ones.', diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index b4f36aa3c..41b31b022 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -302,6 +302,9 @@ class Configuration: self._args_to_config(config, argname='spaces', logstring='Parameter -s/--spaces detected: {}') + self._args_to_config(config, argname='analyze_per_epoch', + logstring='Parameter --analyze-per-epoch detected.') + self._args_to_config(config, argname='print_all', logstring='Parameter --print-all detected ...') diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index ebeb7eb25..fea2a672f 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -24,13 +24,15 @@ from pandas import DataFrame from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN from freqtrade.data.converter import trim_dataframes from freqtrade.data.history import get_timerange +from freqtrade.enums import HyperoptState from freqtrade.exceptions import OperationalException from freqtrade.misc import deep_merge_dicts, file_dump_json, plural from freqtrade.optimize.backtesting import Backtesting # Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules from freqtrade.optimize.hyperopt_auto import HyperOptAuto from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss -from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer +from freqtrade.optimize.hyperopt_tools import (HyperoptStateContainer, HyperoptTools, + hyperopt_serializer) from freqtrade.optimize.optimize_reports import generate_strategy_stats from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver @@ -74,10 +76,14 @@ class Hyperopt: self.dimensions: List[Dimension] = [] self.config = config + self.min_date: datetime + self.max_date: datetime self.backtesting = Backtesting(self.config) self.pairlist = self.backtesting.pairlists.whitelist self.custom_hyperopt: HyperOptAuto + self.analyze_per_epoch = self.config.get('analyze_per_epoch', False) + HyperoptStateContainer.set_state(HyperoptState.STARTUP) if not self.config.get('hyperopt'): self.custom_hyperopt = HyperOptAuto(self.config) @@ -290,6 +296,7 @@ class Hyperopt: Called once per epoch to optimize whatever is configured. Keep this function as optimized as possible! """ + HyperoptStateContainer.set_state(HyperoptState.OPTIMIZE) backtest_start_time = datetime.now(timezone.utc) params_dict = self._get_params_dict(self.dimensions, raw_params) @@ -321,6 +328,10 @@ class Hyperopt: with self.data_pickle_file.open('rb') as f: processed = load(f, mmap_mode='r') + if self.analyze_per_epoch: + # Data is not yet analyzed, rerun populate_indicators. + processed = self.advise_and_trim(processed) + bt_results = self.backtesting.backtest( processed=processed, start_date=self.min_date, @@ -415,19 +426,24 @@ class Hyperopt: return processed def prepare_hyperopt_data(self) -> None: - data, timerange = self.backtesting.load_bt_data() + HyperoptStateContainer.set_state(HyperoptState.DATALOAD) + data, self.timerange = self.backtesting.load_bt_data() self.backtesting.load_bt_data_detail() logger.info("Dataload complete. Calculating indicators") - preprocessed = self.backtesting.strategy.advise_all_indicators(data) + if not self.analyze_per_epoch: + HyperoptStateContainer.set_state(HyperoptState.INDICATORS) - preprocessed = self.advise_and_trim(data) + preprocessed = self.advise_and_trim(data) - logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'({(self.max_date - self.min_date).days} days)..') - # Store non-trimmed data - will be trimmed after signal generation. - dump(preprocessed, self.data_pickle_file) + logger.info(f'Hyperopting with data from ' + f'{self.min_date.strftime(DATETIME_PRINT_FORMAT)} ' + f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} ' + f'({(self.max_date - self.min_date).days} days)..') + # Store non-trimmed data - will be trimmed after signal generation. + dump(preprocessed, self.data_pickle_file) + else: + dump(data, self.data_pickle_file) def get_asked_points(self, n_points: int) -> Tuple[List[List[Any]], List[bool]]: """ diff --git a/freqtrade/strategy/parameters.py b/freqtrade/strategy/parameters.py index e64a1e4c0..c6037ae0b 100644 --- a/freqtrade/strategy/parameters.py +++ b/freqtrade/strategy/parameters.py @@ -7,6 +7,9 @@ from abc import ABC, abstractmethod from contextlib import suppress from typing import Any, Optional, Sequence, Union +from freqtrade.enums.hyperoptstate import HyperoptState +from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer + with suppress(ImportError): from skopt.space import Integer, Real, Categorical @@ -61,6 +64,7 @@ class BaseParameter(ABC): return ( self.in_space and self.optimize + and HyperoptStateContainer.state != HyperoptState.OPTIMIZE ) From 733f716819b2c9ecaf303a357744005eba38ff5b Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:22:43 +0200 Subject: [PATCH 027/592] Update documentation --- docs/hyperopt.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/docs/hyperopt.md b/docs/hyperopt.md index a07bab9de..d230c091e 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -191,7 +191,7 @@ Rarely you may also need to create a [nested class](advanced-hyperopt.md#overrid ### Hyperopt execution logic -Hyperopt will first load your data into memory and will then run `populate_indicators()` once per Pair to generate all indicators. +Hyperopt will first load your data into memory and will then run `populate_indicators()` once per Pair to generate all indicators, unless `--analyze-per-epoch` is specified. Hyperopt will then spawn into different processes (number of processors, or `-j `), and run backtesting over and over again, changing the parameters that are part of the `--spaces` defined. @@ -434,7 +434,8 @@ While this strategy is most likely too simple to provide consistent profit, it s ??? Hint "Performance tip" By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter. While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values). - You should however try to use space ranges as small as possible. Every new column will require more memory, and every possibility hyperopt can try will increase the search space. + As this also has Performance implications, hyperopt provides `--analyze-per-epoch` - which will move the execution of `populate_indicators()` to the epoch process. This will implicitly also change the `.range` functionality to only return the actually used value. + You should however try to use space ranges as small as possible. ## Optimizing protections @@ -885,6 +886,7 @@ To combat these, you have multiple options: * Avoid using `--timeframe-detail` (this loads a lot of additional data into memory). * Reduce the number of parallel processes (`-j `). * Increase the memory of your machine. +* Use `--analyze-per-epoch` if you're using a lot of parameters with `.range` functionality. ## The objective has been evaluated at this point before. From b9d48c32782040ebe0754f4b11cf1dd481264235 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:40:06 +0200 Subject: [PATCH 028/592] use numbers in HyperoptState properly ... --- freqtrade/enums/hyperoptstate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/enums/hyperoptstate.py b/freqtrade/enums/hyperoptstate.py index 332b3354d..6716e123a 100644 --- a/freqtrade/enums/hyperoptstate.py +++ b/freqtrade/enums/hyperoptstate.py @@ -6,7 +6,7 @@ class HyperoptState(Enum): STARTUP = 1 DATALOAD = 2 INDICATORS = 3 - OPTIMIZE = 0 + OPTIMIZE = 4 def __str__(self): return f"{self.name.lower()}" From b44bd0171cf69c6dc527f8e008fe2f50539fcda5 Mon Sep 17 00:00:00 2001 From: Johan van der Vlugt <83158576+JohanVlugt@users.noreply.github.com> Date: Fri, 19 Aug 2022 19:10:37 +0200 Subject: [PATCH 029/592] Example Classifier strat --- .../templates/FreqaiHybridExampleStrategy.py | 377 ++++++++++++++++++ 1 file changed, 377 insertions(+) create mode 100644 freqtrade/templates/FreqaiHybridExampleStrategy.py diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py new file mode 100644 index 000000000..acceccee7 --- /dev/null +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -0,0 +1,377 @@ +import logging +from datetime import datetime, timedelta +from functools import reduce +from typing import Optional + +import numpy as np +import pandas as pd +import talib.abstract as ta +from freqtrade.exchange import timeframe_to_prev_date +from freqtrade.persistence import Trade +from freqtrade.strategy import (DecimalParameter, IntParameter, IStrategy, + merge_informative_pair) +from numpy.lib import math +from pandas import DataFrame +from technical import qtpylib + +logger = logging.getLogger(__name__) + + +class FreqaiExampleHybridStrategy(IStrategy): + """ + Example classifier hybrid strategy showing how the user connects their own + IFreqaiModel to the strategy. Namely, the user uses: + self.freqai.start(dataframe, metadata) + + to make predictions on their data. populate_any_indicators() automatically + generates the variety of features indicated by the user in the + canonical freqtrade configuration file under config['freqai']. + + The underlying original supertrend strat is authored by @juankysoriano (Juan Carlos Soriano) + * github: https://github.com/juankysoriano/ + + This strategy is not designed to be used live + """ + + minimal_roi = {"0": 0.1, "30": 0.75, "60": 0.05, "120": 0.025, "240": -1} + + plot_config = { + "main_plot": {}, + "subplots": { + "prediction": {"prediction": {"color": "blue"}}, + "target_roi": { + "target_roi": {"color": "brown"}, + }, + "do_predict": { + "do_predict": {"color": "brown"}, + }, + }, + } + + process_only_new_candles = True + stoploss = -0.1 + use_exit_signal = True + startup_candle_count: int = 300 + can_short = True + + linear_roi_offset = DecimalParameter( + 0.00, 0.02, default=0.005, space="sell", optimize=False, load=True + ) + max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) + + buy_params = { + "buy_m1": 4, + "buy_m2": 7, + "buy_m3": 1, + "buy_p1": 8, + "buy_p2": 9, + "buy_p3": 8, + } + + # Sell hyperspace params: + sell_params = { + "sell_m1": 1, + "sell_m2": 3, + "sell_m3": 6, + "sell_p1": 16, + "sell_p2": 18, + "sell_p3": 18, + } + + buy_m1 = IntParameter(1, 7, default=1) + buy_m2 = IntParameter(1, 7, default=3) + buy_m3 = IntParameter(1, 7, default=4) + buy_p1 = IntParameter(7, 21, default=14) + buy_p2 = IntParameter(7, 21, default=10) + buy_p3 = IntParameter(7, 21, default=10) + + sell_m1 = IntParameter(1, 7, default=1) + sell_m2 = IntParameter(1, 7, default=3) + sell_m3 = IntParameter(1, 7, default=4) + sell_p1 = IntParameter(7, 21, default=14) + sell_p2 = IntParameter(7, 21, default=10) + sell_p3 = IntParameter(7, 21, default=10) + + def informative_pairs(self): + whitelist_pairs = self.dp.current_whitelist() + corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] + informative_pairs = [] + for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]: + for pair in whitelist_pairs: + informative_pairs.append((pair, tf)) + for pair in corr_pairs: + if pair in whitelist_pairs: + continue # avoid duplication + informative_pairs.append((pair, tf)) + return informative_pairs + + def populate_any_indicators( + self, pair, df, tf, informative=None, set_generalized_indicators=False + ): + """ + Function designed to automatically generate, name and merge features + from user indicated timeframes in the configuration file. User controls the indicators + passed to the training/prediction by prepending indicators with `'%-' + coin ` + (see convention below). I.e. user should not prepend any supporting metrics + (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the + model. + :param pair: pair to be used as informative + :param df: strategy dataframe which will receive merges from informatives + :param tf: timeframe of the dataframe which will modify the feature names + :param informative: the dataframe associated with the informative pair + """ + + coin = pair.split('/')[0] + + if informative is None: + informative = self.dp.get_pair_dataframe(pair, tf) + + # first loop is automatically duplicating indicators for time periods + for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]: + + t = int(t) + informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) + informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) + informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) + informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t) + informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t) + + informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) + + bollinger = qtpylib.bollinger_bands( + qtpylib.typical_price(informative), window=t, stds=2.2 + ) + informative[f"{coin}bb_lowerband-period_{t}"] = bollinger["lower"] + informative[f"{coin}bb_middleband-period_{t}"] = bollinger["mid"] + informative[f"{coin}bb_upperband-period_{t}"] = bollinger["upper"] + + informative[f"%-{coin}bb_width-period_{t}"] = ( + informative[f"{coin}bb_upperband-period_{t}"] + - informative[f"{coin}bb_lowerband-period_{t}"] + ) / informative[f"{coin}bb_middleband-period_{t}"] + informative[f"%-{coin}close-bb_lower-period_{t}"] = ( + informative["close"] / informative[f"{coin}bb_lowerband-period_{t}"] + ) + + informative[f"%-{coin}roc-period_{t}"] = ta.ROC(informative, timeperiod=t) + + informative[f"%-{coin}relative_volume-period_{t}"] = ( + informative["volume"] / informative["volume"].rolling(t).mean() + ) + + informative[f"%-{coin}pct-change"] = informative["close"].pct_change() + informative[f"%-{coin}raw_volume"] = informative["volume"] + informative[f"%-{coin}raw_price"] = informative["close"] + + indicators = [col for col in informative if col.startswith("%")] + # This loop duplicates and shifts all indicators to add a sense of recency to data + for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): + if n == 0: + continue + informative_shift = informative[indicators].shift(n) + informative_shift = informative_shift.add_suffix("_shift-" + str(n)) + informative = pd.concat((informative, informative_shift), axis=1) + + df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True) + skip_columns = [ + (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"] + ] + df = df.drop(columns=skip_columns) + + # Add generalized indicators here (because in live, it will call this + # function to populate indicators during training). Notice how we ensure not to + # add them multiple times + if set_generalized_indicators: + df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7 + df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25 + + # Classifiers are typically set up with strings as targets: + df['&s-up_or_down'] = np.where( df["close"].shift(-50) > + df["close"], 'up', 'down') + + # REGRESSOR Model: Can use single or multi traget + # user adds targets here by prepending them with &- (see convention below) + #df["&-s_close"] = ( + # df["close"] + # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + # .mean() + # / df["close"] + # - 1 + #) + # If user wishes to use multiple targets, they can add more by + # appending more columns with '&'. User should keep in mind that multi targets + # requires a multioutput prediction model such as + # templates/CatboostPredictionMultiModel.py, + + # df["&-s_range"] = ( + # df["close"] + # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + # .max() + # - + # df["close"] + # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + # .min() + # ) + + return df + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + # All indicators must be populated by populate_any_indicators() for live functionality + # to work correctly. + + # the model will return all labels created by user in `populate_any_indicators` + # (& appended targets), an indication of whether or not the prediction should be accepted, + # the target mean/std values for each of the labels created by user in + # `populate_any_indicators()` for each training period. + + for multiplier in self.buy_m1.range: + for period in self.buy_p1.range: + dataframe[f"supertrend_1_buy_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + for multiplier in self.buy_m2.range: + for period in self.buy_p2.range: + dataframe[f"supertrend_2_buy_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + for multiplier in self.buy_m3.range: + for period in self.buy_p3.range: + dataframe[f"supertrend_3_buy_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + for multiplier in self.sell_m1.range: + for period in self.sell_p1.range: + dataframe[f"supertrend_1_sell_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + for multiplier in self.sell_m2.range: + for period in self.sell_p2.range: + dataframe[f"supertrend_2_sell_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + for multiplier in self.sell_m3.range: + for period in self.sell_p3.range: + dataframe[f"supertrend_3_sell_{multiplier}_{period}"] = self.supertrend( + dataframe, multiplier, period + )["STX"] + + dataframe = self.freqai.start(dataframe, metadata, self) + + return dataframe + + def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame: + + df.loc[ + (df[f"supertrend_1_buy_{self.buy_m1.value}_{self.buy_p1.value}"] == "up") & + (df[f"supertrend_2_buy_{self.buy_m2.value}_{self.buy_p2.value}"] == "up") & + (df[f"supertrend_3_buy_{self.buy_m3.value}_{self.buy_p3.value}"] == "up") & + (df["do_predict"] == 1) & + (df['&s-up_or_down'] == 'up'), + "enter_long", + ] = 1 + + df.loc[ + (df[f"supertrend_1_sell_{self.sell_m1.value}_{self.sell_p1.value}"] == "down") & + (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down") & + (df[f"supertrend_3_sell_{self.sell_m3.value}_{self.sell_p3.value}"] == "down") & + (df["do_predict"] == 1) & + (df['&s-up_or_down'] == 'down'), + "enter_short", + ] = 1 + + return df + + def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame: + + df.loc[ + (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down"), + "exit_long", + ] = 1 + + df.loc[ + (df[f"supertrend_2_buy_{self.buy_m2.value}_{self.buy_p2.value}"] == "up"), + "exit_short", + ] = 1 + + return df + + def get_ticker_indicator(self): + return int(self.config["timeframe"][:-1]) + + def confirm_trade_entry(self, pair: str, order_type: str, amount: float, + rate: float, time_in_force: str, current_time, entry_tag, side: str, + **kwargs, ) -> bool: + + df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) + last_candle = df.iloc[-1].squeeze() + + if side == "long": + if rate > (last_candle["close"] * (1 + 0.0025)): + return False + else: + if rate < (last_candle["close"] * (1 - 0.0025)): + return False + + return True + + def leverage(self, pair: str, current_time: datetime, current_rate: float, + proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str, + **kwargs) -> float: + + return 1 + + """ + Supertrend Indicator; adapted for freqtrade, optimized by the math genius. + from: Perkmeister#2394 + """ + + def supertrend(self, dataframe: DataFrame, multiplier, period): + df = dataframe.copy() + last_row = dataframe.tail(1).index.item() + + df['TR'] = ta.TRANGE(df) + df['ATR'] = ta.SMA(df['TR'], period) + + st = 'ST_' + str(period) + '_' + str(multiplier) + stx = 'STX_' + str(period) + '_' + str(multiplier) + + # Compute basic upper and lower bands + BASIC_UB = ((df['high'] + df['low']) / 2 + multiplier * df['ATR']).values + BASIC_LB = ((df['high'] + df['low']) / 2 - multiplier * df['ATR']).values + FINAL_UB = np.zeros(last_row + 1) + FINAL_LB = np.zeros(last_row + 1) + ST = np.zeros(last_row + 1) + CLOSE = df['close'].values + + # Compute final upper and lower bands + for i in range(period, last_row + 1): + FINAL_UB[i] = BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - 1] or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1] + FINAL_LB[i] = BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - 1] or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1] + + # Set the Supertrend value + for i in range(period, last_row + 1): + ST[i] = FINAL_UB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] <= FINAL_UB[i] else \ + FINAL_LB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] > FINAL_UB[i] else \ + FINAL_LB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] >= FINAL_LB[i] else \ + FINAL_UB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] < FINAL_LB[i] else 0.00 + df_ST = pd.DataFrame(ST, columns=[st]) + df = pd.concat([df, df_ST],axis=1) + + # Mark the trend direction up/down + df[stx] = np.where((df[st] > 0.00), np.where((df['close'] < df[st]), 'down', 'up'), np.NaN) + + df.fillna(0, inplace=True) + + return DataFrame(index=df.index, data={ + 'ST' : df[st], + 'STX' : df[stx] + }) From 739b68f8fd5c3ca5cc6eacc1f8a49a76fdedd620 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 19 Aug 2022 22:40:01 -0600 Subject: [PATCH 030/592] ExternalPairList plugin --- freqtrade/constants.py | 3 +- freqtrade/enums/replicate.py | 2 +- freqtrade/freqtradebot.py | 30 +++++---- .../plugins/pairlist/ExternalPairList.py | 61 +++++++++++++++++-- freqtrade/rpc/replicate/__init__.py | 27 +++++--- 5 files changed, 96 insertions(+), 27 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 416b4646f..55363cca1 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -33,7 +33,8 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss', AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'AgeFilter', 'OffsetFilter', 'PerformanceFilter', 'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter', - 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter'] + 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter', + 'ExternalPairList'] AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard'] AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5'] BACKTEST_BREAKDOWNS = ['day', 'week', 'month'] diff --git a/freqtrade/enums/replicate.py b/freqtrade/enums/replicate.py index 501d119f3..73be996c0 100644 --- a/freqtrade/enums/replicate.py +++ b/freqtrade/enums/replicate.py @@ -7,4 +7,4 @@ class ReplicateModeType(str, Enum): class LeaderMessageType(str, Enum): - whitelist = "whitelist" + pairlist = "pairlist" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index ac6a998c5..b2ec1448e 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -17,8 +17,8 @@ from freqtrade.constants import BuySell, LongShort from freqtrade.data.converter import order_book_to_dataframe from freqtrade.data.dataprovider import DataProvider from freqtrade.edge import Edge -from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode, SignalDirection, - State, TradingMode) +from freqtrade.enums import (ExitCheckTuple, ExitType, LeaderMessageType, RPCMessageType, RunMode, + SignalDirection, State, TradingMode) from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError, InvalidOrderException, PricingError) from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds @@ -257,6 +257,22 @@ class FreqtradeBot(LoggingMixin): self.pairlists.refresh_pairlist() _whitelist = self.pairlists.whitelist + # If replicate leader, broadcast whitelist data + # Should we broadcast before trade pairs are added? What if + # the follower doesn't have trades with those pairs. They would be added for + # no reason. + + # Or should this class be made available to the PairListManager and ran + # when filter_pairlist is called? + if self.replicate_controller: + if self.replicate_controller.is_leader(): + self.replicate_controller.send_message( + { + "data_type": LeaderMessageType.pairlist, + "data": _whitelist + } + ) + # Calculating Edge positioning if self.edge: self.edge.calculate(_whitelist) @@ -267,16 +283,6 @@ class FreqtradeBot(LoggingMixin): # It ensures that candle (OHLCV) data are downloaded for open trades as well _whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist]) - # If replicate leader, broadcast whitelist data - if self.replicate_controller: - if self.replicate_controller.is_leader(): - self.replicate_controller.send_message( - { - "data_type": "whitelist", - "data": _whitelist - } - ) - return _whitelist def get_free_open_trades(self) -> int: diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py index 832c3d5eb..82fc12ff9 100644 --- a/freqtrade/plugins/pairlist/ExternalPairList.py +++ b/freqtrade/plugins/pairlist/ExternalPairList.py @@ -4,6 +4,7 @@ External Pair List provider Provides pair list from Leader data """ import logging +from threading import Event from typing import Any, Dict, List from freqtrade.plugins.pairlist.IPairList import IPairList @@ -13,16 +14,41 @@ logger = logging.getLogger(__name__) class ExternalPairList(IPairList): + """ + PairList plugin for use with replicate follower mode. + Will use pairs given from leader data. + + Usage: + "pairlists": [ + { + "method": "ExternalPairList", + "number_assets": 5, # We can limit the amount of pairs to use from leader + } + ], + """ def __init__(self, exchange, pairlistmanager, config: Dict[str, Any], pairlistconfig: Dict[str, Any], pairlist_pos: int) -> None: super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) - self._num_assets = self._pairlistconfig.get('num_assets') - self._allow_inactive = self._pairlistconfig.get('allow_inactive', False) + # Not sure how to enforce ExternalPairList as the only PairList + + self._num_assets = self._pairlistconfig.get('number_assets') self._leader_pairs: List[str] = [] + self._has_data = Event() + + def _clamped_pairlist(self): + """ + Return the self._leader_pairs pairlist limited to the maximum set num_assets + or the length of it. + """ + length = len(self._leader_pairs) + if self._num_assets: + return self._leader_pairs[:min(length, self._num_assets)] + else: + return self._leader_pairs @property def needstickers(self) -> bool: @@ -40,13 +66,40 @@ class ExternalPairList(IPairList): """ return f"{self.name}" + def add_pairlist_data(self, pairlist: List[str]): + """ + Add pairs from Leader + """ + + # If some pairs were removed on Leader, remove them here + for pair in self._leader_pairs: + if pair not in pairlist: + logger.debug(f"Leader removed pair: {pair}") + self._leader_pairs.remove(pair) + + # Only add new pairs + seen = set(self._leader_pairs) + for pair in pairlist: + if pair in seen: + logger.debug(f"Encountered already existing pair {pair}") + continue + self._leader_pairs.append(pair) + + if not self._has_data.is_set(): + self._has_data.set() + def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: List of pairs """ - pass + if not self._has_data.is_set(): + logger.info("Waiting on pairlists from Leaders...") + self._has_data.wait() + logger.info("Pairlist data received...") + + return self._clamped_pairlist() def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: """ @@ -56,4 +109,4 @@ class ExternalPairList(IPairList): :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: new whitelist """ - pass + return self._clamped_pairlist() diff --git a/freqtrade/rpc/replicate/__init__.py b/freqtrade/rpc/replicate/__init__.py index 80ac0836c..fd718197e 100644 --- a/freqtrade/rpc/replicate/__init__.py +++ b/freqtrade/rpc/replicate/__init__.py @@ -40,6 +40,7 @@ class ReplicateController(RPCHandler): """ super().__init__(rpc, config) + self.freqtrade = rpc._freqtrade self.api_server = api_server if not self.api_server: @@ -122,7 +123,6 @@ class ReplicateController(RPCHandler): raise RuntimeError("Loop must be started before any function can" " be submitted") - logger.debug(f"Running coroutine {repr(coroutine)} in loop") try: return asyncio.run_coroutine_threadsafe(coroutine, self._loop) except Exception as e: @@ -185,6 +185,8 @@ class ReplicateController(RPCHandler): def send_message(self, msg: Dict[str, Any]) -> None: """ Push message through """ + # We should probably do some type of schema validation here + if self.channel_manager.has_channels(): self._send_message(msg) else: @@ -199,7 +201,7 @@ class ReplicateController(RPCHandler): if self._queue: queue = self._queue.sync_q - queue.put(msg) + queue.put(msg) # This will block if the queue is full else: logger.warning("Can not send data, leader loop has not started yet!") @@ -235,7 +237,7 @@ class ReplicateController(RPCHandler): try: await self._broadcast_queue_data() except Exception as e: - logger.error("Exception occurred in leader loop: ") + logger.error("Exception occurred in Leader loop: ") logger.exception(e) async def _broadcast_queue_data(self): @@ -342,10 +344,14 @@ class ReplicateController(RPCHandler): logger.info("Starting rpc.replicate in Follower mode") try: - await self._connect_to_leaders() + results = await self._connect_to_leaders() except Exception as e: - logger.error("Exception occurred in follower loop: ") + logger.error("Exception occurred in Follower loop: ") logger.exception(e) + finally: + for result in results: + if isinstance(result, Exception): + logger.debug(f"Exception in Follower loop: {result}") async def _connect_to_leaders(self): """ @@ -372,7 +378,7 @@ class ReplicateController(RPCHandler): websocket_url = f"{url}?token={token}" - logger.info(f"Attempting to connect to leader at: {url}") + logger.info(f"Attempting to connect to Leader at: {url}") # TODO: limit the amount of connection retries while True: try: @@ -415,9 +421,12 @@ class ReplicateController(RPCHandler): except asyncio.CancelledError: pass - async def _handle_leader_message(self, message): + async def _handle_leader_message(self, message: Dict[str, Any]): type = message.get('data_type') data = message.get('data') - if type == LeaderMessageType.whitelist: - logger.info(f"Received whitelist from Leader: {data}") + logger.info(f"Received message from Leader: {type} - {data}") + + if type == LeaderMessageType.pairlist: + # Add the data to the ExternalPairlist + self.freqtrade.pairlists._pairlist_handlers[0].add_pairlist_data(data) From 665cf4431de06e86d3edf96114c8e3b33341cc07 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 19 Aug 2022 15:49:31 +0200 Subject: [PATCH 031/592] Add explicit test cov. for .range behavior --- tests/strategy/test_interface.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py index 83f7d19b7..65ee05d71 100644 --- a/tests/strategy/test_interface.py +++ b/tests/strategy/test_interface.py @@ -12,7 +12,9 @@ from freqtrade.configuration import TimeRange from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history import load_data from freqtrade.enums import ExitCheckTuple, ExitType, SignalDirection +from freqtrade.enums.hyperoptstate import HyperoptState from freqtrade.exceptions import OperationalException, StrategyError +from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer from freqtrade.optimize.space import SKDecimal from freqtrade.persistence import PairLocks, Trade from freqtrade.resolvers import StrategyResolver @@ -859,7 +861,9 @@ def test_strategy_safe_wrapper_trade_copy(fee): def test_hyperopt_parameters(): + HyperoptStateContainer.set_state(HyperoptState.INDICATORS) from skopt.space import Categorical, Integer, Real + with pytest.raises(OperationalException, match=r"Name is determined.*"): IntParameter(low=0, high=5, default=1, name='hello') @@ -937,6 +941,12 @@ def test_hyperopt_parameters(): assert list(boolpar.range) == [True, False] + HyperoptStateContainer.set_state(HyperoptState.OPTIMIZE) + assert len(list(intpar.range)) == 1 + assert len(list(fltpar.range)) == 1 + assert len(list(catpar.range)) == 1 + assert len(list(boolpar.range)) == 1 + def test_auto_hyperopt_interface(default_conf): default_conf.update({'strategy': 'HyperoptableStrategyV2'}) From aa3da092a0262a1efbf6387fbcadc928b5b04306 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 20 Aug 2022 10:55:52 +0200 Subject: [PATCH 032/592] Dont' use classProperty - that's not supported on 3.8 --- freqtrade/optimize/hyperopt_tools.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py index 7f339eec1..9b022d519 100755 --- a/freqtrade/optimize/hyperopt_tools.py +++ b/freqtrade/optimize/hyperopt_tools.py @@ -35,16 +35,11 @@ def hyperopt_serializer(x): class HyperoptStateContainer(): """ Singleton class to track state of hyperopt""" - __state = HyperoptState.OPTIMIZE + state: HyperoptState = HyperoptState.OPTIMIZE @classmethod def set_state(cls, value: HyperoptState): - cls.__state = value - - @classmethod - @property - def state(cls) -> HyperoptState: - return cls.__state + cls.state = value class HyperoptTools(): From 90c03178b1a8a9ee458b6d46c10525bdd7ff4966 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 20 Aug 2022 17:02:18 +0200 Subject: [PATCH 033/592] provide user directions, clean up strategy, remove unnecessary code. --- config_examples/config_freqai.example.json | 1 - .../templates/FreqaiHybridExampleStrategy.py | 204 +++++++----------- 2 files changed, 82 insertions(+), 123 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index aeb1cb13d..330bcd9f5 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -75,7 +75,6 @@ "weight_factor": 0.9, "principal_component_analysis": false, "use_SVM_to_remove_outliers": true, - "stratify_training_data": 0, "indicator_max_period_candles": 20, "indicator_periods_candles": [10, 20] }, diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index acceccee7..99abf27d4 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -1,64 +1,72 @@ import logging -from datetime import datetime, timedelta -from functools import reduce from typing import Optional import numpy as np import pandas as pd import talib.abstract as ta -from freqtrade.exchange import timeframe_to_prev_date -from freqtrade.persistence import Trade from freqtrade.strategy import (DecimalParameter, IntParameter, IStrategy, merge_informative_pair) -from numpy.lib import math from pandas import DataFrame -from technical import qtpylib logger = logging.getLogger(__name__) class FreqaiExampleHybridStrategy(IStrategy): """ - Example classifier hybrid strategy showing how the user connects their own - IFreqaiModel to the strategy. Namely, the user uses: - self.freqai.start(dataframe, metadata) + Example of a hybrid FreqAI strat, designed to illustrate how a user may employ + FreqAI to bolster a typical Freqtrade strategy. + + Launching this strategy would be: + + freqtrade trade --strategy FreqaiExampleHyridStrategy --strategy-path freqtrade/templates + --freqaimodel CatboostClassifier --config config_examples/config_freqai.example.json + + or the user simply adds this to their config: + + "freqai": { + "enabled": true, + "purge_old_models": true, + "train_period_days": 15, + "identifier": "uniqe-id", + "feature_parameters": { + "include_timeframes": [ + "3m", + "15m", + "1h" + ], + "include_corr_pairlist": [ + "BTC/USDT", + "ETH/USDT" + ], + "label_period_candles": 20, + "include_shifted_candles": 2, + "DI_threshold": 0.9, + "weight_factor": 0.9, + "principal_component_analysis": false, + "use_SVM_to_remove_outliers": true, + "indicator_max_period_candles": 20, + "indicator_periods_candles": [10, 20] + }, + "data_split_parameters": { + "test_size": 0.33, + "random_state": 1 + }, + "model_training_parameters": { + "n_estimators": 800 + } + }, - to make predictions on their data. populate_any_indicators() automatically - generates the variety of features indicated by the user in the - canonical freqtrade configuration file under config['freqai']. - - The underlying original supertrend strat is authored by @juankysoriano (Juan Carlos Soriano) - * github: https://github.com/juankysoriano/ - This strategy is not designed to be used live """ minimal_roi = {"0": 0.1, "30": 0.75, "60": 0.05, "120": 0.025, "240": -1} - plot_config = { - "main_plot": {}, - "subplots": { - "prediction": {"prediction": {"color": "blue"}}, - "target_roi": { - "target_roi": {"color": "brown"}, - }, - "do_predict": { - "do_predict": {"color": "brown"}, - }, - }, - } - process_only_new_candles = True stoploss = -0.1 use_exit_signal = True startup_candle_count: int = 300 can_short = True - linear_roi_offset = DecimalParameter( - 0.00, 0.02, default=0.005, space="sell", optimize=False, load=True - ) - max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) - buy_params = { "buy_m1": 4, "buy_m2": 7, @@ -77,7 +85,7 @@ class FreqaiExampleHybridStrategy(IStrategy): "sell_p2": 18, "sell_p3": 18, } - + buy_m1 = IntParameter(1, 7, default=1) buy_m2 = IntParameter(1, 7, default=3) buy_m3 = IntParameter(1, 7, default=4) @@ -92,6 +100,7 @@ class FreqaiExampleHybridStrategy(IStrategy): sell_p2 = IntParameter(7, 21, default=10) sell_p3 = IntParameter(7, 21, default=10) + # FreqAI required function, leave as is or add you additional informatives to existing structure. def informative_pairs(self): whitelist_pairs = self.dp.current_whitelist() corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] @@ -105,16 +114,15 @@ class FreqaiExampleHybridStrategy(IStrategy): informative_pairs.append((pair, tf)) return informative_pairs + # FreqAI required function, user can add or remove indicators, but general structure + # must stay the same. def populate_any_indicators( self, pair, df, tf, informative=None, set_generalized_indicators=False ): """ - Function designed to automatically generate, name and merge features - from user indicated timeframes in the configuration file. User controls the indicators - passed to the training/prediction by prepending indicators with `'%-' + coin ` - (see convention below). I.e. user should not prepend any supporting metrics - (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the - model. + User feeds these indicators to FreqAI to train a classifier to decide + if the market will go up or down. + :param pair: pair to be used as informative :param df: strategy dataframe which will receive merges from informatives :param tf: timeframe of the dataframe which will modify the feature names @@ -135,34 +143,14 @@ class FreqaiExampleHybridStrategy(IStrategy): informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t) informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t) - informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - - bollinger = qtpylib.bollinger_bands( - qtpylib.typical_price(informative), window=t, stds=2.2 - ) - informative[f"{coin}bb_lowerband-period_{t}"] = bollinger["lower"] - informative[f"{coin}bb_middleband-period_{t}"] = bollinger["mid"] - informative[f"{coin}bb_upperband-period_{t}"] = bollinger["upper"] - - informative[f"%-{coin}bb_width-period_{t}"] = ( - informative[f"{coin}bb_upperband-period_{t}"] - - informative[f"{coin}bb_lowerband-period_{t}"] - ) / informative[f"{coin}bb_middleband-period_{t}"] - informative[f"%-{coin}close-bb_lower-period_{t}"] = ( - informative["close"] / informative[f"{coin}bb_lowerband-period_{t}"] - ) - informative[f"%-{coin}roc-period_{t}"] = ta.ROC(informative, timeperiod=t) - informative[f"%-{coin}relative_volume-period_{t}"] = ( informative["volume"] / informative["volume"].rolling(t).mean() ) - informative[f"%-{coin}pct-change"] = informative["close"].pct_change() - informative[f"%-{coin}raw_volume"] = informative["volume"] - informative[f"%-{coin}raw_price"] = informative["close"] - + # FreqAI needs the following lines in order to detect features and automatically + # expand upon them. indicators = [col for col in informative if col.startswith("%")] # This loop duplicates and shifts all indicators to add a sense of recency to data for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): @@ -178,56 +166,22 @@ class FreqaiExampleHybridStrategy(IStrategy): ] df = df.drop(columns=skip_columns) - # Add generalized indicators here (because in live, it will call this - # function to populate indicators during training). Notice how we ensure not to - # add them multiple times + # User can set the "target" here (in present case it is the + # "up" or "down") if set_generalized_indicators: - df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7 - df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25 - - # Classifiers are typically set up with strings as targets: - df['&s-up_or_down'] = np.where( df["close"].shift(-50) > - df["close"], 'up', 'down') - - # REGRESSOR Model: Can use single or multi traget - # user adds targets here by prepending them with &- (see convention below) - #df["&-s_close"] = ( - # df["close"] - # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - # .mean() - # / df["close"] - # - 1 - #) - # If user wishes to use multiple targets, they can add more by - # appending more columns with '&'. User should keep in mind that multi targets - # requires a multioutput prediction model such as - # templates/CatboostPredictionMultiModel.py, - - # df["&-s_range"] = ( - # df["close"] - # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - # .max() - # - - # df["close"] - # .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - # .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - # .min() - # ) + # User "looks into the future" here to figure out if the future + # will be "up" or "down". This same column name is available to + # the user + df['&s-up_or_down'] = np.where(df["close"].shift(-50) > + df["close"], 'up', 'down') return df def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - # All indicators must be populated by populate_any_indicators() for live functionality - # to work correctly. + # User creates their own custom strat here. Present example is a supertrend + # based strategy. - # the model will return all labels created by user in `populate_any_indicators` - # (& appended targets), an indication of whether or not the prediction should be accepted, - # the target mean/std values for each of the labels created by user in - # `populate_any_indicators()` for each training period. - for multiplier in self.buy_m1.range: for period in self.buy_p1.range: dataframe[f"supertrend_1_buy_{multiplier}_{period}"] = self.supertrend( @@ -270,20 +224,23 @@ class FreqaiExampleHybridStrategy(IStrategy): def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame: + # User now can use their custom strat creation in addition to their + # future prediction "up" or "down". + df.loc[ (df[f"supertrend_1_buy_{self.buy_m1.value}_{self.buy_p1.value}"] == "up") & (df[f"supertrend_2_buy_{self.buy_m2.value}_{self.buy_p2.value}"] == "up") & (df[f"supertrend_3_buy_{self.buy_m3.value}_{self.buy_p3.value}"] == "up") & (df["do_predict"] == 1) & - (df['&s-up_or_down'] == 'up'), + (df['&s-up_or_down'] == 'up'), "enter_long", ] = 1 df.loc[ - (df[f"supertrend_1_sell_{self.sell_m1.value}_{self.sell_p1.value}"] == "down") & - (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down") & - (df[f"supertrend_3_sell_{self.sell_m3.value}_{self.sell_p3.value}"] == "down") & - (df["do_predict"] == 1) & + (df[f"supertrend_1_sell_{self.sell_m1.value}_{self.sell_p1.value}"] == "down") & + (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down") & + (df[f"supertrend_3_sell_{self.sell_m3.value}_{self.sell_p3.value}"] == "down") & + (df["do_predict"] == 1) & (df['&s-up_or_down'] == 'down'), "enter_short", ] = 1 @@ -291,7 +248,7 @@ class FreqaiExampleHybridStrategy(IStrategy): return df def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame: - + df.loc[ (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down"), "exit_long", @@ -308,8 +265,8 @@ class FreqaiExampleHybridStrategy(IStrategy): return int(self.config["timeframe"][:-1]) def confirm_trade_entry(self, pair: str, order_type: str, amount: float, - rate: float, time_in_force: str, current_time, entry_tag, side: str, - **kwargs, ) -> bool: + rate: float, time_in_force: str, current_time, entry_tag, side: str, + **kwargs, ) -> bool: df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) last_candle = df.iloc[-1].squeeze() @@ -322,7 +279,7 @@ class FreqaiExampleHybridStrategy(IStrategy): return False return True - + def leverage(self, pair: str, current_time: datetime, current_rate: float, proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str, **kwargs) -> float: @@ -335,6 +292,7 @@ class FreqaiExampleHybridStrategy(IStrategy): """ def supertrend(self, dataframe: DataFrame, multiplier, period): + df = dataframe.copy() last_row = dataframe.tail(1).index.item() @@ -354,17 +312,19 @@ class FreqaiExampleHybridStrategy(IStrategy): # Compute final upper and lower bands for i in range(period, last_row + 1): - FINAL_UB[i] = BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - 1] or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1] - FINAL_LB[i] = BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - 1] or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1] + FINAL_UB[i] = BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - + 1] or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1] + FINAL_LB[i] = BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - + 1] or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1] # Set the Supertrend value for i in range(period, last_row + 1): ST[i] = FINAL_UB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] <= FINAL_UB[i] else \ - FINAL_LB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] > FINAL_UB[i] else \ + FINAL_LB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] > FINAL_UB[i] else \ FINAL_LB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] >= FINAL_LB[i] else \ - FINAL_UB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] < FINAL_LB[i] else 0.00 + FINAL_UB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] < FINAL_LB[i] else 0.00 df_ST = pd.DataFrame(ST, columns=[st]) - df = pd.concat([df, df_ST],axis=1) + df = pd.concat([df, df_ST], axis=1) # Mark the trend direction up/down df[stx] = np.where((df[st] > 0.00), np.where((df['close'] < df[st]), 'down', 'up'), np.NaN) @@ -372,6 +332,6 @@ class FreqaiExampleHybridStrategy(IStrategy): df.fillna(0, inplace=True) return DataFrame(index=df.index, data={ - 'ST' : df[st], - 'STX' : df[stx] + 'ST': df[st], + 'STX': df[stx] }) From 64b083443752e9aa9af5fd81a2c77cf42db4c690 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 20 Aug 2022 17:04:38 +0200 Subject: [PATCH 034/592] add credit in docstring --- freqtrade/templates/FreqaiHybridExampleStrategy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index 99abf27d4..145590add 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -56,7 +56,7 @@ class FreqaiExampleHybridStrategy(IStrategy): } }, - This strategy is not designed to be used live + Thanks to @smarm and @jooopieeert for developing and sharing the strategy. """ minimal_roi = {"0": 0.1, "30": 0.75, "60": 0.05, "120": 0.025, "240": -1} From 6189aa817ce3dcb6b5185d62350e641d32c41a3e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 20 Aug 2022 19:50:18 +0200 Subject: [PATCH 035/592] Fix HybridExample formatting --- .../templates/FreqaiHybridExampleStrategy.py | 25 ++++++++----------- 1 file changed, 10 insertions(+), 15 deletions(-) diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index 145590add..bb9c37b03 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -1,13 +1,13 @@ import logging -from typing import Optional import numpy as np import pandas as pd import talib.abstract as ta -from freqtrade.strategy import (DecimalParameter, IntParameter, IStrategy, - merge_informative_pair) from pandas import DataFrame +from freqtrade.strategy import IntParameter, IStrategy, merge_informative_pair + + logger = logging.getLogger(__name__) @@ -100,7 +100,7 @@ class FreqaiExampleHybridStrategy(IStrategy): sell_p2 = IntParameter(7, 21, default=10) sell_p3 = IntParameter(7, 21, default=10) - # FreqAI required function, leave as is or add you additional informatives to existing structure. + # FreqAI required function, leave as is or add additional informatives to existing structure. def informative_pairs(self): whitelist_pairs = self.dp.current_whitelist() corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] @@ -120,7 +120,7 @@ class FreqaiExampleHybridStrategy(IStrategy): self, pair, df, tf, informative=None, set_generalized_indicators=False ): """ - User feeds these indicators to FreqAI to train a classifier to decide + User feeds these indicators to FreqAI to train a classifier to decide if the market will go up or down. :param pair: pair to be used as informative @@ -177,6 +177,7 @@ class FreqaiExampleHybridStrategy(IStrategy): return df + # flake8: noqa: C901 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # User creates their own custom strat here. Present example is a supertrend @@ -280,12 +281,6 @@ class FreqaiExampleHybridStrategy(IStrategy): return True - def leverage(self, pair: str, current_time: datetime, current_rate: float, - proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str, - **kwargs) -> float: - - return 1 - """ Supertrend Indicator; adapted for freqtrade, optimized by the math genius. from: Perkmeister#2394 @@ -312,10 +307,10 @@ class FreqaiExampleHybridStrategy(IStrategy): # Compute final upper and lower bands for i in range(period, last_row + 1): - FINAL_UB[i] = BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - - 1] or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1] - FINAL_LB[i] = BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - - 1] or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1] + FINAL_UB[i] = (BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - 1] + or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1]) + FINAL_LB[i] = (BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - 1] + or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1]) # Set the Supertrend value for i in range(period, last_row + 1): From 6f5478cc029bc146e3980affa61dd7956c5cb416 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 21 Aug 2022 22:45:36 -0600 Subject: [PATCH 036/592] DataFrame transmission, strategy follower logic --- freqtrade/data/dataprovider.py | 57 ++++++++++- freqtrade/enums/replicate.py | 1 + freqtrade/freqtradebot.py | 43 +++++++-- freqtrade/misc.py | 22 +++++ .../plugins/pairlist/ExternalPairList.py | 3 +- freqtrade/rpc/replicate/__init__.py | 94 +++++++++++-------- freqtrade/rpc/replicate/channel.py | 16 +++- freqtrade/rpc/replicate/serializer.py | 27 +++++- freqtrade/rpc/replicate/types.py | 3 +- freqtrade/rpc/rpc.py | 39 +++++++- freqtrade/rpc/rpc_manager.py | 13 ++- freqtrade/strategy/interface.py | 92 +++++++++++++++--- requirements-replicate.txt | 1 + 13 files changed, 332 insertions(+), 79 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 21cead77f..3de73bb0d 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -7,6 +7,7 @@ Common Interface for bot and strategy to access data. import logging from collections import deque from datetime import datetime, timezone +from threading import Event from typing import Any, Dict, List, Optional, Tuple from pandas import DataFrame @@ -28,13 +29,16 @@ MAX_DATAFRAME_CANDLES = 1000 class DataProvider: - def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None: + def __init__(self, config: dict, exchange: Optional[Exchange], + pairlists=None, replicate_controller=None) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} self.__slice_index: Optional[int] = None self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {} + self.__external_pairs_df: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} + self.__external_pairs_event: Dict[str, Event] = {} self._msg_queue: deque = deque() self.__msg_cache = PeriodicCache( @@ -63,9 +67,58 @@ class DataProvider: :param dataframe: analyzed dataframe :param candle_type: Any of the enum CandleType (must match trading mode!) """ - self.__cached_pairs[(pair, timeframe, candle_type)] = ( + pair_key = (pair, timeframe, candle_type) + self.__cached_pairs[pair_key] = ( dataframe, datetime.now(timezone.utc)) + def add_external_df( + self, + pair: str, + timeframe: str, + dataframe: DataFrame, + candle_type: CandleType + ) -> None: + """ + Add the DataFrame to the __external_pairs_df. If a pair event exists, + set it to release the main thread from waiting. + """ + pair_key = (pair, timeframe, candle_type) + + # Delete stale data + if pair_key in self.__external_pairs_df: + del self.__external_pairs_df[pair_key] + + self.__external_pairs_df[pair_key] = (dataframe, datetime.now(timezone.utc)) + + pair_event = self.__external_pairs_event.get(pair) + if pair_event: + logger.debug(f"Leader data for pair {pair_key} has been added") + pair_event.set() + + def get_external_df( + self, + pair: str, + timeframe: str, + candle_type: CandleType + ) -> DataFrame: + """ + If the pair exists in __external_pairs_df, return it. If it doesn't, + create a new threading Event in __external_pairs_event and wait on it. + """ + pair_key = (pair, timeframe, candle_type) + if pair_key not in self.__external_pairs_df: + pair_event = Event() + self.__external_pairs_event[pair] = pair_event + + logger.debug(f"Waiting on Leader data for: {pair_key}") + self.__external_pairs_event[pair].wait() + + if pair_key in self.__external_pairs_df: + return self.__external_pairs_df[pair_key] + + # Because of the waiting mechanism, this should never return + return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + def add_pairlisthandler(self, pairlists) -> None: """ Allow adding pairlisthandler after initialization diff --git a/freqtrade/enums/replicate.py b/freqtrade/enums/replicate.py index 73be996c0..8d036f0b9 100644 --- a/freqtrade/enums/replicate.py +++ b/freqtrade/enums/replicate.py @@ -8,3 +8,4 @@ class ReplicateModeType(str, Enum): class LeaderMessageType(str, Enum): pairlist = "pairlist" + analyzed_df = "analyzed_df" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index b2ec1448e..3b850dd4e 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -23,7 +23,7 @@ from freqtrade.exceptions import (DependencyException, ExchangeError, Insufficie InvalidOrderException, PricingError) from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds from freqtrade.exchange.exchange import timeframe_to_next_date -from freqtrade.misc import safe_value_fallback, safe_value_fallback2 +from freqtrade.misc import dataframe_to_json, safe_value_fallback, safe_value_fallback2 from freqtrade.mixins import LoggingMixin from freqtrade.persistence import Order, PairLocks, Trade, init_db from freqtrade.plugins.pairlistmanager import PairListManager @@ -77,6 +77,8 @@ class FreqtradeBot(LoggingMixin): self.replicate_controller = None + self.pairlists = PairListManager(self.exchange, self.config) + # RPC runs in separate threads, can start handling external commands just after # initialization, even before Freqtradebot has a chance to start its throttling, # so anything in the Freqtradebot instance should be ready (initialized), including @@ -84,8 +86,6 @@ class FreqtradeBot(LoggingMixin): # Keep this at the end of this initialization method. self.rpc: RPCManager = RPCManager(self) - self.pairlists = PairListManager(self.exchange, self.config) - self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists) # Attach Dataprovider to strategy instance @@ -93,6 +93,9 @@ class FreqtradeBot(LoggingMixin): # Attach Wallets to strategy instance self.strategy.wallets = self.wallets + # Attach ReplicateController to the strategy + # self.strategy.replicate_controller = self.replicate_controller + # Initializing Edge only if enabled self.edge = Edge(self.config, self.exchange, self.strategy) if \ self.config.get('edge', {}).get('enabled', False) else None @@ -194,7 +197,28 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - self.strategy.analyze(self.active_pair_whitelist) + if self.replicate_controller: + if not self.replicate_controller.is_leader(): + # Run Follower mode analyzing + leader_pairs = self.pairlists._whitelist + self.strategy.analyze_external(self.active_pair_whitelist, leader_pairs) + else: + # We are leader, make sure to pass callback func to emit data + def emit_on_finish(pair, dataframe, timeframe, candle_type): + logger.debug(f"Emitting dataframe for {pair}") + return self.rpc.emit_data( + { + "data_type": LeaderMessageType.analyzed_df, + "data": { + "key": (pair, timeframe, candle_type), + "value": dataframe_to_json(dataframe) + } + } + ) + + self.strategy.analyze(self.active_pair_whitelist, finish_callback=emit_on_finish) + else: + self.strategy.analyze(self.active_pair_whitelist) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace @@ -264,14 +288,13 @@ class FreqtradeBot(LoggingMixin): # Or should this class be made available to the PairListManager and ran # when filter_pairlist is called? + if self.replicate_controller: if self.replicate_controller.is_leader(): - self.replicate_controller.send_message( - { - "data_type": LeaderMessageType.pairlist, - "data": _whitelist - } - ) + self.rpc.emit_data({ + "data_type": LeaderMessageType.pairlist, + "data": _whitelist + }) # Calculating Edge positioning if self.edge: diff --git a/freqtrade/misc.py b/freqtrade/misc.py index c3968e61c..bc644a7ec 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -10,6 +10,7 @@ from typing import Any, Iterator, List from typing.io import IO from urllib.parse import urlparse +import pandas import rapidjson from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN @@ -249,3 +250,24 @@ def parse_db_uri_for_logging(uri: str): return uri pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0] return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@') + + +def dataframe_to_json(dataframe: pandas.DataFrame) -> str: + """ + Serialize a DataFrame for transmission over the wire using JSON + :param dataframe: A pandas DataFrame + :returns: A JSON string of the pandas DataFrame + """ + return dataframe.to_json(orient='records') + + +def json_to_dataframe(data: str) -> pandas.DataFrame: + """ + Deserialize JSON into a DataFrame + :param data: A JSON string + :returns: A pandas DataFrame from the JSON string + """ + dataframe = pandas.read_json(data) + dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True) + + return dataframe diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py index 82fc12ff9..bd36c7cf3 100644 --- a/freqtrade/plugins/pairlist/ExternalPairList.py +++ b/freqtrade/plugins/pairlist/ExternalPairList.py @@ -81,11 +81,10 @@ class ExternalPairList(IPairList): seen = set(self._leader_pairs) for pair in pairlist: if pair in seen: - logger.debug(f"Encountered already existing pair {pair}") continue self._leader_pairs.append(pair) - if not self._has_data.is_set(): + if not self._has_data.is_set() and len(self._leader_pairs) > 0: self._has_data.set() def gen_pairlist(self, tickers: Dict) -> List[str]: diff --git a/freqtrade/rpc/replicate/__init__.py b/freqtrade/rpc/replicate/__init__.py index fd718197e..5cc2ae6a9 100644 --- a/freqtrade/rpc/replicate/__init__.py +++ b/freqtrade/rpc/replicate/__init__.py @@ -5,6 +5,7 @@ import asyncio import logging import secrets import socket +import traceback from threading import Event, Thread from typing import Any, Coroutine, Dict, Union @@ -17,6 +18,7 @@ from freqtrade.enums import LeaderMessageType, ReplicateModeType, RPCMessageType from freqtrade.rpc import RPC, RPCHandler from freqtrade.rpc.replicate.channel import ChannelManager from freqtrade.rpc.replicate.thread_queue import Queue as ThreadedQueue +from freqtrade.rpc.replicate.types import MessageType from freqtrade.rpc.replicate.utils import is_websocket_alive @@ -79,11 +81,11 @@ class ReplicateController(RPCHandler): self.mode = ReplicateModeType[self.replicate_config.get('mode', 'leader').lower()] self.leaders_list = self.replicate_config.get('leaders', []) - self.push_throttle_secs = self.replicate_config.get('push_throttle_secs', 1) + self.push_throttle_secs = self.replicate_config.get('push_throttle_secs', 0.1) self.reply_timeout = self.replicate_config.get('follower_reply_timeout', 10) self.ping_timeout = self.replicate_config.get('follower_ping_timeout', 2) - self.sleep_time = self.replicate_config.get('follower_sleep_time', 1) + self.sleep_time = self.replicate_config.get('follower_sleep_time', 5) if self.mode == ReplicateModeType.follower and len(self.leaders_list) == 0: raise ValueError("You must specify at least 1 leader in follower mode.") @@ -143,6 +145,8 @@ class ReplicateController(RPCHandler): except asyncio.CancelledError: pass + except Exception: + pass finally: self._loop.stop() @@ -170,22 +174,19 @@ class ReplicateController(RPCHandler): self._thread.join() - def send_msg(self, msg: Dict[str, Any]) -> None: + def send_msg(self, msg: MessageType) -> None: """ Support RPC calls """ if msg["type"] == RPCMessageType.EMIT_DATA: - self.send_message( - { - "data_type": msg.get("data_type"), - "data": msg.get("data") - } - ) + message = msg.get("message") + if message: + self.send_message(message) + else: + logger.error(f"Message is empty! {msg}") - def send_message(self, msg: Dict[str, Any]) -> None: - """ Push message through """ - - # We should probably do some type of schema validation here + def send_message(self, msg: MessageType) -> None: + """ Broadcast message over all channels if there are any """ if self.channel_manager.has_channels(): self._send_message(msg) @@ -193,12 +194,11 @@ class ReplicateController(RPCHandler): logger.debug("No listening followers, skipping...") pass - def _send_message(self, msg: Dict[Any, Any]): + def _send_message(self, msg: MessageType): """ Add data to the internal queue to be broadcasted. This func will block if the queue is full. This is meant to be called in the main thread. """ - if self._queue: queue = self._queue.sync_q queue.put(msg) # This will block if the queue is full @@ -226,7 +226,6 @@ class ReplicateController(RPCHandler): This starts all of the leader coros and registers the endpoint on the ApiServer """ - logger.info("Running rpc.replicate in Leader mode") logger.info("-" * 15) logger.info(f"API_KEY: {self.secret_api_key}") @@ -253,16 +252,17 @@ class ReplicateController(RPCHandler): # Get data from queue data = await async_queue.get() - logger.info(f"Found data - broadcasting: {data}") - # Broadcast it to everyone await self.channel_manager.broadcast(data) # Sleep await asyncio.sleep(self.push_throttle_secs) + except asyncio.CancelledError: # Silently stop pass + except Exception as e: + logger.exception(e) async def get_api_token( self, @@ -285,7 +285,6 @@ class ReplicateController(RPCHandler): :param path: The endpoint path """ - if not self.api_server: raise RuntimeError("The leader needs the ApiServer to be active") @@ -312,10 +311,13 @@ class ReplicateController(RPCHandler): # we may not have to send initial data at all. Further testing # required. + await self.send_initial_data(channel) + # Keep connection open until explicitly closed, and sleep try: while not channel.is_closed(): - await channel.recv() + request = await channel.recv() + logger.info(f"Follower request - {request}") except WebSocketDisconnect: # Handle client disconnects @@ -332,6 +334,17 @@ class ReplicateController(RPCHandler): logger.error(f"Failed to serve - {websocket.client}") await self.channel_manager.on_disconnect(websocket) + async def send_initial_data(self, channel): + logger.info("Sending initial data through channel") + + # We first send pairlist data + initial_data = { + "data_type": LeaderMessageType.pairlist, + "data": self.freqtrade.pairlists.whitelist + } + + await channel.send(initial_data) + # -------------------------------FOLLOWER LOGIC---------------------------- async def follower_loop(self): @@ -340,18 +353,27 @@ class ReplicateController(RPCHandler): This starts all of the follower connection coros """ - logger.info("Starting rpc.replicate in Follower mode") - try: - results = await self._connect_to_leaders() - except Exception as e: - logger.error("Exception occurred in Follower loop: ") - logger.exception(e) - finally: - for result in results: - if isinstance(result, Exception): - logger.debug(f"Exception in Follower loop: {result}") + responses = await self._connect_to_leaders() + + # Eventually add the ability to send requests to the Leader + # await self._send_requests() + + for result in responses: + if isinstance(result, Exception): + logger.debug(f"Exception in Follower loop: {result}") + traceback_message = ''.join(traceback.format_tb(result.__traceback__)) + logger.error(traceback_message) + + async def _handle_leader_message(self, message: MessageType): + """ + Handle message received from a Leader + """ + type = message.get("data_type") + data = message.get("data") + + self._rpc._handle_emitted_data(type, data) async def _connect_to_leaders(self): """ @@ -375,7 +397,6 @@ class ReplicateController(RPCHandler): """ try: url, token = leader["url"], leader["token"] - websocket_url = f"{url}?token={token}" logger.info(f"Attempting to connect to Leader at: {url}") @@ -384,6 +405,7 @@ class ReplicateController(RPCHandler): try: async with websockets.connect(websocket_url) as ws: channel = await self.channel_manager.on_connect(ws) + logger.info(f"Connection to Leader at {url} successful") while True: try: data = await asyncio.wait_for( @@ -420,13 +442,3 @@ class ReplicateController(RPCHandler): except asyncio.CancelledError: pass - - async def _handle_leader_message(self, message: Dict[str, Any]): - type = message.get('data_type') - data = message.get('data') - - logger.info(f"Received message from Leader: {type} - {data}") - - if type == LeaderMessageType.pairlist: - # Add the data to the ExternalPairlist - self.freqtrade.pairlists._pairlist_handlers[0].add_pairlist_data(data) diff --git a/freqtrade/rpc/replicate/channel.py b/freqtrade/rpc/replicate/channel.py index 7aa316ff5..62ed3e025 100644 --- a/freqtrade/rpc/replicate/channel.py +++ b/freqtrade/rpc/replicate/channel.py @@ -2,7 +2,7 @@ import logging from typing import Type from freqtrade.rpc.replicate.proxy import WebSocketProxy -from freqtrade.rpc.replicate.serializer import JSONWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.replicate.serializer import MsgPackWebSocketSerializer, WebSocketSerializer from freqtrade.rpc.replicate.types import WebSocketType @@ -17,7 +17,7 @@ class WebSocketChannel: def __init__( self, websocket: WebSocketType, - serializer_cls: Type[WebSocketSerializer] = JSONWebSocketSerializer + serializer_cls: Type[WebSocketSerializer] = MsgPackWebSocketSerializer ): # The WebSocket object self._websocket = WebSocketProxy(websocket) @@ -34,6 +34,7 @@ class WebSocketChannel: """ Send data on the wrapped websocket """ + # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") await self._wrapped_ws.send(data) async def recv(self): @@ -116,6 +117,17 @@ class ChannelManager: # Handle cannot send after close cases await self.on_disconnect(websocket) + async def send_direct(self, channel, data): + """ + Send data directly through direct_channel only + + :param direct_channel: The WebSocketChannel object to send data through + :param data: The data to send + """ + # We iterate over the channels to get reference to the websocket object + # so we can disconnect incase of failure + await channel.send(data) + def has_channels(self): """ Flag for more than 0 channels diff --git a/freqtrade/rpc/replicate/serializer.py b/freqtrade/rpc/replicate/serializer.py index 717458f09..98bdc8934 100644 --- a/freqtrade/rpc/replicate/serializer.py +++ b/freqtrade/rpc/replicate/serializer.py @@ -1,9 +1,16 @@ import json +import logging from abc import ABC, abstractmethod +import msgpack +import orjson + from freqtrade.rpc.replicate.proxy import WebSocketProxy +logger = logging.getLogger(__name__) + + class WebSocketSerializer(ABC): def __init__(self, websocket: WebSocketProxy): self._websocket: WebSocketProxy = websocket @@ -34,9 +41,25 @@ class WebSocketSerializer(ABC): class JSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data): - # json expects string not bytes return json.dumps(data) def _deserialize(self, data): - # The WebSocketSerializer gives bytes not string return json.loads(data) + + +class ORJSONWebSocketSerializer(WebSocketSerializer): + ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY + + def _serialize(self, data): + return orjson.dumps(data, option=self.ORJSON_OPTIONS) + + def _deserialize(self, data): + return orjson.loads(data, option=self.ORJSON_OPTIONS) + + +class MsgPackWebSocketSerializer(WebSocketSerializer): + def _serialize(self, data): + return msgpack.packb(data, use_bin_type=True) + + def _deserialize(self, data): + return msgpack.unpackb(data, raw=False) diff --git a/freqtrade/rpc/replicate/types.py b/freqtrade/rpc/replicate/types.py index 763147196..814fe6649 100644 --- a/freqtrade/rpc/replicate/types.py +++ b/freqtrade/rpc/replicate/types.py @@ -1,7 +1,8 @@ -from typing import TypeVar +from typing import Any, Dict, TypeVar from fastapi import WebSocket as FastAPIWebSocket from websockets import WebSocketClientProtocol as WebSocket WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) +MessageType = Dict[str, Any] diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index ed7f13a96..2c7b2ec72 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -19,12 +19,12 @@ from freqtrade.configuration.timerange import TimeRange from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT from freqtrade.data.history import load_data from freqtrade.data.metrics import calculate_max_drawdown -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State, - TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, LeaderMessageType, + SignalDirection, State, TradingMode) from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler -from freqtrade.misc import decimals_per_coin, shorten_date +from freqtrade.misc import decimals_per_coin, json_to_dataframe, shorten_date from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1089,3 +1089,36 @@ class RPC: 'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT), 'last_process_ts': int(last_p.timestamp()), } + + def _handle_emitted_data(self, type, data): + """ + Handles the emitted data from the Leaders + + :param type: The data_type of the data + :param data: The data + """ + logger.debug(f"Handling emitted data of type ({type})") + + if type == LeaderMessageType.pairlist: + pairlist = data + + logger.debug(pairlist) + + # Add the pairlist data to the ExternalPairList object + external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] + external_pairlist.add_pairlist_data(pairlist) + + elif type == LeaderMessageType.analyzed_df: + # Convert the dataframe back from json + key, value = data["key"], data["value"] + + pair, timeframe, candle_type = key + dataframe = json_to_dataframe(value) + + dataprovider = self._freqtrade.dataprovider + + logger.debug(f"Received analyzed dataframe for {pair}") + logger.debug(dataframe.tail()) + + # Add the dataframe to the dataprovider + dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 8eaec21ea..3d561cc8e 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -20,6 +20,7 @@ class RPCManager: def __init__(self, freqtrade) -> None: """ Initializes all enabled rpc modules """ self.registered_modules: List[RPCHandler] = [] + self._freqtrade = freqtrade self._rpc = RPC(freqtrade) config = freqtrade.config # Enable telegram @@ -82,7 +83,8 @@ class RPCManager: 'status': 'stopping bot' } """ - logger.info('Sending rpc message: %s', msg) + if msg.get("type") != RPCMessageType.EMIT_DATA: + logger.info('Sending rpc message: %s', msg) if 'pair' in msg: msg.update({ 'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair']) @@ -141,3 +143,12 @@ class RPCManager: 'type': RPCMessageType.STARTUP, 'status': f'Using Protections: \n{prots}' }) + + def emit_data(self, data: Dict[str, Any]): + """ + Send a message via RPC with type RPCMessageType.EMIT_DATA + """ + self.send_msg({ + "type": RPCMessageType.EMIT_DATA, + "message": data + }) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 79dbd4c69..ddd10dd8e 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -5,7 +5,7 @@ This module defines the interface to apply for strategies import logging from abc import ABC, abstractmethod from datetime import datetime, timedelta, timezone -from typing import Dict, List, Optional, Tuple, Union +from typing import Callable, Dict, List, Optional, Tuple, Union import arrow from pandas import DataFrame @@ -18,6 +18,7 @@ from freqtrade.enums.runmode import RunMode from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds from freqtrade.persistence import Order, PairLocks, Trade +from freqtrade.rpc.replicate import ReplicateController from freqtrade.strategy.hyper import HyperStrategyMixin from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators, _create_and_merge_informative_pair, @@ -110,6 +111,7 @@ class IStrategy(ABC, HyperStrategyMixin): # the dataprovider (dp) (access to other candles, historic data, ...) # and wallets - access to the current balance. dp: DataProvider + replicate_controller: Optional[ReplicateController] wallets: Optional[Wallets] = None # Filled from configuration stake_currency: str @@ -123,6 +125,7 @@ class IStrategy(ABC, HyperStrategyMixin): self.config = config # Dict to determine if analysis is necessary self._last_candle_seen_per_pair: Dict[str, datetime] = {} + self._last_candle_seen_external: Dict[str, datetime] = {} super().__init__(config) # Gather informative pairs from @informative-decorated methods. @@ -678,7 +681,12 @@ class IStrategy(ABC, HyperStrategyMixin): lock_time = timeframe_to_next_date(self.timeframe, candle_date) return PairLocks.is_pair_locked(pair, lock_time, side=side) - def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + def analyze_ticker( + self, + dataframe: DataFrame, + metadata: dict, + populate_indicators: bool = True + ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame add several TA indicators and entry order signal to it @@ -687,12 +695,19 @@ class IStrategy(ABC, HyperStrategyMixin): :return: DataFrame of candle (OHLCV) data with indicator data and signals added """ logger.debug("TA Analysis Launched") - dataframe = self.advise_indicators(dataframe, metadata) + if populate_indicators: + dataframe = self.advise_indicators(dataframe, metadata) dataframe = self.advise_entry(dataframe, metadata) dataframe = self.advise_exit(dataframe, metadata) return dataframe - def _analyze_ticker_internal(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + def _analyze_ticker_internal( + self, + dataframe: DataFrame, + metadata: dict, + external_data: bool = False, + finish_callback: Optional[Callable] = None, + ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame add several TA indicators and buy signal to it @@ -707,12 +722,19 @@ class IStrategy(ABC, HyperStrategyMixin): # always run if process_only_new_candles is set to false if (not self.process_only_new_candles or self._last_candle_seen_per_pair.get(pair, None) != dataframe.iloc[-1]['date']): + + populate_indicators = not external_data # Defs that only make change on new candle data. - dataframe = self.analyze_ticker(dataframe, metadata) + dataframe = self.analyze_ticker(dataframe, metadata, populate_indicators) + self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date'] - self.dp._set_cached_df( - pair, self.timeframe, dataframe, - candle_type=self.config.get('candle_type_def', CandleType.SPOT)) + + candle_type = self.config.get('candle_type_def', CandleType.SPOT) + self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) + + if finish_callback: + finish_callback(pair, dataframe, self.timeframe, candle_type) + else: logger.debug("Skipping TA Analysis for already analyzed candle") dataframe[SignalType.ENTER_LONG.value] = 0 @@ -726,16 +748,25 @@ class IStrategy(ABC, HyperStrategyMixin): return dataframe - def analyze_pair(self, pair: str) -> None: + def analyze_pair( + self, + pair: str, + external_data: bool = False, + finish_callback: Optional[Callable] = None, + ) -> None: """ Fetch data for this pair from dataprovider and analyze. Stores the dataframe into the dataprovider. The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`. :param pair: Pair to analyze. """ - dataframe = self.dp.ohlcv( - pair, self.timeframe, candle_type=self.config.get('candle_type_def', CandleType.SPOT) - ) + candle_type = self.config.get('candle_type_def', CandleType.SPOT) + + if not external_data: + dataframe = self.dp.ohlcv(pair, self.timeframe, candle_type) + else: + dataframe, last_analyzed = self.dp.get_external_df(pair, self.timeframe, candle_type) + if not isinstance(dataframe, DataFrame) or dataframe.empty: logger.warning('Empty candle (OHLCV) data for pair %s', pair) return @@ -745,7 +776,7 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = strategy_safe_wrapper( self._analyze_ticker_internal, message="" - )(dataframe, {'pair': pair}) + )(dataframe, {'pair': pair}, external_data, finish_callback) self.assert_df(dataframe, df_len, df_close, df_date) except StrategyError as error: @@ -756,15 +787,43 @@ class IStrategy(ABC, HyperStrategyMixin): logger.warning('Empty dataframe for pair %s', pair) return - def analyze(self, pairs: List[str]) -> None: + def analyze( + self, + pairs: List[str], + finish_callback: Optional[Callable] = None + ) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze """ for pair in pairs: + self.analyze_pair(pair, finish_callback=finish_callback) + + def analyze_external(self, pairs: List[str], leader_pairs: List[str]) -> None: + """ + Analyze the pre-populated dataframes from the Leader + + :param pairs: The active pair whitelist + :param leader_pairs: The list of pairs from the Leaders + """ + + # Get the extra pairs not listed in Leader pairs, and process + # them normally. + # List order is not preserved when doing this! + # We use ^ instead of - for symmetric difference + # What do we do with these? + extra_pairs = list(set(pairs) ^ set(leader_pairs)) + # These would be the pairs that we have trades in, which means + # we would have to analyze them normally + + for pair in leader_pairs: + # Analyze the pairs, but get the dataframe from the external data + self.analyze_pair(pair, external_data=True) + + for pair in extra_pairs: self.analyze_pair(pair) - @staticmethod + @ staticmethod def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]: """ keep some data for dataframes """ return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1] @@ -1185,6 +1244,9 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = _create_and_merge_informative_pair( self, dataframe, metadata, inf_data, populate_fn) + # If in follower mode, get analyzed dataframe from leader df's in dp + # otherise run populate_indicators + return self.populate_indicators(dataframe, metadata) def advise_entry(self, dataframe: DataFrame, metadata: dict) -> DataFrame: diff --git a/requirements-replicate.txt b/requirements-replicate.txt index 7ee351d9d..2c994ea2f 100644 --- a/requirements-replicate.txt +++ b/requirements-replicate.txt @@ -3,3 +3,4 @@ # Required for follower websockets +msgpack From 4fa01548f6c6ac49e63b7a4960ede268c0bf3aab Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 21 Aug 2022 22:49:42 -0600 Subject: [PATCH 037/592] Remove old var from strategy interface --- freqtrade/strategy/interface.py | 1 - 1 file changed, 1 deletion(-) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index ddd10dd8e..1084838ec 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -125,7 +125,6 @@ class IStrategy(ABC, HyperStrategyMixin): self.config = config # Dict to determine if analysis is necessary self._last_candle_seen_per_pair: Dict[str, datetime] = {} - self._last_candle_seen_external: Dict[str, datetime] = {} super().__init__(config) # Gather informative pairs from @informative-decorated methods. From ac42c0153da716e0a70abd7a8024d8d3162e4ba6 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 22 Aug 2022 18:19:07 +0200 Subject: [PATCH 038/592] deprecate indicator_max_period_candles, automatically compute startup candles for FreqAI backtesting. --- config_examples/config_freqai.example.json | 2 +- docs/freqai.md | 2 +- docs/strategy-customization.md | 2 +- freqtrade/data/dataprovider.py | 13 +++++++- freqtrade/freqai/data_kitchen.py | 32 +++++++++---------- freqtrade/optimize/backtesting.py | 33 ++++++++++++++------ freqtrade/strategy/interface.py | 1 + freqtrade/templates/FreqaiExampleStrategy.py | 3 +- tests/freqai/conftest.py | 1 - tests/freqai/test_freqai_backtesting.py | 10 +++--- 10 files changed, 61 insertions(+), 38 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index aeb1cb13d..093e11b2a 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -9,6 +9,7 @@ "dry_run": true, "timeframe": "3m", "dry_run_wallet": 1000, + "startup_candle_count": 20, "cancel_open_orders_on_exit": true, "unfilledtimeout": { "entry": 10, @@ -53,7 +54,6 @@ ], "freqai": { "enabled": true, - "startup_candles": 10000, "purge_old_models": true, "train_period_days": 15, "backtest_period_days": 7, diff --git a/docs/freqai.md b/docs/freqai.md index b22e1cd31..f3c9021ed 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -113,7 +113,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points.
**Datatype:** boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reproducibility. But these and all others can be added/changed in this dictionary.
**Datatype:** dictionary. | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing.
**Datatype:** positive integer. -| `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
**Datatype:** positive integer. +| `indicator_max_period_candles` | **Deprecated in favor of** strategy set `startup_candle_count`, however, both configuration parameters provide the same functionality; the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
**Datatype:** positive integer. | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set.
**Datatype:** list of positive integers. | `use_DBSCAN_to_remove_outliers` | Inactive by default. If true, FreqAI clusters data using DBSCAN to identify and remove outliers from training and prediction data.
**Datatype:** float (fraction of 1). | | **Data split parameters** diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index 260e253c4..a452b8f05 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -166,7 +166,7 @@ Additional technical libraries can be installed as necessary, or custom indicato Most indicators have an instable startup period, in which they are either not available (NaN), or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be. To account for this, the strategy can be assigned the `startup_candle_count` attribute. -This should be set to the maximum number of candles that the strategy requires to calculate stable indicators. +This should be set to the maximum number of candles that the strategy requires to calculate stable indicators. In the case where a user includes higher timeframes with informative pairs, the `startup_candle_count` does not necessarily change. The value is the maximum period (in candles) that any of the informatives timeframes need to compute stable indicators. In this example strategy, this should be set to 100 (`startup_candle_count = 100`), since the longest needed history is 100 candles. diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 21cead77f..529a12690 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -92,7 +92,7 @@ class DataProvider: 'timerange') is None else str(self._config.get('timerange'))) # Move informative start time respecting startup_candle_count timerange.subtract_start( - timeframe_to_seconds(str(timeframe)) * self._config.get('startup_candle_count', 0) + self.get_required_startup_seconds(str(timeframe)) ) self.__cached_pairs_backtesting[saved_pair] = load_pair_history( pair=pair, @@ -105,6 +105,17 @@ class DataProvider: ) return self.__cached_pairs_backtesting[saved_pair].copy() + def get_required_startup_seconds(self, timeframe: str) -> int: + tf_seconds = timeframe_to_seconds(timeframe) + base_seconds = tf_seconds * self._config.get('startup_candle_count', 0) + if not self._config['freqai']['enabled']: + return base_seconds + else: + train_seconds = self._config['freqai']['train_period_days'] * 86400 + # multiplied by safety factor of 2 because FreqAI users + # typically do not know the correct window. + return base_seconds * 2 + int(train_seconds) + def get_pair_dataframe( self, pair: str, diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 6541261eb..c768fc30e 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -20,6 +20,8 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data from freqtrade.exceptions import OperationalException from freqtrade.exchange import timeframe_to_seconds +from freqtrade.exchange.exchange import market_is_active +from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist from freqtrade.strategy.interface import IStrategy @@ -834,9 +836,7 @@ class FreqaiDataKitchen: # We notice that users like to use exotic indicators where # they do not know the required timeperiod. Here we include a factor # of safety by multiplying the user considered "max" by 2. - max_period = self.freqai_config["feature_parameters"].get( - "indicator_max_period_candles", 20 - ) * 2 + max_period = self.config.get('startup_candle_count', 20) * 2 additional_seconds = max_period * max_tf_seconds if trained_timestamp != 0: @@ -1015,12 +1015,15 @@ def download_all_data_for_training(timerange: TimeRange, and training the model. :param dp: DataProvider instance attached to the strategy """ - all_pairs = copy.deepcopy( - config["freqai"]["feature_parameters"].get("include_corr_pairlist", []) - ) - for pair in config.get("exchange", "").get("pair_whitelist"): - if pair not in all_pairs: - all_pairs.append(pair) + + if dp._exchange is not None: + markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) + or config.get('include_inactive')] + else: + # This should not occur: + raise OperationalException('No exchange object found.') + + all_pairs = dynamic_expand_pairlist(config, markets) new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) if not dp._exchange: @@ -1048,7 +1051,6 @@ def get_required_data_timerange( user. """ time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - trained_timerange = TimeRange() data_load_timerange = TimeRange() timeframes = config["freqai"]["feature_parameters"].get("include_timeframes") @@ -1059,15 +1061,9 @@ def get_required_data_timerange( if secs > max_tf_seconds: max_tf_seconds = secs - max_period = config["freqai"]["feature_parameters"].get( - "indicator_max_period_candles", 20 - ) * 2 - additional_seconds = max_period * max_tf_seconds + max_period = config.get('startup_candle_count', 20) * 2 - trained_timerange.startts = int( - time - config["freqai"].get("train_period_days", 0) * SECONDS_IN_DAY - ) - trained_timerange.stopts = int(time) + additional_seconds = max_period * max_tf_seconds data_load_timerange.startts = int( time diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 6528481d5..8f0302ada 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -211,21 +211,21 @@ class Backtesting: """ self.progress.init_step(BacktestState.DATALOAD, 1) - if self.config.get('freqai', {}).get('enabled', False): - startup_candles = int(self.config.get('freqai', {}).get('startup_candles', 0)) - if not startup_candles: - raise OperationalException('FreqAI backtesting module requires user set ' - 'startup_candles in config.') - self.required_startup += int(self.config.get('freqai', {}).get('startup_candles', 0)) - logger.info(f'Increasing startup_candle_count for freqai to {self.required_startup}') - self.config['startup_candle_count'] = self.required_startup + # if self.config.get('freqai', {}).get('enabled', False): + # startup_candles = int(self.config.get('freqai', {}).get('startup_candles', 0)) + # if not startup_candles: + # raise OperationalException('FreqAI backtesting module requires user set ' + # 'startup_candles in config.') + # self.required_startup += int(self.config.get('freqai', {}).get('startup_candles', 0)) + # logger.info(f'Increasing startup_candle_count for freqai to {self.required_startup}') + # self.config['startup_candle_count'] = self.required_startup data = history.load_data( datadir=self.config['datadir'], pairs=self.pairlists.whitelist, timeframe=self.timeframe, timerange=self.timerange, - startup_candles=self.required_startup, + startup_candles=self.get_required_startup(self.timeframe), fail_without_data=True, data_format=self.config.get('dataformat_ohlcv', 'json'), candle_type=self.config.get('candle_type_def', CandleType.SPOT) @@ -244,6 +244,21 @@ class Backtesting: self.progress.set_new_value(1) return data, self.timerange + def get_required_startup(self, timeframe: str) -> int: + if not self.config['freqai']['enabled']: + return self.required_startup + else: + if not self.config['startup_candle_count']: + raise OperationalException('FreqAI backtesting module requires strategy ' + 'set startup_candle_count.') + tf_seconds = timeframe_to_seconds(timeframe) + train_candles = self.config['freqai']['train_period_days'] * 86400 / tf_seconds + # multiplied by safety factor of 2 because FreqAI users + # typically do not know the correct window. + total_candles = self.required_startup * 2 + train_candles + logger.info(f'Increasing startup_candle_count for freqai to {total_candles}') + return total_candles + def load_bt_data_detail(self) -> None: """ Loads backtest detail data (smaller timeframe) if necessary. diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 1e51701f7..284727d2b 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -163,6 +163,7 @@ class IStrategy(ABC, HyperStrategyMixin): ) data_load_timerange = get_required_data_timerange(self.config) download_all_data_for_training(data_load_timerange, self.dp, self.config) + else: # Gracious failures if freqAI is disabled but "start" is called. class DummyClass(): diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index 5810e7881..aa584bfbc 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -43,7 +43,8 @@ class FreqaiExampleStrategy(IStrategy): process_only_new_candles = True stoploss = -0.05 use_exit_signal = True - startup_candle_count: int = 300 + # this is the maximum period fed to talib (timeframe independent) + startup_candle_count: int = 20 can_short = False linear_roi_offset = DecimalParameter( diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 6ace13677..113cb3a79 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -44,7 +44,6 @@ def freqai_conf(default_conf, tmpdir): "principal_component_analysis": False, "use_SVM_to_remove_outliers": True, "stratify_training_data": 0, - "indicator_max_period_candles": 10, "indicator_periods_candles": [10], }, "data_split_parameters": {"test_size": 0.33, "random_state": 1}, diff --git a/tests/freqai/test_freqai_backtesting.py b/tests/freqai/test_freqai_backtesting.py index 273791609..c8a51edb0 100644 --- a/tests/freqai/test_freqai_backtesting.py +++ b/tests/freqai/test_freqai_backtesting.py @@ -48,10 +48,10 @@ def test_freqai_backtest_load_data(freqai_conf, mocker, caplog): assert log_has_re('Increasing startup_candle_count for freqai to.*', caplog) - del freqai_conf['freqai']['startup_candles'] - backtesting = Backtesting(freqai_conf) - with pytest.raises(OperationalException, - match=r'FreqAI backtesting module.*startup_candles in config.'): - backtesting.load_bt_data() + # del freqai_conf['freqai']['startup_candles'] + # backtesting = Backtesting(freqai_conf) + # with pytest.raises(OperationalException, + # match=r'FreqAI backtesting module.*startup_candles in config.'): + # backtesting.load_bt_data() Backtesting.cleanup() From 32faad93336f83c9969de9c955a5487c7af7f2d3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 24 Aug 2022 20:36:08 +0200 Subject: [PATCH 039/592] Fix backtest calculation problem with DCA closes #7287 --- freqtrade/optimize/backtesting.py | 21 +++++++++++++++------ freqtrade/persistence/trade_model.py | 5 ++--- 2 files changed, 17 insertions(+), 9 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index e81698eef..725ff2406 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -25,7 +25,7 @@ from freqtrade.enums import (BacktestState, CandleType, ExitCheckTuple, ExitType from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds from freqtrade.exchange.exchange import (amount_to_contracts, amount_to_precision, - contracts_to_amount) + contracts_to_amount, price_to_precision) from freqtrade.mixins import LoggingMixin from freqtrade.optimize.backtest_caching import get_strategy_run_id from freqtrade.optimize.bt_progress import BTProgress @@ -658,7 +658,13 @@ class Backtesting: self.order_id_counter += 1 exit_candle_time = sell_row[DATE_IDX].to_pydatetime() order_type = self.strategy.order_types['exit'] - amount = amount or trade.amount + # amount = amount or trade.amount + amount = contracts_to_amount( + amount_to_precision( + amount_to_contracts(amount or trade.amount, trade.contract_size), + trade.amount_precision, self.precision_mode), + trade.contract_size) + rate = price_to_precision(close_rate, trade.price_precision, self.precision_mode) order = Order( id=self.order_id_counter, ft_trade_id=trade.id, @@ -672,12 +678,12 @@ class Backtesting: side=trade.exit_side, order_type=order_type, status="open", - price=close_rate, - average=close_rate, + price=rate, + average=rate, amount=amount, filled=0, remaining=amount, - cost=amount * close_rate, + cost=amount * rate, ) trade.orders.append(order) return trade @@ -823,7 +829,10 @@ class Backtesting: if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount): self.order_id_counter += 1 base_currency = self.exchange.get_pair_base_currency(pair) + precision_price = self.exchange.get_precision_price(pair) + propose_rate = price_to_precision(propose_rate, precision_price, self.precision_mode) amount_p = (stake_amount / propose_rate) * leverage + contract_size = self.exchange.get_contract_size(pair) precision_amount = self.exchange.get_precision_amount(pair) amount = contracts_to_amount( @@ -863,7 +872,7 @@ class Backtesting: leverage=leverage, # interest_rate=interest_rate, amount_precision=precision_amount, - price_precision=self.exchange.get_precision_price(pair), + price_precision=precision_price, precision_mode=self.precision_mode, contract_size=contract_size, orders=[], diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index b25487993..9ab608321 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -847,7 +847,7 @@ class LocalTrade(): avg_price = FtPrecise(0.0) close_profit = 0.0 close_profit_abs = 0.0 - + profit = None for o in self.orders: if o.ft_is_open or not o.filled: continue @@ -874,8 +874,6 @@ class LocalTrade(): close_profit_abs += profit close_profit = self.calc_profit_ratio( exit_rate, amount=exit_amount, open_rate=avg_price) - if current_amount <= ZERO: - profit = close_profit_abs else: total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price) @@ -900,6 +898,7 @@ class LocalTrade(): # Close profit abs / maximum owned # Fees are considered as they are part of close_profit_abs self.close_profit = (close_profit_abs / total_stake) * self.leverage + self.close_profit_abs = close_profit_abs def select_order_by_order_id(self, order_id: str) -> Optional[Order]: """ From 592373f096ce80c458673b92715b82b09e6b57eb Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 24 Aug 2022 18:30:30 -0600 Subject: [PATCH 040/592] Remove pairlist waiting, add .db files to .gitignore --- .gitignore | 1 + freqtrade/plugins/pairlist/ExternalPairList.py | 10 ---------- 2 files changed, 1 insertion(+), 10 deletions(-) diff --git a/.gitignore b/.gitignore index df2121990..015c0a8d9 100644 --- a/.gitignore +++ b/.gitignore @@ -115,3 +115,4 @@ target/ !config_examples/config_freqai.example.json *-config.json +*.db* diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py index bd36c7cf3..40e3f9a7f 100644 --- a/freqtrade/plugins/pairlist/ExternalPairList.py +++ b/freqtrade/plugins/pairlist/ExternalPairList.py @@ -4,7 +4,6 @@ External Pair List provider Provides pair list from Leader data """ import logging -from threading import Event from typing import Any, Dict, List from freqtrade.plugins.pairlist.IPairList import IPairList @@ -37,7 +36,6 @@ class ExternalPairList(IPairList): self._num_assets = self._pairlistconfig.get('number_assets') self._leader_pairs: List[str] = [] - self._has_data = Event() def _clamped_pairlist(self): """ @@ -84,20 +82,12 @@ class ExternalPairList(IPairList): continue self._leader_pairs.append(pair) - if not self._has_data.is_set() and len(self._leader_pairs) > 0: - self._has_data.set() - def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: List of pairs """ - if not self._has_data.is_set(): - logger.info("Waiting on pairlists from Leaders...") - self._has_data.wait() - logger.info("Pairlist data received...") - return self._clamped_pairlist() def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: From d474111a65a07c3133d7e2502be648b362fb72ce Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 24 Aug 2022 22:42:29 -0600 Subject: [PATCH 041/592] Renamed to external signals, controller class refactored --- freqtrade/constants.py | 8 +- freqtrade/data/dataprovider.py | 33 +- freqtrade/enums/__init__.py | 2 +- .../enums/{replicate.py => externalsignal.py} | 2 +- freqtrade/freqtradebot.py | 19 +- .../plugins/pairlist/ExternalPairList.py | 4 +- freqtrade/rpc/external_signal/__init__.py | 5 + .../{replicate => external_signal}/channel.py | 6 +- .../controller.py} | 288 +++++++++--------- .../{replicate => external_signal}/proxy.py | 2 +- .../serializer.py | 2 +- .../thread_queue.py | 0 .../{replicate => external_signal}/types.py | 0 .../{replicate => external_signal}/utils.py | 0 freqtrade/rpc/rpc.py | 10 +- freqtrade/rpc/rpc_manager.py | 12 +- freqtrade/strategy/interface.py | 4 +- 17 files changed, 203 insertions(+), 194 deletions(-) rename freqtrade/enums/{replicate.py => externalsignal.py} (80%) create mode 100644 freqtrade/rpc/external_signal/__init__.py rename freqtrade/rpc/{replicate => external_signal}/channel.py (94%) rename freqtrade/rpc/{replicate/__init__.py => external_signal/controller.py} (74%) rename freqtrade/rpc/{replicate => external_signal}/proxy.py (96%) rename freqtrade/rpc/{replicate => external_signal}/serializer.py (96%) rename freqtrade/rpc/{replicate => external_signal}/thread_queue.py (100%) rename freqtrade/rpc/{replicate => external_signal}/types.py (100%) rename freqtrade/rpc/{replicate => external_signal}/utils.py (100%) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 55363cca1..ad0758e22 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -245,7 +245,7 @@ CONF_SCHEMA = { 'exchange': {'$ref': '#/definitions/exchange'}, 'edge': {'$ref': '#/definitions/edge'}, 'freqai': {'$ref': '#/definitions/freqai'}, - 'replicate': {'$ref': '#/definitions/replicate'}, + 'external_signal': {'$ref': '#/definitions/external_signal'}, 'experimental': { 'type': 'object', 'properties': { @@ -487,7 +487,7 @@ CONF_SCHEMA = { }, 'required': ['process_throttle_secs', 'allowed_risk'] }, - 'replicate': { + 'external_signal': { 'type': 'object', 'properties': { 'enabled': {'type': 'boolean', 'default': False}, @@ -495,14 +495,14 @@ CONF_SCHEMA = { 'type': 'string', 'enum': FOLLOWER_MODE_OPTIONS }, - 'api_key': {'type': 'string', 'default': ''}, + 'api_token': {'type': 'string', 'default': ''}, 'leaders': { 'type': 'array', 'items': { 'type': 'object', 'properties': { 'url': {'type': 'string', 'default': ''}, - 'token': {'type': 'string', 'default': ''}, + 'api_token': {'type': 'string', 'default': ''}, } } }, diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 3de73bb0d..036005c84 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -29,8 +29,7 @@ MAX_DATAFRAME_CANDLES = 1000 class DataProvider: - def __init__(self, config: dict, exchange: Optional[Exchange], - pairlists=None, replicate_controller=None) -> None: + def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists @@ -99,25 +98,33 @@ class DataProvider: self, pair: str, timeframe: str, - candle_type: CandleType + candle_type: CandleType, + wait: bool = True ) -> DataFrame: """ - If the pair exists in __external_pairs_df, return it. If it doesn't, - create a new threading Event in __external_pairs_event and wait on it. + If the pair exists in __external_pairs_df, return it. + If it doesn't, and wait is False, then return an empty df with the columns filled. + If it doesn't, and wait is True (default) create a new threading Event + in __external_pairs_event and wait on it. """ pair_key = (pair, timeframe, candle_type) + if pair_key not in self.__external_pairs_df: - pair_event = Event() - self.__external_pairs_event[pair] = pair_event + if wait: + pair_event = Event() + self.__external_pairs_event[pair] = pair_event - logger.debug(f"Waiting on Leader data for: {pair_key}") - self.__external_pairs_event[pair].wait() + logger.debug(f"Waiting on Leader data for: {pair_key}") + self.__external_pairs_event[pair].wait(timeout=5) - if pair_key in self.__external_pairs_df: - return self.__external_pairs_df[pair_key] + if pair_key not in self.__external_pairs_df: + # Return empty dataframe but with expected columns merged and filled with NaN + return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + else: + # Return empty dataframe but with expected columns merged and filled with NaN + return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) - # Because of the waiting mechanism, this should never return - return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + return self.__external_pairs_df[pair_key] def add_pairlisthandler(self, pairlists) -> None: """ diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index e1057208a..913ef82dd 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -3,9 +3,9 @@ from freqtrade.enums.backteststate import BacktestState from freqtrade.enums.candletype import CandleType from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType +from freqtrade.enums.externalsignal import ExternalSignalModeType, LeaderMessageType from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues -from freqtrade.enums.replicate import LeaderMessageType, ReplicateModeType from freqtrade.enums.rpcmessagetype import RPCMessageType from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType diff --git a/freqtrade/enums/replicate.py b/freqtrade/enums/externalsignal.py similarity index 80% rename from freqtrade/enums/replicate.py rename to freqtrade/enums/externalsignal.py index 8d036f0b9..4695a4eab 100644 --- a/freqtrade/enums/replicate.py +++ b/freqtrade/enums/externalsignal.py @@ -1,7 +1,7 @@ from enum import Enum -class ReplicateModeType(str, Enum): +class ExternalSignalModeType(str, Enum): leader = "leader" follower = "follower" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 3b850dd4e..9704b7e08 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -75,7 +75,7 @@ class FreqtradeBot(LoggingMixin): PairLocks.timeframe = self.config['timeframe'] - self.replicate_controller = None + self.external_signal_controller = None self.pairlists = PairListManager(self.exchange, self.config) @@ -93,9 +93,6 @@ class FreqtradeBot(LoggingMixin): # Attach Wallets to strategy instance self.strategy.wallets = self.wallets - # Attach ReplicateController to the strategy - # self.strategy.replicate_controller = self.replicate_controller - # Initializing Edge only if enabled self.edge = Edge(self.config, self.exchange, self.strategy) if \ self.config.get('edge', {}).get('enabled', False) else None @@ -197,8 +194,8 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - if self.replicate_controller: - if not self.replicate_controller.is_leader(): + if self.external_signal_controller: + if not self.external_signal_controller.is_leader(): # Run Follower mode analyzing leader_pairs = self.pairlists._whitelist self.strategy.analyze_external(self.active_pair_whitelist, leader_pairs) @@ -281,16 +278,14 @@ class FreqtradeBot(LoggingMixin): self.pairlists.refresh_pairlist() _whitelist = self.pairlists.whitelist - # If replicate leader, broadcast whitelist data - # Should we broadcast before trade pairs are added? What if - # the follower doesn't have trades with those pairs. They would be added for - # no reason. + # If external signal leader, broadcast whitelist data + # Should we broadcast before trade pairs are added? # Or should this class be made available to the PairListManager and ran # when filter_pairlist is called? - if self.replicate_controller: - if self.replicate_controller.is_leader(): + if self.external_signal_controller: + if self.external_signal_controller.is_leader(): self.rpc.emit_data({ "data_type": LeaderMessageType.pairlist, "data": _whitelist diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py index 40e3f9a7f..27a328060 100644 --- a/freqtrade/plugins/pairlist/ExternalPairList.py +++ b/freqtrade/plugins/pairlist/ExternalPairList.py @@ -14,7 +14,7 @@ logger = logging.getLogger(__name__) class ExternalPairList(IPairList): """ - PairList plugin for use with replicate follower mode. + PairList plugin for use with external signal follower mode. Will use pairs given from leader data. Usage: @@ -67,6 +67,8 @@ class ExternalPairList(IPairList): def add_pairlist_data(self, pairlist: List[str]): """ Add pairs from Leader + + :param pairlist: List of pairs """ # If some pairs were removed on Leader, remove them here diff --git a/freqtrade/rpc/external_signal/__init__.py b/freqtrade/rpc/external_signal/__init__.py new file mode 100644 index 000000000..c1b05b3f0 --- /dev/null +++ b/freqtrade/rpc/external_signal/__init__.py @@ -0,0 +1,5 @@ +# flake8: noqa: F401 +from freqtrade.rpc.external_signal.controller import ExternalSignalController + + +__all__ = ('ExternalSignalController') diff --git a/freqtrade/rpc/replicate/channel.py b/freqtrade/rpc/external_signal/channel.py similarity index 94% rename from freqtrade/rpc/replicate/channel.py rename to freqtrade/rpc/external_signal/channel.py index 62ed3e025..585b6bae5 100644 --- a/freqtrade/rpc/replicate/channel.py +++ b/freqtrade/rpc/external_signal/channel.py @@ -1,9 +1,9 @@ import logging from typing import Type -from freqtrade.rpc.replicate.proxy import WebSocketProxy -from freqtrade.rpc.replicate.serializer import MsgPackWebSocketSerializer, WebSocketSerializer -from freqtrade.rpc.replicate.types import WebSocketType +from freqtrade.rpc.external_signal.proxy import WebSocketProxy +from freqtrade.rpc.external_signal.serializer import MsgPackWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.external_signal.types import WebSocketType logger = logging.getLogger(__name__) diff --git a/freqtrade/rpc/replicate/__init__.py b/freqtrade/rpc/external_signal/controller.py similarity index 74% rename from freqtrade/rpc/replicate/__init__.py rename to freqtrade/rpc/external_signal/controller.py index 5cc2ae6a9..af91a67b7 100644 --- a/freqtrade/rpc/replicate/__init__.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -5,8 +5,7 @@ import asyncio import logging import secrets import socket -import traceback -from threading import Event, Thread +from threading import Thread from typing import Any, Coroutine, Dict, Union import websockets @@ -14,18 +13,18 @@ from fastapi import Depends from fastapi import WebSocket as FastAPIWebSocket from fastapi import WebSocketDisconnect, status -from freqtrade.enums import LeaderMessageType, ReplicateModeType, RPCMessageType +from freqtrade.enums import ExternalSignalModeType, LeaderMessageType, RPCMessageType from freqtrade.rpc import RPC, RPCHandler -from freqtrade.rpc.replicate.channel import ChannelManager -from freqtrade.rpc.replicate.thread_queue import Queue as ThreadedQueue -from freqtrade.rpc.replicate.types import MessageType -from freqtrade.rpc.replicate.utils import is_websocket_alive +from freqtrade.rpc.external_signal.channel import ChannelManager +from freqtrade.rpc.external_signal.thread_queue import Queue as ThreadedQueue +from freqtrade.rpc.external_signal.types import MessageType +from freqtrade.rpc.external_signal.utils import is_websocket_alive logger = logging.getLogger(__name__) -class ReplicateController(RPCHandler): +class ExternalSignalController(RPCHandler): """ This class handles all websocket communication """ def __init__( @@ -35,9 +34,10 @@ class ReplicateController(RPCHandler): api_server: Union[Any, None] = None ) -> None: """ - Init the ReplicateRPC class, and init the super class RPCHandler + Init the ExternalSignalController class, and init the super class RPCHandler :param rpc: instance of RPC Helper class :param config: Configuration object + :param api_server: The ApiServer object :return: None """ super().__init__(rpc, config) @@ -46,48 +46,50 @@ class ReplicateController(RPCHandler): self.api_server = api_server if not self.api_server: - raise RuntimeError("The API server must be enabled for replicate to work") + raise RuntimeError("The API server must be enabled for external signals to work") self._loop = None self._running = False self._thread = None self._queue = None - self._stop_event = Event() - self._follower_tasks = None + self._main_task = None + self._sub_tasks = None self.channel_manager = ChannelManager() - self.replicate_config = config.get('replicate', {}) + self.external_signal_config = config.get('external_signal', {}) # What the config should look like - # "replicate": { + # "external_signal": { # "enabled": true, # "mode": "follower", # "leaders": [ # { - # "url": "ws://localhost:8080/replicate/ws", - # "token": "test" + # "url": "ws://localhost:8080/signals/ws", + # "api_token": "test" # } # ] # } - # "replicate": { + # "external_signal": { # "enabled": true, # "mode": "leader", - # "api_key": "test" + # "api_token": "test" # } - self.mode = ReplicateModeType[self.replicate_config.get('mode', 'leader').lower()] + self.mode = ExternalSignalModeType[ + self.external_signal_config.get('mode', 'leader').lower() + ] - self.leaders_list = self.replicate_config.get('leaders', []) - self.push_throttle_secs = self.replicate_config.get('push_throttle_secs', 0.1) + self.leaders_list = self.external_signal_config.get('leaders', []) + self.push_throttle_secs = self.external_signal_config.get('push_throttle_secs', 0.1) - self.reply_timeout = self.replicate_config.get('follower_reply_timeout', 10) - self.ping_timeout = self.replicate_config.get('follower_ping_timeout', 2) - self.sleep_time = self.replicate_config.get('follower_sleep_time', 5) + self.reply_timeout = self.external_signal_config.get('follower_reply_timeout', 10) + self.ping_timeout = self.external_signal_config.get('follower_ping_timeout', 2) + self.sleep_time = self.external_signal_config.get('follower_sleep_time', 5) - if self.mode == ReplicateModeType.follower and len(self.leaders_list) == 0: + if self.mode == ExternalSignalModeType.follower and len(self.leaders_list) == 0: raise ValueError("You must specify at least 1 leader in follower mode.") # This is only used by the leader, the followers use the tokens specified @@ -95,12 +97,23 @@ class ReplicateController(RPCHandler): # If you do not specify an API key in the config, one will be randomly # generated and logged on startup default_api_key = secrets.token_urlsafe(16) - self.secret_api_key = self.replicate_config.get('api_key', default_api_key) + self.secret_api_key = self.external_signal_config.get('api_token', default_api_key) self.start_threaded_loop() - self.start() + def is_leader(self): + """ + Leader flag + """ + return self.enabled() and self.mode == ExternalSignalModeType.leader + + def enabled(self): + """ + Enabled flag + """ + return self.external_signal_config.get('enabled', False) + def start_threaded_loop(self): """ Start the main internal loop in another thread to run coroutines @@ -125,36 +138,29 @@ class ReplicateController(RPCHandler): raise RuntimeError("Loop must be started before any function can" " be submitted") - try: - return asyncio.run_coroutine_threadsafe(coroutine, self._loop) - except Exception as e: - logger.error(f"Error running coroutine - {str(e)}") - return None - - async def main_loop(self): - """ - Main loop coro - - Start the loop based on what mode we're in - """ - try: - if self.mode == ReplicateModeType.leader: - await self.leader_loop() - elif self.mode == ReplicateModeType.follower: - await self.follower_loop() - - except asyncio.CancelledError: - pass - except Exception: - pass - finally: - self._loop.stop() + return asyncio.run_coroutine_threadsafe(coroutine, self._loop) def start(self): """ Start the controller main loop """ - self.submit_coroutine(self.main_loop()) + self._main_task = self.submit_coroutine(self.main()) + + async def shutdown(self): + """ + Shutdown all tasks and close up + """ + logger.info("Stopping rpc.externalsignalcontroller") + + # Flip running flag + self._running = False + + # Cancel sub tasks + for task in self._sub_tasks: + task.cancel() + + # Then disconnect all channels + await self.channel_manager.disconnect_all() def cleanup(self) -> None: """ @@ -162,18 +168,44 @@ class ReplicateController(RPCHandler): """ if self._thread: if self._loop.is_running(): - - self._running = False - - # Tell all coroutines submitted to the loop they're cancelled - pending = asyncio.all_tasks(loop=self._loop) - for task in pending: - task.cancel() - - self._loop.call_soon_threadsafe(self.channel_manager.disconnect_all) - + self._main_task.cancel() self._thread.join() + async def main(self): + """ + Main coro + + Start the loop based on what mode we're in + """ + try: + if self.mode == ExternalSignalModeType.leader: + logger.info("Starting rpc.externalsignalcontroller in Leader mode") + + await self.run_leader_mode() + elif self.mode == ExternalSignalModeType.follower: + logger.info("Starting rpc.externalsignalcontroller in Follower mode") + + await self.run_follower_mode() + + except asyncio.CancelledError: + # We're cancelled + await self.shutdown() + except Exception as e: + # Log the error + logger.error(f"Exception occurred in main task: {e}") + logger.exception(e) + finally: + # This coroutine is the last thing to be ended, so it should stop the loop + self._loop.stop() + + def log_api_token(self): + """ + Log the API token + """ + logger.info("-" * 15) + logger.info(f"API_KEY: {self.secret_api_key}") + logger.info("-" * 15) + def send_msg(self, msg: MessageType) -> None: """ Support RPC calls @@ -186,7 +218,9 @@ class ReplicateController(RPCHandler): logger.error(f"Message is empty! {msg}") def send_message(self, msg: MessageType) -> None: - """ Broadcast message over all channels if there are any """ + """ + Broadcast message over all channels if there are any + """ if self.channel_manager.has_channels(): self._send_message(msg) @@ -205,39 +239,60 @@ class ReplicateController(RPCHandler): else: logger.warning("Can not send data, leader loop has not started yet!") - def is_leader(self): - """ - Leader flag - """ - return self.enabled() and self.mode == ReplicateModeType.leader + async def send_initial_data(self, channel): + logger.info("Sending initial data through channel") - def enabled(self): - """ - Enabled flag - """ - return self.replicate_config.get('enabled', False) + # We first send pairlist data + # We should move this to a func in the RPC object + initial_data = { + "data_type": LeaderMessageType.pairlist, + "data": self.freqtrade.pairlists.whitelist + } - # ----------------------- LEADER LOGIC ------------------------------ + await channel.send(initial_data) - async def leader_loop(self): + async def _handle_leader_message(self, message: MessageType): + """ + Handle message received from a Leader + """ + type = message.get("data_type") + data = message.get("data") + + self._rpc._handle_emitted_data(type, data) + + # ---------------------------------------------------------------------- + + async def run_leader_mode(self): """ Main leader coroutine This starts all of the leader coros and registers the endpoint on the ApiServer """ - logger.info("Running rpc.replicate in Leader mode") - logger.info("-" * 15) - logger.info(f"API_KEY: {self.secret_api_key}") - logger.info("-" * 15) - self.register_leader_endpoint() + self.log_api_token() - try: - await self._broadcast_queue_data() - except Exception as e: - logger.error("Exception occurred in Leader loop: ") - logger.exception(e) + self._sub_tasks = [ + self._loop.create_task(self._broadcast_queue_data()) + ] + + return await asyncio.gather(*self._sub_tasks) + + async def run_follower_mode(self): + """ + Main follower coroutine + + This starts all of the follower connection coros + """ + + rpc_lock = asyncio.Lock() + + self._sub_tasks = [ + self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) + for leader in self.leaders_list + ] + + return await asyncio.gather(*self._sub_tasks) async def _broadcast_queue_data(self): """ @@ -261,8 +316,6 @@ class ReplicateController(RPCHandler): except asyncio.CancelledError: # Silently stop pass - except Exception as e: - logger.exception(e) async def get_api_token( self, @@ -279,7 +332,7 @@ class ReplicateController(RPCHandler): logger.info("Denying websocket request...") await websocket.close(code=status.WS_1008_POLICY_VIOLATION) - def register_leader_endpoint(self, path: str = "/replicate/ws"): + def register_leader_endpoint(self, path: str = "/signals/ws"): """ Attach and start the main leader loop to the ApiServer @@ -334,73 +387,16 @@ class ReplicateController(RPCHandler): logger.error(f"Failed to serve - {websocket.client}") await self.channel_manager.on_disconnect(websocket) - async def send_initial_data(self, channel): - logger.info("Sending initial data through channel") - - # We first send pairlist data - initial_data = { - "data_type": LeaderMessageType.pairlist, - "data": self.freqtrade.pairlists.whitelist - } - - await channel.send(initial_data) - - # -------------------------------FOLLOWER LOGIC---------------------------- - - async def follower_loop(self): - """ - Main follower coroutine - - This starts all of the follower connection coros - """ - logger.info("Starting rpc.replicate in Follower mode") - - responses = await self._connect_to_leaders() - - # Eventually add the ability to send requests to the Leader - # await self._send_requests() - - for result in responses: - if isinstance(result, Exception): - logger.debug(f"Exception in Follower loop: {result}") - traceback_message = ''.join(traceback.format_tb(result.__traceback__)) - logger.error(traceback_message) - - async def _handle_leader_message(self, message: MessageType): - """ - Handle message received from a Leader - """ - type = message.get("data_type") - data = message.get("data") - - self._rpc._handle_emitted_data(type, data) - - async def _connect_to_leaders(self): - """ - For each leader in `self.leaders_list` create a connection and - listen for data. - """ - rpc_lock = asyncio.Lock() - - logger.info("Starting connections to Leaders...") - - self.follower_tasks = [ - self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) - for leader in self.leaders_list - ] - return await asyncio.gather(*self.follower_tasks, return_exceptions=True) - async def _handle_leader_connection(self, leader, lock): """ Given a leader, connect and wait on data. If connection is lost, it will attempt to reconnect. """ try: - url, token = leader["url"], leader["token"] + url, token = leader["url"], leader["api_token"] websocket_url = f"{url}?token={token}" logger.info(f"Attempting to connect to Leader at: {url}") - # TODO: limit the amount of connection retries while True: try: async with websockets.connect(websocket_url) as ws: diff --git a/freqtrade/rpc/replicate/proxy.py b/freqtrade/rpc/external_signal/proxy.py similarity index 96% rename from freqtrade/rpc/replicate/proxy.py rename to freqtrade/rpc/external_signal/proxy.py index aae536b6d..36ff4a74e 100644 --- a/freqtrade/rpc/replicate/proxy.py +++ b/freqtrade/rpc/external_signal/proxy.py @@ -3,7 +3,7 @@ from typing import Union from fastapi import WebSocket as FastAPIWebSocket from websockets import WebSocketClientProtocol as WebSocket -from freqtrade.rpc.replicate.types import WebSocketType +from freqtrade.rpc.external_signal.types import WebSocketType class WebSocketProxy: diff --git a/freqtrade/rpc/replicate/serializer.py b/freqtrade/rpc/external_signal/serializer.py similarity index 96% rename from freqtrade/rpc/replicate/serializer.py rename to freqtrade/rpc/external_signal/serializer.py index 98bdc8934..2a0f53037 100644 --- a/freqtrade/rpc/replicate/serializer.py +++ b/freqtrade/rpc/external_signal/serializer.py @@ -5,7 +5,7 @@ from abc import ABC, abstractmethod import msgpack import orjson -from freqtrade.rpc.replicate.proxy import WebSocketProxy +from freqtrade.rpc.external_signal.proxy import WebSocketProxy logger = logging.getLogger(__name__) diff --git a/freqtrade/rpc/replicate/thread_queue.py b/freqtrade/rpc/external_signal/thread_queue.py similarity index 100% rename from freqtrade/rpc/replicate/thread_queue.py rename to freqtrade/rpc/external_signal/thread_queue.py diff --git a/freqtrade/rpc/replicate/types.py b/freqtrade/rpc/external_signal/types.py similarity index 100% rename from freqtrade/rpc/replicate/types.py rename to freqtrade/rpc/external_signal/types.py diff --git a/freqtrade/rpc/replicate/utils.py b/freqtrade/rpc/external_signal/utils.py similarity index 100% rename from freqtrade/rpc/replicate/utils.py rename to freqtrade/rpc/external_signal/utils.py diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 2c7b2ec72..68871a15a 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1109,16 +1109,22 @@ class RPC: external_pairlist.add_pairlist_data(pairlist) elif type == LeaderMessageType.analyzed_df: + # Convert the dataframe back from json key, value = data["key"], data["value"] pair, timeframe, candle_type = key - dataframe = json_to_dataframe(value) - dataprovider = self._freqtrade.dataprovider + # Skip any pairs that we don't have in the pairlist? + # leader_pairlist = self._freqtrade.pairlists._whitelist + # if pair not in leader_pairlist: + # return + + dataframe = json_to_dataframe(value) logger.debug(f"Received analyzed dataframe for {pair}") logger.debug(dataframe.tail()) # Add the dataframe to the dataprovider + dataprovider = self._freqtrade.dataprovider dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 3d561cc8e..0a0e285a4 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -54,14 +54,14 @@ class RPCManager: # Enable Replicate mode # For this to be enabled, the API server must also be enabled - if config.get('replicate', {}).get('enabled', False): - logger.info('Enabling rpc.replicate') - from freqtrade.rpc.replicate import ReplicateController - replicate_rpc = ReplicateController(self._rpc, config, apiserver) - self.registered_modules.append(replicate_rpc) + if config.get('external_signal', {}).get('enabled', False): + logger.info('Enabling RPC.ExternalSignalController') + from freqtrade.rpc.external_signal import ExternalSignalController + external_signal_rpc = ExternalSignalController(self._rpc, config, apiserver) + self.registered_modules.append(external_signal_rpc) # Attach the controller to FreqTrade - freqtrade.replicate_controller = replicate_rpc + freqtrade.external_signal_controller = external_signal_rpc apiserver.start_api() diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 1084838ec..22a10b4d3 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -18,7 +18,6 @@ from freqtrade.enums.runmode import RunMode from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds from freqtrade.persistence import Order, PairLocks, Trade -from freqtrade.rpc.replicate import ReplicateController from freqtrade.strategy.hyper import HyperStrategyMixin from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators, _create_and_merge_informative_pair, @@ -111,7 +110,6 @@ class IStrategy(ABC, HyperStrategyMixin): # the dataprovider (dp) (access to other candles, historic data, ...) # and wallets - access to the current balance. dp: DataProvider - replicate_controller: Optional[ReplicateController] wallets: Optional[Wallets] = None # Filled from configuration stake_currency: str @@ -764,7 +762,7 @@ class IStrategy(ABC, HyperStrategyMixin): if not external_data: dataframe = self.dp.ohlcv(pair, self.timeframe, candle_type) else: - dataframe, last_analyzed = self.dp.get_external_df(pair, self.timeframe, candle_type) + dataframe, _ = self.dp.get_external_df(pair, self.timeframe, candle_type) if not isinstance(dataframe, DataFrame) or dataframe.empty: logger.warning('Empty candle (OHLCV) data for pair %s', pair) From 3e786a9b8b791f06c1cf24e7af738ea29f23dc75 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 24 Aug 2022 22:44:22 -0600 Subject: [PATCH 042/592] added example configs --- .gitignore | 2 + config_examples/config_follower.example.json | 85 +++++++++++++++++ config_examples/config_leader.example.json | 97 ++++++++++++++++++++ 3 files changed, 184 insertions(+) create mode 100644 config_examples/config_follower.example.json create mode 100644 config_examples/config_leader.example.json diff --git a/.gitignore b/.gitignore index 015c0a8d9..b8c4c3846 100644 --- a/.gitignore +++ b/.gitignore @@ -113,6 +113,8 @@ target/ !config_examples/config_full.example.json !config_examples/config_kraken.example.json !config_examples/config_freqai.example.json +!config_examples/config_leader.example.json +!config_examples/config_follower.example.json *-config.json *.db* diff --git a/config_examples/config_follower.example.json b/config_examples/config_follower.example.json new file mode 100644 index 000000000..5317c8df2 --- /dev/null +++ b/config_examples/config_follower.example.json @@ -0,0 +1,85 @@ + +{ + "db_url": "sqlite:///follower.db", + "strategy": "SampleStrategy", + "max_open_trades": 3, + "stake_currency": "USDT", + "stake_amount": 100, + "tradable_balance_ratio": 0.99, + "fiat_display_currency": "USD", + "dry_run": true, + "cancel_open_orders_on_exit": false, + "trading_mode": "spot", + "margin_mode": "", + "unfilledtimeout": { + "entry": 10, + "exit": 10, + "exit_timeout_count": 0, + "unit": "minutes" + }, + "entry_pricing": { + "price_side": "same", + "use_order_book": true, + "order_book_top": 1, + "price_last_balance": 0.0, + "check_depth_of_market": { + "enabled": false, + "bids_to_ask_delta": 1 + } + }, + "exit_pricing":{ + "price_side": "same", + "use_order_book": true, + "order_book_top": 1 + }, + "exchange": { + "name": "kucoin", + "key": "", + "secret": "", + "password": "", + "ccxt_config": {}, + "ccxt_async_config": {}, + "pair_whitelist": [ + ], + "pair_blacklist": [ + ] + }, + "pairlists": [ + { + "method": "ExternalPairList", + "number_assets": 5, + } + ], + "telegram": { + "enabled": false, + "token": "", + "chat_id": "" + }, + "api_server": { + "enabled": true, + "listen_ip_address": "127.0.0.1", + "listen_port": 8081, + "verbosity": "error", + "enable_openapi": false, + "jwt_secret_key": "fcc24d31d6581ad2c90c3fc438c8a8b2ccce1393126959934568707f0bd2d647", + "CORS_origins": [], + "username": "freqtrader", + "password": "testing123" + }, + "external_signal": { + "enabled": true, + "mode": "follower", + "leaders": [ + { + "url": "ws://localhost:8080/signals/ws", + "api_token": "testtoken" + } + ] + }, + "bot_name": "freqtrade", + "initial_state": "running", + "force_entry_enable": false, + "internals": { + "process_throttle_secs": 5, + } +} diff --git a/config_examples/config_leader.example.json b/config_examples/config_leader.example.json new file mode 100644 index 000000000..5103fdbd4 --- /dev/null +++ b/config_examples/config_leader.example.json @@ -0,0 +1,97 @@ + +{ + "db_url": "sqlite:///leader.db", + "strategy": "SampleStrategy", + "max_open_trades": 3, + "stake_currency": "USDT", + "stake_amount": 100, + "tradable_balance_ratio": 0.99, + "fiat_display_currency": "USD", + "dry_run": true, + "cancel_open_orders_on_exit": false, + "trading_mode": "spot", + "margin_mode": "", + "unfilledtimeout": { + "entry": 10, + "exit": 10, + "exit_timeout_count": 0, + "unit": "minutes" + }, + "entry_pricing": { + "price_side": "same", + "use_order_book": true, + "order_book_top": 1, + "price_last_balance": 0.0, + "check_depth_of_market": { + "enabled": false, + "bids_to_ask_delta": 1 + } + }, + "exit_pricing":{ + "price_side": "same", + "use_order_book": true, + "order_book_top": 1 + }, + "exchange": { + "name": "kucoin", + "key": "", + "secret": "", + "password": "", + "ccxt_config": {}, + "ccxt_async_config": {}, + "pair_whitelist": [ + ], + "pair_blacklist": [ + ] + }, + "pairlists": [ + { + "method": "VolumePairList", + "number_assets": 20, + "sort_key": "quoteVolume", + "min_value": 0, + "refresh_period": 1800 + } + ], + "edge": { + "enabled": false, + "process_throttle_secs": 3600, + "calculate_since_number_of_days": 7, + "allowed_risk": 0.01, + "stoploss_range_min": -0.01, + "stoploss_range_max": -0.1, + "stoploss_range_step": -0.01, + "minimum_winrate": 0.60, + "minimum_expectancy": 0.20, + "min_trade_number": 10, + "max_trade_duration_minute": 1440, + "remove_pumps": false + }, + "telegram": { + "enabled": false, + "token": "", + "chat_id": "" + }, + "api_server": { + "enabled": true, + "listen_ip_address": "127.0.0.1", + "listen_port": 8080, + "verbosity": "error", + "enable_openapi": false, + "jwt_secret_key": "fcc24d31d6581ad2c90c3fc438c8a8b2ccce1393126959934568707f0bd2d647", + "CORS_origins": [], + "username": "freqtrader", + "password": "testing123" + }, + "external_signal": { + "enabled": true, + "mode": "leader", + "api_token": "testtoken", + }, + "bot_name": "freqtrade", + "initial_state": "running", + "force_entry_enable": false, + "internals": { + "process_throttle_secs": 5, + } +} From 70df037690aed351b7d374d3bdac7554205b4015 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 24 Aug 2022 20:44:48 +0200 Subject: [PATCH 043/592] Improve test precision --- tests/optimize/test_backtesting.py | 29 +++++++++++++++-------------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index 98d18c156..368e368c5 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -550,6 +550,7 @@ def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None: mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf')) mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=100) + mocker.patch("freqtrade.optimize.backtesting.price_to_precision", lambda p, *args: p) patch_exchange(mocker) default_conf_usdt['stake_amount'] = 300 default_conf_usdt['max_open_trades'] = 2 @@ -562,10 +563,10 @@ def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None: pair = 'ETH/USDT:USDT' row = [ pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0), - 0.001, # Open - 0.0012, # High - 0.00099, # Low - 0.0011, # Close + 0.1, # Open + 0.12, # High + 0.099, # Low + 0.11, # Close 1, # enter_long 0, # exit_long 1, # enter_short @@ -580,8 +581,8 @@ def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None: return_value=(0.01, 0.01)) # leverage = 5 - # ep1(trade.open_rate) = 0.001 - # position(trade.amount) = 1500000 + # ep1(trade.open_rate) = 0.1 + # position(trade.amount) = 15000 # stake_amount = 300 -> wb = 300 / 5 = 60 # mmr = 0.01 # cum_b = 0.01 @@ -591,26 +592,26 @@ def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None: # Binance, Long # liquidation_price # = ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position)) - # = ((300 + 0.01) - (1 * 1500000 * 0.001)) / ((1500000 * 0.01) - (1 * 1500000)) + # = ((300 + 0.01) - (1 * 15000 * 0.1)) / ((15000 * 0.01) - (1 * 15000)) # = 0.0008080740740740741 # freqtrade_liquidation_price = liq + (abs(open_rate - liq) * liq_buffer * side_1) - # = 0.0008080740740740741 + ((0.001 - 0.0008080740740740741) * 0.05 * 1) - # = 0.0008176703703703704 + # = 0.08080740740740741 + ((0.1 - 0.08080740740740741) * 0.05 * 1) + # = 0.08176703703703704 trade = backtesting._enter_trade(pair, row=row, direction='long') - assert pytest.approx(trade.liquidation_price) == 0.00081767037 + assert pytest.approx(trade.liquidation_price) == 0.081767037 # Binance, Short # liquidation_price # = ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position)) - # = ((300 + 0.01) - ((-1) * 1500000 * 0.001)) / ((1500000 * 0.01) - ((-1) * 1500000)) + # = ((300 + 0.01) - ((-1) * 15000 * 0.1)) / ((15000 * 0.01) - ((-1) * 15000)) # = 0.0011881254125412541 # freqtrade_liquidation_price = liq + (abs(open_rate - liq) * liq_buffer * side_1) - # = 0.0011881254125412541 + (abs(0.001 - 0.0011881254125412541) * 0.05 * -1) - # = 0.0011787191419141915 + # = 0.11881254125412541 + (abs(0.1 - 0.11881254125412541) * 0.05 * -1) + # = 0.11787191419141915 trade = backtesting._enter_trade(pair, row=row, direction='short') - assert pytest.approx(trade.liquidation_price) == 0.0011787191 + assert pytest.approx(trade.liquidation_price) == 0.11787191 # Stake-amount too high! mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0) From 205ab26e9225bf8bc0b3d30d68207f30ed0af889 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 24 Aug 2022 20:54:22 +0200 Subject: [PATCH 044/592] Remove TODO in test --- tests/test_persistence.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index d8973e9d0..2460fde68 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -2894,8 +2894,8 @@ def test_order_to_ccxt(limit_buy_order_open): (('buy', 100, 9), (200.0, 8.5, 1700.0, 0.0, None, None)), (('sell', 100, 10), (100.0, 8.5, 850.0, 150.0, 150.0, 0.17647059)), (('buy', 150, 11), (250.0, 10, 2500.0, 150.0, 150.0, 0.17647059)), - (('sell', 100, 12), (150.0, 10.0, 1500.0, 350.0, 350.0, 0.2)), - (('sell', 150, 14), (150.0, 10.0, 1500.0, 950.0, 950.0, 0.40)), + (('sell', 100, 12), (150.0, 10.0, 1500.0, 350.0, 200.0, 0.2)), + (('sell', 150, 14), (150.0, 10.0, 1500.0, 950.0, 600.0, 0.40)), ], 'end_profit': 950.0, 'end_profit_ratio': 0.283582, @@ -2960,9 +2960,8 @@ def test_recalc_trade_from_orders_dca(data) -> None: assert trade.amount == result[0] assert trade.open_rate == result[1] assert trade.stake_amount == result[2] - # TODO: enable the below. assert pytest.approx(trade.realized_profit) == result[3] - # assert pytest.approx(trade.close_profit_abs) == result[4] + assert pytest.approx(trade.close_profit_abs) == result[4] assert pytest.approx(trade.close_profit) == result[5] trade.close(price) From 9e48e6a40b917a6d24cb4084904bc1942f6285c4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 25 Aug 2022 06:46:57 +0200 Subject: [PATCH 045/592] Update docs about precision limits in backtesting --- docs/backtesting.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/docs/backtesting.md b/docs/backtesting.md index a7baf6932..8b2fdc345 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -561,6 +561,14 @@ BTC trades at 22.000\$ today (0.001 BTC is related to this) - but the backtestin Today's minimum would be `0.001 * 22_000` - or 22\$. However the limit could also be 50$ - based on `0.001 * 50_000` in some historic setting. +#### Trading precision limits + +Most exchanges pose precision limits on both price and amounts, so you cannot buy 1.0020401 of a pair, or at a price of 1.24567123123. +Instead, these prices and amounts will be rounded or truncated (based on the exchange definition) to the defined trading precision. +The above values may for example be rounded to an amount of 1.002, and a price of 1.24567. + +These precision values are based on current exchange limits (as described in the [above section](#trading-limits-in-backtesting)), as historic precision limits are not available. + ## Improved backtest accuracy One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?). From 6636f17e0f587dfc4ee0505040cb5e9aa6b30ed8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 25 Aug 2022 07:08:22 +0200 Subject: [PATCH 046/592] Simplify usage of amount_to_contract precision --- freqtrade/exchange/__init__.py | 10 ++++---- freqtrade/exchange/exchange.py | 23 +++++++++++++++++++ freqtrade/optimize/backtesting.py | 19 +++++---------- freqtrade/persistence/trade_model.py | 14 ++++------- .../test_backtesting_adjust_position.py | 3 ++- 5 files changed, 41 insertions(+), 28 deletions(-) diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py index 57114a342..ff7ec7e04 100644 --- a/freqtrade/exchange/__init__.py +++ b/freqtrade/exchange/__init__.py @@ -9,11 +9,11 @@ from freqtrade.exchange.bitpanda import Bitpanda from freqtrade.exchange.bittrex import Bittrex from freqtrade.exchange.bybit import Bybit from freqtrade.exchange.coinbasepro import Coinbasepro -from freqtrade.exchange.exchange import (amount_to_contracts, amount_to_precision, - available_exchanges, ccxt_exchanges, contracts_to_amount, - date_minus_candles, is_exchange_known_ccxt, - is_exchange_officially_supported, market_is_active, - price_to_precision, timeframe_to_minutes, +from freqtrade.exchange.exchange import (amount_to_contract_precision, amount_to_contracts, + amount_to_precision, available_exchanges, ccxt_exchanges, + contracts_to_amount, date_minus_candles, + is_exchange_known_ccxt, is_exchange_officially_supported, + market_is_active, price_to_precision, timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date, timeframe_to_prev_date, timeframe_to_seconds, validate_exchange, validate_exchanges) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 7d2a2f5c5..3264b82e2 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2943,6 +2943,29 @@ def amount_to_precision(amount: float, amount_precision: Optional[float], return amount +def amount_to_contract_precision( + amount, amount_precision: Optional[float], precisionMode: Optional[int], + contract_size: Optional[float]) -> float: + """ + Returns the amount to buy or sell to a precision the Exchange accepts + including calculation to and from contracts. + Re-implementation of ccxt internal methods - ensuring we can test the result is correct + based on our definitions. + :param amount: amount to truncate + :param amount_precision: amount precision to use. + should be retrieved from markets[pair]['precision']['amount'] + :param precisionMode: precision mode to use. Should be used from precisionMode + one of ccxt's DECIMAL_PLACES, SIGNIFICANT_DIGITS, or TICK_SIZE + :param contract_size: contract size - taken from exchange.get_contract_size(pair) + :return: truncated amount + """ + if amount_precision is not None and precisionMode is not None: + contracts = amount_to_contracts(amount, contract_size) + amount_p = amount_to_precision(contracts, amount_precision, precisionMode) + return contracts_to_amount(amount_p, contract_size) + return amount + + def price_to_precision(price: float, price_precision: Optional[float], precisionMode: Optional[int]) -> float: """ diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 725ff2406..248300fad 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -23,9 +23,8 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import (BacktestState, CandleType, ExitCheckTuple, ExitType, RunMode, TradingMode) from freqtrade.exceptions import DependencyException, OperationalException -from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds -from freqtrade.exchange.exchange import (amount_to_contracts, amount_to_precision, - contracts_to_amount, price_to_precision) +from freqtrade.exchange import (amount_to_contract_precision, price_to_precision, + timeframe_to_minutes, timeframe_to_seconds) from freqtrade.mixins import LoggingMixin from freqtrade.optimize.backtest_caching import get_strategy_run_id from freqtrade.optimize.bt_progress import BTProgress @@ -659,11 +658,8 @@ class Backtesting: exit_candle_time = sell_row[DATE_IDX].to_pydatetime() order_type = self.strategy.order_types['exit'] # amount = amount or trade.amount - amount = contracts_to_amount( - amount_to_precision( - amount_to_contracts(amount or trade.amount, trade.contract_size), - trade.amount_precision, self.precision_mode), - trade.contract_size) + amount = amount_to_contract_precision(amount or trade.amount, trade.amount_precision, + self.precision_mode, trade.contract_size) rate = price_to_precision(close_rate, trade.price_precision, self.precision_mode) order = Order( id=self.order_id_counter, @@ -835,11 +831,8 @@ class Backtesting: contract_size = self.exchange.get_contract_size(pair) precision_amount = self.exchange.get_precision_amount(pair) - amount = contracts_to_amount( - amount_to_precision( - amount_to_contracts(amount_p, contract_size), - precision_amount, self.precision_mode), - contract_size) + amount = amount_to_contract_precision(amount_p, precision_amount, self.precision_mode, + contract_size) # Backcalculate actual stake amount. stake_amount = amount * propose_rate / leverage diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 9ab608321..23997f835 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -14,8 +14,7 @@ from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPE BuySell, LongShort) from freqtrade.enums import ExitType, TradingMode from freqtrade.exceptions import DependencyException, OperationalException -from freqtrade.exchange import amount_to_precision, price_to_precision -from freqtrade.exchange.exchange import amount_to_contracts, contracts_to_amount +from freqtrade.exchange import amount_to_contract_precision, price_to_precision from freqtrade.leverage import interest from freqtrade.persistence.base import _DECL_BASE from freqtrade.util import FtPrecise @@ -625,11 +624,8 @@ class LocalTrade(): else: logger.warning( f'Got different open_order_id {self.open_order_id} != {order.order_id}') - amount_tr = contracts_to_amount( - amount_to_precision( - amount_to_contracts(self.amount, self.contract_size), - self.amount_precision, self.precision_mode), - self.contract_size) + amount_tr = amount_to_contract_precision(self.amount, self.amount_precision, + self.precision_mode, self.contract_size) if isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC): self.close(order.safe_price) else: @@ -882,8 +878,8 @@ class LocalTrade(): self.realized_profit = close_profit_abs self.close_profit_abs = profit - current_amount_tr = amount_to_precision(float(current_amount), - self.amount_precision, self.precision_mode) + current_amount_tr = amount_to_contract_precision( + float(current_amount), self.amount_precision, self.precision_mode, self.contract_size) if current_amount_tr > 0.0: # Trade is still open # Leverage not updated, as we don't allow changing leverage through DCA at the moment. diff --git a/tests/optimize/test_backtesting_adjust_position.py b/tests/optimize/test_backtesting_adjust_position.py index f0829ea1e..71f8cdcea 100644 --- a/tests/optimize/test_backtesting_adjust_position.py +++ b/tests/optimize/test_backtesting_adjust_position.py @@ -18,7 +18,8 @@ from tests.conftest import patch_exchange def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None: default_conf['use_exit_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) - mocker.patch('freqtrade.optimize.backtesting.amount_to_precision', lambda x, y, z: round(x, 8)) + mocker.patch('freqtrade.optimize.backtesting.amount_to_contract_precision', + lambda x, *args, **kwargs: round(x, 8)) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf')) patch_exchange(mocker) From f2a356a80c6f7581f0dc3f1bb0bd5bdcf9756818 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 25 Aug 2022 07:08:58 +0200 Subject: [PATCH 047/592] Fix some imports --- freqtrade/commands/data_commands.py | 3 +-- freqtrade/edge/edge_positioning.py | 2 +- freqtrade/freqtradebot.py | 3 +-- 3 files changed, 3 insertions(+), 5 deletions(-) diff --git a/freqtrade/commands/data_commands.py b/freqtrade/commands/data_commands.py index ce26d39ab..360387aa6 100644 --- a/freqtrade/commands/data_commands.py +++ b/freqtrade/commands/data_commands.py @@ -11,8 +11,7 @@ from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_oh refresh_backtest_trades_data) from freqtrade.enums import CandleType, RunMode, TradingMode from freqtrade.exceptions import OperationalException -from freqtrade.exchange import timeframe_to_minutes -from freqtrade.exchange.exchange import market_is_active +from freqtrade.exchange import market_is_active, timeframe_to_minutes from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist, expand_pairlist from freqtrade.resolvers import ExchangeResolver diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py index 2fe41a17b..af20e1645 100644 --- a/freqtrade/edge/edge_positioning.py +++ b/freqtrade/edge/edge_positioning.py @@ -15,7 +15,7 @@ from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT from freqtrade.data.history import get_timerange, load_data, refresh_data from freqtrade.enums import CandleType, ExitType, RunMode from freqtrade.exceptions import OperationalException -from freqtrade.exchange.exchange import timeframe_to_seconds +from freqtrade.exchange import timeframe_to_seconds from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.strategy.interface import IStrategy diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 5791a816d..1967de1fe 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -21,8 +21,7 @@ from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode, State, TradingMode) from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError, InvalidOrderException, PricingError) -from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds -from freqtrade.exchange.exchange import timeframe_to_next_date +from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds from freqtrade.misc import safe_value_fallback, safe_value_fallback2 from freqtrade.mixins import LoggingMixin from freqtrade.persistence import Order, PairLocks, Trade, init_db From 1fd223c815caab3ac104986701c7d9d6df281a66 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 25 Aug 2022 17:03:41 +0200 Subject: [PATCH 048/592] Update --prepend help string closes #7290 --- docs/data-download.md | 2 +- freqtrade/commands/cli_options.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/data-download.md b/docs/data-download.md index be36d579d..b72e7f337 100644 --- a/docs/data-download.md +++ b/docs/data-download.md @@ -63,7 +63,7 @@ optional arguments: `jsongz`). --trading-mode {spot,margin,futures} Select Trading mode - --prepend Allow data prepending. + --prepend Allow data prepending. (Data-appending is disabled) Common arguments: -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index a458c1591..b9e9e26f7 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -455,7 +455,7 @@ AVAILABLE_CLI_OPTIONS = { ), "prepend_data": Arg( '--prepend', - help='Allow data prepending.', + help='Allow data prepending. (Data-appending is disabled)', action='store_true', ), "erase": Arg( From 53d46a0385e859e199b8aa038205169f0d38bc22 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 25 Aug 2022 20:36:17 +0200 Subject: [PATCH 049/592] align `max_entry_position_adjustment` behavior of backtesting to live closes #7293 --- freqtrade/optimize/backtesting.py | 23 +++++++++++------------ 1 file changed, 11 insertions(+), 12 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 248300fad..00cd8fa4a 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -534,12 +534,16 @@ class Backtesting: # Check if we should increase our position if stake_amount is not None and stake_amount > 0.0: - - pos_trade = self._enter_trade( - trade.pair, row, 'short' if trade.is_short else 'long', stake_amount, trade) - if pos_trade is not None: - self.wallets.update() - return pos_trade + check_adjust_entry = True + if self.strategy.max_entry_position_adjustment > -1: + entry_count = trade.nr_of_successful_entries + check_adjust_entry = (entry_count <= self.strategy.max_entry_position_adjustment) + if check_adjust_entry: + pos_trade = self._enter_trade( + trade.pair, row, 'short' if trade.is_short else 'long', stake_amount, trade) + if pos_trade is not None: + self.wallets.update() + return pos_trade if stake_amount is not None and stake_amount < 0.0: amount = abs(stake_amount) / current_rate @@ -570,12 +574,7 @@ class Backtesting: # Check if we need to adjust our current positions if self.strategy.position_adjustment_enable: - check_adjust_entry = True - if self.strategy.max_entry_position_adjustment > -1: - entry_count = trade.nr_of_successful_entries - check_adjust_entry = (entry_count <= self.strategy.max_entry_position_adjustment) - if check_adjust_entry: - trade = self._get_adjust_trade_entry_for_candle(trade, row) + trade = self._get_adjust_trade_entry_for_candle(trade, row) enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX] exit_sig = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX] From 4b7e640f31f2a35ba3b73a3bfbbfb2882ecb7a81 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 26 Aug 2022 13:56:44 +0200 Subject: [PATCH 050/592] reduce code duplication, optimize auto data download per tf --- freqtrade/data/dataprovider.py | 26 ++++++------ freqtrade/freqai/data_kitchen.py | 67 +++++++++++-------------------- freqtrade/optimize/backtesting.py | 26 +----------- freqtrade/strategy/interface.py | 7 ++-- 4 files changed, 41 insertions(+), 85 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 529a12690..a21114901 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -91,9 +91,9 @@ class DataProvider: timerange = TimeRange.parse_timerange(None if self._config.get( 'timerange') is None else str(self._config.get('timerange'))) # Move informative start time respecting startup_candle_count - timerange.subtract_start( - self.get_required_startup_seconds(str(timeframe)) - ) + startup_candles = self.get_required_startup(str(timeframe)) + tf_seconds = timeframe_to_seconds(str(timeframe)) + timerange.subtract_start(tf_seconds * startup_candles) self.__cached_pairs_backtesting[saved_pair] = load_pair_history( pair=pair, timeframe=timeframe or self._config['timeframe'], @@ -105,16 +105,18 @@ class DataProvider: ) return self.__cached_pairs_backtesting[saved_pair].copy() - def get_required_startup_seconds(self, timeframe: str) -> int: - tf_seconds = timeframe_to_seconds(timeframe) - base_seconds = tf_seconds * self._config.get('startup_candle_count', 0) - if not self._config['freqai']['enabled']: - return base_seconds + def get_required_startup(self, timeframe: str) -> int: + if not self._config.get('freqai', {}).get('enabled', False): + return self._config.get('startup_candle_count', 0) else: - train_seconds = self._config['freqai']['train_period_days'] * 86400 - # multiplied by safety factor of 2 because FreqAI users - # typically do not know the correct window. - return base_seconds * 2 + int(train_seconds) + if not self._config['startup_candle_count']: + raise OperationalException('FreqAI backtesting module requires strategy ' + 'set startup_candle_count.') + tf_seconds = timeframe_to_seconds(timeframe) + train_candles = self._config['freqai']['train_period_days'] * 86400 / tf_seconds + total_candles = int(self._config.get('startup_candle_count', 0) + train_candles) + logger.info(f'Increasing startup_candle_count for freqai to {total_candles}') + return total_candles def get_pair_dataframe( self, diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index c768fc30e..1a8063add 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1006,8 +1006,7 @@ class FreqaiDataKitchen: # Methods called by interface.py (load_freqai_model()) -def download_all_data_for_training(timerange: TimeRange, - dp: DataProvider, config: dict) -> None: +def download_all_data_for_training(dp: DataProvider, config: dict) -> None: """ Called only once upon start of bot to download the necessary data for populating indicators and training the model. @@ -1025,51 +1024,31 @@ def download_all_data_for_training(timerange: TimeRange, all_pairs = dynamic_expand_pairlist(config, markets) - new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) if not dp._exchange: # Not realistic - this is only called in live mode. raise OperationalException("Dataprovider did not have an exchange attached.") - refresh_backtest_ohlcv_data( - dp._exchange, - pairs=all_pairs, - timeframes=config["freqai"]["feature_parameters"].get("include_timeframes"), - datadir=config["datadir"], - timerange=timerange, - new_pairs_days=new_pairs_days, - erase=False, - data_format=config.get("dataformat_ohlcv", "json"), - trading_mode=config.get("trading_mode", "spot"), - prepend=config.get("prepend_data", False), - ) - -def get_required_data_timerange( - config: dict -) -> TimeRange: - """ - Used by interface.py to pre-download necessary data for FreqAI - user. - """ time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - data_load_timerange = TimeRange() - timeframes = config["freqai"]["feature_parameters"].get("include_timeframes") - - max_tf_seconds = 0 - for tf in timeframes: - secs = timeframe_to_seconds(tf) - if secs > max_tf_seconds: - max_tf_seconds = secs - - max_period = config.get('startup_candle_count', 20) * 2 - - additional_seconds = max_period * max_tf_seconds - - data_load_timerange.startts = int( - time - - config["freqai"].get("train_period_days", 0) * SECONDS_IN_DAY - - additional_seconds - ) - data_load_timerange.stopts = int(time) - - return data_load_timerange + for tf in config["freqai"]["feature_parameters"].get("include_timeframes"): + timerange = TimeRange() + timerange.startts = int(time) + timerange.stopts = int(time) + startup_candles = dp.get_required_startup(str(tf)) + tf_seconds = timeframe_to_seconds(str(tf)) + timerange.subtract_start(tf_seconds * startup_candles) + new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) + # FIXME: now that we are looping on `refresh_backtest_ohlcv_data`, the function + # redownloads the funding rate for each pair. + refresh_backtest_ohlcv_data( + dp._exchange, + pairs=all_pairs, + timeframes=[tf], + datadir=config["datadir"], + timerange=timerange, + new_pairs_days=new_pairs_days, + erase=False, + data_format=config.get("dataformat_ohlcv", "json"), + trading_mode=config.get("trading_mode", "spot"), + prepend=config.get("prepend_data", False), + ) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 8f0302ada..3d715c82d 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -211,21 +211,12 @@ class Backtesting: """ self.progress.init_step(BacktestState.DATALOAD, 1) - # if self.config.get('freqai', {}).get('enabled', False): - # startup_candles = int(self.config.get('freqai', {}).get('startup_candles', 0)) - # if not startup_candles: - # raise OperationalException('FreqAI backtesting module requires user set ' - # 'startup_candles in config.') - # self.required_startup += int(self.config.get('freqai', {}).get('startup_candles', 0)) - # logger.info(f'Increasing startup_candle_count for freqai to {self.required_startup}') - # self.config['startup_candle_count'] = self.required_startup - data = history.load_data( datadir=self.config['datadir'], pairs=self.pairlists.whitelist, timeframe=self.timeframe, timerange=self.timerange, - startup_candles=self.get_required_startup(self.timeframe), + startup_candles=self.dataprovider.get_required_startup(self.timeframe), fail_without_data=True, data_format=self.config.get('dataformat_ohlcv', 'json'), candle_type=self.config.get('candle_type_def', CandleType.SPOT) @@ -244,21 +235,6 @@ class Backtesting: self.progress.set_new_value(1) return data, self.timerange - def get_required_startup(self, timeframe: str) -> int: - if not self.config['freqai']['enabled']: - return self.required_startup - else: - if not self.config['startup_candle_count']: - raise OperationalException('FreqAI backtesting module requires strategy ' - 'set startup_candle_count.') - tf_seconds = timeframe_to_seconds(timeframe) - train_candles = self.config['freqai']['train_period_days'] * 86400 / tf_seconds - # multiplied by safety factor of 2 because FreqAI users - # typically do not know the correct window. - total_candles = self.required_startup * 2 + train_candles - logger.info(f'Increasing startup_candle_count for freqai to {total_candles}') - return total_candles - def load_bt_data_detail(self) -> None: """ Loads backtest detail data (smaller timeframe) if necessary. diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 284727d2b..9124a0427 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -148,8 +148,7 @@ class IStrategy(ABC, HyperStrategyMixin): def load_freqAI_model(self) -> None: if self.config.get('freqai', {}).get('enabled', False): # Import here to avoid importing this if freqAI is disabled - from freqtrade.freqai.data_kitchen import (download_all_data_for_training, - get_required_data_timerange) + from freqtrade.freqai.data_kitchen import (download_all_data_for_training) from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver self.freqai = FreqaiModelResolver.load_freqaimodel(self.config) self.freqai_info = self.config["freqai"] @@ -161,8 +160,8 @@ class IStrategy(ABC, HyperStrategyMixin): "corr_pairlist, this may take a while if you do not have the " "data saved" ) - data_load_timerange = get_required_data_timerange(self.config) - download_all_data_for_training(data_load_timerange, self.dp, self.config) + # data_load_timerange = get_required_data_timerange(self.config) + download_all_data_for_training(self.dp, self.config) else: # Gracious failures if freqAI is disabled but "start" is called. From 65b552e310fe751989e43848498e03157cc50232 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 26 Aug 2022 15:30:01 +0200 Subject: [PATCH 051/592] make docs reflect reality, move download_all_data to new utils.py file, automatic startup_candle detection --- docs/freqai.md | 7 +++-- freqtrade/data/dataprovider.py | 14 +++++---- freqtrade/freqai/data_kitchen.py | 54 -------------------------------- freqtrade/strategy/interface.py | 2 +- 4 files changed, 14 insertions(+), 63 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index f3c9021ed..bd746c984 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -113,7 +113,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points.
**Datatype:** boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reproducibility. But these and all others can be added/changed in this dictionary.
**Datatype:** dictionary. | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing.
**Datatype:** positive integer. -| `indicator_max_period_candles` | **Deprecated in favor of** strategy set `startup_candle_count`, however, both configuration parameters provide the same functionality; the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
**Datatype:** positive integer. +| `indicator_max_period_candles` | **No longer used**. User must use the strategy set `startup_candle_count` which defines the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
**Datatype:** positive integer. | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set.
**Datatype:** list of positive integers. | `use_DBSCAN_to_remove_outliers` | Inactive by default. If true, FreqAI clusters data using DBSCAN to identify and remove outliers from training and prediction data.
**Datatype:** float (fraction of 1). | | **Data split parameters** @@ -162,7 +162,6 @@ The user interface is isolated to the typical config file. A typical FreqAI conf "label_period_candles": 24, "include_shifted_candles": 2, "weight_factor": 0, - "indicator_max_period_candles": 20, "indicator_periods_candles": [10, 20] }, "data_split_parameters" : { @@ -387,6 +386,10 @@ The FreqAI strategy requires the user to include the following lines of code in ```python + # user should define the maximum startup candle count (the largest number of candles + # passed to any single indicator) + startup_candle_count: int = 20 + def informative_pairs(self): whitelist_pairs = self.dp.current_whitelist() corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index a21114901..4151b7419 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -106,15 +106,17 @@ class DataProvider: return self.__cached_pairs_backtesting[saved_pair].copy() def get_required_startup(self, timeframe: str) -> int: - if not self._config.get('freqai', {}).get('enabled', False): + freqai_config = self._config.get('freqai', {}) + if not freqai_config.get('enabled', False): return self._config.get('startup_candle_count', 0) else: - if not self._config['startup_candle_count']: - raise OperationalException('FreqAI backtesting module requires strategy ' - 'set startup_candle_count.') + startup_candles = self._config.get('startup_candle_count', 0) + indicator_periods = freqai_config['feature_parameters']['indicator_periods_candles'] + # make sure the startupcandles is at least the set maximum indicator periods + self._config['startup_candle_count'] = max(startup_candles, max(indicator_periods)) tf_seconds = timeframe_to_seconds(timeframe) - train_candles = self._config['freqai']['train_period_days'] * 86400 / tf_seconds - total_candles = int(self._config.get('startup_candle_count', 0) + train_candles) + train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds + total_candles = int(self._config['startup_candle_count'] + train_candles) logger.info(f'Increasing startup_candle_count for freqai to {total_candles}') return total_candles diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 1a8063add..1b88405c1 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -16,12 +16,8 @@ from sklearn.model_selection import train_test_split from sklearn.neighbors import NearestNeighbors from freqtrade.configuration import TimeRange -from freqtrade.data.dataprovider import DataProvider -from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data from freqtrade.exceptions import OperationalException from freqtrade.exchange import timeframe_to_seconds -from freqtrade.exchange.exchange import market_is_active -from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist from freqtrade.strategy.interface import IStrategy @@ -1002,53 +998,3 @@ class FreqaiDataKitchen: if self.unique_classes: for label in self.unique_classes: self.unique_class_list += list(self.unique_classes[label]) - -# Methods called by interface.py (load_freqai_model()) - - -def download_all_data_for_training(dp: DataProvider, config: dict) -> None: - """ - Called only once upon start of bot to download the necessary data for - populating indicators and training the model. - :param timerange: TimeRange = The full data timerange for populating the indicators - and training the model. - :param dp: DataProvider instance attached to the strategy - """ - - if dp._exchange is not None: - markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) - or config.get('include_inactive')] - else: - # This should not occur: - raise OperationalException('No exchange object found.') - - all_pairs = dynamic_expand_pairlist(config, markets) - - if not dp._exchange: - # Not realistic - this is only called in live mode. - raise OperationalException("Dataprovider did not have an exchange attached.") - - time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - - for tf in config["freqai"]["feature_parameters"].get("include_timeframes"): - timerange = TimeRange() - timerange.startts = int(time) - timerange.stopts = int(time) - startup_candles = dp.get_required_startup(str(tf)) - tf_seconds = timeframe_to_seconds(str(tf)) - timerange.subtract_start(tf_seconds * startup_candles) - new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY) - # FIXME: now that we are looping on `refresh_backtest_ohlcv_data`, the function - # redownloads the funding rate for each pair. - refresh_backtest_ohlcv_data( - dp._exchange, - pairs=all_pairs, - timeframes=[tf], - datadir=config["datadir"], - timerange=timerange, - new_pairs_days=new_pairs_days, - erase=False, - data_format=config.get("dataformat_ohlcv", "json"), - trading_mode=config.get("trading_mode", "spot"), - prepend=config.get("prepend_data", False), - ) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 9124a0427..c9ec466de 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -148,7 +148,7 @@ class IStrategy(ABC, HyperStrategyMixin): def load_freqAI_model(self) -> None: if self.config.get('freqai', {}).get('enabled', False): # Import here to avoid importing this if freqAI is disabled - from freqtrade.freqai.data_kitchen import (download_all_data_for_training) + from freqtrade.freqai.utils import download_all_data_for_training from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver self.freqai = FreqaiModelResolver.load_freqaimodel(self.config) self.freqai_info = self.config["freqai"] From e7261cf51577dc30b530370f81df620c898f6a11 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 26 Aug 2022 15:30:28 +0200 Subject: [PATCH 052/592] add freqai utils.py file --- freqtrade/freqai/utils.py | 56 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 freqtrade/freqai/utils.py diff --git a/freqtrade/freqai/utils.py b/freqtrade/freqai/utils.py new file mode 100644 index 000000000..056458115 --- /dev/null +++ b/freqtrade/freqai/utils.py @@ -0,0 +1,56 @@ +from freqtrade.data.dataprovider import DataProvider +from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist +from freqtrade.exchange.exchange import market_is_active +from freqtrade.exchange import timeframe_to_seconds +from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data +from datetime import datetime, timezone +from freqtrade.exceptions import OperationalException +from freqtrade.configuration import TimeRange + + +def download_all_data_for_training(dp: DataProvider, config: dict) -> None: + """ + Called only once upon start of bot to download the necessary data for + populating indicators and training a FreqAI model. + :param timerange: TimeRange = The full data timerange for populating the indicators + and training the model. + :param dp: DataProvider instance attached to the strategy + """ + + if dp._exchange is not None: + markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) + or config.get('include_inactive')] + else: + # This should not occur: + raise OperationalException('No exchange object found.') + + all_pairs = dynamic_expand_pairlist(config, markets) + + if not dp._exchange: + # Not realistic - this is only called in live mode. + raise OperationalException("Dataprovider did not have an exchange attached.") + + time = datetime.now(tz=timezone.utc).timestamp() + + for tf in config["freqai"]["feature_parameters"].get("include_timeframes"): + timerange = TimeRange() + timerange.startts = int(time) + timerange.stopts = int(time) + startup_candles = dp.get_required_startup(str(tf)) + tf_seconds = timeframe_to_seconds(str(tf)) + timerange.subtract_start(tf_seconds * startup_candles) + new_pairs_days = int((timerange.stopts - timerange.startts) / 86400) + # FIXME: now that we are looping on `refresh_backtest_ohlcv_data`, the function + # redownloads the funding rate for each pair. + refresh_backtest_ohlcv_data( + dp._exchange, + pairs=all_pairs, + timeframes=[tf], + datadir=config["datadir"], + timerange=timerange, + new_pairs_days=new_pairs_days, + erase=False, + data_format=config.get("dataformat_ohlcv", "json"), + trading_mode=config.get("trading_mode", "spot"), + prepend=config.get("prepend_data", False), + ) From bb3523f3838686f92420b27e58cc1b5a37df6b9e Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 26 Aug 2022 18:51:42 +0200 Subject: [PATCH 053/592] download data homogeneously across timeframes --- freqtrade/freqai/utils.py | 140 +++++++++++++++++++++++++------- freqtrade/strategy/interface.py | 6 +- 2 files changed, 113 insertions(+), 33 deletions(-) diff --git a/freqtrade/freqai/utils.py b/freqtrade/freqai/utils.py index 056458115..d56702049 100644 --- a/freqtrade/freqai/utils.py +++ b/freqtrade/freqai/utils.py @@ -1,17 +1,22 @@ -from freqtrade.data.dataprovider import DataProvider -from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist -from freqtrade.exchange.exchange import market_is_active -from freqtrade.exchange import timeframe_to_seconds -from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data +import logging from datetime import datetime, timezone -from freqtrade.exceptions import OperationalException + from freqtrade.configuration import TimeRange +from freqtrade.data.dataprovider import DataProvider +from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data +from freqtrade.exceptions import OperationalException +from freqtrade.exchange import timeframe_to_seconds +from freqtrade.exchange.exchange import market_is_active +from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist + + +logger = logging.getLogger(__name__) def download_all_data_for_training(dp: DataProvider, config: dict) -> None: """ Called only once upon start of bot to download the necessary data for - populating indicators and training a FreqAI model. + populating indicators and training the model. :param timerange: TimeRange = The full data timerange for populating the indicators and training the model. :param dp: DataProvider instance attached to the strategy @@ -26,31 +31,108 @@ def download_all_data_for_training(dp: DataProvider, config: dict) -> None: all_pairs = dynamic_expand_pairlist(config, markets) + timerange = get_required_data_timerange(config) + + new_pairs_days = int((timerange.stopts - timerange.startts) / 86400) if not dp._exchange: # Not realistic - this is only called in live mode. raise OperationalException("Dataprovider did not have an exchange attached.") + refresh_backtest_ohlcv_data( + dp._exchange, + pairs=all_pairs, + timeframes=config["freqai"]["feature_parameters"].get("include_timeframes"), + datadir=config["datadir"], + timerange=timerange, + new_pairs_days=new_pairs_days, + erase=False, + data_format=config.get("dataformat_ohlcv", "json"), + trading_mode=config.get("trading_mode", "spot"), + prepend=config.get("prepend_data", False), + ) + +def get_required_data_timerange( + config: dict +) -> TimeRange: + """ + Used to compute the required data download time range + for auto data-download in FreqAI + """ time = datetime.now(tz=timezone.utc).timestamp() + data_load_timerange = TimeRange() - for tf in config["freqai"]["feature_parameters"].get("include_timeframes"): - timerange = TimeRange() - timerange.startts = int(time) - timerange.stopts = int(time) - startup_candles = dp.get_required_startup(str(tf)) - tf_seconds = timeframe_to_seconds(str(tf)) - timerange.subtract_start(tf_seconds * startup_candles) - new_pairs_days = int((timerange.stopts - timerange.startts) / 86400) - # FIXME: now that we are looping on `refresh_backtest_ohlcv_data`, the function - # redownloads the funding rate for each pair. - refresh_backtest_ohlcv_data( - dp._exchange, - pairs=all_pairs, - timeframes=[tf], - datadir=config["datadir"], - timerange=timerange, - new_pairs_days=new_pairs_days, - erase=False, - data_format=config.get("dataformat_ohlcv", "json"), - trading_mode=config.get("trading_mode", "spot"), - prepend=config.get("prepend_data", False), - ) + timeframes = config["freqai"]["feature_parameters"].get("include_timeframes") + + max_tf_seconds = 0 + for tf in timeframes: + secs = timeframe_to_seconds(tf) + if secs > max_tf_seconds: + max_tf_seconds = secs + + startup_candles = config.get('startup_candle_count', 0) + indicator_periods = config["freqai"]["feature_parameters"]["indicator_periods_candles"] + + # factor the max_period as a factor of safety. + max_period = int(max(startup_candles, max(indicator_periods)) * 1.5) + config['startup_candle_count'] = max_period + logger.info(f'FreqAI auto-downloader using {max_period} startup candles.') + + additional_seconds = max_period * max_tf_seconds + + data_load_timerange.startts = int( + time + - config["freqai"].get("train_period_days", 0) * 86400 + - additional_seconds + ) + data_load_timerange.stopts = int(time) + + return data_load_timerange + + +# Keep below for when we wish to download heterogeneously lengthed data for FreqAI. +# def download_all_data_for_training(dp: DataProvider, config: dict) -> None: +# """ +# Called only once upon start of bot to download the necessary data for +# populating indicators and training a FreqAI model. +# :param timerange: TimeRange = The full data timerange for populating the indicators +# and training the model. +# :param dp: DataProvider instance attached to the strategy +# """ + +# if dp._exchange is not None: +# markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) +# or config.get('include_inactive')] +# else: +# # This should not occur: +# raise OperationalException('No exchange object found.') + +# all_pairs = dynamic_expand_pairlist(config, markets) + +# if not dp._exchange: +# # Not realistic - this is only called in live mode. +# raise OperationalException("Dataprovider did not have an exchange attached.") + +# time = datetime.now(tz=timezone.utc).timestamp() + +# for tf in config["freqai"]["feature_parameters"].get("include_timeframes"): +# timerange = TimeRange() +# timerange.startts = int(time) +# timerange.stopts = int(time) +# startup_candles = dp.get_required_startup(str(tf)) +# tf_seconds = timeframe_to_seconds(str(tf)) +# timerange.subtract_start(tf_seconds * startup_candles) +# new_pairs_days = int((timerange.stopts - timerange.startts) / 86400) +# # FIXME: now that we are looping on `refresh_backtest_ohlcv_data`, the function +# # redownloads the funding rate for each pair. +# refresh_backtest_ohlcv_data( +# dp._exchange, +# pairs=all_pairs, +# timeframes=[tf], +# datadir=config["datadir"], +# timerange=timerange, +# new_pairs_days=new_pairs_days, +# erase=False, +# data_format=config.get("dataformat_ohlcv", "json"), +# trading_mode=config.get("trading_mode", "spot"), +# prepend=config.get("prepend_data", False), +# ) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index c9ec466de..3ea1a3fae 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -157,12 +157,10 @@ class IStrategy(ABC, HyperStrategyMixin): if self.config.get('runmode') in (RunMode.DRY_RUN, RunMode.LIVE): logger.info( "Downloading all training data for all pairs in whitelist and " - "corr_pairlist, this may take a while if you do not have the " - "data saved" + "corr_pairlist, this may take a while if the data is not " + "already on disk." ) - # data_load_timerange = get_required_data_timerange(self.config) download_all_data_for_training(self.dp, self.config) - else: # Gracious failures if freqAI is disabled but "start" is called. class DummyClass(): From b2d664c63c061e06ed6b136792146d57c8ffabe8 Mon Sep 17 00:00:00 2001 From: elintornquist <107926911+elintornquist@users.noreply.github.com> Date: Fri, 26 Aug 2022 18:57:27 +0200 Subject: [PATCH 054/592] Change MinPts calculation --- freqtrade/freqai/data_kitchen.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index e480ab135..102a4857e 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -635,7 +635,7 @@ class FreqaiDataKitchen: cos(angle) * (point[1] - origin[1]) return (x, y) - MinPts = len(self.data_dictionary['train_features'].columns) * 2 + MinPts = int(len(self.data_dictionary['train_features'].index) * 0.25) # measure pairwise distances to train_features.shape[1]*2 nearest neighbours neighbors = NearestNeighbors( n_neighbors=MinPts, n_jobs=self.thread_count) From 753d1b2aad18eacfafea3f718a66747418657d4f Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 26 Aug 2022 19:34:51 +0200 Subject: [PATCH 055/592] Update leverage tier terminology to be clear and aligned with ccxt --- freqtrade/exchange/exchange.py | 25 +- freqtrade/exchange/okx.py | 2 +- tests/conftest.py | 456 ++++++++++++++++---------------- tests/exchange/test_binance.py | 104 ++++---- tests/exchange/test_exchange.py | 16 +- tests/exchange/test_okx.py | 48 ++-- 6 files changed, 326 insertions(+), 325 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 3264b82e2..afda824f2 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2316,10 +2316,10 @@ class Exchange: def parse_leverage_tier(self, tier) -> Dict: info = tier.get('info', {}) return { - 'min': tier['minNotional'], - 'max': tier['maxNotional'], - 'mmr': tier['maintenanceMarginRate'], - 'lev': tier['maxLeverage'], + 'minNotional': tier['minNotional'], + 'maxNotional': tier['maxNotional'], + 'maintenanceMarginRate': tier['maintenanceMarginRate'], + 'maxLeverage': tier['maxLeverage'], 'maintAmt': float(info['cum']) if 'cum' in info else None, } @@ -2348,18 +2348,18 @@ class Exchange: pair_tiers = self._leverage_tiers[pair] if stake_amount == 0: - return self._leverage_tiers[pair][0]['lev'] # Max lev for lowest amount + return self._leverage_tiers[pair][0]['maxLeverage'] # Max lev for lowest amount for tier_index in range(len(pair_tiers)): tier = pair_tiers[tier_index] - lev = tier['lev'] + lev = tier['maxLeverage'] if tier_index < len(pair_tiers) - 1: next_tier = pair_tiers[tier_index + 1] - next_floor = next_tier['min'] / next_tier['lev'] + next_floor = next_tier['minNotional'] / next_tier['maxLeverage'] if next_floor > stake_amount: # Next tier min too high for stake amount - return min((tier['max'] / stake_amount), lev) + return min((tier['maxNotional'] / stake_amount), lev) # # With the two leverage tiers below, # - a stake amount of 150 would mean a max leverage of (10000 / 150) = 66.66 @@ -2380,10 +2380,11 @@ class Exchange: # else: # if on the last tier - if stake_amount > tier['max']: # If stake is > than max tradeable amount + if stake_amount > tier['maxNotional']: + # If stake is > than max tradeable amount raise InvalidOrderException(f'Amount {stake_amount} too high for {pair}') else: - return tier['lev'] + return tier['maxLeverage'] raise OperationalException( 'Looped through all tiers without finding a max leverage. Should never be reached' @@ -2749,8 +2750,8 @@ class Exchange: pair_tiers = self._leverage_tiers[pair] for tier in reversed(pair_tiers): - if nominal_value >= tier['min']: - return (tier['mmr'], tier['maintAmt']) + if nominal_value >= tier['minNotional']: + return (tier['maintenanceMarginRate'], tier['maintAmt']) raise OperationalException("nominal value can not be lower than 0") # The lowest notional_floor for any pair in fetch_leverage_tiers is always 0 because it diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py index 80373e071..f039f2b3f 100644 --- a/freqtrade/exchange/okx.py +++ b/freqtrade/exchange/okx.py @@ -146,4 +146,4 @@ class Okx(Exchange): return float('inf') pair_tiers = self._leverage_tiers[pair] - return pair_tiers[-1]['max'] / leverage + return pair_tiers[-1]['maxNotional'] / leverage diff --git a/tests/conftest.py b/tests/conftest.py index a02fc4566..fffac8e0a 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -3085,416 +3085,416 @@ def leverage_tiers(): return { "1000SHIB/USDT": [ { - 'min': 0, - 'max': 50000, - 'mmr': 0.01, - 'lev': 50, + 'minNotional': 0, + 'maxNotional': 50000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 50, 'maintAmt': 0.0 }, { - 'min': 50000, - 'max': 150000, - 'mmr': 0.025, - 'lev': 20, + 'minNotional': 50000, + 'maxNotional': 150000, + 'maintenanceMarginRate': 0.025, + 'maxLeverage': 20, 'maintAmt': 750.0 }, { - 'min': 150000, - 'max': 250000, - 'mmr': 0.05, - 'lev': 10, + 'minNotional': 150000, + 'maxNotional': 250000, + 'maintenanceMarginRate': 0.05, + 'maxLeverage': 10, 'maintAmt': 4500.0 }, { - 'min': 250000, - 'max': 500000, - 'mmr': 0.1, - 'lev': 5, + 'minNotional': 250000, + 'maxNotional': 500000, + 'maintenanceMarginRate': 0.1, + 'maxLeverage': 5, 'maintAmt': 17000.0 }, { - 'min': 500000, - 'max': 1000000, - 'mmr': 0.125, - 'lev': 4, + 'minNotional': 500000, + 'maxNotional': 1000000, + 'maintenanceMarginRate': 0.125, + 'maxLeverage': 4, 'maintAmt': 29500.0 }, { - 'min': 1000000, - 'max': 2000000, - 'mmr': 0.25, - 'lev': 2, + 'minNotional': 1000000, + 'maxNotional': 2000000, + 'maintenanceMarginRate': 0.25, + 'maxLeverage': 2, 'maintAmt': 154500.0 }, { - 'min': 2000000, - 'max': 30000000, - 'mmr': 0.5, - 'lev': 1, + 'minNotional': 2000000, + 'maxNotional': 30000000, + 'maintenanceMarginRate': 0.5, + 'maxLeverage': 1, 'maintAmt': 654500.0 }, ], "1INCH/USDT": [ { - 'min': 0, - 'max': 5000, - 'mmr': 0.012, - 'lev': 50, + 'minNotional': 0, + 'maxNotional': 5000, + 'maintenanceMarginRate': 0.012, + 'maxLeverage': 50, 'maintAmt': 0.0 }, { - 'min': 5000, - 'max': 25000, - 'mmr': 0.025, - 'lev': 20, + 'minNotional': 5000, + 'maxNotional': 25000, + 'maintenanceMarginRate': 0.025, + 'maxLeverage': 20, 'maintAmt': 65.0 }, { - 'min': 25000, - 'max': 100000, - 'mmr': 0.05, - 'lev': 10, + 'minNotional': 25000, + 'maxNotional': 100000, + 'maintenanceMarginRate': 0.05, + 'maxLeverage': 10, 'maintAmt': 690.0 }, { - 'min': 100000, - 'max': 250000, - 'mmr': 0.1, - 'lev': 5, + 'minNotional': 100000, + 'maxNotional': 250000, + 'maintenanceMarginRate': 0.1, + 'maxLeverage': 5, 'maintAmt': 5690.0 }, { - 'min': 250000, - 'max': 1000000, - 'mmr': 0.125, - 'lev': 2, + 'minNotional': 250000, + 'maxNotional': 1000000, + 'maintenanceMarginRate': 0.125, + 'maxLeverage': 2, 'maintAmt': 11940.0 }, { - 'min': 1000000, - 'max': 100000000, - 'mmr': 0.5, - 'lev': 1, + 'minNotional': 1000000, + 'maxNotional': 100000000, + 'maintenanceMarginRate': 0.5, + 'maxLeverage': 1, 'maintAmt': 386940.0 }, ], "AAVE/USDT": [ { - 'min': 0, - 'max': 5000, - 'mmr': 0.01, - 'lev': 50, + 'minNotional': 0, + 'maxNotional': 5000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 50, 'maintAmt': 0.0 }, { - 'min': 5000, - 'max': 25000, - 'mmr': 0.02, - 'lev': 25, + 'minNotional': 5000, + 'maxNotional': 25000, + 'maintenanceMarginRate': 0.02, + 'maxLeverage': 25, 'maintAmt': 75.0 }, { - 'min': 25000, - 'max': 100000, - 'mmr': 0.05, - 'lev': 10, + 'minNotional': 25000, + 'maxNotional': 100000, + 'maintenanceMarginRate': 0.05, + 'maxLeverage': 10, 'maintAmt': 700.0 }, { - 'min': 100000, - 'max': 250000, - 'mmr': 0.1, - 'lev': 5, + 'minNotional': 100000, + 'maxNotional': 250000, + 'maintenanceMarginRate': 0.1, + 'maxLeverage': 5, 'maintAmt': 5700.0 }, { - 'min': 250000, - 'max': 1000000, - 'mmr': 0.125, - 'lev': 2, + 'minNotional': 250000, + 'maxNotional': 1000000, + 'maintenanceMarginRate': 0.125, + 'maxLeverage': 2, 'maintAmt': 11950.0 }, { - 'min': 10000000, - 'max': 50000000, - 'mmr': 0.5, - 'lev': 1, + 'minNotional': 10000000, + 'maxNotional': 50000000, + 'maintenanceMarginRate': 0.5, + 'maxLeverage': 1, 'maintAmt': 386950.0 }, ], "ADA/BUSD": [ { - "min": 0, - "max": 100000, - "mmr": 0.025, - "lev": 20, + "minNotional": 0, + "maxNotional": 100000, + "maintenanceMarginRate": 0.025, + "maxLeverage": 20, "maintAmt": 0.0 }, { - "min": 100000, - "max": 500000, - "mmr": 0.05, - "lev": 10, + "minNotional": 100000, + "maxNotional": 500000, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10, "maintAmt": 2500.0 }, { - "min": 500000, - "max": 1000000, - "mmr": 0.1, - "lev": 5, + "minNotional": 500000, + "maxNotional": 1000000, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5, "maintAmt": 27500.0 }, { - "min": 1000000, - "max": 2000000, - "mmr": 0.15, - "lev": 3, + "minNotional": 1000000, + "maxNotional": 2000000, + "maintenanceMarginRate": 0.15, + "maxLeverage": 3, "maintAmt": 77500.0 }, { - "min": 2000000, - "max": 5000000, - "mmr": 0.25, - "lev": 2, + "minNotional": 2000000, + "maxNotional": 5000000, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2, "maintAmt": 277500.0 }, { - "min": 5000000, - "max": 30000000, - "mmr": 0.5, - "lev": 1, + "minNotional": 5000000, + "maxNotional": 30000000, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1, "maintAmt": 1527500.0 }, ], 'BNB/BUSD': [ { - "min": 0, # stake(before leverage) = 0 - "max": 100000, # max stake(before leverage) = 5000 - "mmr": 0.025, - "lev": 20, + "minNotional": 0, # stake(before leverage) = 0 + "maxNotional": 100000, # max stake(before leverage) = 5000 + "maintenanceMarginRate": 0.025, + "maxLeverage": 20, "maintAmt": 0.0 }, { - "min": 100000, # stake = 10000.0 - "max": 500000, # max_stake = 50000.0 - "mmr": 0.05, - "lev": 10, + "minNotional": 100000, # stake = 10000.0 + "maxNotional": 500000, # max_stake = 50000.0 + "maintenanceMarginRate": 0.05, + "maxLeverage": 10, "maintAmt": 2500.0 }, { - "min": 500000, # stake = 100000.0 - "max": 1000000, # max_stake = 200000.0 - "mmr": 0.1, - "lev": 5, + "minNotional": 500000, # stake = 100000.0 + "maxNotional": 1000000, # max_stake = 200000.0 + "maintenanceMarginRate": 0.1, + "maxLeverage": 5, "maintAmt": 27500.0 }, { - "min": 1000000, # stake = 333333.3333333333 - "max": 2000000, # max_stake = 666666.6666666666 - "mmr": 0.15, - "lev": 3, + "minNotional": 1000000, # stake = 333333.3333333333 + "maxNotional": 2000000, # max_stake = 666666.6666666666 + "maintenanceMarginRate": 0.15, + "maxLeverage": 3, "maintAmt": 77500.0 }, { - "min": 2000000, # stake = 1000000.0 - "max": 5000000, # max_stake = 2500000.0 - "mmr": 0.25, - "lev": 2, + "minNotional": 2000000, # stake = 1000000.0 + "maxNotional": 5000000, # max_stake = 2500000.0 + "maintenanceMarginRate": 0.25, + "maxLeverage": 2, "maintAmt": 277500.0 }, { - "min": 5000000, # stake = 5000000.0 - "max": 30000000, # max_stake = 30000000.0 - "mmr": 0.5, - "lev": 1, + "minNotional": 5000000, # stake = 5000000.0 + "maxNotional": 30000000, # max_stake = 30000000.0 + "maintenanceMarginRate": 0.5, + "maxLeverage": 1, "maintAmt": 1527500.0 } ], 'BNB/USDT': [ { - "min": 0, # stake = 0.0 - "max": 10000, # max_stake = 133.33333333333334 - "mmr": 0.0065, - "lev": 75, + "minNotional": 0, # stake = 0.0 + "maxNotional": 10000, # max_stake = 133.33333333333334 + "maintenanceMarginRate": 0.0065, + "maxLeverage": 75, "maintAmt": 0.0 }, { - "min": 10000, # stake = 200.0 - "max": 50000, # max_stake = 1000.0 - "mmr": 0.01, - "lev": 50, + "minNotional": 10000, # stake = 200.0 + "maxNotional": 50000, # max_stake = 1000.0 + "maintenanceMarginRate": 0.01, + "maxLeverage": 50, "maintAmt": 35.0 }, { - "min": 50000, # stake = 2000.0 - "max": 250000, # max_stake = 10000.0 - "mmr": 0.02, - "lev": 25, + "minNotional": 50000, # stake = 2000.0 + "maxNotional": 250000, # max_stake = 10000.0 + "maintenanceMarginRate": 0.02, + "maxLeverage": 25, "maintAmt": 535.0 }, { - "min": 250000, # stake = 25000.0 - "max": 1000000, # max_stake = 100000.0 - "mmr": 0.05, - "lev": 10, + "minNotional": 250000, # stake = 25000.0 + "maxNotional": 1000000, # max_stake = 100000.0 + "maintenanceMarginRate": 0.05, + "maxLeverage": 10, "maintAmt": 8035.0 }, { - "min": 1000000, # stake = 200000.0 - "max": 2000000, # max_stake = 400000.0 - "mmr": 0.1, - "lev": 5, + "minNotional": 1000000, # stake = 200000.0 + "maxNotional": 2000000, # max_stake = 400000.0 + "maintenanceMarginRate": 0.1, + "maxLeverage": 5, "maintAmt": 58035.0 }, { - "min": 2000000, # stake = 500000.0 - "max": 5000000, # max_stake = 1250000.0 - "mmr": 0.125, - "lev": 4, + "minNotional": 2000000, # stake = 500000.0 + "maxNotional": 5000000, # max_stake = 1250000.0 + "maintenanceMarginRate": 0.125, + "maxLeverage": 4, "maintAmt": 108035.0 }, { - "min": 5000000, # stake = 1666666.6666666667 - "max": 10000000, # max_stake = 3333333.3333333335 - "mmr": 0.15, - "lev": 3, + "minNotional": 5000000, # stake = 1666666.6666666667 + "maxNotional": 10000000, # max_stake = 3333333.3333333335 + "maintenanceMarginRate": 0.15, + "maxLeverage": 3, "maintAmt": 233035.0 }, { - "min": 10000000, # stake = 5000000.0 - "max": 20000000, # max_stake = 10000000.0 - "mmr": 0.25, - "lev": 2, + "minNotional": 10000000, # stake = 5000000.0 + "maxNotional": 20000000, # max_stake = 10000000.0 + "maintenanceMarginRate": 0.25, + "maxLeverage": 2, "maintAmt": 1233035.0 }, { - "min": 20000000, # stake = 20000000.0 - "max": 50000000, # max_stake = 50000000.0 - "mmr": 0.5, - "lev": 1, + "minNotional": 20000000, # stake = 20000000.0 + "maxNotional": 50000000, # max_stake = 50000000.0 + "maintenanceMarginRate": 0.5, + "maxLeverage": 1, "maintAmt": 6233035.0 }, ], 'BTC/USDT': [ { - "min": 0, # stake = 0.0 - "max": 50000, # max_stake = 400.0 - "mmr": 0.004, - "lev": 125, + "minNotional": 0, # stake = 0.0 + "maxNotional": 50000, # max_stake = 400.0 + "maintenanceMarginRate": 0.004, + "maxLeverage": 125, "maintAmt": 0.0 }, { - "min": 50000, # stake = 500.0 - "max": 250000, # max_stake = 2500.0 - "mmr": 0.005, - "lev": 100, + "minNotional": 50000, # stake = 500.0 + "maxNotional": 250000, # max_stake = 2500.0 + "maintenanceMarginRate": 0.005, + "maxLeverage": 100, "maintAmt": 50.0 }, { - "min": 250000, # stake = 5000.0 - "max": 1000000, # max_stake = 20000.0 - "mmr": 0.01, - "lev": 50, + "minNotional": 250000, # stake = 5000.0 + "maxNotional": 1000000, # max_stake = 20000.0 + "maintenanceMarginRate": 0.01, + "maxLeverage": 50, "maintAmt": 1300.0 }, { - "min": 1000000, # stake = 50000.0 - "max": 7500000, # max_stake = 375000.0 - "mmr": 0.025, - "lev": 20, + "minNotional": 1000000, # stake = 50000.0 + "maxNotional": 7500000, # max_stake = 375000.0 + "maintenanceMarginRate": 0.025, + "maxLeverage": 20, "maintAmt": 16300.0 }, { - "min": 7500000, # stake = 750000.0 - "max": 40000000, # max_stake = 4000000.0 - "mmr": 0.05, - "lev": 10, + "minNotional": 7500000, # stake = 750000.0 + "maxNotional": 40000000, # max_stake = 4000000.0 + "maintenanceMarginRate": 0.05, + "maxLeverage": 10, "maintAmt": 203800.0 }, { - "min": 40000000, # stake = 8000000.0 - "max": 100000000, # max_stake = 20000000.0 - "mmr": 0.1, - "lev": 5, + "minNotional": 40000000, # stake = 8000000.0 + "maxNotional": 100000000, # max_stake = 20000000.0 + "maintenanceMarginRate": 0.1, + "maxLeverage": 5, "maintAmt": 2203800.0 }, { - "min": 100000000, # stake = 25000000.0 - "max": 200000000, # max_stake = 50000000.0 - "mmr": 0.125, - "lev": 4, + "minNotional": 100000000, # stake = 25000000.0 + "maxNotional": 200000000, # max_stake = 50000000.0 + "maintenanceMarginRate": 0.125, + "maxLeverage": 4, "maintAmt": 4703800.0 }, { - "min": 200000000, # stake = 66666666.666666664 - "max": 400000000, # max_stake = 133333333.33333333 - "mmr": 0.15, - "lev": 3, + "minNotional": 200000000, # stake = 66666666.666666664 + "maxNotional": 400000000, # max_stake = 133333333.33333333 + "maintenanceMarginRate": 0.15, + "maxLeverage": 3, "maintAmt": 9703800.0 }, { - "min": 400000000, # stake = 200000000.0 - "max": 600000000, # max_stake = 300000000.0 - "mmr": 0.25, - "lev": 2, + "minNotional": 400000000, # stake = 200000000.0 + "maxNotional": 600000000, # max_stake = 300000000.0 + "maintenanceMarginRate": 0.25, + "maxLeverage": 2, "maintAmt": 4.97038E7 }, { - "min": 600000000, # stake = 600000000.0 - "max": 1000000000, # max_stake = 1000000000.0 - "mmr": 0.5, - "lev": 1, + "minNotional": 600000000, # stake = 600000000.0 + "maxNotional": 1000000000, # max_stake = 1000000000.0 + "maintenanceMarginRate": 0.5, + "maxLeverage": 1, "maintAmt": 1.997038E8 }, ], "ZEC/USDT": [ { - 'min': 0, - 'max': 50000, - 'mmr': 0.01, - 'lev': 50, + 'minNotional': 0, + 'maxNotional': 50000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 50, 'maintAmt': 0.0 }, { - 'min': 50000, - 'max': 150000, - 'mmr': 0.025, - 'lev': 20, + 'minNotional': 50000, + 'maxNotional': 150000, + 'maintenanceMarginRate': 0.025, + 'maxLeverage': 20, 'maintAmt': 750.0 }, { - 'min': 150000, - 'max': 250000, - 'mmr': 0.05, - 'lev': 10, + 'minNotional': 150000, + 'maxNotional': 250000, + 'maintenanceMarginRate': 0.05, + 'maxLeverage': 10, 'maintAmt': 4500.0 }, { - 'min': 250000, - 'max': 500000, - 'mmr': 0.1, - 'lev': 5, + 'minNotional': 250000, + 'maxNotional': 500000, + 'maintenanceMarginRate': 0.1, + 'maxLeverage': 5, 'maintAmt': 17000.0 }, { - 'min': 500000, - 'max': 1000000, - 'mmr': 0.125, - 'lev': 4, + 'minNotional': 500000, + 'maxNotional': 1000000, + 'maintenanceMarginRate': 0.125, + 'maxLeverage': 4, 'maintAmt': 29500.0 }, { - 'min': 1000000, - 'max': 2000000, - 'mmr': 0.25, - 'lev': 2, + 'minNotional': 1000000, + 'maxNotional': 2000000, + 'maintenanceMarginRate': 0.25, + 'maxLeverage': 2, 'maintAmt': 154500.0 }, { - 'min': 2000000, - 'max': 30000000, - 'mmr': 0.5, - 'lev': 1, + 'minNotional': 2000000, + 'maxNotional': 30000000, + 'maintenanceMarginRate': 0.5, + 'maxLeverage': 1, 'maintAmt': 654500.0 }, ] diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py index 45f8a3817..4d1c40647 100644 --- a/tests/exchange/test_binance.py +++ b/tests/exchange/test_binance.py @@ -376,96 +376,96 @@ def test_fill_leverage_tiers_binance(default_conf, mocker): assert exchange._leverage_tiers == { 'ADA/BUSD': [ { - "min": 0, - "max": 100000, - "mmr": 0.025, - "lev": 20, + "minNotional": 0, + "maxNotional": 100000, + "maintenanceMarginRate": 0.025, + "maxLeverage": 20, "maintAmt": 0.0 }, { - "min": 100000, - "max": 500000, - "mmr": 0.05, - "lev": 10, + "minNotional": 100000, + "maxNotional": 500000, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10, "maintAmt": 2500.0 }, { - "min": 500000, - "max": 1000000, - "mmr": 0.1, - "lev": 5, + "minNotional": 500000, + "maxNotional": 1000000, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5, "maintAmt": 27500.0 }, { - "min": 1000000, - "max": 2000000, - "mmr": 0.15, - "lev": 3, + "minNotional": 1000000, + "maxNotional": 2000000, + "maintenanceMarginRate": 0.15, + "maxLeverage": 3, "maintAmt": 77500.0 }, { - "min": 2000000, - "max": 5000000, - "mmr": 0.25, - "lev": 2, + "minNotional": 2000000, + "maxNotional": 5000000, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2, "maintAmt": 277500.0 }, { - "min": 5000000, - "max": 30000000, - "mmr": 0.5, - "lev": 1, + "minNotional": 5000000, + "maxNotional": 30000000, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1, "maintAmt": 1527500.0 } ], "ZEC/USDT": [ { - 'min': 0, - 'max': 50000, - 'mmr': 0.01, - 'lev': 50, + 'minNotional': 0, + 'maxNotional': 50000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 50, 'maintAmt': 0.0 }, { - 'min': 50000, - 'max': 150000, - 'mmr': 0.025, - 'lev': 20, + 'minNotional': 50000, + 'maxNotional': 150000, + 'maintenanceMarginRate': 0.025, + 'maxLeverage': 20, 'maintAmt': 750.0 }, { - 'min': 150000, - 'max': 250000, - 'mmr': 0.05, - 'lev': 10, + 'minNotional': 150000, + 'maxNotional': 250000, + 'maintenanceMarginRate': 0.05, + 'maxLeverage': 10, 'maintAmt': 4500.0 }, { - 'min': 250000, - 'max': 500000, - 'mmr': 0.1, - 'lev': 5, + 'minNotional': 250000, + 'maxNotional': 500000, + 'maintenanceMarginRate': 0.1, + 'maxLeverage': 5, 'maintAmt': 17000.0 }, { - 'min': 500000, - 'max': 1000000, - 'mmr': 0.125, - 'lev': 4, + 'minNotional': 500000, + 'maxNotional': 1000000, + 'maintenanceMarginRate': 0.125, + 'maxLeverage': 4, 'maintAmt': 29500.0 }, { - 'min': 1000000, - 'max': 2000000, - 'mmr': 0.25, - 'lev': 2, + 'minNotional': 1000000, + 'maxNotional': 2000000, + 'maintenanceMarginRate': 0.25, + 'maxLeverage': 2, 'maintAmt': 154500.0 }, { - 'min': 2000000, - 'max': 30000000, - 'mmr': 0.5, - 'lev': 1, + 'minNotional': 2000000, + 'maxNotional': 30000000, + 'maintenanceMarginRate': 0.5, + 'maxLeverage': 1, 'maintAmt': 654500.0 }, ] diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 5002a33e1..650a20197 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4826,10 +4826,10 @@ def test_parse_leverage_tier(mocker, default_conf): } assert exchange.parse_leverage_tier(tier) == { - "min": 0, - "max": 100000, - "mmr": 0.025, - "lev": 20, + "minNotional": 0, + "maxNotional": 100000, + "maintenanceMarginRate": 0.025, + "maxLeverage": 20, "maintAmt": 0.0, } @@ -4855,10 +4855,10 @@ def test_parse_leverage_tier(mocker, default_conf): } assert exchange.parse_leverage_tier(tier2) == { - 'min': 0, - 'max': 2000, - 'mmr': 0.01, - 'lev': 75, + 'minNotional': 0, + 'maxNotional': 2000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 75, "maintAmt": None, } diff --git a/tests/exchange/test_okx.py b/tests/exchange/test_okx.py index 10e087ced..b475b84ff 100644 --- a/tests/exchange/test_okx.py +++ b/tests/exchange/test_okx.py @@ -414,47 +414,47 @@ def test_load_leverage_tiers_okx(default_conf, mocker, markets, tmpdir, caplog, assert exchange._leverage_tiers == { 'ADA/USDT:USDT': [ { - 'min': 0, - 'max': 500, - 'mmr': 0.02, - 'lev': 75, + 'minNotional': 0, + 'maxNotional': 500, + 'maintenanceMarginRate': 0.02, + 'maxLeverage': 75, 'maintAmt': None }, { - 'min': 501, - 'max': 1000, - 'mmr': 0.025, - 'lev': 50, + 'minNotional': 501, + 'maxNotional': 1000, + 'maintenanceMarginRate': 0.025, + 'maxLeverage': 50, 'maintAmt': None }, { - 'min': 1001, - 'max': 2000, - 'mmr': 0.03, - 'lev': 20, + 'minNotional': 1001, + 'maxNotional': 2000, + 'maintenanceMarginRate': 0.03, + 'maxLeverage': 20, 'maintAmt': None }, ], 'ETH/USDT:USDT': [ { - 'min': 0, - 'max': 2000, - 'mmr': 0.01, - 'lev': 75, + 'minNotional': 0, + 'maxNotional': 2000, + 'maintenanceMarginRate': 0.01, + 'maxLeverage': 75, 'maintAmt': None }, { - 'min': 2001, - 'max': 4000, - 'mmr': 0.015, - 'lev': 50, + 'minNotional': 2001, + 'maxNotional': 4000, + 'maintenanceMarginRate': 0.015, + 'maxLeverage': 50, 'maintAmt': None }, { - 'min': 4001, - 'max': 8000, - 'mmr': 0.02, - 'lev': 20, + 'minNotional': 4001, + 'maxNotional': 8000, + 'maintenanceMarginRate': 0.02, + 'maxLeverage': 20, 'maintAmt': None }, ], From 01126c43f78bf932c5dbeab7e5517cbab4fe52d6 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 26 Aug 2022 20:04:36 +0200 Subject: [PATCH 056/592] Fix liquidation price tier calculation closes #7294 --- freqtrade/exchange/binance.py | 21 ++++++++++++--------- freqtrade/exchange/exchange.py | 26 +++++++++++++++----------- freqtrade/freqtradebot.py | 1 + freqtrade/optimize/backtesting.py | 1 + tests/exchange/test_exchange.py | 17 +++++++++++------ 5 files changed, 40 insertions(+), 26 deletions(-) diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py index 37a3c419d..a5e9fd37c 100644 --- a/freqtrade/exchange/binance.py +++ b/freqtrade/exchange/binance.py @@ -137,23 +137,27 @@ class Binance(Exchange): pair: str, open_rate: float, # Entry price of position is_short: bool, - position: float, # Absolute value of position size + amount: float, + stake_amount: float, wallet_balance: float, # Or margin balance mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: """ + Important: Must be fetching data from cached values as this is used by backtesting! MARGIN: https://www.binance.com/en/support/faq/f6b010588e55413aa58b7d63ee0125ed PERPETUAL: https://www.binance.com/en/support/faq/b3c689c1f50a44cabb3a84e663b81d93 :param exchange_name: - :param open_rate: (EP1) Entry price of position + :param open_rate: Entry price of position :param is_short: True if the trade is a short, false otherwise - :param position: Absolute value of position size (in base currency) - :param wallet_balance: (WB) + :param amount: Absolute value of position size incl. leverage (in base currency) + :param stake_amount: Stake amount - Collateral in settle currency. + :param trading_mode: SPOT, MARGIN, FUTURES, etc. + :param margin_mode: Either ISOLATED or CROSS + :param wallet_balance: Amount of margin_mode in the wallet being used to trade Cross-Margin Mode: crossWalletBalance Isolated-Margin Mode: isolatedWalletBalance - :param maintenance_amt: # * Only required for Cross :param mm_ex_1: (TMM) @@ -165,12 +169,11 @@ class Binance(Exchange): """ side_1 = -1 if is_short else 1 - position = abs(position) cross_vars = upnl_ex_1 - mm_ex_1 if self.margin_mode == MarginMode.CROSS else 0.0 # mm_ratio: Binance's formula specifies maintenance margin rate which is mm_ratio * 100% # maintenance_amt: (CUM) Maintenance Amount of position - mm_ratio, maintenance_amt = self.get_maintenance_ratio_and_amt(pair, position) + mm_ratio, maintenance_amt = self.get_maintenance_ratio_and_amt(pair, stake_amount) if (maintenance_amt is None): raise OperationalException( @@ -182,9 +185,9 @@ class Binance(Exchange): return ( ( (wallet_balance + cross_vars + maintenance_amt) - - (side_1 * position * open_rate) + (side_1 * amount * open_rate) ) / ( - (position * mm_ratio) - (side_1 * position) + (amount * mm_ratio) - (side_1 * amount) ) ) else: diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index afda824f2..4386f47f6 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2437,6 +2437,7 @@ class Exchange: pair: str, open_rate: float, amount: float, # quote currency, includes leverage + stake_amount: float, leverage: float, is_short: bool ) -> Optional[float]: @@ -2446,13 +2447,13 @@ class Exchange: elif ( self.trading_mode == TradingMode.FUTURES ): - wallet_balance = (amount * open_rate) / leverage isolated_liq = self.get_or_calculate_liquidation_price( pair=pair, open_rate=open_rate, is_short=is_short, - position=amount, - wallet_balance=wallet_balance, + amount=amount, + stake_amount=stake_amount, + wallet_balance=stake_amount, # In isolated mode, stake-amount = wallet size mm_ex_1=0.0, upnl_ex_1=0.0, ) @@ -2627,14 +2628,14 @@ class Exchange: # Dry-run open_rate: float, # Entry price of position is_short: bool, - position: float, # Absolute value of position size + amount: float, # Absolute value of position size + stake_amount: float, wallet_balance: float, # Or margin balance mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: """ Set's the margin mode on the exchange to cross or isolated for a specific pair - :param pair: base/quote currency pair (e.g. "ADA/USDT") """ if self.trading_mode == TradingMode.SPOT: return None @@ -2648,7 +2649,8 @@ class Exchange: pair=pair, open_rate=open_rate, is_short=is_short, - position=position, + amount=amount, + stake_amount=stake_amount, wallet_balance=wallet_balance, mm_ex_1=mm_ex_1, upnl_ex_1=upnl_ex_1 @@ -2677,22 +2679,24 @@ class Exchange: pair: str, open_rate: float, # Entry price of position is_short: bool, - position: float, # Absolute value of position size + amount: float, + stake_amount: float, wallet_balance: float, # Or margin balance mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: """ + Important: Must be fetching data from cached values as this is used by backtesting! PERPETUAL: gateio: https://www.gate.io/help/futures/perpetual/22160/calculation-of-liquidation-price okex: https://www.okex.com/support/hc/en-us/articles/ 360053909592-VI-Introduction-to-the-isolated-mode-of-Single-Multi-currency-Portfolio-margin - Important: Must be fetching data from cached values as this is used by backtesting! :param exchange_name: :param open_rate: Entry price of position :param is_short: True if the trade is a short, false otherwise - :param position: Absolute value of position size incl. leverage (in base currency) + :param amount: Absolute value of position size incl. leverage (in base currency) + :param stake_amount: Stake amount - Collateral in settle currency. :param trading_mode: SPOT, MARGIN, FUTURES, etc. :param margin_mode: Either ISOLATED or CROSS :param wallet_balance: Amount of margin_mode in the wallet being used to trade @@ -2706,7 +2710,7 @@ class Exchange: market = self.markets[pair] taker_fee_rate = market['taker'] - mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, position) + mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, stake_amount) if self.trading_mode == TradingMode.FUTURES and self.margin_mode == MarginMode.ISOLATED: @@ -2714,7 +2718,7 @@ class Exchange: raise OperationalException( "Freqtrade does not yet support inverse contracts") - value = wallet_balance / position + value = wallet_balance / amount mm_ratio_taker = (mm_ratio + taker_fee_rate) if is_short: diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 1967de1fe..f4731220c 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1734,6 +1734,7 @@ class FreqtradeBot(LoggingMixin): leverage=trade.leverage, pair=trade.pair, amount=trade.amount, + stake_amount=trade.stake_amount, open_rate=trade.open_rate, is_short=trade.is_short )) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 00cd8fa4a..ff30dbc2a 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -876,6 +876,7 @@ class Backtesting: pair=pair, open_rate=propose_rate, amount=amount, + stake_amount=trade.stake_amount, leverage=leverage, is_short=is_short, )) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 650a20197..093284668 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4132,7 +4132,8 @@ def test_get_or_calculate_liquidation_price(mocker, default_conf): pair='NEAR/USDT:USDT', open_rate=18.884, is_short=False, - position=0.8, + amount=0.8, + stake_amount=18.884 * 0.8, wallet_balance=0.8, ) assert liq_price == 17.47 @@ -4143,7 +4144,8 @@ def test_get_or_calculate_liquidation_price(mocker, default_conf): pair='NEAR/USDT:USDT', open_rate=18.884, is_short=False, - position=0.8, + amount=0.8, + stake_amount=18.884 * 0.8, wallet_balance=0.8, ) assert liq_price == 17.540699999999998 @@ -4543,7 +4545,8 @@ def test_liquidation_price_is_none( pair='DOGE/USDT', open_rate=open_rate, is_short=is_short, - position=71200.81144, + amount=71200.81144, + stake_amount=open_rate * 71200.81144, wallet_balance=-56354.57, mm_ex_1=0.10, upnl_ex_1=0.0 @@ -4552,7 +4555,7 @@ def test_liquidation_price_is_none( @pytest.mark.parametrize( 'exchange_name, is_short, trading_mode, margin_mode, wallet_balance, ' - 'mm_ex_1, upnl_ex_1, maintenance_amt, position, open_rate, ' + 'mm_ex_1, upnl_ex_1, maintenance_amt, amount, open_rate, ' 'mm_ratio, expected', [ ("binance", False, 'futures', 'isolated', 1535443.01, 0.0, @@ -4566,7 +4569,7 @@ def test_liquidation_price_is_none( ]) def test_liquidation_price( mocker, default_conf, exchange_name, open_rate, is_short, trading_mode, - margin_mode, wallet_balance, mm_ex_1, upnl_ex_1, maintenance_amt, position, mm_ratio, expected + margin_mode, wallet_balance, mm_ex_1, upnl_ex_1, maintenance_amt, amount, mm_ratio, expected ): default_conf['trading_mode'] = trading_mode default_conf['margin_mode'] = margin_mode @@ -4580,7 +4583,8 @@ def test_liquidation_price( wallet_balance=wallet_balance, mm_ex_1=mm_ex_1, upnl_ex_1=upnl_ex_1, - position=position, + amount=amount, + stake_amount=open_rate * amount, ), 2), expected) @@ -5111,6 +5115,7 @@ def test_get_liquidation_price( pair='ETH/USDT:USDT', open_rate=open_rate, amount=amount, + stake_amount=amount * open_rate / leverage, leverage=leverage, is_short=is_short, ) From efe4fd3e2415b605d57866567f142d30461c34b5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 26 Aug 2022 20:21:19 +0200 Subject: [PATCH 057/592] Add libgomp1 to dockerfile --- Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfile b/Dockerfile index 14a67edc8..e84a4d095 100644 --- a/Dockerfile +++ b/Dockerfile @@ -11,7 +11,7 @@ ENV FT_APP_ENV="docker" # Prepare environment RUN mkdir /freqtrade \ && apt-get update \ - && apt-get -y install sudo libatlas3-base curl sqlite3 libhdf5-serial-dev \ + && apt-get -y install sudo libatlas3-base curl sqlite3 libhdf5-serial-dev libgomp1 \ && apt-get clean \ && useradd -u 1000 -G sudo -U -m -s /bin/bash ftuser \ && chown ftuser:ftuser /freqtrade \ From 2ef4534fee008fc91066c0d39b5a5e722e913d03 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 26 Aug 2022 20:44:36 +0200 Subject: [PATCH 058/592] Fix ccxt / longrun tests --- tests/exchange/test_ccxt_compat.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 29b317c3c..49b7684f8 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -468,6 +468,7 @@ class TestCCXTExchange(): False, 100, 100, + 100, ) assert (isinstance(liquidation_price, float)) assert liquidation_price >= 0.0 @@ -478,6 +479,7 @@ class TestCCXTExchange(): False, 100, 100, + 100, ) assert (isinstance(liquidation_price, float)) assert liquidation_price >= 0.0 From a998d6d7735a37b37259e988bf2ed17152891338 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 26 Aug 2022 14:52:15 -0600 Subject: [PATCH 059/592] fix tests --- tests/rpc/test_rpc_apiserver.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 9aa965da2..9a7bdfef6 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -52,6 +52,7 @@ def botclient(default_conf, mocker): try: apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(rpc) + apiserver.start_api() yield ftbot, TestClient(apiserver.app) # Cleanup ... ? finally: @@ -332,6 +333,7 @@ def test_api_run(default_conf, mocker, caplog): apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) + apiserver.start_api() assert server_mock.call_count == 1 assert apiserver._config == default_conf apiserver.start_api() @@ -406,6 +408,7 @@ def test_api_cleanup(default_conf, mocker, caplog): apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) + apiserver.start_api() apiserver.cleanup() assert apiserver._server.cleanup.call_count == 1 From 86c5ac44e4f9803dd302c2154320008037f5c50f Mon Sep 17 00:00:00 2001 From: elintornquist <107926911+elintornquist@users.noreply.github.com> Date: Fri, 26 Aug 2022 23:05:07 +0200 Subject: [PATCH 060/592] Add outlier percentage check --- freqtrade/freqai/data_kitchen.py | 37 ++++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 102a4857e..c58cfa75a 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -513,6 +513,19 @@ class FreqaiDataKitchen: return avg_mean_dist + def get_outlier_percentage(self, dropped_pts: npt.ArrayLike) -> float: + """ + Check if more than X% of points werer dropped during outlier detection. + """ + outlier_protection_pct = self.freqai_config["feature_parameters"].get( + "outlier_protection_percentage", 30) + outlier_pct = dropped_pts.sum() / len(dropped_pts) + if outlier_pct >= outlier_protection_pct: + self.svm_model = None + return outlier_pct + else: + return 0.0 + def use_SVM_to_remove_outliers(self, predict: bool) -> None: """ Build/inference a Support Vector Machine to detect outliers @@ -552,6 +565,14 @@ class FreqaiDataKitchen: y_pred = self.svm_model.predict(self.data_dictionary["train_features"]) dropped_points = np.where(y_pred == -1, 0, y_pred) # keep_index = np.where(y_pred == 1) + outlier_ptc = self.get_outlier_percentage(dropped_points) + if outlier_ptc: + logger.warning( + f"SVM detected >{outlier_ptc}% of the points as outliers." + f"Keeping original dataset." + ) + return + self.data_dictionary["train_features"] = self.data_dictionary["train_features"][ (y_pred == 1) ] @@ -667,6 +688,14 @@ class FreqaiDataKitchen: self.data['DBSCAN_min_samples'] = MinPts dropped_points = np.where(clustering.labels_ == -1, 1, 0) + outlier_ptc = self.get_outlier_percentage(dropped_points) + if outlier_ptc: + logger.warning( + f"DBSCAN detected >{outlier_ptc}% of the points as outliers." + f"Keeping original dataset." + ) + return + self.data_dictionary['train_features'] = self.data_dictionary['train_features'][ (clustering.labels_ != -1) ] @@ -722,6 +751,14 @@ class FreqaiDataKitchen: 0, ) + outlier_ptc = self.get_outlier_percentage(1 - do_predict) + if outlier_ptc: + logger.warning( + f"DBSCAN detected >{outlier_ptc}% of the points as outliers." + f"Keeping original dataset." + ) + return + if (len(do_predict) - do_predict.sum()) > 0: logger.info( f"DI tossed {len(do_predict) - do_predict.sum()} predictions for " From 9204f013124761d21ee1374fff4a976131ec75bb Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 07:23:02 +0200 Subject: [PATCH 061/592] Don't lock pairs on partial exit --- freqtrade/freqtradebot.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index f4731220c..d84d50b7c 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1552,9 +1552,10 @@ class FreqtradeBot(LoggingMixin): trade.close_rate_requested = limit trade.exit_reason = exit_reason - # Lock pair for one candle to prevent immediate re-trading - self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc), - reason='Auto lock') + if not sub_trade_amt: + # Lock pair for one candle to prevent immediate re-trading + self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc), + reason='Auto lock') self._notify_exit(trade, order_type, sub_trade=bool(sub_trade_amt), order=order_obj) # In case of market sell orders the order can be closed immediately From 2b5f0678772bea0abaf4abe93efc55de43ea3e0e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 26 Aug 2022 23:40:13 -0600 Subject: [PATCH 062/592] Refactoring, minor improvements, data provider improvements --- freqtrade/constants.py | 6 + freqtrade/data/dataprovider.py | 106 ++++++++++++------ freqtrade/enums/__init__.py | 2 +- freqtrade/enums/externalsignal.py | 7 ++ freqtrade/freqtradebot.py | 3 - freqtrade/misc.py | 17 +++ freqtrade/rpc/api_server/webserver.py | 1 + freqtrade/rpc/external_signal/channel.py | 40 ++++--- freqtrade/rpc/external_signal/controller.py | 34 ++++-- freqtrade/rpc/external_signal/utils.py | 12 ++ freqtrade/rpc/rpc.py | 72 ++++++++---- freqtrade/rpc/rpc_manager.py | 13 +-- ...te.txt => requirements-externalsignals.txt | 1 + tests/rpc/test_rpc_apiserver.py | 2 - 14 files changed, 218 insertions(+), 98 deletions(-) rename requirements-replicate.txt => requirements-externalsignals.txt (94%) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index ad0758e22..b1f189093 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -62,6 +62,7 @@ TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent'] WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw'] FOLLOWER_MODE_OPTIONS = ['follower', 'leader'] +WAIT_DATA_POLICY_OPTIONS = ['none', 'first', 'all'] ENV_VAR_PREFIX = 'FREQTRADE__' @@ -509,6 +510,11 @@ CONF_SCHEMA = { 'follower_reply_timeout': {'type': 'integer'}, 'follower_sleep_time': {'type': 'integer'}, 'follower_ping_timeout': {'type': 'integer'}, + 'wait_data_policy': { + 'type': 'string', + 'enum': WAIT_DATA_POLICY_OPTIONS + }, + 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False} }, 'required': ['mode'] }, diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 036005c84..cd70db9a3 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -15,7 +15,7 @@ from pandas import DataFrame from freqtrade.configuration import TimeRange from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe from freqtrade.data.history import load_pair_history -from freqtrade.enums import CandleType, RunMode +from freqtrade.enums import CandleType, RunMode, WaitDataPolicy from freqtrade.exceptions import ExchangeError, OperationalException from freqtrade.exchange import Exchange, timeframe_to_seconds from freqtrade.util import PeriodicCache @@ -29,7 +29,12 @@ MAX_DATAFRAME_CANDLES = 1000 class DataProvider: - def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None: + def __init__( + self, + config: dict, + exchange: Optional[Exchange], + pairlists=None + ) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists @@ -37,12 +42,18 @@ class DataProvider: self.__slice_index: Optional[int] = None self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {} self.__external_pairs_df: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} - self.__external_pairs_event: Dict[str, Event] = {} + self.__external_pairs_event: Dict[PairWithTimeframe, Tuple[int, Event]] = {} self._msg_queue: deque = deque() self.__msg_cache = PeriodicCache( maxsize=1000, ttl=timeframe_to_seconds(self._config.get('timeframe', '1h'))) + self._num_sources = len(self._config.get('external_signal', {}).get('leader_list', [])) + self._wait_data_policy = self._config.get('external_signal', {}).get( + 'wait_data_policy', WaitDataPolicy.all) + self._wait_data_timeout = self._config.get( + 'external_signal', {}).get('wait_data_timeout', 5) + def _set_dataframe_max_index(self, limit_index: int): """ Limit analyzed dataframe to max specified index. @@ -75,57 +86,88 @@ class DataProvider: pair: str, timeframe: str, dataframe: DataFrame, - candle_type: CandleType + candle_type: CandleType, ) -> None: """ - Add the DataFrame to the __external_pairs_df. If a pair event exists, - set it to release the main thread from waiting. + Add the pair data to this class from an external source. + + :param pair: pair to get the data for + :param timeframe: Timeframe to get data for + :param candle_type: Any of the enum CandleType (must match trading mode!) """ pair_key = (pair, timeframe, candle_type) - # Delete stale data - if pair_key in self.__external_pairs_df: - del self.__external_pairs_df[pair_key] - + # For multiple leaders, if the data already exists, we'd merge self.__external_pairs_df[pair_key] = (dataframe, datetime.now(timezone.utc)) - - pair_event = self.__external_pairs_event.get(pair) - if pair_event: - logger.debug(f"Leader data for pair {pair_key} has been added") - pair_event.set() + self._set_data_event(pair_key) def get_external_df( self, pair: str, timeframe: str, - candle_type: CandleType, - wait: bool = True + candle_type: CandleType ) -> DataFrame: """ - If the pair exists in __external_pairs_df, return it. - If it doesn't, and wait is False, then return an empty df with the columns filled. - If it doesn't, and wait is True (default) create a new threading Event - in __external_pairs_event and wait on it. + Get the pair data from the external sources. Will wait if the policy is + set to, and data is not available. + + :param pair: pair to get the data for + :param timeframe: Timeframe to get data for + :param candle_type: Any of the enum CandleType (must match trading mode!) """ pair_key = (pair, timeframe, candle_type) if pair_key not in self.__external_pairs_df: - if wait: - pair_event = Event() - self.__external_pairs_event[pair] = pair_event + self._wait_on_data(pair_key) - logger.debug(f"Waiting on Leader data for: {pair_key}") - self.__external_pairs_event[pair].wait(timeout=5) - - if pair_key not in self.__external_pairs_df: - # Return empty dataframe but with expected columns merged and filled with NaN - return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) - else: - # Return empty dataframe but with expected columns merged and filled with NaN + if pair_key not in self.__external_pairs_df: return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) return self.__external_pairs_df[pair_key] + def _set_data_event(self, key: PairWithTimeframe): + """ + Depending on the WaitDataPolicy, if an event exists for this PairWithTimeframe + then set the event to release main thread from waiting. + + :param key: PairWithTimeframe + """ + pair_event = self.__external_pairs_event.get(key) + + if pair_event: + num_concat, event = pair_event + self.__external_pairs_event[key] = (num_concat + 1, event) + + if self._wait_data_policy == WaitDataPolicy.one: + logger.debug("Setting Data as policy is One") + event.set() + elif self._wait_data_policy == WaitDataPolicy.all and num_concat == self._num_sources: + logger.debug("Setting Data as policy is all, and is complete") + event.set() + + del self.__external_pairs_event[key] + + def _wait_on_data(self, key: PairWithTimeframe): + """ + Depending on the WaitDataPolicy, we will create and wait on an event until + set that determines the full amount of data is available + + :param key: PairWithTimeframe + """ + if self._wait_data_policy is not WaitDataPolicy.none: + pair, timeframe, candle_type = key + + pair_event = Event() + self.__external_pairs_event[key] = (0, pair_event) + + timeout = self._wait_data_timeout \ + if self._wait_data_policy is not WaitDataPolicy.all else 0 + + timeout_str = f"for {timeout} seconds" if timeout > 0 else "indefinitely" + logger.debug(f"Waiting for external data on {pair} for {timeout_str}") + + pair_event.wait(timeout=timeout) + def add_pairlisthandler(self, pairlists) -> None: """ Allow adding pairlisthandler after initialization diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index 913ef82dd..ffeb8cc12 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -3,7 +3,7 @@ from freqtrade.enums.backteststate import BacktestState from freqtrade.enums.candletype import CandleType from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType -from freqtrade.enums.externalsignal import ExternalSignalModeType, LeaderMessageType +from freqtrade.enums.externalsignal import ExternalSignalModeType, LeaderMessageType, WaitDataPolicy from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues from freqtrade.enums.rpcmessagetype import RPCMessageType diff --git a/freqtrade/enums/externalsignal.py b/freqtrade/enums/externalsignal.py index 4695a4eab..05dc604a2 100644 --- a/freqtrade/enums/externalsignal.py +++ b/freqtrade/enums/externalsignal.py @@ -7,5 +7,12 @@ class ExternalSignalModeType(str, Enum): class LeaderMessageType(str, Enum): + default = "default" pairlist = "pairlist" analyzed_df = "analyzed_df" + + +class WaitDataPolicy(str, Enum): + none = "none" + one = "one" + all = "all" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 9704b7e08..6aee3d104 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -281,9 +281,6 @@ class FreqtradeBot(LoggingMixin): # If external signal leader, broadcast whitelist data # Should we broadcast before trade pairs are added? - # Or should this class be made available to the PairListManager and ran - # when filter_pairlist is called? - if self.external_signal_controller: if self.external_signal_controller.is_leader(): self.rpc.emit_data({ diff --git a/freqtrade/misc.py b/freqtrade/misc.py index bc644a7ec..ceace4ed8 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -14,6 +14,7 @@ import pandas import rapidjson from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN +from freqtrade.enums.signaltype import SignalTagType, SignalType logger = logging.getLogger(__name__) @@ -271,3 +272,19 @@ def json_to_dataframe(data: str) -> pandas.DataFrame: dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True) return dataframe + + +def remove_entry_exit_signals(dataframe: pandas.DataFrame): + """ + Remove Entry and Exit signals from a DataFrame + + :param dataframe: The DataFrame to remove signals from + """ + dataframe[SignalType.ENTER_LONG.value] = 0 + dataframe[SignalType.EXIT_LONG.value] = 0 + dataframe[SignalType.ENTER_SHORT.value] = 0 + dataframe[SignalType.EXIT_SHORT.value] = 0 + dataframe[SignalTagType.ENTER_TAG.value] = None + dataframe[SignalTagType.EXIT_TAG.value] = None + + return dataframe diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index c98fb9fd4..049e7dbc2 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -74,6 +74,7 @@ class ApiServer(RPCHandler): default_response_class=FTJSONResponse, ) self.configure_app(self.app, self._config) + self.start_api() def add_rpc_handler(self, rpc: RPC): """ diff --git a/freqtrade/rpc/external_signal/channel.py b/freqtrade/rpc/external_signal/channel.py index 585b6bae5..4ccb2d864 100644 --- a/freqtrade/rpc/external_signal/channel.py +++ b/freqtrade/rpc/external_signal/channel.py @@ -1,4 +1,5 @@ import logging +from threading import RLock from typing import Type from freqtrade.rpc.external_signal.proxy import WebSocketProxy @@ -63,6 +64,7 @@ class WebSocketChannel: class ChannelManager: def __init__(self): self.channels = dict() + self._lock = RLock() # Re-entrant Lock async def on_connect(self, websocket: WebSocketType): """ @@ -78,7 +80,9 @@ class ChannelManager: return ws_channel = WebSocketChannel(websocket) - self.channels[websocket] = ws_channel + + with self._lock: + self.channels[websocket] = ws_channel return ws_channel @@ -88,21 +92,26 @@ class ChannelManager: :param websocket: The WebSocket objet attached to the Channel """ - if websocket in self.channels.keys(): - channel = self.channels[websocket] + with self._lock: + channel = self.channels.get(websocket) + if channel: + logger.debug(f"Disconnecting channel - {channel}") - logger.debug(f"Disconnecting channel - {channel}") + if not channel.is_closed(): + await channel.close() - if not channel.is_closed(): - await channel.close() - del self.channels[websocket] + del self.channels[websocket] async def disconnect_all(self): """ Disconnect all Channels """ - for websocket in self.channels.keys(): - await self.on_disconnect(websocket) + with self._lock: + for websocket, channel in self.channels.items(): + if not channel.is_closed(): + await channel.close() + + self.channels = dict() async def broadcast(self, data): """ @@ -110,12 +119,13 @@ class ChannelManager: :param data: The data to send """ - for websocket, channel in self.channels.items(): - try: - await channel.send(data) - except RuntimeError: - # Handle cannot send after close cases - await self.on_disconnect(websocket) + with self._lock: + for websocket, channel in self.channels.items(): + try: + await channel.send(data) + except RuntimeError: + # Handle cannot send after close cases + await self.on_disconnect(websocket) async def send_direct(self, channel, data): """ diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py index af91a67b7..01c15fc15 100644 --- a/freqtrade/rpc/external_signal/controller.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -6,7 +6,7 @@ import logging import secrets import socket from threading import Thread -from typing import Any, Coroutine, Dict, Union +from typing import Any, Callable, Coroutine, Dict, Union import websockets from fastapi import Depends @@ -56,8 +56,13 @@ class ExternalSignalController(RPCHandler): self._main_task = None self._sub_tasks = None - self.channel_manager = ChannelManager() + self._message_handlers = { + LeaderMessageType.pairlist: self._rpc._handle_pairlist_message, + LeaderMessageType.analyzed_df: self._rpc._handle_analyzed_df_message, + LeaderMessageType.default: self._rpc._handle_default_message + } + self.channel_manager = ChannelManager() self.external_signal_config = config.get('external_signal', {}) # What the config should look like @@ -89,6 +94,8 @@ class ExternalSignalController(RPCHandler): self.ping_timeout = self.external_signal_config.get('follower_ping_timeout', 2) self.sleep_time = self.external_signal_config.get('follower_sleep_time', 5) + # Validate external_signal_config here? + if self.mode == ExternalSignalModeType.follower and len(self.leaders_list) == 0: raise ValueError("You must specify at least 1 leader in follower mode.") @@ -99,7 +106,6 @@ class ExternalSignalController(RPCHandler): default_api_key = secrets.token_urlsafe(16) self.secret_api_key = self.external_signal_config.get('api_token', default_api_key) - self.start_threaded_loop() self.start() def is_leader(self): @@ -114,6 +120,12 @@ class ExternalSignalController(RPCHandler): """ return self.external_signal_config.get('enabled', False) + def num_leaders(self): + """ + The number of leaders we should be connected to + """ + return len(self.leaders_list) + def start_threaded_loop(self): """ Start the main internal loop in another thread to run coroutines @@ -144,6 +156,7 @@ class ExternalSignalController(RPCHandler): """ Start the controller main loop """ + self.start_threaded_loop() self._main_task = self.submit_coroutine(self.main()) async def shutdown(self): @@ -242,23 +255,20 @@ class ExternalSignalController(RPCHandler): async def send_initial_data(self, channel): logger.info("Sending initial data through channel") - # We first send pairlist data - # We should move this to a func in the RPC object - initial_data = { - "data_type": LeaderMessageType.pairlist, - "data": self.freqtrade.pairlists.whitelist - } + data = self._rpc._initial_leader_data() - await channel.send(initial_data) + for message in data: + await channel.send(message) async def _handle_leader_message(self, message: MessageType): """ Handle message received from a Leader """ - type = message.get("data_type") + type = message.get("data_type", LeaderMessageType.default) data = message.get("data") - self._rpc._handle_emitted_data(type, data) + handler: Callable = self._message_handlers[type] + handler(type, data) # ---------------------------------------------------------------------- diff --git a/freqtrade/rpc/external_signal/utils.py b/freqtrade/rpc/external_signal/utils.py index 7b703810e..e5469dce3 100644 --- a/freqtrade/rpc/external_signal/utils.py +++ b/freqtrade/rpc/external_signal/utils.py @@ -1,5 +1,8 @@ +from pandas import DataFrame from starlette.websockets import WebSocket, WebSocketState +from freqtrade.enums.signaltype import SignalTagType, SignalType + async def is_websocket_alive(ws: WebSocket) -> bool: if ( @@ -8,3 +11,12 @@ async def is_websocket_alive(ws: WebSocket) -> bool: ): return True return False + + +def remove_entry_exit_signals(dataframe: DataFrame): + dataframe[SignalType.ENTER_LONG.value] = 0 + dataframe[SignalType.EXIT_LONG.value] = 0 + dataframe[SignalType.ENTER_SHORT.value] = 0 + dataframe[SignalType.EXIT_SHORT.value] = 0 + dataframe[SignalTagType.ENTER_TAG.value] = None + dataframe[SignalTagType.EXIT_TAG.value] = None diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 68871a15a..82d50f33c 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -24,7 +24,8 @@ from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, LeaderMessage from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler -from freqtrade.misc import decimals_per_coin, json_to_dataframe, shorten_date +from freqtrade.misc import (decimals_per_coin, json_to_dataframe, remove_entry_exit_signals, + shorten_date) from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1090,41 +1091,64 @@ class RPC: 'last_process_ts': int(last_p.timestamp()), } - def _handle_emitted_data(self, type, data): + # ------------------------------ EXTERNAL SIGNALS ----------------------- + + def _initial_leader_data(self): + # We create a list of Messages to send to the follower on connect + data = [] + + # Send Pairlist data + data.append({ + "data_type": LeaderMessageType.pairlist, + "data": self._freqtrade.pairlists._whitelist + }) + + return data + + def _handle_pairlist_message(self, type, data): """ - Handles the emitted data from the Leaders + Handles the emitted pairlists from the Leaders :param type: The data_type of the data :param data: The data """ - logger.debug(f"Handling emitted data of type ({type})") + pairlist = data - if type == LeaderMessageType.pairlist: - pairlist = data + logger.debug(f"Handling Pairlist message: {pairlist}") - logger.debug(pairlist) + external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] + external_pairlist.add_pairlist_data(pairlist) - # Add the pairlist data to the ExternalPairList object - external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] - external_pairlist.add_pairlist_data(pairlist) + def _handle_analyzed_df_message(self, type, data): + """ + Handles the analyzed dataframes from the Leaders - elif type == LeaderMessageType.analyzed_df: + :param type: The data_type of the data + :param data: The data + """ + key, value = data["key"], data["value"] + pair, timeframe, candle_type = key - # Convert the dataframe back from json - key, value = data["key"], data["value"] + # Skip any pairs that we don't have in the pairlist? + # leader_pairlist = self._freqtrade.pairlists._whitelist + # if pair not in leader_pairlist: + # return - pair, timeframe, candle_type = key + dataframe = json_to_dataframe(value) - # Skip any pairs that we don't have in the pairlist? - # leader_pairlist = self._freqtrade.pairlists._whitelist - # if pair not in leader_pairlist: - # return + if self._config.get('external_signal', {}).get('remove_signals_analyzed_df', False): + dataframe = remove_entry_exit_signals(dataframe) - dataframe = json_to_dataframe(value) + logger.debug(f"Handling analyzed dataframe for {pair}") + logger.debug(dataframe.tail()) - logger.debug(f"Received analyzed dataframe for {pair}") - logger.debug(dataframe.tail()) + # Add the dataframe to the dataprovider + dataprovider = self._freqtrade.dataprovider + dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) - # Add the dataframe to the dataprovider - dataprovider = self._freqtrade.dataprovider - dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) + def _handle_default_message(self, type, data): + """ + Default leader message handler, just logs it. We should never have to + run this unless the leader sends us some weird message. + """ + logger.debug(f"Received message from Leader of type {type}: {data}") diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 0a0e285a4..11e21da6f 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -45,25 +45,20 @@ class RPCManager: if config.get('api_server', {}).get('enabled', False): logger.info('Enabling rpc.api_server') from freqtrade.rpc.api_server import ApiServer - - # Pass replicate_rpc as param or defer starting api_server - # until we register the replicate rpc enpoint? apiserver = ApiServer(config) apiserver.add_rpc_handler(self._rpc) self.registered_modules.append(apiserver) - # Enable Replicate mode + # Enable External Signals mode # For this to be enabled, the API server must also be enabled if config.get('external_signal', {}).get('enabled', False): logger.info('Enabling RPC.ExternalSignalController') from freqtrade.rpc.external_signal import ExternalSignalController - external_signal_rpc = ExternalSignalController(self._rpc, config, apiserver) - self.registered_modules.append(external_signal_rpc) + external_signals = ExternalSignalController(self._rpc, config, apiserver) + self.registered_modules.append(external_signals) # Attach the controller to FreqTrade - freqtrade.external_signal_controller = external_signal_rpc - - apiserver.start_api() + freqtrade.external_signal_controller = external_signals def cleanup(self) -> None: """ Stops all enabled rpc modules """ diff --git a/requirements-replicate.txt b/requirements-externalsignals.txt similarity index 94% rename from requirements-replicate.txt rename to requirements-externalsignals.txt index 2c994ea2f..7920b34f6 100644 --- a/requirements-replicate.txt +++ b/requirements-externalsignals.txt @@ -4,3 +4,4 @@ # Required for follower websockets msgpack +janus diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 9a7bdfef6..af9f9d248 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -52,7 +52,6 @@ def botclient(default_conf, mocker): try: apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(rpc) - apiserver.start_api() yield ftbot, TestClient(apiserver.app) # Cleanup ... ? finally: @@ -333,7 +332,6 @@ def test_api_run(default_conf, mocker, caplog): apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) - apiserver.start_api() assert server_mock.call_count == 1 assert apiserver._config == default_conf apiserver.start_api() From fcceb744c5b0362464b59c13fb462291f4a977bb Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 26 Aug 2022 23:43:05 -0600 Subject: [PATCH 063/592] Add janus to requirements.txt --- freqtrade/rpc/external_signal/controller.py | 2 +- freqtrade/rpc/external_signal/thread_queue.py | 650 ------------------ 2 files changed, 1 insertion(+), 651 deletions(-) delete mode 100644 freqtrade/rpc/external_signal/thread_queue.py diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py index 01c15fc15..0d43b0b2d 100644 --- a/freqtrade/rpc/external_signal/controller.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -12,11 +12,11 @@ import websockets from fastapi import Depends from fastapi import WebSocket as FastAPIWebSocket from fastapi import WebSocketDisconnect, status +from janus import Queue as ThreadedQueue from freqtrade.enums import ExternalSignalModeType, LeaderMessageType, RPCMessageType from freqtrade.rpc import RPC, RPCHandler from freqtrade.rpc.external_signal.channel import ChannelManager -from freqtrade.rpc.external_signal.thread_queue import Queue as ThreadedQueue from freqtrade.rpc.external_signal.types import MessageType from freqtrade.rpc.external_signal.utils import is_websocket_alive diff --git a/freqtrade/rpc/external_signal/thread_queue.py b/freqtrade/rpc/external_signal/thread_queue.py deleted file mode 100644 index 88321321b..000000000 --- a/freqtrade/rpc/external_signal/thread_queue.py +++ /dev/null @@ -1,650 +0,0 @@ -import asyncio -import sys -import threading -from asyncio import QueueEmpty as AsyncQueueEmpty -from asyncio import QueueFull as AsyncQueueFull -from collections import deque -from heapq import heappop, heappush -from queue import Empty as SyncQueueEmpty -from queue import Full as SyncQueueFull -from typing import Any, Callable, Deque, Generic, List, Optional, Set, TypeVar - -from typing_extensions import Protocol - - -__version__ = "1.0.0" -__all__ = ( - "Queue", - "PriorityQueue", - "LifoQueue", - "SyncQueue", - "AsyncQueue", - "BaseQueue", -) - - -T = TypeVar("T") -OptFloat = Optional[float] - - -class BaseQueue(Protocol[T]): - @property - def maxsize(self) -> int: - ... - - @property - def closed(self) -> bool: - ... - - def task_done(self) -> None: - ... - - def qsize(self) -> int: - ... - - @property - def unfinished_tasks(self) -> int: - ... - - def empty(self) -> bool: - ... - - def full(self) -> bool: - ... - - def put_nowait(self, item: T) -> None: - ... - - def get_nowait(self) -> T: - ... - - -class SyncQueue(BaseQueue[T], Protocol[T]): - @property - def maxsize(self) -> int: - ... - - @property - def closed(self) -> bool: - ... - - def task_done(self) -> None: - ... - - def qsize(self) -> int: - ... - - @property - def unfinished_tasks(self) -> int: - ... - - def empty(self) -> bool: - ... - - def full(self) -> bool: - ... - - def put_nowait(self, item: T) -> None: - ... - - def get_nowait(self) -> T: - ... - - def put(self, item: T, block: bool = True, timeout: OptFloat = None) -> None: - ... - - def get(self, block: bool = True, timeout: OptFloat = None) -> T: - ... - - def join(self) -> None: - ... - - -class AsyncQueue(BaseQueue[T], Protocol[T]): - async def put(self, item: T) -> None: - ... - - async def get(self) -> T: - ... - - async def join(self) -> None: - ... - - -class Queue(Generic[T]): - def __init__(self, maxsize: int = 0) -> None: - self._loop = asyncio.get_running_loop() - self._maxsize = maxsize - - self._init(maxsize) - - self._unfinished_tasks = 0 - - self._sync_mutex = threading.Lock() - self._sync_not_empty = threading.Condition(self._sync_mutex) - self._sync_not_full = threading.Condition(self._sync_mutex) - self._all_tasks_done = threading.Condition(self._sync_mutex) - - self._async_mutex = asyncio.Lock() - if sys.version_info[:3] == (3, 10, 0): - # Workaround for Python 3.10 bug, see #358: - getattr(self._async_mutex, "_get_loop", lambda: None)() - self._async_not_empty = asyncio.Condition(self._async_mutex) - self._async_not_full = asyncio.Condition(self._async_mutex) - self._finished = asyncio.Event() - self._finished.set() - - self._closing = False - self._pending = set() # type: Set[asyncio.Future[Any]] - - def checked_call_soon_threadsafe( - callback: Callable[..., None], *args: Any - ) -> None: - try: - self._loop.call_soon_threadsafe(callback, *args) - except RuntimeError: - # swallowing agreed in #2 - pass - - self._call_soon_threadsafe = checked_call_soon_threadsafe - - def checked_call_soon(callback: Callable[..., None], *args: Any) -> None: - if not self._loop.is_closed(): - self._loop.call_soon(callback, *args) - - self._call_soon = checked_call_soon - - self._sync_queue = _SyncQueueProxy(self) - self._async_queue = _AsyncQueueProxy(self) - - def close(self) -> None: - with self._sync_mutex: - self._closing = True - for fut in self._pending: - fut.cancel() - self._finished.set() # unblocks all async_q.join() - self._all_tasks_done.notify_all() # unblocks all sync_q.join() - - async def wait_closed(self) -> None: - # should be called from loop after close(). - # Nobody should put/get at this point, - # so lock acquiring is not required - if not self._closing: - raise RuntimeError("Waiting for non-closed queue") - # give execution chances for the task-done callbacks - # of async tasks created inside - # _notify_async_not_empty, _notify_async_not_full - # methods. - await asyncio.sleep(0) - if not self._pending: - return - await asyncio.wait(self._pending) - - @property - def closed(self) -> bool: - return self._closing and not self._pending - - @property - def maxsize(self) -> int: - return self._maxsize - - @property - def sync_q(self) -> "_SyncQueueProxy[T]": - return self._sync_queue - - @property - def async_q(self) -> "_AsyncQueueProxy[T]": - return self._async_queue - - # Override these methods to implement other queue organizations - # (e.g. stack or priority queue). - # These will only be called with appropriate locks held - - def _init(self, maxsize: int) -> None: - self._queue = deque() # type: Deque[T] - - def _qsize(self) -> int: - return len(self._queue) - - # Put a new item in the queue - def _put(self, item: T) -> None: - self._queue.append(item) - - # Get an item from the queue - def _get(self) -> T: - return self._queue.popleft() - - def _put_internal(self, item: T) -> None: - self._put(item) - self._unfinished_tasks += 1 - self._finished.clear() - - def _notify_sync_not_empty(self) -> None: - def f() -> None: - with self._sync_mutex: - self._sync_not_empty.notify() - - self._loop.run_in_executor(None, f) - - def _notify_sync_not_full(self) -> None: - def f() -> None: - with self._sync_mutex: - self._sync_not_full.notify() - - fut = asyncio.ensure_future(self._loop.run_in_executor(None, f)) - fut.add_done_callback(self._pending.discard) - self._pending.add(fut) - - def _notify_async_not_empty(self, *, threadsafe: bool) -> None: - async def f() -> None: - async with self._async_mutex: - self._async_not_empty.notify() - - def task_maker() -> None: - task = self._loop.create_task(f()) - task.add_done_callback(self._pending.discard) - self._pending.add(task) - - if threadsafe: - self._call_soon_threadsafe(task_maker) - else: - self._call_soon(task_maker) - - def _notify_async_not_full(self, *, threadsafe: bool) -> None: - async def f() -> None: - async with self._async_mutex: - self._async_not_full.notify() - - def task_maker() -> None: - task = self._loop.create_task(f()) - task.add_done_callback(self._pending.discard) - self._pending.add(task) - - if threadsafe: - self._call_soon_threadsafe(task_maker) - else: - self._call_soon(task_maker) - - def _check_closing(self) -> None: - if self._closing: - raise RuntimeError("Operation on the closed queue is forbidden") - - -class _SyncQueueProxy(SyncQueue[T]): - """Create a queue object with a given maximum size. - - If maxsize is <= 0, the queue size is infinite. - """ - - def __init__(self, parent: Queue[T]): - self._parent = parent - - @property - def maxsize(self) -> int: - return self._parent._maxsize - - @property - def closed(self) -> bool: - return self._parent.closed - - def task_done(self) -> None: - """Indicate that a formerly enqueued task is complete. - - Used by Queue consumer threads. For each get() used to fetch a task, - a subsequent call to task_done() tells the queue that the processing - on the task is complete. - - If a join() is currently blocking, it will resume when all items - have been processed (meaning that a task_done() call was received - for every item that had been put() into the queue). - - Raises a ValueError if called more times than there were items - placed in the queue. - """ - self._parent._check_closing() - with self._parent._all_tasks_done: - unfinished = self._parent._unfinished_tasks - 1 - if unfinished <= 0: - if unfinished < 0: - raise ValueError("task_done() called too many times") - self._parent._all_tasks_done.notify_all() - self._parent._loop.call_soon_threadsafe(self._parent._finished.set) - self._parent._unfinished_tasks = unfinished - - def join(self) -> None: - """Blocks until all items in the Queue have been gotten and processed. - - The count of unfinished tasks goes up whenever an item is added to the - queue. The count goes down whenever a consumer thread calls task_done() - to indicate the item was retrieved and all work on it is complete. - - When the count of unfinished tasks drops to zero, join() unblocks. - """ - self._parent._check_closing() - with self._parent._all_tasks_done: - while self._parent._unfinished_tasks: - self._parent._all_tasks_done.wait() - self._parent._check_closing() - - def qsize(self) -> int: - """Return the approximate size of the queue (not reliable!).""" - return self._parent._qsize() - - @property - def unfinished_tasks(self) -> int: - """Return the number of unfinished tasks.""" - return self._parent._unfinished_tasks - - def empty(self) -> bool: - """Return True if the queue is empty, False otherwise (not reliable!). - - This method is likely to be removed at some point. Use qsize() == 0 - as a direct substitute, but be aware that either approach risks a race - condition where a queue can grow before the result of empty() or - qsize() can be used. - - To create code that needs to wait for all queued tasks to be - completed, the preferred technique is to use the join() method. - """ - return not self._parent._qsize() - - def full(self) -> bool: - """Return True if the queue is full, False otherwise (not reliable!). - - This method is likely to be removed at some point. Use qsize() >= n - as a direct substitute, but be aware that either approach risks a race - condition where a queue can shrink before the result of full() or - qsize() can be used. - """ - return 0 < self._parent._maxsize <= self._parent._qsize() - - def put(self, item: T, block: bool = True, timeout: OptFloat = None) -> None: - """Put an item into the queue. - - If optional args 'block' is true and 'timeout' is None (the default), - block if necessary until a free slot is available. If 'timeout' is - a non-negative number, it blocks at most 'timeout' seconds and raises - the Full exception if no free slot was available within that time. - Otherwise ('block' is false), put an item on the queue if a free slot - is immediately available, else raise the Full exception ('timeout' - is ignored in that case). - """ - self._parent._check_closing() - with self._parent._sync_not_full: - if self._parent._maxsize > 0: - if not block: - if self._parent._qsize() >= self._parent._maxsize: - raise SyncQueueFull - elif timeout is None: - while self._parent._qsize() >= self._parent._maxsize: - self._parent._sync_not_full.wait() - elif timeout < 0: - raise ValueError("'timeout' must be a non-negative number") - else: - time = self._parent._loop.time - endtime = time() + timeout - while self._parent._qsize() >= self._parent._maxsize: - remaining = endtime - time() - if remaining <= 0.0: - raise SyncQueueFull - self._parent._sync_not_full.wait(remaining) - self._parent._put_internal(item) - self._parent._sync_not_empty.notify() - self._parent._notify_async_not_empty(threadsafe=True) - - def get(self, block: bool = True, timeout: OptFloat = None) -> T: - """Remove and return an item from the queue. - - If optional args 'block' is true and 'timeout' is None (the default), - block if necessary until an item is available. If 'timeout' is - a non-negative number, it blocks at most 'timeout' seconds and raises - the Empty exception if no item was available within that time. - Otherwise ('block' is false), return an item if one is immediately - available, else raise the Empty exception ('timeout' is ignored - in that case). - """ - self._parent._check_closing() - with self._parent._sync_not_empty: - if not block: - if not self._parent._qsize(): - raise SyncQueueEmpty - elif timeout is None: - while not self._parent._qsize(): - self._parent._sync_not_empty.wait() - elif timeout < 0: - raise ValueError("'timeout' must be a non-negative number") - else: - time = self._parent._loop.time - endtime = time() + timeout - while not self._parent._qsize(): - remaining = endtime - time() - if remaining <= 0.0: - raise SyncQueueEmpty - self._parent._sync_not_empty.wait(remaining) - item = self._parent._get() - self._parent._sync_not_full.notify() - self._parent._notify_async_not_full(threadsafe=True) - return item - - def put_nowait(self, item: T) -> None: - """Put an item into the queue without blocking. - - Only enqueue the item if a free slot is immediately available. - Otherwise raise the Full exception. - """ - return self.put(item, block=False) - - def get_nowait(self) -> T: - """Remove and return an item from the queue without blocking. - - Only get an item if one is immediately available. Otherwise - raise the Empty exception. - """ - return self.get(block=False) - - -class _AsyncQueueProxy(AsyncQueue[T]): - """Create a queue object with a given maximum size. - - If maxsize is <= 0, the queue size is infinite. - """ - - def __init__(self, parent: Queue[T]): - self._parent = parent - - @property - def closed(self) -> bool: - return self._parent.closed - - def qsize(self) -> int: - """Number of items in the queue.""" - return self._parent._qsize() - - @property - def unfinished_tasks(self) -> int: - """Return the number of unfinished tasks.""" - return self._parent._unfinished_tasks - - @property - def maxsize(self) -> int: - """Number of items allowed in the queue.""" - return self._parent._maxsize - - def empty(self) -> bool: - """Return True if the queue is empty, False otherwise.""" - return self.qsize() == 0 - - def full(self) -> bool: - """Return True if there are maxsize items in the queue. - - Note: if the Queue was initialized with maxsize=0 (the default), - then full() is never True. - """ - if self._parent._maxsize <= 0: - return False - else: - return self.qsize() >= self._parent._maxsize - - async def put(self, item: T) -> None: - """Put an item into the queue. - - Put an item into the queue. If the queue is full, wait until a free - slot is available before adding item. - - This method is a coroutine. - """ - self._parent._check_closing() - async with self._parent._async_not_full: - self._parent._sync_mutex.acquire() - locked = True - try: - if self._parent._maxsize > 0: - do_wait = True - while do_wait: - do_wait = self._parent._qsize() >= self._parent._maxsize - if do_wait: - locked = False - self._parent._sync_mutex.release() - await self._parent._async_not_full.wait() - self._parent._sync_mutex.acquire() - locked = True - - self._parent._put_internal(item) - self._parent._async_not_empty.notify() - self._parent._notify_sync_not_empty() - finally: - if locked: - self._parent._sync_mutex.release() - - def put_nowait(self, item: T) -> None: - """Put an item into the queue without blocking. - - If no free slot is immediately available, raise QueueFull. - """ - self._parent._check_closing() - with self._parent._sync_mutex: - if self._parent._maxsize > 0: - if self._parent._qsize() >= self._parent._maxsize: - raise AsyncQueueFull - - self._parent._put_internal(item) - self._parent._notify_async_not_empty(threadsafe=False) - self._parent._notify_sync_not_empty() - - async def get(self) -> T: - """Remove and return an item from the queue. - - If queue is empty, wait until an item is available. - - This method is a coroutine. - """ - self._parent._check_closing() - async with self._parent._async_not_empty: - self._parent._sync_mutex.acquire() - locked = True - try: - do_wait = True - while do_wait: - do_wait = self._parent._qsize() == 0 - - if do_wait: - locked = False - self._parent._sync_mutex.release() - await self._parent._async_not_empty.wait() - self._parent._sync_mutex.acquire() - locked = True - - item = self._parent._get() - self._parent._async_not_full.notify() - self._parent._notify_sync_not_full() - return item - finally: - if locked: - self._parent._sync_mutex.release() - - def get_nowait(self) -> T: - """Remove and return an item from the queue. - - Return an item if one is immediately available, else raise QueueEmpty. - """ - self._parent._check_closing() - with self._parent._sync_mutex: - if self._parent._qsize() == 0: - raise AsyncQueueEmpty - - item = self._parent._get() - self._parent._notify_async_not_full(threadsafe=False) - self._parent._notify_sync_not_full() - return item - - def task_done(self) -> None: - """Indicate that a formerly enqueued task is complete. - - Used by queue consumers. For each get() used to fetch a task, - a subsequent call to task_done() tells the queue that the processing - on the task is complete. - - If a join() is currently blocking, it will resume when all items have - been processed (meaning that a task_done() call was received for every - item that had been put() into the queue). - - Raises ValueError if called more times than there were items placed in - the queue. - """ - self._parent._check_closing() - with self._parent._all_tasks_done: - if self._parent._unfinished_tasks <= 0: - raise ValueError("task_done() called too many times") - self._parent._unfinished_tasks -= 1 - if self._parent._unfinished_tasks == 0: - self._parent._finished.set() - self._parent._all_tasks_done.notify_all() - - async def join(self) -> None: - """Block until all items in the queue have been gotten and processed. - - The count of unfinished tasks goes up whenever an item is added to the - queue. The count goes down whenever a consumer calls task_done() to - indicate that the item was retrieved and all work on it is complete. - When the count of unfinished tasks drops to zero, join() unblocks. - """ - while True: - with self._parent._sync_mutex: - self._parent._check_closing() - if self._parent._unfinished_tasks == 0: - break - await self._parent._finished.wait() - - -class PriorityQueue(Queue[T]): - """Variant of Queue that retrieves open entries in priority order - (lowest first). - - Entries are typically tuples of the form: (priority number, data). - - """ - - def _init(self, maxsize: int) -> None: - self._heap_queue = [] # type: List[T] - - def _qsize(self) -> int: - return len(self._heap_queue) - - def _put(self, item: T) -> None: - heappush(self._heap_queue, item) - - def _get(self) -> T: - return heappop(self._heap_queue) - - -class LifoQueue(Queue[T]): - """Variant of Queue that retrieves most recently added entries first.""" - - def _qsize(self) -> int: - return len(self._queue) - - def _put(self, item: T) -> None: - self._queue.append(item) - - def _get(self) -> T: - return self._queue.pop() From 05ca673883146a543bfb3d739a1ad05368dd28bc Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 27 Aug 2022 00:06:03 -0600 Subject: [PATCH 064/592] Catch status code errors --- freqtrade/rpc/external_signal/controller.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py index 0d43b0b2d..29a318b53 100644 --- a/freqtrade/rpc/external_signal/controller.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -437,12 +437,12 @@ class ExternalSignalController(RPCHandler): # as we might call the RPC module in the main thread await self._handle_leader_message(data) - except socket.gaierror: - logger.info(f"Socket error - retrying connection in {self.sleep_time}s") + except (socket.gaierror, ConnectionRefusedError): + logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") await asyncio.sleep(self.sleep_time) continue - except ConnectionRefusedError: - logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") + except websockets.exceptions.InvalidStatusCode as e: + logger.error(f"Connection Refused - {e}") await asyncio.sleep(self.sleep_time) continue From 2b70c3d0c00d6e90c1f5c14782e00eb86f14d52f Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 08:50:09 +0200 Subject: [PATCH 065/592] support price callback for partial exits in bt This will align results to how live works. closes #7292 --- docs/bot-basics.md | 2 +- docs/strategy-callbacks.md | 2 +- freqtrade/optimize/backtesting.py | 38 +++++++++++++++++-------------- 3 files changed, 23 insertions(+), 19 deletions(-) diff --git a/docs/bot-basics.md b/docs/bot-basics.md index 14823722e..3df926371 100644 --- a/docs/bot-basics.md +++ b/docs/bot-basics.md @@ -70,7 +70,7 @@ This loop will be repeated again and again until the bot is stopped. * Determine stake size by calling the `custom_stake_amount()` callback. * Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested. * Call `custom_stoploss()` and `custom_exit()` to find custom exit points. - * For exits based on exit-signal and custom-exit: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle). + * For exits based on exit-signal, custom-exit and partial exits: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle). * Generate backtest report output !!! Note diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md index 8d46f42e1..32ad1b288 100644 --- a/docs/strategy-callbacks.md +++ b/docs/strategy-callbacks.md @@ -423,7 +423,7 @@ class AwesomeStrategy(IStrategy): !!! Warning "Backtesting" Custom prices are supported in backtesting (starting with 2021.12), and orders will fill if the price falls within the candle's low/high range. Orders that don't fill immediately are subject to regular timeout handling, which happens once per (detail) candle. - `custom_exit_price()` is only called for sells of type exit_signal and Custom exit. All other exit-types will use regular backtesting prices. + `custom_exit_price()` is only called for sells of type exit_signal, Custom exit and partial exits. All other exit-types will use regular backtesting prices. ## Custom order timeout rules diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index ff30dbc2a..57b272e86 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -554,7 +554,8 @@ class Backtesting: if remaining < min_stake: # Remaining stake is too low to be sold. return trade - pos_trade = self._exit_trade(trade, row, current_rate, amount) + exit_ = ExitCheckTuple(ExitType.PARTIAL_EXIT) + pos_trade = self._get_exit_for_signal(trade, row, exit_, amount) if pos_trade is not None: order = pos_trade.orders[-1] if self._get_order_filled(order.price, row): @@ -589,14 +590,15 @@ class Backtesting: return t return None - def _get_exit_for_signal(self, trade: LocalTrade, row: Tuple, - exit_: ExitCheckTuple) -> Optional[LocalTrade]: + def _get_exit_for_signal( + self, trade: LocalTrade, row: Tuple, exit_: ExitCheckTuple, + amount: Optional[float] = None) -> Optional[LocalTrade]: exit_candle_time: datetime = row[DATE_IDX].to_pydatetime() if exit_.exit_flag: trade.close_date = exit_candle_time exit_reason = exit_.exit_reason - + amount_ = amount if amount is not None else trade.amount trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60) try: close_rate = self._get_close_rate(row, trade, exit_, trade_dur) @@ -605,7 +607,8 @@ class Backtesting: # call the custom exit price,with default value as previous close_rate current_profit = trade.calc_profit_ratio(close_rate) order_type = self.strategy.order_types['exit'] - if exit_.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT): + if exit_.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT, + ExitType.PARTIAL_EXIT): # Checks and adds an exit tag, after checking that the length of the # row has the length for an exit tag column if ( @@ -633,22 +636,23 @@ class Backtesting: # Confirm trade exit: time_in_force = self.strategy.order_time_in_force['exit'] - if (exit_.exit_type != ExitType.LIQUIDATION and not strategy_safe_wrapper( - self.strategy.confirm_trade_exit, default_retval=True)( - pair=trade.pair, - trade=trade, # type: ignore[arg-type] - order_type=order_type, - amount=trade.amount, - rate=close_rate, - time_in_force=time_in_force, - sell_reason=exit_reason, # deprecated - exit_reason=exit_reason, - current_time=exit_candle_time)): + if (exit_.exit_type not in (ExitType.LIQUIDATION, ExitType.PARTIAL_EXIT) + and not strategy_safe_wrapper( + self.strategy.confirm_trade_exit, default_retval=True)( + pair=trade.pair, + trade=trade, # type: ignore[arg-type] + order_type=order_type, + amount=amount_, + rate=close_rate, + time_in_force=time_in_force, + sell_reason=exit_reason, # deprecated + exit_reason=exit_reason, + current_time=exit_candle_time)): return None trade.exit_reason = exit_reason - return self._exit_trade(trade, row, close_rate, trade.amount) + return self._exit_trade(trade, row, close_rate, amount_) return None def _exit_trade(self, trade: LocalTrade, sell_row: Tuple, From c3e74e6e8d59f002185112547f88ddb187484bee Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 08:55:29 +0200 Subject: [PATCH 066/592] Improve doc wording --- docs/hyperopt.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/hyperopt.md b/docs/hyperopt.md index d230c091e..6b6c2a772 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -432,10 +432,10 @@ While this strategy is most likely too simple to provide consistent profit, it s `range` property may also be used with `DecimalParameter` and `CategoricalParameter`. `RealParameter` does not provide this property due to infinite search space. ??? Hint "Performance tip" - By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter. - While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values). - As this also has Performance implications, hyperopt provides `--analyze-per-epoch` - which will move the execution of `populate_indicators()` to the epoch process. This will implicitly also change the `.range` functionality to only return the actually used value. - You should however try to use space ranges as small as possible. + During normal hyperopting, indicators are calculated once and supplied to each epoch, linearly increasing RAM usage as a factor of increasing cores. As this also has performance implications, hyperopt provides `--analyze-per-epoch` which will move the execution of `populate_indicators()` to the epoch process, calculating a single value per parameter per epoch instead of using the `.range` functionality. In this case, `.range` functionality will only return the actually used value. This will reduce RAM usage, but increase CPU usage. However, your hyperopting run will be less likely to fail due to Out Of Memory (OOM) issues. + + In either case, you should try to use space ranges as small as possible this will improve CPU/RAM usage in both scenarios. + ## Optimizing protections From 104a73025dac841c2d13819b260cf1ab70325fce Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 10:24:56 +0200 Subject: [PATCH 067/592] Uppercase TimeInForce (align with ccxt) --- config_examples/config_full.example.json | 4 ++-- docs/configuration.md | 8 ++++---- docs/exchanges.md | 2 +- docs/strategy_migration.md | 4 ++-- freqtrade/constants.py | 3 ++- freqtrade/exchange/binance.py | 3 +-- freqtrade/exchange/exchange.py | 12 ++++++------ freqtrade/exchange/gateio.py | 7 +++---- freqtrade/exchange/kraken.py | 2 +- freqtrade/exchange/kucoin.py | 3 +-- freqtrade/exchange/okx.py | 2 +- freqtrade/strategy/interface.py | 4 ++-- freqtrade/templates/base_strategy.py.j2 | 4 ++-- freqtrade/templates/sample_strategy.py | 4 ++-- tests/exchange/test_exchange.py | 20 ++++++++++---------- tests/exchange/test_kraken.py | 2 +- tests/strategy/test_strategy_loading.py | 8 ++++---- tests/test_configuration.py | 8 ++++---- 18 files changed, 49 insertions(+), 51 deletions(-) diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 74457d2b6..8155cb145 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -64,8 +64,8 @@ "stoploss_on_exchange_limit_ratio": 0.99 }, "order_time_in_force": { - "entry": "gtc", - "exit": "gtc" + "entry": "GTC", + "exit": "GTC" }, "pairlists": [ {"method": "StaticPairList"}, diff --git a/docs/configuration.md b/docs/configuration.md index d5c0b3d8b..851bbcd82 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -525,16 +525,16 @@ It means if the order is not executed immediately AND fully then it is cancelled It is the same as FOK (above) except it can be partially fulfilled. The remaining part is automatically cancelled by the exchange. -The `order_time_in_force` parameter contains a dict with buy and sell time in force policy values. +The `order_time_in_force` parameter contains a dict with entry and exit time in force policy values. This can be set in the configuration file or in the strategy. Values set in the configuration file overwrites values set in the strategy. -The possible values are: `gtc` (default), `fok` or `ioc`. +The possible values are: `GTC` (default), `FOK` or `IOC`. ``` python "order_time_in_force": { - "entry": "gtc", - "exit": "gtc" + "entry": "GTC", + "exit": "GTC" }, ``` diff --git a/docs/exchanges.md b/docs/exchanges.md index 50ebf9e0a..407a67d70 100644 --- a/docs/exchanges.md +++ b/docs/exchanges.md @@ -278,7 +278,7 @@ For example, to test the order type `FOK` with Kraken, and modify candle limit t "exchange": { "name": "kraken", "_ft_has_params": { - "order_time_in_force": ["gtc", "fok"], + "order_time_in_force": ["GTC", "FOK"], "ohlcv_candle_limit": 200 } //... diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md index 064e7a59d..ac65abff4 100644 --- a/docs/strategy_migration.md +++ b/docs/strategy_migration.md @@ -332,8 +332,8 @@ After: ``` python hl_lines="2 3" order_time_in_force: Dict = { - "entry": "gtc", - "exit": "gtc", + "entry": "GTC", + "exit": "GTC", } ``` diff --git a/freqtrade/constants.py b/freqtrade/constants.py index ddbc84fa9..bab8c4816 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -23,7 +23,8 @@ REQUIRED_ORDERTIF = ['entry', 'exit'] REQUIRED_ORDERTYPES = ['entry', 'exit', 'stoploss', 'stoploss_on_exchange'] PRICING_SIDES = ['ask', 'bid', 'same', 'other'] ORDERTYPE_POSSIBILITIES = ['limit', 'market'] -ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc'] +_ORDERTIF_POSSIBILITIES = ['GTC', 'FOK', 'IOC', 'PO'] +ORDERTIF_POSSIBILITIES = _ORDERTIF_POSSIBILITIES + [t.lower() for t in _ORDERTIF_POSSIBILITIES] HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss', 'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily', 'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily', diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py index a5e9fd37c..026ba1c65 100644 --- a/freqtrade/exchange/binance.py +++ b/freqtrade/exchange/binance.py @@ -23,8 +23,7 @@ class Binance(Exchange): _ft_has: Dict = { "stoploss_on_exchange": True, "stoploss_order_types": {"limit": "stop_loss_limit"}, - "order_time_in_force": ['gtc', 'fok', 'ioc'], - "time_in_force_parameter": "timeInForce", + "order_time_in_force": ['GTC', 'FOK', 'IOC'], "ohlcv_candle_limit": 1000, "trades_pagination": "id", "trades_pagination_arg": "fromId", diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 4386f47f6..586a364c5 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -62,7 +62,7 @@ class Exchange: # or by specifying them in the configuration. _ft_has_default: Dict = { "stoploss_on_exchange": False, - "order_time_in_force": ["gtc"], + "order_time_in_force": ["GTC"], "time_in_force_parameter": "timeInForce", "ohlcv_params": {}, "ohlcv_candle_limit": 500, @@ -611,7 +611,7 @@ class Exchange: """ Checks if order time in force configured in strategy/config are supported """ - if any(v not in self._ft_has["order_time_in_force"] + if any(v.upper() not in self._ft_has["order_time_in_force"] for k, v in order_time_in_force.items()): raise OperationalException( f'Time in force policies are not supported for {self.name} yet.') @@ -989,12 +989,12 @@ class Exchange: ordertype: str, leverage: float, reduceOnly: bool, - time_in_force: str = 'gtc', + time_in_force: str = 'GTC', ) -> Dict: params = self._params.copy() - if time_in_force != 'gtc' and ordertype != 'market': + if time_in_force != 'GTC' and ordertype != 'market': param = self._ft_has.get('time_in_force_parameter', '') - params.update({param: time_in_force}) + params.update({param: time_in_force.upper()}) if reduceOnly: params.update({'reduceOnly': True}) return params @@ -1009,7 +1009,7 @@ class Exchange: rate: float, leverage: float, reduceOnly: bool = False, - time_in_force: str = 'gtc', + time_in_force: str = 'GTC', ) -> Dict: if self._config['dry_run']: dry_order = self.create_dry_run_order( diff --git a/freqtrade/exchange/gateio.py b/freqtrade/exchange/gateio.py index 426a4b64d..ab127a036 100644 --- a/freqtrade/exchange/gateio.py +++ b/freqtrade/exchange/gateio.py @@ -25,8 +25,7 @@ class Gateio(Exchange): _ft_has: Dict = { "ohlcv_candle_limit": 1000, - "time_in_force_parameter": "timeInForce", - "order_time_in_force": ['gtc', 'ioc'], + "order_time_in_force": ['GTC', 'IOC'], "stoploss_order_types": {"limit": "limit"}, "stoploss_on_exchange": True, } @@ -57,7 +56,7 @@ class Gateio(Exchange): ordertype: str, leverage: float, reduceOnly: bool, - time_in_force: str = 'gtc', + time_in_force: str = 'GTC', ) -> Dict: params = super()._get_params( side=side, @@ -69,7 +68,7 @@ class Gateio(Exchange): if ordertype == 'market' and self.trading_mode == TradingMode.FUTURES: params['type'] = 'market' param = self._ft_has.get('time_in_force_parameter', '') - params.update({param: 'ioc'}) + params.update({param: 'IOC'}) return params def get_trades_for_order(self, order_id: str, pair: str, since: datetime, diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py index 0103e2702..6c9b88eae 100644 --- a/freqtrade/exchange/kraken.py +++ b/freqtrade/exchange/kraken.py @@ -171,7 +171,7 @@ class Kraken(Exchange): ordertype: str, leverage: float, reduceOnly: bool, - time_in_force: str = 'gtc' + time_in_force: str = 'GTC' ) -> Dict: params = super()._get_params( side=side, diff --git a/freqtrade/exchange/kucoin.py b/freqtrade/exchange/kucoin.py index 21eaa4bc3..f05fd3f56 100644 --- a/freqtrade/exchange/kucoin.py +++ b/freqtrade/exchange/kucoin.py @@ -23,8 +23,7 @@ class Kucoin(Exchange): "stoploss_order_types": {"limit": "limit", "market": "market"}, "l2_limit_range": [20, 100], "l2_limit_range_required": False, - "order_time_in_force": ['gtc', 'fok', 'ioc'], - "time_in_force_parameter": "timeInForce", + "order_time_in_force": ['GTC', 'FOK', 'IOC'], "ohlcv_candle_limit": 1500, } diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py index f039f2b3f..9340dd0e4 100644 --- a/freqtrade/exchange/okx.py +++ b/freqtrade/exchange/okx.py @@ -98,7 +98,7 @@ class Okx(Exchange): ordertype: str, leverage: float, reduceOnly: bool, - time_in_force: str = 'gtc', + time_in_force: str = 'GTC', ) -> Dict: params = super()._get_params( side=side, diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 79dbd4c69..db16ac383 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -78,8 +78,8 @@ class IStrategy(ABC, HyperStrategyMixin): # Optional time in force order_time_in_force: Dict = { - 'entry': 'gtc', - 'exit': 'gtc', + 'entry': 'GTC', + 'exit': 'GTC', } # run "populate_indicators" only for new candle diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2 index 610a7a96e..5a4504687 100644 --- a/freqtrade/templates/base_strategy.py.j2 +++ b/freqtrade/templates/base_strategy.py.j2 @@ -88,8 +88,8 @@ class {{ strategy }}(IStrategy): # Optional order time in force. order_time_in_force = { - 'entry': 'gtc', - 'exit': 'gtc' + 'entry': 'GTC', + 'exit': 'GTC' } {{ plot_config | indent(4) }} diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index 1b375714a..1eb3d4256 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -88,8 +88,8 @@ class SampleStrategy(IStrategy): # Optional order time in force. order_time_in_force = { - 'entry': 'gtc', - 'exit': 'gtc' + 'entry': 'GTC', + 'exit': 'GTC' } plot_config = { diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 093284668..b1f22e647 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -275,7 +275,7 @@ def test_validate_order_time_in_force(default_conf, mocker, caplog): ex.validate_order_time_in_force(tif2) # Patch to see if this will pass if the values are in the ft dict - ex._ft_has.update({"order_time_in_force": ["gtc", "fok", "ioc"]}) + ex._ft_has.update({"order_time_in_force": ["GTC", "FOK", "IOC"]}) ex.validate_order_time_in_force(tif2) @@ -1503,7 +1503,7 @@ def test_buy_considers_time_in_force(default_conf, mocker, exchange_name): assert api_mock.create_order.call_args[0][3] == 1 assert api_mock.create_order.call_args[0][4] == 200 assert "timeInForce" in api_mock.create_order.call_args[0][5] - assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force + assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force.upper() order_type = 'market' time_in_force = 'ioc' @@ -1642,10 +1642,10 @@ def test_sell_considers_time_in_force(default_conf, mocker, exchange_name): assert api_mock.create_order.call_args[0][3] == 1 assert api_mock.create_order.call_args[0][4] == 200 assert "timeInForce" in api_mock.create_order.call_args[0][5] - assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force + assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force.upper() order_type = 'market' - time_in_force = 'ioc' + time_in_force = 'IOC' order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200, leverage=1.0, time_in_force=time_in_force) @@ -3319,7 +3319,7 @@ def test_merge_ft_has_dict(default_conf, mocker): ex = Binance(default_conf) assert ex._ft_has != Exchange._ft_has_default assert ex.get_option('stoploss_on_exchange') - assert ex.get_option('order_time_in_force') == ['gtc', 'fok', 'ioc'] + assert ex.get_option('order_time_in_force') == ['GTC', 'FOK', 'IOC'] assert ex.get_option('trades_pagination') == 'id' assert ex.get_option('trades_pagination_arg') == 'fromId' @@ -4954,7 +4954,7 @@ def test__get_params(mocker, default_conf, exchange_name): params1 = {'test': True} params2 = { 'test': True, - 'timeInForce': 'ioc', + 'timeInForce': 'IOC', 'reduceOnly': True, } @@ -4969,7 +4969,7 @@ def test__get_params(mocker, default_conf, exchange_name): side="buy", ordertype='market', reduceOnly=False, - time_in_force='gtc', + time_in_force='GTC', leverage=1.0, ) == params1 @@ -4977,7 +4977,7 @@ def test__get_params(mocker, default_conf, exchange_name): side="buy", ordertype='market', reduceOnly=False, - time_in_force='ioc', + time_in_force='IOC', leverage=1.0, ) == params1 @@ -4985,7 +4985,7 @@ def test__get_params(mocker, default_conf, exchange_name): side="buy", ordertype='limit', reduceOnly=False, - time_in_force='gtc', + time_in_force='GTC', leverage=1.0, ) == params1 @@ -4998,7 +4998,7 @@ def test__get_params(mocker, default_conf, exchange_name): side="buy", ordertype='limit', reduceOnly=True, - time_in_force='ioc', + time_in_force='IOC', leverage=3.0, ) == params2 diff --git a/tests/exchange/test_kraken.py b/tests/exchange/test_kraken.py index 02df60990..66006f2fe 100644 --- a/tests/exchange/test_kraken.py +++ b/tests/exchange/test_kraken.py @@ -50,7 +50,7 @@ def test_buy_kraken_trading_agreement(default_conf, mocker): assert api_mock.create_order.call_args[0][2] == 'buy' assert api_mock.create_order.call_args[0][3] == 1 assert api_mock.create_order.call_args[0][4] == 200 - assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'ioc', + assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'IOC', 'trading_agreement': 'agree'} diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index b794cdc99..bf81cd068 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -275,8 +275,8 @@ def test_strategy_override_order_tif(caplog, default_conf): caplog.set_level(logging.INFO) order_time_in_force = { - 'entry': 'fok', - 'exit': 'gtc', + 'entry': 'FOK', + 'exit': 'GTC', } default_conf.update({ @@ -290,11 +290,11 @@ def test_strategy_override_order_tif(caplog, default_conf): assert strategy.order_time_in_force[method] == order_time_in_force[method] assert log_has("Override strategy 'order_time_in_force' with value in config file:" - " {'entry': 'fok', 'exit': 'gtc'}.", caplog) + " {'entry': 'FOK', 'exit': 'GTC'}.", caplog) default_conf.update({ 'strategy': CURRENT_TEST_STRATEGY, - 'order_time_in_force': {'entry': 'fok'} + 'order_time_in_force': {'entry': 'FOK'} }) # Raise error for invalid configuration with pytest.raises(ImportError, diff --git a/tests/test_configuration.py b/tests/test_configuration.py index db87c405f..2825ede5c 100644 --- a/tests/test_configuration.py +++ b/tests/test_configuration.py @@ -973,17 +973,17 @@ def test_validate_time_in_force(default_conf, caplog) -> None: conf = deepcopy(default_conf) conf['order_time_in_force'] = { 'buy': 'gtc', - 'sell': 'gtc', + 'sell': 'GTC', } validate_config_consistency(conf) assert log_has_re(r"DEPRECATED: Using 'buy' and 'sell' for time_in_force is.*", caplog) assert conf['order_time_in_force']['entry'] == 'gtc' - assert conf['order_time_in_force']['exit'] == 'gtc' + assert conf['order_time_in_force']['exit'] == 'GTC' conf = deepcopy(default_conf) conf['order_time_in_force'] = { - 'buy': 'gtc', - 'sell': 'gtc', + 'buy': 'GTC', + 'sell': 'GTC', } conf['trading_mode'] = 'futures' with pytest.raises(OperationalException, From c61b986c3d7638640ed9b682db42a91f2c8ffe72 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 10:30:38 +0200 Subject: [PATCH 068/592] FTX - support time_in_force (and PO ordertype) closes #7175 --- docs/configuration.md | 9 ++++++++- freqtrade/exchange/ftx.py | 1 + 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/docs/configuration.md b/docs/configuration.md index 851bbcd82..940d5e8b0 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -525,6 +525,13 @@ It means if the order is not executed immediately AND fully then it is cancelled It is the same as FOK (above) except it can be partially fulfilled. The remaining part is automatically cancelled by the exchange. +**PO (Post only):** + +Post only order. The order is either placed as a maker order, or it is canceled. +This means the order must be placed on orderbook for at at least time in an unfilled state. + +#### time_in_force config + The `order_time_in_force` parameter contains a dict with entry and exit time in force policy values. This can be set in the configuration file or in the strategy. Values set in the configuration file overwrites values set in the strategy. @@ -539,7 +546,7 @@ The possible values are: `GTC` (default), `FOK` or `IOC`. ``` !!! Warning - This is ongoing work. For now, it is supported only for binance and kucoin. + This is ongoing work. For now, it is supported only for binance, gate, ftx and kucoin. Please don't change the default value unless you know what you are doing and have researched the impact of using different values for your particular exchange. ### What values can be used for fiat_display_currency? diff --git a/freqtrade/exchange/ftx.py b/freqtrade/exchange/ftx.py index b3c219542..6a43ab302 100644 --- a/freqtrade/exchange/ftx.py +++ b/freqtrade/exchange/ftx.py @@ -19,6 +19,7 @@ logger = logging.getLogger(__name__) class Ftx(Exchange): _ft_has: Dict = { + "order_time_in_force": ['GTC', 'IOC', 'PO'], "stoploss_on_exchange": True, "ohlcv_candle_limit": 1500, "ohlcv_require_since": True, From 71f7d687832316ae5524c3a87491f50ddbfa28f9 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Sat, 27 Aug 2022 12:44:55 +0200 Subject: [PATCH 069/592] Fixed mypy error --- freqtrade/freqai/data_kitchen.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index c58cfa75a..eb9f6beb7 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -513,7 +513,7 @@ class FreqaiDataKitchen: return avg_mean_dist - def get_outlier_percentage(self, dropped_pts: npt.ArrayLike) -> float: + def get_outlier_percentage(self, dropped_pts: npt.NDArray) -> float: """ Check if more than X% of points werer dropped during outlier detection. """ @@ -568,7 +568,7 @@ class FreqaiDataKitchen: outlier_ptc = self.get_outlier_percentage(dropped_points) if outlier_ptc: logger.warning( - f"SVM detected >{outlier_ptc}% of the points as outliers." + f"SVM detected > {outlier_ptc}% of the points as outliers." f"Keeping original dataset." ) return @@ -691,7 +691,7 @@ class FreqaiDataKitchen: outlier_ptc = self.get_outlier_percentage(dropped_points) if outlier_ptc: logger.warning( - f"DBSCAN detected >{outlier_ptc}% of the points as outliers." + f"DBSCAN detected > {outlier_ptc}% of the points as outliers." f"Keeping original dataset." ) return @@ -754,7 +754,7 @@ class FreqaiDataKitchen: outlier_ptc = self.get_outlier_percentage(1 - do_predict) if outlier_ptc: logger.warning( - f"DBSCAN detected >{outlier_ptc}% of the points as outliers." + f"DI detected > {outlier_ptc}% of the points as outliers." f"Keeping original dataset." ) return From 59a723aec82bdc2c8cacbb2ebe90bb9d8d50f6e2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Aug 2022 15:12:04 +0200 Subject: [PATCH 070/592] Add /health to rest client discovered in #7299 --- docs/rest-api.md | 8 ++++++++ scripts/rest_client.py | 7 +++++++ 2 files changed, 15 insertions(+) diff --git a/docs/rest-api.md b/docs/rest-api.md index d9840a09c..cc82aadda 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -163,6 +163,8 @@ python3 scripts/rest_client.py --config rest_config.json [optional par | `strategy ` | Get specific Strategy content. **Alpha** | `available_pairs` | List available backtest data. **Alpha** | `version` | Show version. +| `sysinfo` | Show informations about the system load. +| `health` | Show bot health (last bot loop). !!! Warning "Alpha status" Endpoints labeled with *Alpha status* above may change at any time without notice. @@ -227,6 +229,11 @@ forceexit Force-exit a trade. :param tradeid: Id of the trade (can be received via status command) + :param ordertype: Order type to use (must be market or limit) + :param amount: Amount to sell. Full sell if not given + +health + Provides a quick health check of the running bot. locks Return current locks @@ -312,6 +319,7 @@ version whitelist Show the current whitelist. + ``` ### OpenAPI interface diff --git a/scripts/rest_client.py b/scripts/rest_client.py index 989e6a50d..ac6d97133 100755 --- a/scripts/rest_client.py +++ b/scripts/rest_client.py @@ -361,6 +361,13 @@ class FtRestClient(): """ return self._get("sysinfo") + def health(self): + """Provides a quick health check of the running bot. + + :return: json object + """ + return self._get("health") + def add_arguments(): parser = argparse.ArgumentParser() From 005594c29cad73c7814059312af5def40ee8bfa6 Mon Sep 17 00:00:00 2001 From: smarmau Date: Sun, 28 Aug 2022 11:29:48 +0200 Subject: [PATCH 071/592] simplify hybrid template --- .../templates/FreqaiHybridExampleStrategy.py | 256 +++++++----------- 1 file changed, 93 insertions(+), 163 deletions(-) diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index bb9c37b03..dfd67ae90 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -4,6 +4,7 @@ import numpy as np import pandas as pd import talib.abstract as ta from pandas import DataFrame +from technical import qtpylib from freqtrade.strategy import IntParameter, IStrategy, merge_informative_pair @@ -48,7 +49,7 @@ class FreqaiExampleHybridStrategy(IStrategy): "indicator_periods_candles": [10, 20] }, "data_split_parameters": { - "test_size": 0.33, + "test_size": 0, "random_state": 1 }, "model_training_parameters": { @@ -56,49 +57,44 @@ class FreqaiExampleHybridStrategy(IStrategy): } }, - Thanks to @smarm and @jooopieeert for developing and sharing the strategy. + Thanks to @smarmau and @johanvulgt for developing and sharing the strategy. """ - minimal_roi = {"0": 0.1, "30": 0.75, "60": 0.05, "120": 0.025, "240": -1} + minimal_roi = { + "60": 0.01, + "30": 0.02, + "0": 0.04 + } + + plot_config = { + 'main_plot': { + 'tema': {}, + }, + 'subplots': { + "MACD": { + 'macd': {'color': 'blue'}, + 'macdsignal': {'color': 'orange'}, + }, + "RSI": { + 'rsi': {'color': 'red'}, + }, + "Up_or_down": { + '&s-up_or_down': {'color': 'green'}, + } + } + } process_only_new_candles = True - stoploss = -0.1 + stoploss = -0.05 use_exit_signal = True startup_candle_count: int = 300 can_short = True - buy_params = { - "buy_m1": 4, - "buy_m2": 7, - "buy_m3": 1, - "buy_p1": 8, - "buy_p2": 9, - "buy_p3": 8, - } - - # Sell hyperspace params: - sell_params = { - "sell_m1": 1, - "sell_m2": 3, - "sell_m3": 6, - "sell_p1": 16, - "sell_p2": 18, - "sell_p3": 18, - } - - buy_m1 = IntParameter(1, 7, default=1) - buy_m2 = IntParameter(1, 7, default=3) - buy_m3 = IntParameter(1, 7, default=4) - buy_p1 = IntParameter(7, 21, default=14) - buy_p2 = IntParameter(7, 21, default=10) - buy_p3 = IntParameter(7, 21, default=10) - - sell_m1 = IntParameter(1, 7, default=1) - sell_m2 = IntParameter(1, 7, default=3) - sell_m3 = IntParameter(1, 7, default=4) - sell_p1 = IntParameter(7, 21, default=14) - sell_p2 = IntParameter(7, 21, default=10) - sell_p3 = IntParameter(7, 21, default=10) + # Hyperoptable parameters + buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) + sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True) + short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True) + exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) # FreqAI required function, leave as is or add additional informatives to existing structure. def informative_pairs(self): @@ -143,7 +139,6 @@ class FreqaiExampleHybridStrategy(IStrategy): informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t) informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t) - informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) informative[f"%-{coin}roc-period_{t}"] = ta.ROC(informative, timeperiod=t) informative[f"%-{coin}relative_volume-period_{t}"] = ( informative["volume"] / informative["volume"].rolling(t).mean() @@ -183,150 +178,85 @@ class FreqaiExampleHybridStrategy(IStrategy): # User creates their own custom strat here. Present example is a supertrend # based strategy. - for multiplier in self.buy_m1.range: - for period in self.buy_p1.range: - dataframe[f"supertrend_1_buy_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - - for multiplier in self.buy_m2.range: - for period in self.buy_p2.range: - dataframe[f"supertrend_2_buy_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - - for multiplier in self.buy_m3.range: - for period in self.buy_p3.range: - dataframe[f"supertrend_3_buy_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - - for multiplier in self.sell_m1.range: - for period in self.sell_p1.range: - dataframe[f"supertrend_1_sell_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - - for multiplier in self.sell_m2.range: - for period in self.sell_p2.range: - dataframe[f"supertrend_2_sell_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - - for multiplier in self.sell_m3.range: - for period in self.sell_p3.range: - dataframe[f"supertrend_3_sell_{multiplier}_{period}"] = self.supertrend( - dataframe, multiplier, period - )["STX"] - dataframe = self.freqai.start(dataframe, metadata, self) + # TA indicators to combine with the Freqai targets + # RSI + dataframe['rsi'] = ta.RSI(dataframe) + + # Bollinger Bands + bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) + dataframe['bb_lowerband'] = bollinger['lower'] + dataframe['bb_middleband'] = bollinger['mid'] + dataframe['bb_upperband'] = bollinger['upper'] + dataframe["bb_percent"] = ( + (dataframe["close"] - dataframe["bb_lowerband"]) / + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) + ) + dataframe["bb_width"] = ( + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"] + ) + + # TEMA - Triple Exponential Moving Average + dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) + return dataframe def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame: - # User now can use their custom strat creation in addition to their - # future prediction "up" or "down". + df.loc[ + ( + # Signal: RSI crosses above 30 + (qtpylib.crossed_above(df['rsi'], self.buy_rsi.value)) & + (df['tema'] <= df['bb_middleband']) & # Guard: tema below BB middle + (df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising + (df['volume'] > 0) & # Make sure Volume is not 0 + (df['do_predict'] == 1) & # Make sure Freqai is confident in the prediction + # Only enter trade if Freqai thinks the trend is in this direction + (df['&s-up_or_down'] == 'up') + ), + 'enter_long'] = 1 df.loc[ - (df[f"supertrend_1_buy_{self.buy_m1.value}_{self.buy_p1.value}"] == "up") & - (df[f"supertrend_2_buy_{self.buy_m2.value}_{self.buy_p2.value}"] == "up") & - (df[f"supertrend_3_buy_{self.buy_m3.value}_{self.buy_p3.value}"] == "up") & - (df["do_predict"] == 1) & - (df['&s-up_or_down'] == 'up'), - "enter_long", - ] = 1 - - df.loc[ - (df[f"supertrend_1_sell_{self.sell_m1.value}_{self.sell_p1.value}"] == "down") & - (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down") & - (df[f"supertrend_3_sell_{self.sell_m3.value}_{self.sell_p3.value}"] == "down") & - (df["do_predict"] == 1) & - (df['&s-up_or_down'] == 'down'), - "enter_short", - ] = 1 + ( + # Signal: RSI crosses above 70 + (qtpylib.crossed_above(df['rsi'], self.short_rsi.value)) & + (df['tema'] > df['bb_middleband']) & # Guard: tema above BB middle + (df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling + (df['volume'] > 0) & # Make sure Volume is not 0 + (df['do_predict'] == 1) & # Make sure Freqai is confident in the prediction + # Only enter trade if Freqai thinks the trend is in this direction + (df['&s-up_or_down'] == 'down') + ), + 'enter_short'] = 1 return df def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame: df.loc[ - (df[f"supertrend_2_sell_{self.sell_m2.value}_{self.sell_p2.value}"] == "down"), - "exit_long", - ] = 1 + ( + # Signal: RSI crosses above 70 + (qtpylib.crossed_above(df['rsi'], self.sell_rsi.value)) & + (df['tema'] > df['bb_middleband']) & # Guard: tema above BB middle + (df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling + (df['volume'] > 0) # Make sure Volume is not 0 + ), + + 'exit_long'] = 1 df.loc[ - (df[f"supertrend_2_buy_{self.buy_m2.value}_{self.buy_p2.value}"] == "up"), - "exit_short", - ] = 1 + ( + # Signal: RSI crosses above 30 + (qtpylib.crossed_above(df['rsi'], self.exit_short_rsi.value)) & + # Guard: tema below BB middle + (df['tema'] <= df['bb_middleband']) & + (df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising + (df['volume'] > 0) # Make sure Volume is not 0 + ), + 'exit_short'] = 1 return df def get_ticker_indicator(self): return int(self.config["timeframe"][:-1]) - - def confirm_trade_entry(self, pair: str, order_type: str, amount: float, - rate: float, time_in_force: str, current_time, entry_tag, side: str, - **kwargs, ) -> bool: - - df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) - last_candle = df.iloc[-1].squeeze() - - if side == "long": - if rate > (last_candle["close"] * (1 + 0.0025)): - return False - else: - if rate < (last_candle["close"] * (1 - 0.0025)): - return False - - return True - - """ - Supertrend Indicator; adapted for freqtrade, optimized by the math genius. - from: Perkmeister#2394 - """ - - def supertrend(self, dataframe: DataFrame, multiplier, period): - - df = dataframe.copy() - last_row = dataframe.tail(1).index.item() - - df['TR'] = ta.TRANGE(df) - df['ATR'] = ta.SMA(df['TR'], period) - - st = 'ST_' + str(period) + '_' + str(multiplier) - stx = 'STX_' + str(period) + '_' + str(multiplier) - - # Compute basic upper and lower bands - BASIC_UB = ((df['high'] + df['low']) / 2 + multiplier * df['ATR']).values - BASIC_LB = ((df['high'] + df['low']) / 2 - multiplier * df['ATR']).values - FINAL_UB = np.zeros(last_row + 1) - FINAL_LB = np.zeros(last_row + 1) - ST = np.zeros(last_row + 1) - CLOSE = df['close'].values - - # Compute final upper and lower bands - for i in range(period, last_row + 1): - FINAL_UB[i] = (BASIC_UB[i] if BASIC_UB[i] < FINAL_UB[i - 1] - or CLOSE[i - 1] > FINAL_UB[i - 1] else FINAL_UB[i - 1]) - FINAL_LB[i] = (BASIC_LB[i] if BASIC_LB[i] > FINAL_LB[i - 1] - or CLOSE[i - 1] < FINAL_LB[i - 1] else FINAL_LB[i - 1]) - - # Set the Supertrend value - for i in range(period, last_row + 1): - ST[i] = FINAL_UB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] <= FINAL_UB[i] else \ - FINAL_LB[i] if ST[i - 1] == FINAL_UB[i - 1] and CLOSE[i] > FINAL_UB[i] else \ - FINAL_LB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] >= FINAL_LB[i] else \ - FINAL_UB[i] if ST[i - 1] == FINAL_LB[i - 1] and CLOSE[i] < FINAL_LB[i] else 0.00 - df_ST = pd.DataFrame(ST, columns=[st]) - df = pd.concat([df, df_ST], axis=1) - - # Mark the trend direction up/down - df[stx] = np.where((df[st] > 0.00), np.where((df['close'] < df[st]), 'down', 'up'), np.NaN) - - df.fillna(0, inplace=True) - - return DataFrame(index=df.index, data={ - 'ST': df[st], - 'STX': df[stx] - }) From b9f35cadb330763e70c52dd867ab74dc4555a94e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 28 Aug 2022 11:32:53 +0200 Subject: [PATCH 072/592] add /stopentry alias for /stopbuy --- README.md | 2 +- docs/faq.md | 4 ++-- docs/strategy-callbacks.md | 2 +- docs/telegram-usage.md | 4 ++-- freqtrade/freqtradebot.py | 2 +- freqtrade/rpc/api_server/api_v1.py | 3 ++- freqtrade/rpc/rpc.py | 4 ++-- freqtrade/rpc/telegram.py | 34 ++++++++++++++++-------------- tests/rpc/test_rpc.py | 6 +++--- tests/rpc/test_rpc_apiserver.py | 11 ++++++++-- tests/rpc/test_rpc_telegram.py | 7 +++--- 11 files changed, 45 insertions(+), 34 deletions(-) diff --git a/README.md b/README.md index 059e80cd9..0cc2364e5 100644 --- a/README.md +++ b/README.md @@ -130,7 +130,7 @@ Telegram is not mandatory. However, this is a great way to control your bot. Mor - `/start`: Starts the trader. - `/stop`: Stops the trader. -- `/stopbuy`: Stop entering new trades. +- `/stopentry`: Stop entering new trades. - `/status |[table]`: Lists all or specific open trades. - `/profit []`: Lists cumulative profit from all finished trades, over the last n days. - `/forceexit |all`: Instantly exits the given trade (Ignoring `minimum_roi`). diff --git a/docs/faq.md b/docs/faq.md index f1542d08e..381bbceb5 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -77,9 +77,9 @@ Freqtrade will not provide incomplete candles to strategies. Using incomplete ca You can use "current" market data by using the [dataprovider](strategy-customization.md#orderbookpair-maximum)'s orderbook or ticker methods - which however cannot be used during backtesting. -### Is there a setting to only SELL the coins being held and not perform anymore BUYS? +### Is there a setting to only Exit the trades being held and not perform any new Entries? -You can use the `/stopbuy` command in Telegram to prevent future buys, followed by `/forceexit all` (sell all open trades). +You can use the `/stopentry` command in Telegram to prevent future trade entry, followed by `/forceexit all` (sell all open trades). ### I want to run multiple bots on the same machine diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md index 32ad1b288..0b8403414 100644 --- a/docs/strategy-callbacks.md +++ b/docs/strategy-callbacks.md @@ -654,7 +654,7 @@ Position adjustments will always be applied in the direction of the trade, so a Stoploss is still calculated from the initial opening price, not averaged price. Regular stoploss rules still apply (cannot move down). - While `/stopbuy` command stops the bot from entering new trades, the position adjustment feature will continue buying new orders on existing trades. + While `/stopentry` command stops the bot from entering new trades, the position adjustment feature will continue buying new orders on existing trades. !!! Warning "Backtesting" During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so run-time performance will be affected. diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md index add889681..ece8700de 100644 --- a/docs/telegram-usage.md +++ b/docs/telegram-usage.md @@ -149,7 +149,7 @@ You can create your own keyboard in `config.json`: !!! Note "Supported Commands" Only the following commands are allowed. Command arguments are not supported! - `/start`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopbuy`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/edge`, `/help`, `/version` + `/start`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopentry`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/edge`, `/help`, `/version` ## Telegram commands @@ -161,7 +161,7 @@ official commands. You can ask at any moment for help with `/help`. |----------|-------------| | `/start` | Starts the trader | `/stop` | Stops the trader -| `/stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules. +| `/stopbuy | /stopentry` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules. | `/reload_config` | Reloads the configuration file | `/show_config` | Shows part of the current configuration with relevant settings to operation | `/logs [limit]` | Show last log messages. diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index d84d50b7c..35ba6bab2 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -239,7 +239,7 @@ class FreqtradeBot(LoggingMixin): 'status': f"{len(open_trades)} open trades active.\n\n" f"Handle these trades manually on {self.exchange.name}, " - f"or '/start' the bot again and use '/stopbuy' " + f"or '/start' the bot again and use '/stopentry' " f"to handle open trades gracefully. \n" f"{'Note: Trades are simulated (dry run).' if self.config['dry_run'] else ''}", } diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index e0fef7be8..bf21715b7 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -216,9 +216,10 @@ def stop(rpc: RPC = Depends(get_rpc)): return rpc._rpc_stop() +@router.post('/stopentry', response_model=StatusMsg, tags=['botcontrol']) @router.post('/stopbuy', response_model=StatusMsg, tags=['botcontrol']) def stop_buy(rpc: RPC = Depends(get_rpc)): - return rpc._rpc_stopbuy() + return rpc._rpc_stopentry() @router.post('/reload_config', response_model=StatusMsg, tags=['botcontrol']) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index ed7f13a96..11311f671 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -657,7 +657,7 @@ class RPC: self._freqtrade.state = State.RELOAD_CONFIG return {'status': 'Reloading config ...'} - def _rpc_stopbuy(self) -> Dict[str, str]: + def _rpc_stopentry(self) -> Dict[str, str]: """ Handler to stop buying, but handle open trades gracefully. """ @@ -665,7 +665,7 @@ class RPC: # Set 'max_open_trades' to 0 self._freqtrade.config['max_open_trades'] = 0 - return {'status': 'No more buy will occur from now. Run /reload_config to reset.'} + return {'status': 'No more entries will occur from now. Run /reload_config to reset.'} def __exec_force_exit(self, trade: Trade, ordertype: Optional[str], amount: Optional[float] = None) -> None: diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py index 8ce2fa2e4..8c988d570 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -114,18 +114,20 @@ class Telegram(RPCHandler): # TODO: DRY! - its not good to list all valid cmds here. But otherwise # this needs refactoring of the whole telegram module (same # problem in _help()). - valid_keys: List[str] = [r'/start$', r'/stop$', r'/status$', r'/status table$', - r'/trades$', r'/performance$', r'/buys', r'/entries', - r'/sells', r'/exits', r'/mix_tags', - r'/daily$', r'/daily \d+$', r'/profit$', r'/profit \d+', - r'/stats$', r'/count$', r'/locks$', r'/balance$', - r'/stopbuy$', r'/reload_config$', r'/show_config$', - r'/logs$', r'/whitelist$', r'/whitelist(\ssorted|\sbaseonly)+$', - r'/blacklist$', r'/bl_delete$', - r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$', - r'/forcebuy$', r'/forcelong$', r'/forceshort$', - r'/forcesell$', r'/forceexit$', - r'/edge$', r'/health$', r'/help$', r'/version$'] + valid_keys: List[str] = [ + r'/start$', r'/stop$', r'/status$', r'/status table$', + r'/trades$', r'/performance$', r'/buys', r'/entries', + r'/sells', r'/exits', r'/mix_tags', + r'/daily$', r'/daily \d+$', r'/profit$', r'/profit \d+', + r'/stats$', r'/count$', r'/locks$', r'/balance$', + r'/stopbuy$', r'/stopentry$', r'/reload_config$', r'/show_config$', + r'/logs$', r'/whitelist$', r'/whitelist(\ssorted|\sbaseonly)+$', + r'/blacklist$', r'/bl_delete$', + r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$', + r'/forcebuy$', r'/forcelong$', r'/forceshort$', + r'/forcesell$', r'/forceexit$', + r'/edge$', r'/health$', r'/help$', r'/version$' + ] # Create keys for generation valid_keys_print = [k.replace('$', '') for k in valid_keys] @@ -182,7 +184,7 @@ class Telegram(RPCHandler): CommandHandler(['unlock', 'delete_locks'], self._delete_locks), CommandHandler(['reload_config', 'reload_conf'], self._reload_config), CommandHandler(['show_config', 'show_conf'], self._show_config), - CommandHandler('stopbuy', self._stopbuy), + CommandHandler(['stopbuy', 'stopentry'], self._stopentry), CommandHandler('whitelist', self._whitelist), CommandHandler('blacklist', self._blacklist), CommandHandler(['blacklist_delete', 'bl_delete'], self._blacklist_delete), @@ -984,7 +986,7 @@ class Telegram(RPCHandler): self._send_msg(f"Status: `{msg['status']}`") @authorized_only - def _stopbuy(self, update: Update, context: CallbackContext) -> None: + def _stopentry(self, update: Update, context: CallbackContext) -> None: """ Handler for /stop_buy. Sets max_open_trades to 0 and gracefully sells all open trades @@ -992,7 +994,7 @@ class Telegram(RPCHandler): :param update: message update :return: None """ - msg = self._rpc._rpc_stopbuy() + msg = self._rpc._rpc_stopentry() self._send_msg(f"Status: `{msg['status']}`") @authorized_only @@ -1488,7 +1490,7 @@ class Telegram(RPCHandler): "------------\n" "*/start:* `Starts the trader`\n" "*/stop:* Stops the trader\n" - "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n" + "*/stopentry:* `Stops entering, but handles open trades gracefully` \n" "*/forceexit |all:* `Instantly exits the given trade or all trades, " "regardless of profit`\n" "*/fx |all:* `Alias to /forceexit`\n" diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py index 7b42bf083..8bbf75a32 100644 --- a/tests/rpc/test_rpc.py +++ b/tests/rpc/test_rpc.py @@ -663,7 +663,7 @@ def test_rpc_stop(mocker, default_conf) -> None: assert freqtradebot.state == State.STOPPED -def test_rpc_stopbuy(mocker, default_conf) -> None: +def test_rpc_stopentry(mocker, default_conf) -> None: mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock()) mocker.patch.multiple( 'freqtrade.exchange.Exchange', @@ -676,8 +676,8 @@ def test_rpc_stopbuy(mocker, default_conf) -> None: freqtradebot.state = State.RUNNING assert freqtradebot.config['max_open_trades'] != 0 - result = rpc._rpc_stopbuy() - assert {'status': 'No more buy will occur from now. Run /reload_config to reset.'} == result + result = rpc._rpc_stopentry() + assert {'status': 'No more entries will occur from now. Run /reload_config to reset.'} == result assert freqtradebot.config['max_open_trades'] == 0 diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 9aa965da2..5dfa77d8b 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -422,13 +422,20 @@ def test_api_reloadconf(botclient): assert ftbot.state == State.RELOAD_CONFIG -def test_api_stopbuy(botclient): +def test_api_stopentry(botclient): ftbot, client = botclient assert ftbot.config['max_open_trades'] != 0 rc = client_post(client, f"{BASE_URI}/stopbuy") assert_response(rc) - assert rc.json() == {'status': 'No more buy will occur from now. Run /reload_config to reset.'} + assert rc.json() == { + 'status': 'No more entries will occur from now. Run /reload_config to reset.'} + assert ftbot.config['max_open_trades'] == 0 + + rc = client_post(client, f"{BASE_URI}/stopentry") + assert_response(rc) + assert rc.json() == { + 'status': 'No more entries will occur from now. Run /reload_config to reset.'} assert ftbot.config['max_open_trades'] == 0 diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py index a30115bd9..cde7025a7 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -103,7 +103,8 @@ def test_telegram_init(default_conf, mocker, caplog) -> None: "['stats'], ['daily'], ['weekly'], ['monthly'], " "['count'], ['locks'], ['unlock', 'delete_locks'], " "['reload_config', 'reload_conf'], ['show_config', 'show_conf'], " - "['stopbuy'], ['whitelist'], ['blacklist'], ['blacklist_delete', 'bl_delete'], " + "['stopbuy', 'stopentry'], ['whitelist'], ['blacklist'], " + "['blacklist_delete', 'bl_delete'], " "['logs'], ['edge'], ['health'], ['help'], ['version']" "]") @@ -896,10 +897,10 @@ def test_stopbuy_handle(default_conf, update, mocker) -> None: telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf) assert freqtradebot.config['max_open_trades'] != 0 - telegram._stopbuy(update=update, context=MagicMock()) + telegram._stopentry(update=update, context=MagicMock()) assert freqtradebot.config['max_open_trades'] == 0 assert msg_mock.call_count == 1 - assert 'No more buy will occur from now. Run /reload_config to reset.' \ + assert 'No more entries will occur from now. Run /reload_config to reset.' \ in msg_mock.call_args_list[0][0][0] From ff3a4995c1c34cc737313908cde420aa0ef50754 Mon Sep 17 00:00:00 2001 From: smarmau Date: Sun, 28 Aug 2022 11:45:20 +0200 Subject: [PATCH 073/592] remove unnecessary code --- freqtrade/templates/FreqaiHybridExampleStrategy.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index dfd67ae90..0a91455f5 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -257,6 +257,3 @@ class FreqaiExampleHybridStrategy(IStrategy): 'exit_short'] = 1 return df - - def get_ticker_indicator(self): - return int(self.config["timeframe"][:-1]) From 22b42e91f3d1875e73780d8ce4dcbbedeac01b92 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 11:53:24 +0200 Subject: [PATCH 074/592] add new parameter to freqai doc --- docs/freqai.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/freqai.md b/docs/freqai.md index bba6faaea..78d71e2f8 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -113,6 +113,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary. | `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean. +| `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
**Datatype:** float. Default: `0.3` | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
**Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
**Datatype:** Positive float < 1. From 1e41c773a067beaf523c7bd3c67717b27fd5e732 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 12:11:29 +0200 Subject: [PATCH 075/592] fix outlier protection --- docs/freqai.md | 2 +- freqtrade/freqai/data_kitchen.py | 28 ++++++++++++++-------------- 2 files changed, 15 insertions(+), 15 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 78d71e2f8..c0f764953 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -113,7 +113,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary. | `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean. -| `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
**Datatype:** float. Default: `0.3` +| `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
**Datatype:** float. Default: `30` | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
**Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
**Datatype:** Positive float < 1. diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index eb9f6beb7..ed3990de0 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -519,7 +519,7 @@ class FreqaiDataKitchen: """ outlier_protection_pct = self.freqai_config["feature_parameters"].get( "outlier_protection_percentage", 30) - outlier_pct = dropped_pts.sum() / len(dropped_pts) + outlier_pct = (dropped_pts.sum() / len(dropped_pts)) * 100 if outlier_pct >= outlier_protection_pct: self.svm_model = None return outlier_pct @@ -563,12 +563,12 @@ class FreqaiDataKitchen: self.data_dictionary["train_features"] ) y_pred = self.svm_model.predict(self.data_dictionary["train_features"]) - dropped_points = np.where(y_pred == -1, 0, y_pred) + kept_points = np.where(y_pred == -1, 0, y_pred) # keep_index = np.where(y_pred == 1) - outlier_ptc = self.get_outlier_percentage(dropped_points) - if outlier_ptc: + outlier_pct = self.get_outlier_percentage(1 - kept_points) + if outlier_pct: logger.warning( - f"SVM detected > {outlier_ptc}% of the points as outliers." + f"SVM detected {outlier_pct:.2f}% of the points as outliers. " f"Keeping original dataset." ) return @@ -584,7 +584,7 @@ class FreqaiDataKitchen: ] logger.info( - f"SVM tossed {len(y_pred) - dropped_points.sum()}" + f"SVM tossed {len(y_pred) - kept_points.sum()}" f" train points from {len(y_pred)} total points." ) @@ -593,7 +593,7 @@ class FreqaiDataKitchen: # to reduce code duplication if self.freqai_config['data_split_parameters'].get('test_size', 0.1) != 0: y_pred = self.svm_model.predict(self.data_dictionary["test_features"]) - dropped_points = np.where(y_pred == -1, 0, y_pred) + kept_points = np.where(y_pred == -1, 0, y_pred) self.data_dictionary["test_features"] = self.data_dictionary["test_features"][ (y_pred == 1) ] @@ -604,7 +604,7 @@ class FreqaiDataKitchen: ] logger.info( - f"SVM tossed {len(y_pred) - dropped_points.sum()}" + f"SVM tossed {len(y_pred) - kept_points.sum()}" f" test points from {len(y_pred)} total points." ) @@ -688,10 +688,10 @@ class FreqaiDataKitchen: self.data['DBSCAN_min_samples'] = MinPts dropped_points = np.where(clustering.labels_ == -1, 1, 0) - outlier_ptc = self.get_outlier_percentage(dropped_points) - if outlier_ptc: + outlier_pct = self.get_outlier_percentage(dropped_points) + if outlier_pct: logger.warning( - f"DBSCAN detected > {outlier_ptc}% of the points as outliers." + f"DBSCAN detected {outlier_pct:.2f}% of the points as outliers. " f"Keeping original dataset." ) return @@ -751,10 +751,10 @@ class FreqaiDataKitchen: 0, ) - outlier_ptc = self.get_outlier_percentage(1 - do_predict) - if outlier_ptc: + outlier_pct = self.get_outlier_percentage(1 - do_predict) + if outlier_pct: logger.warning( - f"DI detected > {outlier_ptc}% of the points as outliers." + f"DI detected {outlier_pct:.2f}% of the points as outliers. " f"Keeping original dataset." ) return From dd628eb525acc407fd0643aba2548d5eac6f3800 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 12:56:39 +0200 Subject: [PATCH 076/592] add tests for outlier detection and removal functions --- freqtrade/freqai/data_drawer.py | 3 +- freqtrade/freqai/data_kitchen.py | 2 +- tests/freqai/conftest.py | 47 ++++++++++++++++++++++++- tests/freqai/test_freqai_datakitchen.py | 31 ++++++++++++++-- 4 files changed, 78 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index b3060deff..477b9e098 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -566,7 +566,7 @@ class FreqaiDataDrawer: for training according to user defined train_period_days metadata: dict = strategy furnished pair metadata """ - + import pytest with self.history_lock: corr_dataframes: Dict[Any, Any] = {} base_dataframes: Dict[Any, Any] = {} @@ -576,6 +576,7 @@ class FreqaiDataDrawer: ) for tf in self.freqai_info["feature_parameters"].get("include_timeframes"): + # pytest.set_trace() base_dataframes[tf] = dk.slice_dataframe(timerange, historic_data[pair][tf]) if pairs: for p in pairs: diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index ed3990de0..8e68c9a38 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -657,7 +657,7 @@ class FreqaiDataKitchen: return (x, y) MinPts = int(len(self.data_dictionary['train_features'].index) * 0.25) - # measure pairwise distances to train_features.shape[1]*2 nearest neighbours + # measure pairwise distances to nearest neighbours neighbors = NearestNeighbors( n_neighbors=MinPts, n_jobs=self.thread_count) neighbors_fit = neighbors.fit(self.data_dictionary['train_features']) diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 6ace13677..98f086ec9 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -2,7 +2,7 @@ from copy import deepcopy from pathlib import Path import pytest - +from unittest.mock import MagicMock from freqtrade.configuration import TimeRange from freqtrade.data.dataprovider import DataProvider from freqtrade.freqai.data_drawer import FreqaiDataDrawer @@ -81,6 +81,51 @@ def get_patched_freqaimodel(mocker, freqaiconf): return freqaimodel +def make_data_dictionary(mocker, freqai_conf): + freqai_conf.update({"timerange": "20180110-20180130"}) + + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange) + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = True + freqai.dk = FreqaiDataKitchen(freqai_conf) + freqai.dk.pair = "ADA/BTC" + timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(timerange, freqai.dk) + + freqai.dd.pair_dict = MagicMock() + + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") + + corr_dataframes, base_dataframes = freqai.dd.get_base_and_corr_dataframes( + data_load_timerange, freqai.dk.pair, freqai.dk + ) + + unfiltered_dataframe = freqai.dk.use_strategy_to_populate_indicators( + strategy, corr_dataframes, base_dataframes, freqai.dk.pair + ) + + unfiltered_dataframe = freqai.dk.slice_dataframe(new_timerange, unfiltered_dataframe) + + freqai.dk.find_features(unfiltered_dataframe) + + features_filtered, labels_filtered = freqai.dk.filter_features( + unfiltered_dataframe, + freqai.dk.training_features_list, + freqai.dk.label_list, + training_filter=True, + ) + + data_dictionary = freqai.dk.make_train_test_datasets(features_filtered, labels_filtered) + + data_dictionary = freqai.dk.normalize_data(data_dictionary) + + return freqai + + def get_freqai_live_analyzed_dataframe(mocker, freqaiconf): strategy = get_patched_freqai_strategy(mocker, freqaiconf) exchange = get_patched_exchange(mocker, freqaiconf) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 9f2a2f71e..581286715 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -5,8 +5,8 @@ from pathlib import Path import pytest from freqtrade.exceptions import OperationalException -from tests.freqai.conftest import get_patched_data_kitchen - +from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary +from tests.conftest import log_has_re @pytest.mark.parametrize( "timerange, train_period_days, expected_result", @@ -66,3 +66,30 @@ def test_check_if_model_expired(mocker, freqai_conf, timestamp, expected): dk = get_patched_data_kitchen(mocker, freqai_conf) assert dk.check_if_model_expired(timestamp) == expected shutil.rmtree(Path(dk.full_path)) + + +def test_use_DBSCAN_to_remove_outliers(mocker, freqai_conf, caplog): + freqai = make_data_dictionary(mocker, freqai_conf) + # freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 1}) + freqai.dk.use_DBSCAN_to_remove_outliers(predict=False) + assert log_has_re( + "DBSCAN found eps of 2.42.", + caplog, + ) + + +def test_compute_distances(mocker, freqai_conf): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai_conf['freqai']['feature_parameters'].update({"DI_threshold": 1}) + avg_mean_dist = freqai.dk.compute_distances() + assert round(avg_mean_dist, 2) == 2.56 + + +def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, caplog): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 0.1}) + freqai.dk.use_SVM_to_remove_outliers(predict=False) + assert log_has_re( + "SVM detected 8.46%", + caplog, + ) From fcb5d1cb5a5419f723d94edde80abe6173d33916 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 13:01:39 +0200 Subject: [PATCH 077/592] remove debugging flag --- freqtrade/freqai/data_drawer.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 477b9e098..b6a1a15d7 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -566,7 +566,6 @@ class FreqaiDataDrawer: for training according to user defined train_period_days metadata: dict = strategy furnished pair metadata """ - import pytest with self.history_lock: corr_dataframes: Dict[Any, Any] = {} base_dataframes: Dict[Any, Any] = {} @@ -576,7 +575,6 @@ class FreqaiDataDrawer: ) for tf in self.freqai_info["feature_parameters"].get("include_timeframes"): - # pytest.set_trace() base_dataframes[tf] = dk.slice_dataframe(timerange, historic_data[pair][tf]) if pairs: for p in pairs: From 6634229cc198f1e264b1fe3a56d4bd919c7216c0 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 13:21:29 +0200 Subject: [PATCH 078/592] appease the flake8 gods --- tests/freqai/test_freqai_datakitchen.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 581286715..6ef2971ee 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -8,6 +8,7 @@ from freqtrade.exceptions import OperationalException from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary from tests.conftest import log_has_re + @pytest.mark.parametrize( "timerange, train_period_days, expected_result", [ From a44a235b563fa96ca893cbd96f3e64d86aa7ff31 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 28 Aug 2022 13:47:01 +0200 Subject: [PATCH 079/592] isort imports in tests/freqai --- tests/freqai/conftest.py | 3 ++- tests/freqai/test_freqai_datakitchen.py | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 98f086ec9..dd148da77 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -1,8 +1,9 @@ from copy import deepcopy from pathlib import Path +from unittest.mock import MagicMock import pytest -from unittest.mock import MagicMock + from freqtrade.configuration import TimeRange from freqtrade.data.dataprovider import DataProvider from freqtrade.freqai.data_drawer import FreqaiDataDrawer diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 6ef2971ee..9ef955695 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -5,8 +5,8 @@ from pathlib import Path import pytest from freqtrade.exceptions import OperationalException -from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary from tests.conftest import log_has_re +from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary @pytest.mark.parametrize( From 8c4e68b8eb21e6bb0e04e47befb15a9d2ad40913 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 28 Aug 2022 13:00:52 -0600 Subject: [PATCH 080/592] updated example configs --- config_examples/config_follower.example.json | 8 +++++--- freqtrade/rpc/external_signal/controller.py | 3 +-- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/config_examples/config_follower.example.json b/config_examples/config_follower.example.json index 5317c8df2..646310d9a 100644 --- a/config_examples/config_follower.example.json +++ b/config_examples/config_follower.example.json @@ -46,8 +46,8 @@ }, "pairlists": [ { - "method": "ExternalPairList", - "number_assets": 5, + "method": "ExternalPairList", // ExternalPairList is required in follower mode + "number_assets": 5, // We can limit the amount of pairs to use from the leaders } ], "telegram": { @@ -74,7 +74,9 @@ "url": "ws://localhost:8080/signals/ws", "api_token": "testtoken" } - ] + ], + "wait_data_policy": "all", // ['all', 'first', none] defaults to all + "remove_signals_analyzed_df": true, // Remove entry/exit signals from Leader df, Defaults to false }, "bot_name": "freqtrade", "initial_state": "running", diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py index 29a318b53..2b29cde6f 100644 --- a/freqtrade/rpc/external_signal/controller.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -373,7 +373,6 @@ class ExternalSignalController(RPCHandler): # Data is being broadcasted right away as soon as startup, # we may not have to send initial data at all. Further testing # required. - await self.send_initial_data(channel) # Keep connection open until explicitly closed, and sleep @@ -434,7 +433,7 @@ class ExternalSignalController(RPCHandler): async with lock: # Acquire lock so only 1 coro handling at a time - # as we might call the RPC module in the main thread + # as we call the RPC module in the main thread await self._handle_leader_message(data) except (socket.gaierror, ConnectionRefusedError): From 8b0cfe12365af01ab38e7b61662d1c4283689216 Mon Sep 17 00:00:00 2001 From: th0rntwig <107926911+th0rntwig@users.noreply.github.com> Date: Sun, 28 Aug 2022 23:27:12 +0200 Subject: [PATCH 081/592] Reduce image sizes in freqai doc (#7304) --- docs/assets/freqai_DI.jpg | Bin 0 -> 314012 bytes docs/assets/freqai_DI.png | Bin 39781127 -> 0 bytes docs/assets/freqai_algo.jpg | Bin 0 -> 353611 bytes docs/assets/freqai_algo.png | Bin 17562663 -> 0 bytes docs/assets/freqai_dbscan.jpg | Bin 0 -> 67965 bytes docs/assets/freqai_dbscan.png | Bin 1992760 -> 0 bytes docs/assets/freqai_moving-window.jpg | Bin 0 -> 276574 bytes docs/assets/freqai_moving-window.png | Bin 3435842 -> 0 bytes docs/assets/freqai_weight-factor.jpg | Bin 0 -> 195825 bytes docs/assets/freqai_weight-factor.png | Bin 4893270 -> 0 bytes docs/assets/weights_factor.png | Bin 129065 -> 0 bytes docs/freqai.md | 10 +++++----- 12 files changed, 5 insertions(+), 5 deletions(-) create mode 100644 docs/assets/freqai_DI.jpg delete mode 100644 docs/assets/freqai_DI.png create mode 100644 docs/assets/freqai_algo.jpg delete mode 100644 docs/assets/freqai_algo.png create mode 100644 docs/assets/freqai_dbscan.jpg delete mode 100644 docs/assets/freqai_dbscan.png create mode 100644 docs/assets/freqai_moving-window.jpg delete mode 100644 docs/assets/freqai_moving-window.png create mode 100644 docs/assets/freqai_weight-factor.jpg delete mode 100644 docs/assets/freqai_weight-factor.png delete mode 100644 docs/assets/weights_factor.png diff --git a/docs/assets/freqai_DI.jpg 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custom An overview of the algorithm is shown below, explaining the data processing pipeline and the model usage. -![freqai-algo](assets/freqai_algo.png) +![freqai-algo](assets/freqai_algo.jpg) ### Important machine learning vocabulary @@ -469,7 +469,7 @@ Additionally, the example classifier models do not accommodate multiple labels, There are two ways to train and deploy an adaptive machine learning model. FreqAI enables live deployment as well as backtesting analyses. In both cases, a model is trained periodically, as shown in the following figure. -![freqai-window](assets/freqai_moving-window.png) +![freqai-window](assets/freqai_moving-window.jpg) ### Running the model live @@ -648,7 +648,7 @@ $$ W_i = \exp(\frac{-i}{\alpha*n}) $$ where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. Below is a figure showing the effect of different weight factors on the data points (candles) in a feature set. -![weight-factor](assets/freqai_weight-factor.png) +![weight-factor](assets/freqai_weight-factor.jpg) `train_test_split()` has a parameters called `shuffle` that allows the user to keep the data unshuffled. This is particularly useful to avoid biasing training with temporally auto-correlated data. @@ -691,7 +691,7 @@ The user can tweak the DI through the `DI_threshold` to increase or decrease the Below is a figure that describes the DI for a 3D data set. -![DI](assets/freqai_DI.png) +![DI](assets/freqai_DI.jpg) #### Removing outliers using a Support Vector Machine (SVM) @@ -728,7 +728,7 @@ DBSCAN is an unsupervised machine learning algorithm that clusters data without Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters the data set by setting all data points that have $N-1$ other data points within a distance of $\varepsilon$ as *core points*. A data point that is within a distance of $\varepsilon$ from a *core point* but that does not have $N-1$ other data points within a distance of $\varepsilon$ from itself is considered an *edge point*. A cluster is then the collection of *core points* and *edge points*. Data points that have no other data points at a distance $<\varepsilon$ are considered outliers. The figure below shows a cluster with $N = 3$. -![dbscan](assets/freqai_dbscan.png) +![dbscan](assets/freqai_dbscan.jpg) FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as double the no. of user-defined features, and `eps` ($\varepsilon$) taken as the longest distance in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. From e9e872ca206eb8b474f3a806812013179746be18 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:18 +0000 Subject: [PATCH 082/592] Bump mkdocs-material from 8.4.1 to 8.4.2 Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 8.4.1 to 8.4.2. - [Release notes](https://github.com/squidfunk/mkdocs-material/releases) - [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG) - [Commits](https://github.com/squidfunk/mkdocs-material/compare/8.4.1...8.4.2) --- updated-dependencies: - dependency-name: mkdocs-material dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- docs/requirements-docs.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt index bffc04d1c..5a6c46471 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,6 +1,6 @@ markdown==3.3.7 mkdocs==1.3.1 -mkdocs-material==8.4.1 +mkdocs-material==8.4.2 mdx_truly_sane_lists==1.3 pymdown-extensions==9.5 jinja2==3.1.2 From 0af4bd294430e087a2e53997d154eb7690569384 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:25 +0000 Subject: [PATCH 083/592] Bump urllib3 from 1.26.11 to 1.26.12 Bumps [urllib3](https://github.com/urllib3/urllib3) from 1.26.11 to 1.26.12. - [Release notes](https://github.com/urllib3/urllib3/releases) - [Changelog](https://github.com/urllib3/urllib3/blob/main/CHANGES.rst) - [Commits](https://github.com/urllib3/urllib3/compare/1.26.11...1.26.12) --- updated-dependencies: - dependency-name: urllib3 dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 4a0531ea8..2d9e42c56 100644 --- a/requirements.txt +++ b/requirements.txt @@ -11,7 +11,7 @@ python-telegram-bot==13.13 arrow==1.2.2 cachetools==4.2.2 requests==2.28.1 -urllib3==1.26.11 +urllib3==1.26.12 jsonschema==4.14.0 TA-Lib==0.4.24 technical==1.3.0 From e9f46f476878a4edbc57e78d14f278646f8e0d43 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:30 +0000 Subject: [PATCH 084/592] Bump nbconvert from 6.5.3 to 7.0.0 Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 6.5.3 to 7.0.0. - [Release notes](https://github.com/jupyter/nbconvert/releases) - [Commits](https://github.com/jupyter/nbconvert/compare/6.5.3...7.0.0) --- updated-dependencies: - dependency-name: nbconvert dependency-type: direct:development update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- requirements-dev.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-dev.txt b/requirements-dev.txt index 9c45e7277..26df7115c 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -20,7 +20,7 @@ isort==5.10.1 time-machine==2.8.1 # Convert jupyter notebooks to markdown documents -nbconvert==6.5.3 +nbconvert==7.0.0 # mypy types types-cachetools==5.2.1 From 49dd1c1d4908fc07033549e2f9060da3ad0ca1e3 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:36 +0000 Subject: [PATCH 085/592] Bump scipy from 1.9.0 to 1.9.1 Bumps [scipy](https://github.com/scipy/scipy) from 1.9.0 to 1.9.1. - [Release notes](https://github.com/scipy/scipy/releases) - [Commits](https://github.com/scipy/scipy/compare/v1.9.0...v1.9.1) --- updated-dependencies: - dependency-name: scipy dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements-hyperopt.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt index 020ccdda8..efa31272a 100644 --- a/requirements-hyperopt.txt +++ b/requirements-hyperopt.txt @@ -2,7 +2,7 @@ -r requirements.txt # Required for hyperopt -scipy==1.9.0 +scipy==1.9.1 scikit-learn==1.1.2 scikit-optimize==0.9.0 filelock==3.8.0 From 3a7441a27d7dbeb8211fc11742243c1a9b4b9835 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:41 +0000 Subject: [PATCH 086/592] Bump uvicorn from 0.18.2 to 0.18.3 Bumps [uvicorn](https://github.com/encode/uvicorn) from 0.18.2 to 0.18.3. - [Release notes](https://github.com/encode/uvicorn/releases) - [Changelog](https://github.com/encode/uvicorn/blob/master/CHANGELOG.md) - [Commits](https://github.com/encode/uvicorn/compare/0.18.2...0.18.3) --- updated-dependencies: - dependency-name: uvicorn dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 4a0531ea8..f59b9631c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -35,7 +35,7 @@ sdnotify==0.3.2 # API Server fastapi==0.79.1 -uvicorn==0.18.2 +uvicorn==0.18.3 pyjwt==2.4.0 aiofiles==0.8.0 psutil==5.9.1 From d734f7612fccc3d3ebc3ed3be4e04f741e85cbe2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:50 +0000 Subject: [PATCH 087/592] Bump orjson from 3.7.12 to 3.8.0 Bumps [orjson](https://github.com/ijl/orjson) from 3.7.12 to 3.8.0. - [Release notes](https://github.com/ijl/orjson/releases) - [Changelog](https://github.com/ijl/orjson/blob/master/CHANGELOG.md) - [Commits](https://github.com/ijl/orjson/compare/3.7.12...3.8.0) --- updated-dependencies: - dependency-name: orjson dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 4a0531ea8..657dfed0c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -28,7 +28,7 @@ py_find_1st==1.1.5 # Load ticker files 30% faster python-rapidjson==1.8 # Properly format api responses -orjson==3.7.12 +orjson==3.8.0 # Notify systemd sdnotify==0.3.2 From d7189847a7ef203d08998251a2b5b18072f8f518 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 03:01:59 +0000 Subject: [PATCH 088/592] Bump ccxt from 1.92.52 to 1.92.84 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.92.52 to 1.92.84. - [Release notes](https://github.com/ccxt/ccxt/releases) - [Changelog](https://github.com/ccxt/ccxt/blob/master/exchanges.cfg) - [Commits](https://github.com/ccxt/ccxt/compare/1.92.52...1.92.84) --- updated-dependencies: - dependency-name: ccxt dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 4a0531ea8..795882ba6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ numpy==1.23.2 pandas==1.4.3 pandas-ta==0.3.14b -ccxt==1.92.52 +ccxt==1.92.84 # Pin cryptography for now due to rust build errors with piwheels cryptography==37.0.4 aiohttp==3.8.1 From 40c00d2d8f76defd5fee2a0106343830404790d5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 06:34:20 +0200 Subject: [PATCH 089/592] Version bump dev version to 2022.9 --- docs/developer.md | 5 +++-- freqtrade/__init__.py | 2 +- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/developer.md b/docs/developer.md index aca4ce4ed..f88754c50 100644 --- a/docs/developer.md +++ b/docs/developer.md @@ -409,8 +409,9 @@ Determine if crucial bugfixes have been made between this commit and the current * Merge the release branch (stable) into this branch. * Edit `freqtrade/__init__.py` and add the version matching the current date (for example `2019.7` for July 2019). Minor versions can be `2019.7.1` should we need to do a second release that month. Version numbers must follow allowed versions from PEP0440 to avoid failures pushing to pypi. -* Commit this part -* push that branch to the remote and create a PR against the stable branch +* Commit this part. +* push that branch to the remote and create a PR against the stable branch. +* Update develop version to next version following the pattern `2019.8-dev`. ### Create changelog from git commits diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 2572c03f1..77c305c66 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2022.8.dev' +__version__ = '2022.9.dev' if 'dev' in __version__: try: From 56cd80926a4159dbc72605003836dcce9a909173 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Aug 2022 04:52:12 +0000 Subject: [PATCH 090/592] Bump fastapi from 0.79.1 to 0.81.0 Bumps [fastapi](https://github.com/tiangolo/fastapi) from 0.79.1 to 0.81.0. - [Release notes](https://github.com/tiangolo/fastapi/releases) - [Commits](https://github.com/tiangolo/fastapi/compare/0.79.1...0.81.0) --- updated-dependencies: - dependency-name: fastapi dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 3578a3659..5c56c91ea 100644 --- a/requirements.txt +++ b/requirements.txt @@ -34,7 +34,7 @@ orjson==3.8.0 sdnotify==0.3.2 # API Server -fastapi==0.79.1 +fastapi==0.81.0 uvicorn==0.18.3 pyjwt==2.4.0 aiofiles==0.8.0 From 226fa5d93c74ebcf5d4d88cfb7c10ac2abfbf990 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 06:45:00 +0200 Subject: [PATCH 091/592] Simplify liquidation price calling structure --- freqtrade/exchange/exchange.py | 34 +------- freqtrade/freqtradebot.py | 6 +- freqtrade/optimize/backtesting.py | 2 +- tests/exchange/test_exchange.py | 128 +++++++++++++++--------------- 4 files changed, 69 insertions(+), 101 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 586a364c5..c9abb1988 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2432,36 +2432,6 @@ class Exchange: """ return 0.0 - def get_liquidation_price( - self, - pair: str, - open_rate: float, - amount: float, # quote currency, includes leverage - stake_amount: float, - leverage: float, - is_short: bool - ) -> Optional[float]: - - if self.trading_mode in TradingMode.SPOT: - return None - elif ( - self.trading_mode == TradingMode.FUTURES - ): - isolated_liq = self.get_or_calculate_liquidation_price( - pair=pair, - open_rate=open_rate, - is_short=is_short, - amount=amount, - stake_amount=stake_amount, - wallet_balance=stake_amount, # In isolated mode, stake-amount = wallet size - mm_ex_1=0.0, - upnl_ex_1=0.0, - ) - return isolated_liq - else: - raise OperationalException( - "Freqtrade currently only supports futures for leverage trading.") - def funding_fee_cutoff(self, open_date: datetime): """ :param open_date: The open date for a trade @@ -2622,7 +2592,7 @@ class Exchange: else: return 0.0 - def get_or_calculate_liquidation_price( + def get_liquidation_price( self, pair: str, # Dry-run @@ -2630,7 +2600,7 @@ class Exchange: is_short: bool, amount: float, # Absolute value of position size stake_amount: float, - wallet_balance: float, # Or margin balance + wallet_balance: float = 0.0, mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 35ba6bab2..ea9221213 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1732,12 +1732,12 @@ class FreqtradeBot(LoggingMixin): # TODO: Margin will need to use interest_rate as well. # interest_rate = self.exchange.get_interest_rate() trade.set_liquidation_price(self.exchange.get_liquidation_price( - leverage=trade.leverage, pair=trade.pair, + open_rate=trade.open_rate, + is_short=trade.is_short, amount=trade.amount, stake_amount=trade.stake_amount, - open_rate=trade.open_rate, - is_short=trade.is_short + wallet_balance=trade.stake_amount, )) # Updating wallets when order is closed diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 57b272e86..d65a75503 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -881,7 +881,7 @@ class Backtesting: open_rate=propose_rate, amount=amount, stake_amount=trade.stake_amount, - leverage=leverage, + wallet_balance=trade.stake_amount, is_short=is_short, )) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index b1f22e647..ff9017c13 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4089,68 +4089,6 @@ def test_combine_funding_and_mark( assert len(df) == 0 -def test_get_or_calculate_liquidation_price(mocker, default_conf): - - api_mock = MagicMock() - positions = [ - { - 'info': {}, - 'symbol': 'NEAR/USDT:USDT', - 'timestamp': 1642164737148, - 'datetime': '2022-01-14T12:52:17.148Z', - 'initialMargin': 1.51072, - 'initialMarginPercentage': 0.1, - 'maintenanceMargin': 0.38916147, - 'maintenanceMarginPercentage': 0.025, - 'entryPrice': 18.884, - 'notional': 15.1072, - 'leverage': 9.97, - 'unrealizedPnl': 0.0048, - 'contracts': 8, - 'contractSize': 0.1, - 'marginRatio': None, - 'liquidationPrice': 17.47, - 'markPrice': 18.89, - 'margin_mode': 1.52549075, - 'marginType': 'isolated', - 'side': 'buy', - 'percentage': 0.003177292946409658 - } - ] - api_mock.fetch_positions = MagicMock(return_value=positions) - mocker.patch.multiple( - 'freqtrade.exchange.Exchange', - exchange_has=MagicMock(return_value=True), - ) - default_conf['dry_run'] = False - default_conf['trading_mode'] = 'futures' - default_conf['margin_mode'] = 'isolated' - default_conf['liquidation_buffer'] = 0.0 - - exchange = get_patched_exchange(mocker, default_conf, api_mock) - liq_price = exchange.get_or_calculate_liquidation_price( - pair='NEAR/USDT:USDT', - open_rate=18.884, - is_short=False, - amount=0.8, - stake_amount=18.884 * 0.8, - wallet_balance=0.8, - ) - assert liq_price == 17.47 - - default_conf['liquidation_buffer'] = 0.05 - exchange = get_patched_exchange(mocker, default_conf, api_mock) - liq_price = exchange.get_or_calculate_liquidation_price( - pair='NEAR/USDT:USDT', - open_rate=18.884, - is_short=False, - amount=0.8, - stake_amount=18.884 * 0.8, - wallet_balance=0.8, - ) - assert liq_price == 17.540699999999998 - - @pytest.mark.parametrize('exchange,rate_start,rate_end,d1,d2,amount,expected_fees', [ ('binance', 0, 2, "2021-09-01 01:00:00", "2021-09-01 04:00:00", 30.0, 0.0), ('binance', 0, 2, "2021-09-01 00:00:00", "2021-09-01 08:00:00", 30.0, -0.00091409999), @@ -4541,7 +4479,7 @@ def test_liquidation_price_is_none( default_conf['trading_mode'] = trading_mode default_conf['margin_mode'] = margin_mode exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) - assert exchange.get_or_calculate_liquidation_price( + assert exchange.get_liquidation_price( pair='DOGE/USDT', open_rate=open_rate, is_short=is_short, @@ -4576,7 +4514,7 @@ def test_liquidation_price( default_conf['liquidation_buffer'] = 0.0 exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(mm_ratio, maintenance_amt)) - assert isclose(round(exchange.get_or_calculate_liquidation_price( + assert isclose(round(exchange.get_liquidation_price( pair='DOGE/USDT', open_rate=open_rate, is_short=is_short, @@ -5003,6 +4941,66 @@ def test__get_params(mocker, default_conf, exchange_name): ) == params2 +def test_get_liquidation_price1(mocker, default_conf): + + api_mock = MagicMock() + positions = [ + { + 'info': {}, + 'symbol': 'NEAR/USDT:USDT', + 'timestamp': 1642164737148, + 'datetime': '2022-01-14T12:52:17.148Z', + 'initialMargin': 1.51072, + 'initialMarginPercentage': 0.1, + 'maintenanceMargin': 0.38916147, + 'maintenanceMarginPercentage': 0.025, + 'entryPrice': 18.884, + 'notional': 15.1072, + 'leverage': 9.97, + 'unrealizedPnl': 0.0048, + 'contracts': 8, + 'contractSize': 0.1, + 'marginRatio': None, + 'liquidationPrice': 17.47, + 'markPrice': 18.89, + 'margin_mode': 1.52549075, + 'marginType': 'isolated', + 'side': 'buy', + 'percentage': 0.003177292946409658 + } + ] + api_mock.fetch_positions = MagicMock(return_value=positions) + mocker.patch.multiple( + 'freqtrade.exchange.Exchange', + exchange_has=MagicMock(return_value=True), + ) + default_conf['dry_run'] = False + default_conf['trading_mode'] = 'futures' + default_conf['margin_mode'] = 'isolated' + default_conf['liquidation_buffer'] = 0.0 + + exchange = get_patched_exchange(mocker, default_conf, api_mock) + liq_price = exchange.get_liquidation_price( + pair='NEAR/USDT:USDT', + open_rate=18.884, + is_short=False, + amount=0.8, + stake_amount=18.884 * 0.8, + ) + assert liq_price == 17.47 + + default_conf['liquidation_buffer'] = 0.05 + exchange = get_patched_exchange(mocker, default_conf, api_mock) + liq_price = exchange.get_liquidation_price( + pair='NEAR/USDT:USDT', + open_rate=18.884, + is_short=False, + amount=0.8, + stake_amount=18.884 * 0.8, + ) + assert liq_price == 17.540699999999998 + + @pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) @pytest.mark.parametrize( "is_short,trading_mode,exchange_name,margin_mode,leverage,open_rate,amount,expected_liq", [ @@ -5116,7 +5114,7 @@ def test_get_liquidation_price( open_rate=open_rate, amount=amount, stake_amount=amount * open_rate / leverage, - leverage=leverage, + # leverage=leverage, is_short=is_short, ) if expected_liq is None: From 27a9f98d5f3370f81bd09d040967ca72ba8a0c33 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 06:59:00 +0200 Subject: [PATCH 092/592] Simplify liquidation price structure, improve test cov --- freqtrade/exchange/exchange.py | 5 ++--- tests/exchange/test_exchange.py | 22 ++++++++++++++++++++++ 2 files changed, 24 insertions(+), 3 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index c9abb1988..9d08d3d19 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2611,8 +2611,9 @@ class Exchange: return None elif (self.trading_mode != TradingMode.FUTURES): raise OperationalException( - f"{self.name} does not support {self.margin_mode.value} {self.trading_mode.value}") + f"{self.name} does not support {self.margin_mode} {self.trading_mode}") + isolated_liq = None if self._config['dry_run'] or not self.exchange_has("fetchPositions"): isolated_liq = self.dry_run_liquidation_price( @@ -2630,8 +2631,6 @@ class Exchange: if len(positions) > 0: pos = positions[0] isolated_liq = pos['liquidationPrice'] - else: - return None if isolated_liq: buffer_amount = abs(open_rate - isolated_liq) * self.liquidation_buffer diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index ff9017c13..47df5c739 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -5000,6 +5000,28 @@ def test_get_liquidation_price1(mocker, default_conf): ) assert liq_price == 17.540699999999998 + api_mock.fetch_positions = MagicMock(return_value=[]) + exchange = get_patched_exchange(mocker, default_conf, api_mock) + liq_price = exchange.get_liquidation_price( + pair='NEAR/USDT:USDT', + open_rate=18.884, + is_short=False, + amount=0.8, + stake_amount=18.884 * 0.8, + ) + assert liq_price is None + default_conf['trading_mode'] = 'margin' + + exchange = get_patched_exchange(mocker, default_conf, api_mock) + with pytest.raises(OperationalException, match=r'.*does not support .* margin'): + exchange.get_liquidation_price( + pair='NEAR/USDT:USDT', + open_rate=18.884, + is_short=False, + amount=0.8, + stake_amount=18.884 * 0.8, + ) + @pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) @pytest.mark.parametrize( From 62c0a174c878a7ca0e630ced835f0d23096c6f74 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 29 Aug 2022 11:04:58 +0200 Subject: [PATCH 093/592] allow users to properly reverse train-test data ordering --- docs/freqai.md | 1 + freqtrade/freqai/data_kitchen.py | 14 +++++++++++--- 2 files changed, 12 insertions(+), 3 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 3d10280dd..e4a451324 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -114,6 +114,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Dictionary. | `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. | `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` +| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 8e68c9a38..5091073aa 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -168,9 +168,17 @@ class FreqaiDataKitchen: train_labels = labels train_weights = weights - return self.build_data_dictionary( - train_features, test_features, train_labels, test_labels, train_weights, test_weights - ) + # Simplest way to reverse the order of training and test data: + if self.freqai_config['feature_parameters'].get('reverse_train_test_order', False): + return self.build_data_dictionary( + test_features, train_features, test_labels, + train_labels, test_weights, train_weights + ) + else: + return self.build_data_dictionary( + train_features, test_features, train_labels, + test_labels, train_weights, test_weights + ) def filter_features( self, From efc3b39fb8f2c747472d42c1226a7f55ed03c454 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 20:01:03 +0200 Subject: [PATCH 094/592] Improve config overwriting wording #7181 --- docs/configuration.md | 26 ++++++++++++++------------ 1 file changed, 14 insertions(+), 12 deletions(-) diff --git a/docs/configuration.md b/docs/configuration.md index 940d5e8b0..f8a600e76 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -57,10 +57,21 @@ You can specify additional configuration files in `add_config_files`. Files spec This is similar to using multiple `--config` parameters, but simpler in usage as you don't have to specify all files for all commands. !!! Tip "Use multiple configuration files to keep secrets secret" - You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself. + You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself. + The 2nd file should only specify what you intend to override. + If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`). + + For one-off commands, you can also use the below syntax by specifying multiple "--config" parameters. + + ``` bash + freqtrade trade --config user_data/config1.json --config user_data/config-private.json <...> + ``` + + The below is equivalent to the example above - but having 2 configuration files in the configuration, for easier reuse. ``` json title="user_data/config.json" "add_config_files": [ + "config1.json", "config-private.json" ] ``` @@ -69,17 +80,6 @@ This is similar to using multiple `--config` parameters, but simpler in usage as freqtrade trade --config user_data/config.json <...> ``` - The 2nd file should only specify what you intend to override. - If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`). - - For one-off commands, you can also use the below syntax by specifying multiple "--config" parameters. - - ``` bash - freqtrade trade --config user_data/config.json --config user_data/config-private.json <...> - ``` - - This is equivalent to the example above - but `config-private.json` is specified as cli argument. - ??? Note "config collision handling" If the same configuration setting takes place in both `config.json` and `config-import.json`, then the parent configuration wins. In the below case, `max_open_trades` would be 3 after the merging - as the reusable "import" configuration has this key overwritten. @@ -110,6 +110,8 @@ This is similar to using multiple `--config` parameters, but simpler in usage as "stake_amount": "unlimited" } ``` + + If multiple files are in the `add_config_files` section, then they will be assumed to be at identical levels, having the last occurrence override the earlier config (unless a parent already defined such a key). ## Configuration parameters From eee2071e32024b18a2879378580258ca2b46947f Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 21:04:09 +0200 Subject: [PATCH 095/592] Fix non-testing liquidation test --- tests/exchange/test_exchange.py | 27 +++++++++++++++------------ 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 47df5c739..51890de79 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -5023,7 +5023,7 @@ def test_get_liquidation_price1(mocker, default_conf): ) -@pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) +@pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) @pytest.mark.parametrize( "is_short,trading_mode,exchange_name,margin_mode,leverage,open_rate,amount,expected_liq", [ (False, 'spot', 'binance', '', 5.0, 10.0, 1.0, None), @@ -5036,20 +5036,22 @@ def test_get_liquidation_price1(mocker, default_conf): (True, 'futures', 'binance', 'isolated', 5.0, 10.0, 1.0, 11.89108910891089), (True, 'futures', 'binance', 'isolated', 3.0, 10.0, 1.0, 13.211221122079207), (True, 'futures', 'binance', 'isolated', 5.0, 8.0, 1.0, 9.514851485148514), - (True, 'futures', 'binance', 'isolated', 5.0, 10.0, 0.6, 12.557755775577558), + (True, 'futures', 'binance', 'isolated', 5.0, 10.0, 0.6, 11.897689768976898), # Binance, long (False, 'futures', 'binance', 'isolated', 5, 10, 1.0, 8.070707070707071), (False, 'futures', 'binance', 'isolated', 5, 8, 1.0, 6.454545454545454), - (False, 'futures', 'binance', 'isolated', 3, 10, 1.0, 6.717171717171718), - (False, 'futures', 'binance', 'isolated', 5, 10, 0.6, 7.39057239057239), + (False, 'futures', 'binance', 'isolated', 3, 10, 1.0, 6.723905723905723), + (False, 'futures', 'binance', 'isolated', 5, 10, 0.6, 8.063973063973064), # Gateio/okx, short - (True, 'futures', 'gateio', 'isolated', 5, 10, 1.0, 11.87413417771621), - (True, 'futures', 'gateio', 'isolated', 5, 10, 2.0, 11.87413417771621), - (True, 'futures', 'gateio', 'isolated', 3, 10, 1.0, 13.476180850346978), - (True, 'futures', 'gateio', 'isolated', 5, 8, 1.0, 9.499307342172967), + (True, 'futures', 'gateio', 'isolated', 5, 10, 1.0, 11.89108910891089), + (True, 'futures', 'gateio', 'isolated', 5, 10, 2.0, 11.886138613861386), + (True, 'futures', 'gateio', 'isolated', 3, 10, 1.0, 13.211221122112212), + (True, 'futures', 'gateio', 'isolated', 5, 8, 1.0, 9.514851485148514), # Gateio/okx, long - (False, 'futures', 'gateio', 'isolated', 5.0, 10.0, 1.0, 8.085708510208207), - (False, 'futures', 'gateio', 'isolated', 3.0, 10.0, 1.0, 6.738090425173506), + (False, 'futures', 'gateio', 'isolated', 5.0, 10.0, 1.0, 8.070707070707071), + (False, 'futures', 'gateio', 'isolated', 3.0, 10.0, 1.0, 6.723905723905723), + (True, 'futures', 'okx', 'isolated', 5, 8, 1.0, 9.514851485148514), + (False, 'futures', 'okx', 'isolated', 3.0, 10.0, 1.0, 6.723905723905723), # (True, 'futures', 'okx', 'isolated', 11.87413417771621), # (False, 'futures', 'okx', 'isolated', 8.085708510208207), ] @@ -5135,7 +5137,8 @@ def test_get_liquidation_price( pair='ETH/USDT:USDT', open_rate=open_rate, amount=amount, - stake_amount=amount * open_rate / leverage, + stake_amount=(amount * open_rate) / leverage, + wallet_balance=(amount * open_rate) / leverage, # leverage=leverage, is_short=is_short, ) @@ -5144,7 +5147,7 @@ def test_get_liquidation_price( else: buffer_amount = liquidation_buffer * abs(open_rate - expected_liq) expected_liq = expected_liq - buffer_amount if is_short else expected_liq + buffer_amount - isclose(expected_liq, liq) + assert pytest.approx(expected_liq) == liq @pytest.mark.parametrize('contract_size,order_amount', [ From 7952e0df25914bef04bc0f8acda729e2b9a685d6 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 29 Aug 2022 13:41:15 -0600 Subject: [PATCH 096/592] initial rework separating server and client impl --- .gitignore | 3 - config_examples/config_follower.example.json | 87 -- config_examples/config_leader.example.json | 97 -- freqtrade/constants.py | 1 + freqtrade/enums/rpcmessagetype.py | 5 +- freqtrade/freqtradebot.py | 41 +- freqtrade/rpc/api_server/api_auth.py | 24 +- freqtrade/rpc/api_server/api_ws.py | 52 ++ freqtrade/rpc/api_server/deps.py | 4 + freqtrade/rpc/api_server/webserver.py | 76 +- freqtrade/rpc/api_server/ws/channel.py | 146 +++ freqtrade/rpc/api_server/ws/proxy.py | 61 ++ freqtrade/rpc/api_server/ws/serializer.py | 65 ++ freqtrade/rpc/api_server/ws/types.py | 8 + freqtrade/rpc/api_server/ws/utils.py | 12 + freqtrade/rpc/external_signal/__init__.py | 10 +- freqtrade/rpc/external_signal/channel.py | 290 +++--- freqtrade/rpc/external_signal/controller.py | 898 +++++++++---------- freqtrade/rpc/external_signal/proxy.py | 122 +-- freqtrade/rpc/external_signal/serializer.py | 130 +-- freqtrade/rpc/external_signal/types.py | 16 +- freqtrade/rpc/external_signal/utils.py | 32 +- freqtrade/rpc/rpc.py | 131 ++- freqtrade/rpc/rpc_manager.py | 28 +- scripts/test_ws_client.py | 58 ++ 25 files changed, 1329 insertions(+), 1068 deletions(-) delete mode 100644 config_examples/config_follower.example.json delete mode 100644 config_examples/config_leader.example.json create mode 100644 freqtrade/rpc/api_server/api_ws.py create mode 100644 freqtrade/rpc/api_server/ws/channel.py create mode 100644 freqtrade/rpc/api_server/ws/proxy.py create mode 100644 freqtrade/rpc/api_server/ws/serializer.py create mode 100644 freqtrade/rpc/api_server/ws/types.py create mode 100644 freqtrade/rpc/api_server/ws/utils.py create mode 100644 scripts/test_ws_client.py diff --git a/.gitignore b/.gitignore index b8c4c3846..6a47a7f81 100644 --- a/.gitignore +++ b/.gitignore @@ -115,6 +115,3 @@ target/ !config_examples/config_freqai.example.json !config_examples/config_leader.example.json !config_examples/config_follower.example.json - -*-config.json -*.db* diff --git a/config_examples/config_follower.example.json b/config_examples/config_follower.example.json deleted file mode 100644 index 646310d9a..000000000 --- a/config_examples/config_follower.example.json +++ /dev/null @@ -1,87 +0,0 @@ - -{ - "db_url": "sqlite:///follower.db", - "strategy": "SampleStrategy", - "max_open_trades": 3, - "stake_currency": "USDT", - "stake_amount": 100, - "tradable_balance_ratio": 0.99, - "fiat_display_currency": "USD", - "dry_run": true, - "cancel_open_orders_on_exit": false, - "trading_mode": "spot", - "margin_mode": "", - "unfilledtimeout": { - "entry": 10, - "exit": 10, - "exit_timeout_count": 0, - "unit": "minutes" - }, - "entry_pricing": { - "price_side": "same", - "use_order_book": true, - "order_book_top": 1, - "price_last_balance": 0.0, - "check_depth_of_market": { - "enabled": false, - "bids_to_ask_delta": 1 - } - }, - "exit_pricing":{ - "price_side": "same", - "use_order_book": true, - "order_book_top": 1 - }, - "exchange": { - "name": "kucoin", - "key": "", - "secret": "", - "password": "", - "ccxt_config": {}, - "ccxt_async_config": {}, - "pair_whitelist": [ - ], - "pair_blacklist": [ - ] - }, - "pairlists": [ - { - "method": "ExternalPairList", // ExternalPairList is required in follower mode - "number_assets": 5, // We can limit the amount of pairs to use from the leaders - } - ], - "telegram": { - "enabled": false, - "token": "", - "chat_id": "" - }, - "api_server": { - "enabled": true, - "listen_ip_address": "127.0.0.1", - "listen_port": 8081, - "verbosity": "error", - "enable_openapi": false, - "jwt_secret_key": "fcc24d31d6581ad2c90c3fc438c8a8b2ccce1393126959934568707f0bd2d647", - "CORS_origins": [], - "username": "freqtrader", - "password": "testing123" - }, - "external_signal": { - "enabled": true, - "mode": "follower", - "leaders": [ - { - "url": "ws://localhost:8080/signals/ws", - "api_token": "testtoken" - } - ], - "wait_data_policy": "all", // ['all', 'first', none] defaults to all - "remove_signals_analyzed_df": true, // Remove entry/exit signals from Leader df, Defaults to false - }, - "bot_name": "freqtrade", - "initial_state": "running", - "force_entry_enable": false, - "internals": { - "process_throttle_secs": 5, - } -} diff --git a/config_examples/config_leader.example.json b/config_examples/config_leader.example.json deleted file mode 100644 index 5103fdbd4..000000000 --- a/config_examples/config_leader.example.json +++ /dev/null @@ -1,97 +0,0 @@ - -{ - "db_url": "sqlite:///leader.db", - "strategy": "SampleStrategy", - "max_open_trades": 3, - "stake_currency": "USDT", - "stake_amount": 100, - "tradable_balance_ratio": 0.99, - "fiat_display_currency": "USD", - "dry_run": true, - "cancel_open_orders_on_exit": false, - "trading_mode": "spot", - "margin_mode": "", - "unfilledtimeout": { - "entry": 10, - "exit": 10, - "exit_timeout_count": 0, - "unit": "minutes" - }, - "entry_pricing": { - "price_side": "same", - "use_order_book": true, - "order_book_top": 1, - "price_last_balance": 0.0, - "check_depth_of_market": { - "enabled": false, - "bids_to_ask_delta": 1 - } - }, - "exit_pricing":{ - "price_side": "same", - "use_order_book": true, - "order_book_top": 1 - }, - "exchange": { - "name": "kucoin", - "key": "", - "secret": "", - "password": "", - "ccxt_config": {}, - "ccxt_async_config": {}, - "pair_whitelist": [ - ], - "pair_blacklist": [ - ] - }, - "pairlists": [ - { - "method": "VolumePairList", - "number_assets": 20, - "sort_key": "quoteVolume", - "min_value": 0, - "refresh_period": 1800 - } - ], - "edge": { - "enabled": false, - "process_throttle_secs": 3600, - "calculate_since_number_of_days": 7, - "allowed_risk": 0.01, - "stoploss_range_min": -0.01, - "stoploss_range_max": -0.1, - "stoploss_range_step": -0.01, - "minimum_winrate": 0.60, - "minimum_expectancy": 0.20, - "min_trade_number": 10, - "max_trade_duration_minute": 1440, - "remove_pumps": false - }, - "telegram": { - "enabled": false, - "token": "", - "chat_id": "" - }, - "api_server": { - "enabled": true, - "listen_ip_address": "127.0.0.1", - "listen_port": 8080, - "verbosity": "error", - "enable_openapi": false, - "jwt_secret_key": "fcc24d31d6581ad2c90c3fc438c8a8b2ccce1393126959934568707f0bd2d647", - "CORS_origins": [], - "username": "freqtrader", - "password": "testing123" - }, - "external_signal": { - "enabled": true, - "mode": "leader", - "api_token": "testtoken", - }, - "bot_name": "freqtrade", - "initial_state": "running", - "force_entry_enable": false, - "internals": { - "process_throttle_secs": 5, - } -} diff --git a/freqtrade/constants.py b/freqtrade/constants.py index b1f189093..96f8413b0 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -404,6 +404,7 @@ CONF_SCHEMA = { }, 'username': {'type': 'string'}, 'password': {'type': 'string'}, + 'api_token': {'type': 'string'}, 'jwt_secret_key': {'type': 'string'}, 'CORS_origins': {'type': 'array', 'items': {'type': 'string'}}, 'verbosity': {'type': 'string', 'enum': ['error', 'info']}, diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index d5b3ce89c..8e4182b33 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -1,7 +1,8 @@ from enum import Enum -class RPCMessageType(Enum): +# We need to inherit from str so we can use as a str +class RPCMessageType(str, Enum): STATUS = 'status' WARNING = 'warning' STARTUP = 'startup' @@ -19,7 +20,7 @@ class RPCMessageType(Enum): STRATEGY_MSG = 'strategy_msg' - EMIT_DATA = 'emit_data' + WHITELIST = 'whitelist' def __repr__(self): return self.value diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 6aee3d104..c9caaace6 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -17,13 +17,13 @@ from freqtrade.constants import BuySell, LongShort from freqtrade.data.converter import order_book_to_dataframe from freqtrade.data.dataprovider import DataProvider from freqtrade.edge import Edge -from freqtrade.enums import (ExitCheckTuple, ExitType, LeaderMessageType, RPCMessageType, RunMode, - SignalDirection, State, TradingMode) +from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode, SignalDirection, + State, TradingMode) from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError, InvalidOrderException, PricingError) from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds from freqtrade.exchange.exchange import timeframe_to_next_date -from freqtrade.misc import dataframe_to_json, safe_value_fallback, safe_value_fallback2 +from freqtrade.misc import safe_value_fallback, safe_value_fallback2 from freqtrade.mixins import LoggingMixin from freqtrade.persistence import Order, PairLocks, Trade, init_db from freqtrade.plugins.pairlistmanager import PairListManager @@ -75,8 +75,6 @@ class FreqtradeBot(LoggingMixin): PairLocks.timeframe = self.config['timeframe'] - self.external_signal_controller = None - self.pairlists = PairListManager(self.exchange, self.config) # RPC runs in separate threads, can start handling external commands just after @@ -194,28 +192,7 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - if self.external_signal_controller: - if not self.external_signal_controller.is_leader(): - # Run Follower mode analyzing - leader_pairs = self.pairlists._whitelist - self.strategy.analyze_external(self.active_pair_whitelist, leader_pairs) - else: - # We are leader, make sure to pass callback func to emit data - def emit_on_finish(pair, dataframe, timeframe, candle_type): - logger.debug(f"Emitting dataframe for {pair}") - return self.rpc.emit_data( - { - "data_type": LeaderMessageType.analyzed_df, - "data": { - "key": (pair, timeframe, candle_type), - "value": dataframe_to_json(dataframe) - } - } - ) - - self.strategy.analyze(self.active_pair_whitelist, finish_callback=emit_on_finish) - else: - self.strategy.analyze(self.active_pair_whitelist) + self.strategy.analyze(self.active_pair_whitelist) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace @@ -278,15 +255,7 @@ class FreqtradeBot(LoggingMixin): self.pairlists.refresh_pairlist() _whitelist = self.pairlists.whitelist - # If external signal leader, broadcast whitelist data - # Should we broadcast before trade pairs are added? - - if self.external_signal_controller: - if self.external_signal_controller.is_leader(): - self.rpc.emit_data({ - "data_type": LeaderMessageType.pairlist, - "data": _whitelist - }) + self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'msg': _whitelist}) # Calculating Edge positioning if self.edge: diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index a39e31b85..fd90918e1 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -1,8 +1,10 @@ +import logging import secrets from datetime import datetime, timedelta +from typing import Any, Dict, Union import jwt -from fastapi import APIRouter, Depends, HTTPException, status +from fastapi import APIRouter, Depends, HTTPException, WebSocket, status from fastapi.security import OAuth2PasswordBearer from fastapi.security.http import HTTPBasic, HTTPBasicCredentials @@ -10,6 +12,8 @@ from freqtrade.rpc.api_server.api_schemas import AccessAndRefreshToken, AccessTo from freqtrade.rpc.api_server.deps import get_api_config +logger = logging.getLogger(__name__) + ALGORITHM = "HS256" router_login = APIRouter() @@ -44,6 +48,24 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access"): return username +# This should be reimplemented to better realign with the existing tools provided +# by FastAPI regarding API Tokens +async def get_ws_token( + ws: WebSocket, + token: Union[str, None] = None, + api_config: Dict[str, Any] = Depends(get_api_config) +): + secret_ws_token = api_config['ws_token'] + + if token == secret_ws_token: + # Just return the token if it matches + return token + else: + logger.debug("Denying websocket request") + # If it doesn't match, close the websocket connection + await ws.close(code=status.WS_1008_POLICY_VIOLATION) + + def create_token(data: dict, secret_key: str, token_type: str = "access") -> str: to_encode = data.copy() if token_type == "access": diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py new file mode 100644 index 000000000..464ea22b2 --- /dev/null +++ b/freqtrade/rpc/api_server/api_ws.py @@ -0,0 +1,52 @@ +import logging + +from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect + +from freqtrade.rpc.api_server.deps import get_channel_manager +from freqtrade.rpc.api_server.ws.utils import is_websocket_alive + + +logger = logging.getLogger(__name__) + +# Private router, protected by API Key authentication +router = APIRouter() + + +@router.websocket("/message/ws") +async def message_endpoint( + ws: WebSocket, + channel_manager=Depends(get_channel_manager) +): + try: + if is_websocket_alive(ws): + logger.info(f"Consumer connected - {ws.client}") + + # TODO: + # Return a channel ID, pass that instead of ws to the rest of the methods + channel = await channel_manager.on_connect(ws) + + # Keep connection open until explicitly closed, and sleep + try: + while not channel.is_closed(): + request = await channel.recv() + + # This is where we'd parse the request. For now this should only + # be a list of topics to subscribe too. List[str] + # Maybe allow the consumer to update the topics subscribed + # during runtime? + logger.info(f"Consumer request - {request}") + + except WebSocketDisconnect: + # Handle client disconnects + logger.info(f"Consumer disconnected - {ws.client}") + await channel_manager.on_disconnect(ws) + except Exception as e: + logger.info(f"Consumer connection failed - {ws.client}") + logger.exception(e) + # Handle cases like - + # RuntimeError('Cannot call "send" once a closed message has been sent') + await channel_manager.on_disconnect(ws) + + except Exception: + logger.error(f"Failed to serve - {ws.client}") + await channel_manager.on_disconnect(ws) diff --git a/freqtrade/rpc/api_server/deps.py b/freqtrade/rpc/api_server/deps.py index 66654c0b1..360771d77 100644 --- a/freqtrade/rpc/api_server/deps.py +++ b/freqtrade/rpc/api_server/deps.py @@ -41,6 +41,10 @@ def get_exchange(config=Depends(get_config)): return ApiServer._exchange +def get_channel_manager(): + return ApiServer._channel_manager + + def is_webserver_mode(config=Depends(get_config)): if config['runmode'] != RunMode.WEBSERVER: raise RPCException('Bot is not in the correct state') diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 049e7dbc2..94cb8cd45 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -1,15 +1,20 @@ +import asyncio import logging from ipaddress import IPv4Address +from threading import Thread from typing import Any, Dict import orjson import uvicorn from fastapi import Depends, FastAPI from fastapi.middleware.cors import CORSMiddleware +# Look into alternatives +from janus import Queue as ThreadedQueue from starlette.responses import JSONResponse from freqtrade.exceptions import OperationalException from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer +from freqtrade.rpc.api_server.ws.channel import ChannelManager from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler @@ -43,6 +48,10 @@ class ApiServer(RPCHandler): _config: Dict[str, Any] = {} # Exchange - only available in webserver mode. _exchange = None + # websocket message queue stuff + _channel_manager = None + _thread = None + _loop = None def __new__(cls, *args, **kwargs): """ @@ -64,10 +73,15 @@ class ApiServer(RPCHandler): return self._standalone: bool = standalone self._server = None + self._queue = None + self._background_task = None + ApiServer.__initialized = True api_config = self._config['api_server'] + ApiServer._channel_manager = ChannelManager() + self.app = FastAPI(title="Freqtrade API", docs_url='/docs' if api_config.get('enable_openapi', False) else None, redoc_url=None, @@ -95,6 +109,18 @@ class ApiServer(RPCHandler): logger.info("Stopping API Server") self._server.cleanup() + if self._thread and self._loop: + logger.info("Stopping API Server background tasks") + + if self._background_task: + # Cancel the queue task + self._background_task.cancel() + + # Finally stop the loop + self._loop.call_soon_threadsafe(self._loop.stop) + + self._thread.join() + @classmethod def shutdown(cls): cls.__initialized = False @@ -104,7 +130,10 @@ class ApiServer(RPCHandler): cls._rpc = None def send_msg(self, msg: Dict[str, str]) -> None: - pass + if self._queue: + logger.info(f"Adding message to queue: {msg}") + sync_q = self._queue.sync_q + sync_q.put(msg) def handle_rpc_exception(self, request, exc): logger.exception(f"API Error calling: {exc}") @@ -114,10 +143,12 @@ class ApiServer(RPCHandler): ) def configure_app(self, app: FastAPI, config): - from freqtrade.rpc.api_server.api_auth import http_basic_or_jwt_token, router_login + from freqtrade.rpc.api_server.api_auth import (get_ws_token, http_basic_or_jwt_token, + router_login) from freqtrade.rpc.api_server.api_backtest import router as api_backtest from freqtrade.rpc.api_server.api_v1 import router as api_v1 from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public + from freqtrade.rpc.api_server.api_ws import router as ws_router from freqtrade.rpc.api_server.web_ui import router_ui app.include_router(api_v1_public, prefix="/api/v1") @@ -128,6 +159,9 @@ class ApiServer(RPCHandler): app.include_router(api_backtest, prefix="/api/v1", dependencies=[Depends(http_basic_or_jwt_token)], ) + app.include_router(ws_router, prefix="/api/v1", + dependencies=[Depends(get_ws_token)] + ) app.include_router(router_login, prefix="/api/v1", tags=["auth"]) # UI Router MUST be last! app.include_router(router_ui, prefix='') @@ -142,6 +176,43 @@ class ApiServer(RPCHandler): app.add_exception_handler(RPCException, self.handle_rpc_exception) + def start_message_queue(self): + # Create a new loop, as it'll be just for the background thread + self._loop = asyncio.new_event_loop() + + # Start the thread + if not self._thread: + self._thread = Thread(target=self._loop.run_forever) + self._thread.start() + else: + raise RuntimeError("Threaded loop is already running") + + # Finally, submit the coro to the thread + self._background_task = asyncio.run_coroutine_threadsafe( + self._broadcast_queue_data(), loop=self._loop) + + async def _broadcast_queue_data(self): + # Instantiate the queue in this coroutine so it's attached to our loop + self._queue = ThreadedQueue() + async_queue = self._queue.async_q + + try: + while True: + logger.debug("Getting queue data...") + # Get data from queue + data = await async_queue.get() + logger.debug(f"Found data: {data}") + # Broadcast it + await self._channel_manager.broadcast(data) + # Sleep, make this configurable? + await asyncio.sleep(0.1) + except asyncio.CancelledError: + # Silently stop + pass + # For testing, shouldn't happen when stable + except Exception as e: + logger.info(f"Exception happened in background task: {e}") + def start_api(self): """ Start API ... should be run in thread. @@ -179,6 +250,7 @@ class ApiServer(RPCHandler): if self._standalone: self._server.run() else: + self.start_message_queue() self._server.run_in_thread() except Exception: logger.exception("Api server failed to start.") diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py new file mode 100644 index 000000000..486e8657b --- /dev/null +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -0,0 +1,146 @@ +import logging +from threading import RLock +from typing import Type + +from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy +from freqtrade.rpc.api_server.ws.serializer import ORJSONWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.api_server.ws.types import WebSocketType + + +logger = logging.getLogger(__name__) + + +class WebSocketChannel: + """ + Object to help facilitate managing a websocket connection + """ + + def __init__( + self, + websocket: WebSocketType, + serializer_cls: Type[WebSocketSerializer] = ORJSONWebSocketSerializer + ): + # The WebSocket object + self._websocket = WebSocketProxy(websocket) + # The Serializing class for the WebSocket object + self._serializer_cls = serializer_cls + + # Internal event to signify a closed websocket + self._closed = False + + # Wrap the WebSocket in the Serializing class + self._wrapped_ws = self._serializer_cls(self._websocket) + + async def send(self, data): + """ + Send data on the wrapped websocket + """ + # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") + await self._wrapped_ws.send(data) + + async def recv(self): + """ + Receive data on the wrapped websocket + """ + return await self._wrapped_ws.recv() + + async def ping(self): + """ + Ping the websocket + """ + return await self._websocket.ping() + + async def close(self): + """ + Close the WebSocketChannel + """ + + self._closed = True + + def is_closed(self): + return self._closed + + +class ChannelManager: + def __init__(self): + self.channels = dict() + self._lock = RLock() # Re-entrant Lock + + async def on_connect(self, websocket: WebSocketType): + """ + Wrap websocket connection into Channel and add to list + + :param websocket: The WebSocket object to attach to the Channel + """ + if hasattr(websocket, "accept"): + try: + await websocket.accept() + except RuntimeError: + # The connection was closed before we could accept it + return + + ws_channel = WebSocketChannel(websocket) + + with self._lock: + self.channels[websocket] = ws_channel + + return ws_channel + + async def on_disconnect(self, websocket: WebSocketType): + """ + Call close on the channel if it's not, and remove from channel list + + :param websocket: The WebSocket objet attached to the Channel + """ + with self._lock: + channel = self.channels.get(websocket) + if channel: + logger.debug(f"Disconnecting channel - {channel}") + + if not channel.is_closed(): + await channel.close() + + del self.channels[websocket] + + async def disconnect_all(self): + """ + Disconnect all Channels + """ + with self._lock: + for websocket, channel in self.channels.items(): + if not channel.is_closed(): + await channel.close() + + self.channels = dict() + + async def broadcast(self, data): + """ + Broadcast data on all Channels + + :param data: The data to send + """ + with self._lock: + logger.debug(f"Broadcasting data: {data}") + for websocket, channel in self.channels.items(): + try: + await channel.send(data) + except RuntimeError: + # Handle cannot send after close cases + await self.on_disconnect(websocket) + + async def send_direct(self, channel, data): + """ + Send data directly through direct_channel only + + :param direct_channel: The WebSocketChannel object to send data through + :param data: The data to send + """ + # We iterate over the channels to get reference to the websocket object + # so we can disconnect incase of failure + await channel.send(data) + + def has_channels(self): + """ + Flag for more than 0 channels + """ + return len(self.channels) > 0 diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py new file mode 100644 index 000000000..6acc1d363 --- /dev/null +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -0,0 +1,61 @@ +from typing import Union + +from fastapi import WebSocket as FastAPIWebSocket +from websockets import WebSocketClientProtocol as WebSocket + +from freqtrade.rpc.api_server.ws.types import WebSocketType + + +class WebSocketProxy: + """ + WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol + under the same API + """ + + def __init__(self, websocket: WebSocketType): + self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket + + async def send(self, data): + """ + Send data on the wrapped websocket + """ + if isinstance(data, str): + data = data.encode() + + if hasattr(self._websocket, "send_bytes"): + await self._websocket.send_bytes(data) + else: + await self._websocket.send(data) + + async def recv(self): + """ + Receive data on the wrapped websocket + """ + if hasattr(self._websocket, "receive_bytes"): + return await self._websocket.receive_bytes() + else: + return await self._websocket.recv() + + async def ping(self): + """ + Ping the websocket, not supported by FastAPI WebSockets + """ + if hasattr(self._websocket, "ping"): + return await self._websocket.ping() + return False + + async def close(self, code: int = 1000): + """ + Close the websocket connection, only supported by FastAPI WebSockets + """ + if hasattr(self._websocket, "close"): + return await self._websocket.close(code) + pass + + async def accept(self): + """ + Accept the WebSocket connection, only support by FastAPI WebSockets + """ + if hasattr(self._websocket, "accept"): + return await self._websocket.accept() + pass diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py new file mode 100644 index 000000000..40cbbfad7 --- /dev/null +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -0,0 +1,65 @@ +import json +import logging +from abc import ABC, abstractmethod + +import msgpack +import orjson + +from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy + + +logger = logging.getLogger(__name__) + + +class WebSocketSerializer(ABC): + def __init__(self, websocket: WebSocketProxy): + self._websocket: WebSocketProxy = websocket + + @abstractmethod + def _serialize(self, data): + raise NotImplementedError() + + @abstractmethod + def _deserialize(self, data): + raise NotImplementedError() + + async def send(self, data: bytes): + await self._websocket.send(self._serialize(data)) + + async def recv(self) -> bytes: + data = await self._websocket.recv() + + return self._deserialize(data) + + async def close(self, code: int = 1000): + await self._websocket.close(code) + +# Going to explore using MsgPack as the serialization, +# as that might be the best method for sending pandas +# dataframes over the wire + + +class JSONWebSocketSerializer(WebSocketSerializer): + def _serialize(self, data): + return json.dumps(data) + + def _deserialize(self, data): + return json.loads(data) + + +class ORJSONWebSocketSerializer(WebSocketSerializer): + ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY + + def _serialize(self, data): + return orjson.dumps(data, option=self.ORJSON_OPTIONS) + + def _deserialize(self, data): + return orjson.loads(data, option=self.ORJSON_OPTIONS) + + +class MsgPackWebSocketSerializer(WebSocketSerializer): + def _serialize(self, data): + return msgpack.packb(data, use_bin_type=True) + + def _deserialize(self, data): + return msgpack.unpackb(data, raw=False) diff --git a/freqtrade/rpc/api_server/ws/types.py b/freqtrade/rpc/api_server/ws/types.py new file mode 100644 index 000000000..814fe6649 --- /dev/null +++ b/freqtrade/rpc/api_server/ws/types.py @@ -0,0 +1,8 @@ +from typing import Any, Dict, TypeVar + +from fastapi import WebSocket as FastAPIWebSocket +from websockets import WebSocketClientProtocol as WebSocket + + +WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) +MessageType = Dict[str, Any] diff --git a/freqtrade/rpc/api_server/ws/utils.py b/freqtrade/rpc/api_server/ws/utils.py new file mode 100644 index 000000000..1ceecab88 --- /dev/null +++ b/freqtrade/rpc/api_server/ws/utils.py @@ -0,0 +1,12 @@ +from fastapi import WebSocket +# fastapi does not make this available through it, so import directly from starlette +from starlette.websockets import WebSocketState + + +async def is_websocket_alive(ws: WebSocket) -> bool: + if ( + ws.application_state == WebSocketState.CONNECTED and + ws.client_state == WebSocketState.CONNECTED + ): + return True + return False diff --git a/freqtrade/rpc/external_signal/__init__.py b/freqtrade/rpc/external_signal/__init__.py index c1b05b3f0..decc51551 100644 --- a/freqtrade/rpc/external_signal/__init__.py +++ b/freqtrade/rpc/external_signal/__init__.py @@ -1,5 +1,5 @@ -# flake8: noqa: F401 -from freqtrade.rpc.external_signal.controller import ExternalSignalController - - -__all__ = ('ExternalSignalController') +# # flake8: noqa: F401 +# from freqtrade.rpc.external_signal.controller import ExternalSignalController +# +# +# __all__ = ('ExternalSignalController') diff --git a/freqtrade/rpc/external_signal/channel.py b/freqtrade/rpc/external_signal/channel.py index 4ccb2d864..5b278dfed 100644 --- a/freqtrade/rpc/external_signal/channel.py +++ b/freqtrade/rpc/external_signal/channel.py @@ -1,145 +1,145 @@ -import logging -from threading import RLock -from typing import Type - -from freqtrade.rpc.external_signal.proxy import WebSocketProxy -from freqtrade.rpc.external_signal.serializer import MsgPackWebSocketSerializer, WebSocketSerializer -from freqtrade.rpc.external_signal.types import WebSocketType - - -logger = logging.getLogger(__name__) - - -class WebSocketChannel: - """ - Object to help facilitate managing a websocket connection - """ - - def __init__( - self, - websocket: WebSocketType, - serializer_cls: Type[WebSocketSerializer] = MsgPackWebSocketSerializer - ): - # The WebSocket object - self._websocket = WebSocketProxy(websocket) - # The Serializing class for the WebSocket object - self._serializer_cls = serializer_cls - - # Internal event to signify a closed websocket - self._closed = False - - # Wrap the WebSocket in the Serializing class - self._wrapped_ws = self._serializer_cls(self._websocket) - - async def send(self, data): - """ - Send data on the wrapped websocket - """ - # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") - await self._wrapped_ws.send(data) - - async def recv(self): - """ - Receive data on the wrapped websocket - """ - return await self._wrapped_ws.recv() - - async def ping(self): - """ - Ping the websocket - """ - return await self._websocket.ping() - - async def close(self): - """ - Close the WebSocketChannel - """ - - self._closed = True - - def is_closed(self): - return self._closed - - -class ChannelManager: - def __init__(self): - self.channels = dict() - self._lock = RLock() # Re-entrant Lock - - async def on_connect(self, websocket: WebSocketType): - """ - Wrap websocket connection into Channel and add to list - - :param websocket: The WebSocket object to attach to the Channel - """ - if hasattr(websocket, "accept"): - try: - await websocket.accept() - except RuntimeError: - # The connection was closed before we could accept it - return - - ws_channel = WebSocketChannel(websocket) - - with self._lock: - self.channels[websocket] = ws_channel - - return ws_channel - - async def on_disconnect(self, websocket: WebSocketType): - """ - Call close on the channel if it's not, and remove from channel list - - :param websocket: The WebSocket objet attached to the Channel - """ - with self._lock: - channel = self.channels.get(websocket) - if channel: - logger.debug(f"Disconnecting channel - {channel}") - - if not channel.is_closed(): - await channel.close() - - del self.channels[websocket] - - async def disconnect_all(self): - """ - Disconnect all Channels - """ - with self._lock: - for websocket, channel in self.channels.items(): - if not channel.is_closed(): - await channel.close() - - self.channels = dict() - - async def broadcast(self, data): - """ - Broadcast data on all Channels - - :param data: The data to send - """ - with self._lock: - for websocket, channel in self.channels.items(): - try: - await channel.send(data) - except RuntimeError: - # Handle cannot send after close cases - await self.on_disconnect(websocket) - - async def send_direct(self, channel, data): - """ - Send data directly through direct_channel only - - :param direct_channel: The WebSocketChannel object to send data through - :param data: The data to send - """ - # We iterate over the channels to get reference to the websocket object - # so we can disconnect incase of failure - await channel.send(data) - - def has_channels(self): - """ - Flag for more than 0 channels - """ - return len(self.channels) > 0 +# import logging +# from threading import RLock +# from typing import Type +# +# from freqtrade.rpc.external_signal.proxy import WebSocketProxy +# from freqtrade.rpc.external_signal.serializer import MsgPackWebSocketSerializer +# from freqtrade.rpc.external_signal.types import WebSocketType +# +# +# logger = logging.getLogger(__name__) +# +# +# class WebSocketChannel: +# """ +# Object to help facilitate managing a websocket connection +# """ +# +# def __init__( +# self, +# websocket: WebSocketType, +# serializer_cls: Type[WebSocketSerializer] = MsgPackWebSocketSerializer +# ): +# # The WebSocket object +# self._websocket = WebSocketProxy(websocket) +# # The Serializing class for the WebSocket object +# self._serializer_cls = serializer_cls +# +# # Internal event to signify a closed websocket +# self._closed = False +# +# # Wrap the WebSocket in the Serializing class +# self._wrapped_ws = self._serializer_cls(self._websocket) +# +# async def send(self, data): +# """ +# Send data on the wrapped websocket +# """ +# # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") +# await self._wrapped_ws.send(data) +# +# async def recv(self): +# """ +# Receive data on the wrapped websocket +# """ +# return await self._wrapped_ws.recv() +# +# async def ping(self): +# """ +# Ping the websocket +# """ +# return await self._websocket.ping() +# +# async def close(self): +# """ +# Close the WebSocketChannel +# """ +# +# self._closed = True +# +# def is_closed(self): +# return self._closed +# +# +# class ChannelManager: +# def __init__(self): +# self.channels = dict() +# self._lock = RLock() # Re-entrant Lock +# +# async def on_connect(self, websocket: WebSocketType): +# """ +# Wrap websocket connection into Channel and add to list +# +# :param websocket: The WebSocket object to attach to the Channel +# """ +# if hasattr(websocket, "accept"): +# try: +# await websocket.accept() +# except RuntimeError: +# # The connection was closed before we could accept it +# return +# +# ws_channel = WebSocketChannel(websocket) +# +# with self._lock: +# self.channels[websocket] = ws_channel +# +# return ws_channel +# +# async def on_disconnect(self, websocket: WebSocketType): +# """ +# Call close on the channel if it's not, and remove from channel list +# +# :param websocket: The WebSocket objet attached to the Channel +# """ +# with self._lock: +# channel = self.channels.get(websocket) +# if channel: +# logger.debug(f"Disconnecting channel - {channel}") +# +# if not channel.is_closed(): +# await channel.close() +# +# del self.channels[websocket] +# +# async def disconnect_all(self): +# """ +# Disconnect all Channels +# """ +# with self._lock: +# for websocket, channel in self.channels.items(): +# if not channel.is_closed(): +# await channel.close() +# +# self.channels = dict() +# +# async def broadcast(self, data): +# """ +# Broadcast data on all Channels +# +# :param data: The data to send +# """ +# with self._lock: +# for websocket, channel in self.channels.items(): +# try: +# await channel.send(data) +# except RuntimeError: +# # Handle cannot send after close cases +# await self.on_disconnect(websocket) +# +# async def send_direct(self, channel, data): +# """ +# Send data directly through direct_channel only +# +# :param direct_channel: The WebSocketChannel object to send data through +# :param data: The data to send +# """ +# # We iterate over the channels to get reference to the websocket object +# # so we can disconnect incase of failure +# await channel.send(data) +# +# def has_channels(self): +# """ +# Flag for more than 0 channels +# """ +# return len(self.channels) > 0 diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py index 2b29cde6f..616ea7801 100644 --- a/freqtrade/rpc/external_signal/controller.py +++ b/freqtrade/rpc/external_signal/controller.py @@ -1,449 +1,449 @@ -""" -This module manages replicate mode communication -""" -import asyncio -import logging -import secrets -import socket -from threading import Thread -from typing import Any, Callable, Coroutine, Dict, Union - -import websockets -from fastapi import Depends -from fastapi import WebSocket as FastAPIWebSocket -from fastapi import WebSocketDisconnect, status -from janus import Queue as ThreadedQueue - -from freqtrade.enums import ExternalSignalModeType, LeaderMessageType, RPCMessageType -from freqtrade.rpc import RPC, RPCHandler -from freqtrade.rpc.external_signal.channel import ChannelManager -from freqtrade.rpc.external_signal.types import MessageType -from freqtrade.rpc.external_signal.utils import is_websocket_alive - - -logger = logging.getLogger(__name__) - - -class ExternalSignalController(RPCHandler): - """ This class handles all websocket communication """ - - def __init__( - self, - rpc: RPC, - config: Dict[str, Any], - api_server: Union[Any, None] = None - ) -> None: - """ - Init the ExternalSignalController class, and init the super class RPCHandler - :param rpc: instance of RPC Helper class - :param config: Configuration object - :param api_server: The ApiServer object - :return: None - """ - super().__init__(rpc, config) - - self.freqtrade = rpc._freqtrade - self.api_server = api_server - - if not self.api_server: - raise RuntimeError("The API server must be enabled for external signals to work") - - self._loop = None - self._running = False - self._thread = None - self._queue = None - - self._main_task = None - self._sub_tasks = None - - self._message_handlers = { - LeaderMessageType.pairlist: self._rpc._handle_pairlist_message, - LeaderMessageType.analyzed_df: self._rpc._handle_analyzed_df_message, - LeaderMessageType.default: self._rpc._handle_default_message - } - - self.channel_manager = ChannelManager() - self.external_signal_config = config.get('external_signal', {}) - - # What the config should look like - # "external_signal": { - # "enabled": true, - # "mode": "follower", - # "leaders": [ - # { - # "url": "ws://localhost:8080/signals/ws", - # "api_token": "test" - # } - # ] - # } - - # "external_signal": { - # "enabled": true, - # "mode": "leader", - # "api_token": "test" - # } - - self.mode = ExternalSignalModeType[ - self.external_signal_config.get('mode', 'leader').lower() - ] - - self.leaders_list = self.external_signal_config.get('leaders', []) - self.push_throttle_secs = self.external_signal_config.get('push_throttle_secs', 0.1) - - self.reply_timeout = self.external_signal_config.get('follower_reply_timeout', 10) - self.ping_timeout = self.external_signal_config.get('follower_ping_timeout', 2) - self.sleep_time = self.external_signal_config.get('follower_sleep_time', 5) - - # Validate external_signal_config here? - - if self.mode == ExternalSignalModeType.follower and len(self.leaders_list) == 0: - raise ValueError("You must specify at least 1 leader in follower mode.") - - # This is only used by the leader, the followers use the tokens specified - # in each of the leaders - # If you do not specify an API key in the config, one will be randomly - # generated and logged on startup - default_api_key = secrets.token_urlsafe(16) - self.secret_api_key = self.external_signal_config.get('api_token', default_api_key) - - self.start() - - def is_leader(self): - """ - Leader flag - """ - return self.enabled() and self.mode == ExternalSignalModeType.leader - - def enabled(self): - """ - Enabled flag - """ - return self.external_signal_config.get('enabled', False) - - def num_leaders(self): - """ - The number of leaders we should be connected to - """ - return len(self.leaders_list) - - def start_threaded_loop(self): - """ - Start the main internal loop in another thread to run coroutines - """ - self._loop = asyncio.new_event_loop() - - if not self._thread: - self._thread = Thread(target=self._loop.run_forever) - self._thread.start() - self._running = True - else: - raise RuntimeError("A loop is already running") - - def submit_coroutine(self, coroutine: Coroutine): - """ - Submit a coroutine to the threaded loop - """ - if not self._running: - raise RuntimeError("Cannot schedule new futures after shutdown") - - if not self._loop or not self._loop.is_running(): - raise RuntimeError("Loop must be started before any function can" - " be submitted") - - return asyncio.run_coroutine_threadsafe(coroutine, self._loop) - - def start(self): - """ - Start the controller main loop - """ - self.start_threaded_loop() - self._main_task = self.submit_coroutine(self.main()) - - async def shutdown(self): - """ - Shutdown all tasks and close up - """ - logger.info("Stopping rpc.externalsignalcontroller") - - # Flip running flag - self._running = False - - # Cancel sub tasks - for task in self._sub_tasks: - task.cancel() - - # Then disconnect all channels - await self.channel_manager.disconnect_all() - - def cleanup(self) -> None: - """ - Cleanup pending module resources. - """ - if self._thread: - if self._loop.is_running(): - self._main_task.cancel() - self._thread.join() - - async def main(self): - """ - Main coro - - Start the loop based on what mode we're in - """ - try: - if self.mode == ExternalSignalModeType.leader: - logger.info("Starting rpc.externalsignalcontroller in Leader mode") - - await self.run_leader_mode() - elif self.mode == ExternalSignalModeType.follower: - logger.info("Starting rpc.externalsignalcontroller in Follower mode") - - await self.run_follower_mode() - - except asyncio.CancelledError: - # We're cancelled - await self.shutdown() - except Exception as e: - # Log the error - logger.error(f"Exception occurred in main task: {e}") - logger.exception(e) - finally: - # This coroutine is the last thing to be ended, so it should stop the loop - self._loop.stop() - - def log_api_token(self): - """ - Log the API token - """ - logger.info("-" * 15) - logger.info(f"API_KEY: {self.secret_api_key}") - logger.info("-" * 15) - - def send_msg(self, msg: MessageType) -> None: - """ - Support RPC calls - """ - if msg["type"] == RPCMessageType.EMIT_DATA: - message = msg.get("message") - if message: - self.send_message(message) - else: - logger.error(f"Message is empty! {msg}") - - def send_message(self, msg: MessageType) -> None: - """ - Broadcast message over all channels if there are any - """ - - if self.channel_manager.has_channels(): - self._send_message(msg) - else: - logger.debug("No listening followers, skipping...") - pass - - def _send_message(self, msg: MessageType): - """ - Add data to the internal queue to be broadcasted. This func will block - if the queue is full. This is meant to be called in the main thread. - """ - if self._queue: - queue = self._queue.sync_q - queue.put(msg) # This will block if the queue is full - else: - logger.warning("Can not send data, leader loop has not started yet!") - - async def send_initial_data(self, channel): - logger.info("Sending initial data through channel") - - data = self._rpc._initial_leader_data() - - for message in data: - await channel.send(message) - - async def _handle_leader_message(self, message: MessageType): - """ - Handle message received from a Leader - """ - type = message.get("data_type", LeaderMessageType.default) - data = message.get("data") - - handler: Callable = self._message_handlers[type] - handler(type, data) - - # ---------------------------------------------------------------------- - - async def run_leader_mode(self): - """ - Main leader coroutine - - This starts all of the leader coros and registers the endpoint on - the ApiServer - """ - self.register_leader_endpoint() - self.log_api_token() - - self._sub_tasks = [ - self._loop.create_task(self._broadcast_queue_data()) - ] - - return await asyncio.gather(*self._sub_tasks) - - async def run_follower_mode(self): - """ - Main follower coroutine - - This starts all of the follower connection coros - """ - - rpc_lock = asyncio.Lock() - - self._sub_tasks = [ - self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) - for leader in self.leaders_list - ] - - return await asyncio.gather(*self._sub_tasks) - - async def _broadcast_queue_data(self): - """ - Loop over queue data and broadcast it - """ - # Instantiate the queue in this coroutine so it's attached to our loop - self._queue = ThreadedQueue() - async_queue = self._queue.async_q - - try: - while self._running: - # Get data from queue - data = await async_queue.get() - - # Broadcast it to everyone - await self.channel_manager.broadcast(data) - - # Sleep - await asyncio.sleep(self.push_throttle_secs) - - except asyncio.CancelledError: - # Silently stop - pass - - async def get_api_token( - self, - websocket: FastAPIWebSocket, - token: Union[str, None] = None - ): - """ - Extract the API key from query param. Must match the - set secret_api_key or the websocket connection will be closed. - """ - if token == self.secret_api_key: - return token - else: - logger.info("Denying websocket request...") - await websocket.close(code=status.WS_1008_POLICY_VIOLATION) - - def register_leader_endpoint(self, path: str = "/signals/ws"): - """ - Attach and start the main leader loop to the ApiServer - - :param path: The endpoint path - """ - if not self.api_server: - raise RuntimeError("The leader needs the ApiServer to be active") - - # The endpoint function for running the main leader loop - @self.api_server.app.websocket(path) - async def leader_endpoint( - websocket: FastAPIWebSocket, - api_key: str = Depends(self.get_api_token) - ): - await self.leader_endpoint_loop(websocket) - - async def leader_endpoint_loop(self, websocket: FastAPIWebSocket): - """ - The WebSocket endpoint served by the ApiServer. This handles connections, - and adding them to the channel manager. - """ - try: - if is_websocket_alive(websocket): - logger.info(f"Follower connected - {websocket.client}") - channel = await self.channel_manager.on_connect(websocket) - - # Send initial data here - # Data is being broadcasted right away as soon as startup, - # we may not have to send initial data at all. Further testing - # required. - await self.send_initial_data(channel) - - # Keep connection open until explicitly closed, and sleep - try: - while not channel.is_closed(): - request = await channel.recv() - logger.info(f"Follower request - {request}") - - except WebSocketDisconnect: - # Handle client disconnects - logger.info(f"Follower disconnected - {websocket.client}") - await self.channel_manager.on_disconnect(websocket) - except Exception as e: - logger.info(f"Follower connection failed - {websocket.client}") - logger.exception(e) - # Handle cases like - - # RuntimeError('Cannot call "send" once a closed message has been sent') - await self.channel_manager.on_disconnect(websocket) - - except Exception: - logger.error(f"Failed to serve - {websocket.client}") - await self.channel_manager.on_disconnect(websocket) - - async def _handle_leader_connection(self, leader, lock): - """ - Given a leader, connect and wait on data. If connection is lost, - it will attempt to reconnect. - """ - try: - url, token = leader["url"], leader["api_token"] - websocket_url = f"{url}?token={token}" - - logger.info(f"Attempting to connect to Leader at: {url}") - while True: - try: - async with websockets.connect(websocket_url) as ws: - channel = await self.channel_manager.on_connect(ws) - logger.info(f"Connection to Leader at {url} successful") - while True: - try: - data = await asyncio.wait_for( - channel.recv(), - timeout=self.reply_timeout - ) - except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): - # We haven't received data yet. Check the connection and continue. - try: - # ping - ping = await channel.ping() - await asyncio.wait_for(ping, timeout=self.ping_timeout) - logger.debug(f"Connection to {url} still alive...") - continue - except Exception: - logger.info( - f"Ping error {url} - retrying in {self.sleep_time}s") - asyncio.sleep(self.sleep_time) - break - - async with lock: - # Acquire lock so only 1 coro handling at a time - # as we call the RPC module in the main thread - await self._handle_leader_message(data) - - except (socket.gaierror, ConnectionRefusedError): - logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - continue - except websockets.exceptions.InvalidStatusCode as e: - logger.error(f"Connection Refused - {e}") - await asyncio.sleep(self.sleep_time) - continue - - except asyncio.CancelledError: - pass +# """ +# This module manages replicate mode communication +# """ +# import asyncio +# import logging +# import secrets +# import socket +# from threading import Thread +# from typing import Any, Callable, Coroutine, Dict, Union +# +# import websockets +# from fastapi import Depends +# from fastapi import WebSocket as FastAPIWebSocket +# from fastapi import WebSocketDisconnect, status +# from janus import Queue as ThreadedQueue +# +# from freqtrade.enums import ExternalSignalModeType, LeaderMessageType, RPCMessageType +# from freqtrade.rpc import RPC, RPCHandler +# from freqtrade.rpc.external_signal.channel import ChannelManager +# from freqtrade.rpc.external_signal.types import MessageType +# from freqtrade.rpc.external_signal.utils import is_websocket_alive +# +# +# logger = logging.getLogger(__name__) +# +# +# class ExternalSignalController(RPCHandler): +# """ This class handles all websocket communication """ +# +# def __init__( +# self, +# rpc: RPC, +# config: Dict[str, Any], +# api_server: Union[Any, None] = None +# ) -> None: +# """ +# Init the ExternalSignalController class, and init the super class RPCHandler +# :param rpc: instance of RPC Helper class +# :param config: Configuration object +# :param api_server: The ApiServer object +# :return: None +# """ +# super().__init__(rpc, config) +# +# self.freqtrade = rpc._freqtrade +# self.api_server = api_server +# +# if not self.api_server: +# raise RuntimeError("The API server must be enabled for external signals to work") +# +# self._loop = None +# self._running = False +# self._thread = None +# self._queue = None +# +# self._main_task = None +# self._sub_tasks = None +# +# self._message_handlers = { +# LeaderMessageType.pairlist: self._rpc._handle_pairlist_message, +# LeaderMessageType.analyzed_df: self._rpc._handle_analyzed_df_message, +# LeaderMessageType.default: self._rpc._handle_default_message +# } +# +# self.channel_manager = ChannelManager() +# self.external_signal_config = config.get('external_signal', {}) +# +# # What the config should look like +# # "external_signal": { +# # "enabled": true, +# # "mode": "follower", +# # "leaders": [ +# # { +# # "url": "ws://localhost:8080/signals/ws", +# # "api_token": "test" +# # } +# # ] +# # } +# +# # "external_signal": { +# # "enabled": true, +# # "mode": "leader", +# # "api_token": "test" +# # } +# +# self.mode = ExternalSignalModeType[ +# self.external_signal_config.get('mode', 'leader').lower() +# ] +# +# self.leaders_list = self.external_signal_config.get('leaders', []) +# self.push_throttle_secs = self.external_signal_config.get('push_throttle_secs', 0.1) +# +# self.reply_timeout = self.external_signal_config.get('follower_reply_timeout', 10) +# self.ping_timeout = self.external_signal_config.get('follower_ping_timeout', 2) +# self.sleep_time = self.external_signal_config.get('follower_sleep_time', 5) +# +# # Validate external_signal_config here? +# +# if self.mode == ExternalSignalModeType.follower and len(self.leaders_list) == 0: +# raise ValueError("You must specify at least 1 leader in follower mode.") +# +# # This is only used by the leader, the followers use the tokens specified +# # in each of the leaders +# # If you do not specify an API key in the config, one will be randomly +# # generated and logged on startup +# default_api_key = secrets.token_urlsafe(16) +# self.secret_api_key = self.external_signal_config.get('api_token', default_api_key) +# +# self.start() +# +# def is_leader(self): +# """ +# Leader flag +# """ +# return self.enabled() and self.mode == ExternalSignalModeType.leader +# +# def enabled(self): +# """ +# Enabled flag +# """ +# return self.external_signal_config.get('enabled', False) +# +# def num_leaders(self): +# """ +# The number of leaders we should be connected to +# """ +# return len(self.leaders_list) +# +# def start_threaded_loop(self): +# """ +# Start the main internal loop in another thread to run coroutines +# """ +# self._loop = asyncio.new_event_loop() +# +# if not self._thread: +# self._thread = Thread(target=self._loop.run_forever) +# self._thread.start() +# self._running = True +# else: +# raise RuntimeError("A loop is already running") +# +# def submit_coroutine(self, coroutine: Coroutine): +# """ +# Submit a coroutine to the threaded loop +# """ +# if not self._running: +# raise RuntimeError("Cannot schedule new futures after shutdown") +# +# if not self._loop or not self._loop.is_running(): +# raise RuntimeError("Loop must be started before any function can" +# " be submitted") +# +# return asyncio.run_coroutine_threadsafe(coroutine, self._loop) +# +# def start(self): +# """ +# Start the controller main loop +# """ +# self.start_threaded_loop() +# self._main_task = self.submit_coroutine(self.main()) +# +# async def shutdown(self): +# """ +# Shutdown all tasks and close up +# """ +# logger.info("Stopping rpc.externalsignalcontroller") +# +# # Flip running flag +# self._running = False +# +# # Cancel sub tasks +# for task in self._sub_tasks: +# task.cancel() +# +# # Then disconnect all channels +# await self.channel_manager.disconnect_all() +# +# def cleanup(self) -> None: +# """ +# Cleanup pending module resources. +# """ +# if self._thread: +# if self._loop.is_running(): +# self._main_task.cancel() +# self._thread.join() +# +# async def main(self): +# """ +# Main coro +# +# Start the loop based on what mode we're in +# """ +# try: +# if self.mode == ExternalSignalModeType.leader: +# logger.info("Starting rpc.externalsignalcontroller in Leader mode") +# +# await self.run_leader_mode() +# elif self.mode == ExternalSignalModeType.follower: +# logger.info("Starting rpc.externalsignalcontroller in Follower mode") +# +# await self.run_follower_mode() +# +# except asyncio.CancelledError: +# # We're cancelled +# await self.shutdown() +# except Exception as e: +# # Log the error +# logger.error(f"Exception occurred in main task: {e}") +# logger.exception(e) +# finally: +# # This coroutine is the last thing to be ended, so it should stop the loop +# self._loop.stop() +# +# def log_api_token(self): +# """ +# Log the API token +# """ +# logger.info("-" * 15) +# logger.info(f"API_KEY: {self.secret_api_key}") +# logger.info("-" * 15) +# +# def send_msg(self, msg: MessageType) -> None: +# """ +# Support RPC calls +# """ +# if msg["type"] == RPCMessageType.EMIT_DATA: +# message = msg.get("message") +# if message: +# self.send_message(message) +# else: +# logger.error(f"Message is empty! {msg}") +# +# def send_message(self, msg: MessageType) -> None: +# """ +# Broadcast message over all channels if there are any +# """ +# +# if self.channel_manager.has_channels(): +# self._send_message(msg) +# else: +# logger.debug("No listening followers, skipping...") +# pass +# +# def _send_message(self, msg: MessageType): +# """ +# Add data to the internal queue to be broadcasted. This func will block +# if the queue is full. This is meant to be called in the main thread. +# """ +# if self._queue: +# queue = self._queue.sync_q +# queue.put(msg) # This will block if the queue is full +# else: +# logger.warning("Can not send data, leader loop has not started yet!") +# +# async def send_initial_data(self, channel): +# logger.info("Sending initial data through channel") +# +# data = self._rpc._initial_leader_data() +# +# for message in data: +# await channel.send(message) +# +# async def _handle_leader_message(self, message: MessageType): +# """ +# Handle message received from a Leader +# """ +# type = message.get("data_type", LeaderMessageType.default) +# data = message.get("data") +# +# handler: Callable = self._message_handlers[type] +# handler(type, data) +# +# # ---------------------------------------------------------------------- +# +# async def run_leader_mode(self): +# """ +# Main leader coroutine +# +# This starts all of the leader coros and registers the endpoint on +# the ApiServer +# """ +# self.register_leader_endpoint() +# self.log_api_token() +# +# self._sub_tasks = [ +# self._loop.create_task(self._broadcast_queue_data()) +# ] +# +# return await asyncio.gather(*self._sub_tasks) +# +# async def run_follower_mode(self): +# """ +# Main follower coroutine +# +# This starts all of the follower connection coros +# """ +# +# rpc_lock = asyncio.Lock() +# +# self._sub_tasks = [ +# self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) +# for leader in self.leaders_list +# ] +# +# return await asyncio.gather(*self._sub_tasks) +# +# async def _broadcast_queue_data(self): +# """ +# Loop over queue data and broadcast it +# """ +# # Instantiate the queue in this coroutine so it's attached to our loop +# self._queue = ThreadedQueue() +# async_queue = self._queue.async_q +# +# try: +# while self._running: +# # Get data from queue +# data = await async_queue.get() +# +# # Broadcast it to everyone +# await self.channel_manager.broadcast(data) +# +# # Sleep +# await asyncio.sleep(self.push_throttle_secs) +# +# except asyncio.CancelledError: +# # Silently stop +# pass +# +# async def get_api_token( +# self, +# websocket: FastAPIWebSocket, +# token: Union[str, None] = None +# ): +# """ +# Extract the API key from query param. Must match the +# set secret_api_key or the websocket connection will be closed. +# """ +# if token == self.secret_api_key: +# return token +# else: +# logger.info("Denying websocket request...") +# await websocket.close(code=status.WS_1008_POLICY_VIOLATION) +# +# def register_leader_endpoint(self, path: str = "/signals/ws"): +# """ +# Attach and start the main leader loop to the ApiServer +# +# :param path: The endpoint path +# """ +# if not self.api_server: +# raise RuntimeError("The leader needs the ApiServer to be active") +# +# # The endpoint function for running the main leader loop +# @self.api_server.app.websocket(path) +# async def leader_endpoint( +# websocket: FastAPIWebSocket, +# api_key: str = Depends(self.get_api_token) +# ): +# await self.leader_endpoint_loop(websocket) +# +# async def leader_endpoint_loop(self, websocket: FastAPIWebSocket): +# """ +# The WebSocket endpoint served by the ApiServer. This handles connections, +# and adding them to the channel manager. +# """ +# try: +# if is_websocket_alive(websocket): +# logger.info(f"Follower connected - {websocket.client}") +# channel = await self.channel_manager.on_connect(websocket) +# +# # Send initial data here +# # Data is being broadcasted right away as soon as startup, +# # we may not have to send initial data at all. Further testing +# # required. +# await self.send_initial_data(channel) +# +# # Keep connection open until explicitly closed, and sleep +# try: +# while not channel.is_closed(): +# request = await channel.recv() +# logger.info(f"Follower request - {request}") +# +# except WebSocketDisconnect: +# # Handle client disconnects +# logger.info(f"Follower disconnected - {websocket.client}") +# await self.channel_manager.on_disconnect(websocket) +# except Exception as e: +# logger.info(f"Follower connection failed - {websocket.client}") +# logger.exception(e) +# # Handle cases like - +# # RuntimeError('Cannot call "send" once a closed message has been sent') +# await self.channel_manager.on_disconnect(websocket) +# +# except Exception: +# logger.error(f"Failed to serve - {websocket.client}") +# await self.channel_manager.on_disconnect(websocket) +# +# async def _handle_leader_connection(self, leader, lock): +# """ +# Given a leader, connect and wait on data. If connection is lost, +# it will attempt to reconnect. +# """ +# try: +# url, token = leader["url"], leader["api_token"] +# websocket_url = f"{url}?token={token}" +# +# logger.info(f"Attempting to connect to Leader at: {url}") +# while True: +# try: +# async with websockets.connect(websocket_url) as ws: +# channel = await self.channel_manager.on_connect(ws) +# logger.info(f"Connection to Leader at {url} successful") +# while True: +# try: +# data = await asyncio.wait_for( +# channel.recv(), +# timeout=self.reply_timeout +# ) +# except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): +# # We haven't received data yet. Check the connection and continue. +# try: +# # ping +# ping = await channel.ping() +# await asyncio.wait_for(ping, timeout=self.ping_timeout) +# logger.debug(f"Connection to {url} still alive...") +# continue +# except Exception: +# logger.info( +# f"Ping error {url} - retrying in {self.sleep_time}s") +# asyncio.sleep(self.sleep_time) +# break +# +# async with lock: +# # Acquire lock so only 1 coro handling at a time +# # as we call the RPC module in the main thread +# await self._handle_leader_message(data) +# +# except (socket.gaierror, ConnectionRefusedError): +# logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") +# await asyncio.sleep(self.sleep_time) +# continue +# except websockets.exceptions.InvalidStatusCode as e: +# logger.error(f"Connection Refused - {e}") +# await asyncio.sleep(self.sleep_time) +# continue +# +# except asyncio.CancelledError: +# pass diff --git a/freqtrade/rpc/external_signal/proxy.py b/freqtrade/rpc/external_signal/proxy.py index 36ff4a74e..df2a07da0 100644 --- a/freqtrade/rpc/external_signal/proxy.py +++ b/freqtrade/rpc/external_signal/proxy.py @@ -1,61 +1,61 @@ -from typing import Union - -from fastapi import WebSocket as FastAPIWebSocket -from websockets import WebSocketClientProtocol as WebSocket - -from freqtrade.rpc.external_signal.types import WebSocketType - - -class WebSocketProxy: - """ - WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol - under the same API - """ - - def __init__(self, websocket: WebSocketType): - self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket - - async def send(self, data): - """ - Send data on the wrapped websocket - """ - if isinstance(data, str): - data = data.encode() - - if hasattr(self._websocket, "send_bytes"): - await self._websocket.send_bytes(data) - else: - await self._websocket.send(data) - - async def recv(self): - """ - Receive data on the wrapped websocket - """ - if hasattr(self._websocket, "receive_bytes"): - return await self._websocket.receive_bytes() - else: - return await self._websocket.recv() - - async def ping(self): - """ - Ping the websocket, not supported by FastAPI WebSockets - """ - if hasattr(self._websocket, "ping"): - return await self._websocket.ping() - return False - - async def close(self, code: int = 1000): - """ - Close the websocket connection, only supported by FastAPI WebSockets - """ - if hasattr(self._websocket, "close"): - return await self._websocket.close(code) - pass - - async def accept(self): - """ - Accept the WebSocket connection, only support by FastAPI WebSockets - """ - if hasattr(self._websocket, "accept"): - return await self._websocket.accept() - pass +# from typing import Union +# +# from fastapi import WebSocket as FastAPIWebSocket +# from websockets import WebSocketClientProtocol as WebSocket +# +# from freqtrade.rpc.external_signal.types import WebSocketType +# +# +# class WebSocketProxy: +# """ +# WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol +# under the same API +# """ +# +# def __init__(self, websocket: WebSocketType): +# self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket +# +# async def send(self, data): +# """ +# Send data on the wrapped websocket +# """ +# if isinstance(data, str): +# data = data.encode() +# +# if hasattr(self._websocket, "send_bytes"): +# await self._websocket.send_bytes(data) +# else: +# await self._websocket.send(data) +# +# async def recv(self): +# """ +# Receive data on the wrapped websocket +# """ +# if hasattr(self._websocket, "receive_bytes"): +# return await self._websocket.receive_bytes() +# else: +# return await self._websocket.recv() +# +# async def ping(self): +# """ +# Ping the websocket, not supported by FastAPI WebSockets +# """ +# if hasattr(self._websocket, "ping"): +# return await self._websocket.ping() +# return False +# +# async def close(self, code: int = 1000): +# """ +# Close the websocket connection, only supported by FastAPI WebSockets +# """ +# if hasattr(self._websocket, "close"): +# return await self._websocket.close(code) +# pass +# +# async def accept(self): +# """ +# Accept the WebSocket connection, only support by FastAPI WebSockets +# """ +# if hasattr(self._websocket, "accept"): +# return await self._websocket.accept() +# pass diff --git a/freqtrade/rpc/external_signal/serializer.py b/freqtrade/rpc/external_signal/serializer.py index 2a0f53037..a23469ef4 100644 --- a/freqtrade/rpc/external_signal/serializer.py +++ b/freqtrade/rpc/external_signal/serializer.py @@ -1,65 +1,65 @@ -import json -import logging -from abc import ABC, abstractmethod - -import msgpack -import orjson - -from freqtrade.rpc.external_signal.proxy import WebSocketProxy - - -logger = logging.getLogger(__name__) - - -class WebSocketSerializer(ABC): - def __init__(self, websocket: WebSocketProxy): - self._websocket: WebSocketProxy = websocket - - @abstractmethod - def _serialize(self, data): - raise NotImplementedError() - - @abstractmethod - def _deserialize(self, data): - raise NotImplementedError() - - async def send(self, data: bytes): - await self._websocket.send(self._serialize(data)) - - async def recv(self) -> bytes: - data = await self._websocket.recv() - - return self._deserialize(data) - - async def close(self, code: int = 1000): - await self._websocket.close(code) - -# Going to explore using MsgPack as the serialization, -# as that might be the best method for sending pandas -# dataframes over the wire - - -class JSONWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data): - return json.dumps(data) - - def _deserialize(self, data): - return json.loads(data) - - -class ORJSONWebSocketSerializer(WebSocketSerializer): - ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY - - def _serialize(self, data): - return orjson.dumps(data, option=self.ORJSON_OPTIONS) - - def _deserialize(self, data): - return orjson.loads(data, option=self.ORJSON_OPTIONS) - - -class MsgPackWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data): - return msgpack.packb(data, use_bin_type=True) - - def _deserialize(self, data): - return msgpack.unpackb(data, raw=False) +# import json +# import logging +# from abc import ABC, abstractmethod +# +# import msgpack +# import orjson +# +# from freqtrade.rpc.external_signal.proxy import WebSocketProxy +# +# +# logger = logging.getLogger(__name__) +# +# +# class WebSocketSerializer(ABC): +# def __init__(self, websocket: WebSocketProxy): +# self._websocket: WebSocketProxy = websocket +# +# @abstractmethod +# def _serialize(self, data): +# raise NotImplementedError() +# +# @abstractmethod +# def _deserialize(self, data): +# raise NotImplementedError() +# +# async def send(self, data: bytes): +# await self._websocket.send(self._serialize(data)) +# +# async def recv(self) -> bytes: +# data = await self._websocket.recv() +# +# return self._deserialize(data) +# +# async def close(self, code: int = 1000): +# await self._websocket.close(code) +# +# # Going to explore using MsgPack as the serialization, +# # as that might be the best method for sending pandas +# # dataframes over the wire +# +# +# class JSONWebSocketSerializer(WebSocketSerializer): +# def _serialize(self, data): +# return json.dumps(data) +# +# def _deserialize(self, data): +# return json.loads(data) +# +# +# class ORJSONWebSocketSerializer(WebSocketSerializer): +# ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY +# +# def _serialize(self, data): +# return orjson.dumps(data, option=self.ORJSON_OPTIONS) +# +# def _deserialize(self, data): +# return orjson.loads(data, option=self.ORJSON_OPTIONS) +# +# +# class MsgPackWebSocketSerializer(WebSocketSerializer): +# def _serialize(self, data): +# return msgpack.packb(data, use_bin_type=True) +# +# def _deserialize(self, data): +# return msgpack.unpackb(data, raw=False) diff --git a/freqtrade/rpc/external_signal/types.py b/freqtrade/rpc/external_signal/types.py index 814fe6649..38e43f667 100644 --- a/freqtrade/rpc/external_signal/types.py +++ b/freqtrade/rpc/external_signal/types.py @@ -1,8 +1,8 @@ -from typing import Any, Dict, TypeVar - -from fastapi import WebSocket as FastAPIWebSocket -from websockets import WebSocketClientProtocol as WebSocket - - -WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) -MessageType = Dict[str, Any] +# from typing import Any, Dict, TypeVar +# +# from fastapi import WebSocket as FastAPIWebSocket +# from websockets import WebSocketClientProtocol as WebSocket +# +# +# WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) +# MessageType = Dict[str, Any] diff --git a/freqtrade/rpc/external_signal/utils.py b/freqtrade/rpc/external_signal/utils.py index e5469dce3..72c8d2ef8 100644 --- a/freqtrade/rpc/external_signal/utils.py +++ b/freqtrade/rpc/external_signal/utils.py @@ -1,22 +1,10 @@ -from pandas import DataFrame -from starlette.websockets import WebSocket, WebSocketState - -from freqtrade.enums.signaltype import SignalTagType, SignalType - - -async def is_websocket_alive(ws: WebSocket) -> bool: - if ( - ws.application_state == WebSocketState.CONNECTED and - ws.client_state == WebSocketState.CONNECTED - ): - return True - return False - - -def remove_entry_exit_signals(dataframe: DataFrame): - dataframe[SignalType.ENTER_LONG.value] = 0 - dataframe[SignalType.EXIT_LONG.value] = 0 - dataframe[SignalType.ENTER_SHORT.value] = 0 - dataframe[SignalType.EXIT_SHORT.value] = 0 - dataframe[SignalTagType.ENTER_TAG.value] = None - dataframe[SignalTagType.EXIT_TAG.value] = None +# from starlette.websockets import WebSocket, WebSocketState +# +# +# async def is_websocket_alive(ws: WebSocket) -> bool: +# if ( +# ws.application_state == WebSocketState.CONNECTED and +# ws.client_state == WebSocketState.CONNECTED +# ): +# return True +# return False diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 82d50f33c..3c7558158 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -19,13 +19,12 @@ from freqtrade.configuration.timerange import TimeRange from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT from freqtrade.data.history import load_data from freqtrade.data.metrics import calculate_max_drawdown -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, LeaderMessageType, - SignalDirection, State, TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State, + TradingMode) from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler -from freqtrade.misc import (decimals_per_coin, json_to_dataframe, remove_entry_exit_signals, - shorten_date) +from freqtrade.misc import decimals_per_coin, shorten_date from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1090,65 +1089,65 @@ class RPC: 'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT), 'last_process_ts': int(last_p.timestamp()), } - - # ------------------------------ EXTERNAL SIGNALS ----------------------- - - def _initial_leader_data(self): - # We create a list of Messages to send to the follower on connect - data = [] - - # Send Pairlist data - data.append({ - "data_type": LeaderMessageType.pairlist, - "data": self._freqtrade.pairlists._whitelist - }) - - return data - - def _handle_pairlist_message(self, type, data): - """ - Handles the emitted pairlists from the Leaders - - :param type: The data_type of the data - :param data: The data - """ - pairlist = data - - logger.debug(f"Handling Pairlist message: {pairlist}") - - external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] - external_pairlist.add_pairlist_data(pairlist) - - def _handle_analyzed_df_message(self, type, data): - """ - Handles the analyzed dataframes from the Leaders - - :param type: The data_type of the data - :param data: The data - """ - key, value = data["key"], data["value"] - pair, timeframe, candle_type = key - - # Skip any pairs that we don't have in the pairlist? - # leader_pairlist = self._freqtrade.pairlists._whitelist - # if pair not in leader_pairlist: - # return - - dataframe = json_to_dataframe(value) - - if self._config.get('external_signal', {}).get('remove_signals_analyzed_df', False): - dataframe = remove_entry_exit_signals(dataframe) - - logger.debug(f"Handling analyzed dataframe for {pair}") - logger.debug(dataframe.tail()) - - # Add the dataframe to the dataprovider - dataprovider = self._freqtrade.dataprovider - dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) - - def _handle_default_message(self, type, data): - """ - Default leader message handler, just logs it. We should never have to - run this unless the leader sends us some weird message. - """ - logger.debug(f"Received message from Leader of type {type}: {data}") + # + # # ------------------------------ EXTERNAL SIGNALS ----------------------- + # + # def _initial_leader_data(self): + # # We create a list of Messages to send to the follower on connect + # data = [] + # + # # Send Pairlist data + # data.append({ + # "data_type": LeaderMessageType.pairlist, + # "data": self._freqtrade.pairlists._whitelist + # }) + # + # return data + # + # def _handle_pairlist_message(self, type, data): + # """ + # Handles the emitted pairlists from the Leaders + # + # :param type: The data_type of the data + # :param data: The data + # """ + # pairlist = data + # + # logger.debug(f"Handling Pairlist message: {pairlist}") + # + # external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] + # external_pairlist.add_pairlist_data(pairlist) + # + # def _handle_analyzed_df_message(self, type, data): + # """ + # Handles the analyzed dataframes from the Leaders + # + # :param type: The data_type of the data + # :param data: The data + # """ + # key, value = data["key"], data["value"] + # pair, timeframe, candle_type = key + # + # # Skip any pairs that we don't have in the pairlist? + # # leader_pairlist = self._freqtrade.pairlists._whitelist + # # if pair not in leader_pairlist: + # # return + # + # dataframe = json_to_dataframe(value) + # + # if self._config.get('external_signal', {}).get('remove_signals_analyzed_df', False): + # dataframe = remove_entry_exit_signals(dataframe) + # + # logger.debug(f"Handling analyzed dataframe for {pair}") + # logger.debug(dataframe.tail()) + # + # # Add the dataframe to the dataprovider + # dataprovider = self._freqtrade.dataprovider + # dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) + # + # def _handle_default_message(self, type, data): + # """ + # Default leader message handler, just logs it. We should never have to + # run this unless the leader sends us some weird message. + # """ + # logger.debug(f"Received message from Leader of type {type}: {data}") diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 11e21da6f..c5e93e3b4 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -51,14 +51,14 @@ class RPCManager: # Enable External Signals mode # For this to be enabled, the API server must also be enabled - if config.get('external_signal', {}).get('enabled', False): - logger.info('Enabling RPC.ExternalSignalController') - from freqtrade.rpc.external_signal import ExternalSignalController - external_signals = ExternalSignalController(self._rpc, config, apiserver) - self.registered_modules.append(external_signals) - - # Attach the controller to FreqTrade - freqtrade.external_signal_controller = external_signals + # if config.get('external_signal', {}).get('enabled', False): + # logger.info('Enabling RPC.ExternalSignalController') + # from freqtrade.rpc.external_signal import ExternalSignalController + # external_signals = ExternalSignalController(self._rpc, config, apiserver) + # self.registered_modules.append(external_signals) + # + # # Attach the controller to FreqTrade + # freqtrade.external_signal_controller = external_signals def cleanup(self) -> None: """ Stops all enabled rpc modules """ @@ -78,8 +78,7 @@ class RPCManager: 'status': 'stopping bot' } """ - if msg.get("type") != RPCMessageType.EMIT_DATA: - logger.info('Sending rpc message: %s', msg) + logger.info('Sending rpc message: %s', msg) if 'pair' in msg: msg.update({ 'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair']) @@ -138,12 +137,3 @@ class RPCManager: 'type': RPCMessageType.STARTUP, 'status': f'Using Protections: \n{prots}' }) - - def emit_data(self, data: Dict[str, Any]): - """ - Send a message via RPC with type RPCMessageType.EMIT_DATA - """ - self.send_msg({ - "type": RPCMessageType.EMIT_DATA, - "message": data - }) diff --git a/scripts/test_ws_client.py b/scripts/test_ws_client.py new file mode 100644 index 000000000..caa495a19 --- /dev/null +++ b/scripts/test_ws_client.py @@ -0,0 +1,58 @@ +import asyncio +import logging +import socket + +import websockets + + +logging.basicConfig(level=logging.DEBUG) +logger = logging.getLogger(__name__) + + +async def _client(): + try: + while True: + try: + url = "ws://localhost:8080/api/v1/message/ws?token=testtoken" + async with websockets.connect(url) as ws: + logger.info("Connection successful") + while True: + try: + data = await asyncio.wait_for( + ws.recv(), + timeout=5 + ) + logger.info(f"Data received - {data}") + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Check the connection and continue. + try: + # ping + ping = await ws.ping() + await asyncio.wait_for(ping, timeout=2) + logger.debug(f"Connection to {url} still alive...") + continue + except Exception: + logger.info( + f"Ping error {url} - retrying in 5s") + asyncio.sleep(2) + break + + except (socket.gaierror, ConnectionRefusedError): + logger.info("Connection Refused - retrying connection in 5s") + await asyncio.sleep(2) + continue + except websockets.exceptions.InvalidStatusCode as e: + logger.error(f"Connection Refused - {e}") + await asyncio.sleep(2) + continue + + except (asyncio.CancelledError, KeyboardInterrupt): + pass + + +def main(): + asyncio.run(_client()) + + +if __name__ == "__main__": + main() From 71846ecbf22188396ab9275b4da8cda4fa345a86 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 29 Aug 2022 21:51:10 +0200 Subject: [PATCH 097/592] Partially revert prior commit, use correct exchange class --- tests/exchange/test_exchange.py | 28 +++++++++++++--------------- 1 file changed, 13 insertions(+), 15 deletions(-) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 51890de79..800aa5381 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -5023,7 +5023,7 @@ def test_get_liquidation_price1(mocker, default_conf): ) -@pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) +@pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05]) @pytest.mark.parametrize( "is_short,trading_mode,exchange_name,margin_mode,leverage,open_rate,amount,expected_liq", [ (False, 'spot', 'binance', '', 5.0, 10.0, 1.0, None), @@ -5043,17 +5043,15 @@ def test_get_liquidation_price1(mocker, default_conf): (False, 'futures', 'binance', 'isolated', 3, 10, 1.0, 6.723905723905723), (False, 'futures', 'binance', 'isolated', 5, 10, 0.6, 8.063973063973064), # Gateio/okx, short - (True, 'futures', 'gateio', 'isolated', 5, 10, 1.0, 11.89108910891089), - (True, 'futures', 'gateio', 'isolated', 5, 10, 2.0, 11.886138613861386), - (True, 'futures', 'gateio', 'isolated', 3, 10, 1.0, 13.211221122112212), - (True, 'futures', 'gateio', 'isolated', 5, 8, 1.0, 9.514851485148514), + (True, 'futures', 'gateio', 'isolated', 5, 10, 1.0, 11.87413417771621), + (True, 'futures', 'gateio', 'isolated', 5, 10, 2.0, 11.87413417771621), + (True, 'futures', 'gateio', 'isolated', 3, 10, 1.0, 13.193482419684678), + (True, 'futures', 'gateio', 'isolated', 5, 8, 1.0, 9.499307342172967), + (True, 'futures', 'okx', 'isolated', 3, 10, 1.0, 13.193482419684678), # Gateio/okx, long - (False, 'futures', 'gateio', 'isolated', 5.0, 10.0, 1.0, 8.070707070707071), - (False, 'futures', 'gateio', 'isolated', 3.0, 10.0, 1.0, 6.723905723905723), - (True, 'futures', 'okx', 'isolated', 5, 8, 1.0, 9.514851485148514), - (False, 'futures', 'okx', 'isolated', 3.0, 10.0, 1.0, 6.723905723905723), - # (True, 'futures', 'okx', 'isolated', 11.87413417771621), - # (False, 'futures', 'okx', 'isolated', 8.085708510208207), + (False, 'futures', 'gateio', 'isolated', 5.0, 10.0, 1.0, 8.085708510208207), + (False, 'futures', 'gateio', 'isolated', 3.0, 10.0, 1.0, 6.738090425173506), + (False, 'futures', 'okx', 'isolated', 3.0, 10.0, 1.0, 6.738090425173506), ] ) def test_get_liquidation_price( @@ -5126,7 +5124,7 @@ def test_get_liquidation_price( default_conf_usdt['exchange']['name'] = exchange_name default_conf_usdt['margin_mode'] = margin_mode mocker.patch('freqtrade.exchange.Gateio.validate_ordertypes') - exchange = get_patched_exchange(mocker, default_conf_usdt) + exchange = get_patched_exchange(mocker, default_conf_usdt, id=exchange_name) exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(0.01, 0.01)) exchange.name = exchange_name @@ -5137,8 +5135,8 @@ def test_get_liquidation_price( pair='ETH/USDT:USDT', open_rate=open_rate, amount=amount, - stake_amount=(amount * open_rate) / leverage, - wallet_balance=(amount * open_rate) / leverage, + stake_amount=amount * open_rate / leverage, + wallet_balance=amount * open_rate / leverage, # leverage=leverage, is_short=is_short, ) @@ -5147,7 +5145,7 @@ def test_get_liquidation_price( else: buffer_amount = liquidation_buffer * abs(open_rate - expected_liq) expected_liq = expected_liq - buffer_amount if is_short else expected_liq + buffer_amount - assert pytest.approx(expected_liq) == liq + assert isclose(expected_liq, liq) @pytest.mark.parametrize('contract_size,order_amount', [ From 47f7c384fbea381926a3b9aad0c6c99935b5e8d2 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 29 Aug 2022 15:48:29 -0600 Subject: [PATCH 098/592] consumer subscriptions, fix serializer bug --- freqtrade/rpc/api_server/api_ws.py | 11 +++++++- freqtrade/rpc/api_server/ws/__init__.py | 0 freqtrade/rpc/api_server/ws/channel.py | 31 ++++++++++++++++++++--- freqtrade/rpc/api_server/ws/serializer.py | 2 +- scripts/test_ws_client.py | 15 ++++++++--- 5 files changed, 50 insertions(+), 9 deletions(-) create mode 100644 freqtrade/rpc/api_server/ws/__init__.py diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 464ea22b2..405beed79 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -2,6 +2,7 @@ import logging from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect +from freqtrade.enums import RPCMessageType from freqtrade.rpc.api_server.deps import get_channel_manager from freqtrade.rpc.api_server.ws.utils import is_websocket_alive @@ -34,7 +35,15 @@ async def message_endpoint( # be a list of topics to subscribe too. List[str] # Maybe allow the consumer to update the topics subscribed # during runtime? - logger.info(f"Consumer request - {request}") + + # If the request isn't a list then skip it + if not isinstance(request, list): + continue + + # Check if all topics listed are an RPCMessageType + if all([any(x.value == topic for x in RPCMessageType) for topic in request]): + logger.debug(f"{ws.client} subscribed to topics: {request}") + channel.set_subscriptions(request) except WebSocketDisconnect: # Handle client disconnects diff --git a/freqtrade/rpc/api_server/ws/__init__.py b/freqtrade/rpc/api_server/ws/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 486e8657b..f24713a77 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -1,6 +1,6 @@ import logging from threading import RLock -from typing import Type +from typing import List, Type from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy from freqtrade.rpc.api_server.ws.serializer import ORJSONWebSocketSerializer, WebSocketSerializer @@ -25,6 +25,8 @@ class WebSocketChannel: # The Serializing class for the WebSocket object self._serializer_cls = serializer_cls + self._subscriptions: List[str] = [] + # Internal event to signify a closed websocket self._closed = False @@ -57,9 +59,28 @@ class WebSocketChannel: self._closed = True - def is_closed(self): + def is_closed(self) -> bool: + """ + Closed flag + """ return self._closed + def set_subscriptions(self, subscriptions: List[str] = []) -> None: + """ + Set which subscriptions this channel is subscribed to + + :param subscriptions: List of subscriptions, List[str] + """ + self._subscriptions = subscriptions + + def subscribed_to(self, message_type: str) -> bool: + """ + Check if this channel is subscribed to the message_type + + :param message_type: The message type to check + """ + return message_type in self._subscriptions + class ChannelManager: def __init__(self): @@ -120,10 +141,12 @@ class ChannelManager: :param data: The data to send """ with self._lock: - logger.debug(f"Broadcasting data: {data}") + message_type = data.get('type') + logger.debug(f"Broadcasting data: {message_type} - {data}") for websocket, channel in self.channels.items(): try: - await channel.send(data) + if channel.subscribed_to(message_type): + await channel.send(data) except RuntimeError: # Handle cannot send after close cases await self.on_disconnect(websocket) diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index 40cbbfad7..ae2857f0b 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -54,7 +54,7 @@ class ORJSONWebSocketSerializer(WebSocketSerializer): return orjson.dumps(data, option=self.ORJSON_OPTIONS) def _deserialize(self, data): - return orjson.loads(data, option=self.ORJSON_OPTIONS) + return orjson.loads(data) class MsgPackWebSocketSerializer(WebSocketSerializer): diff --git a/scripts/test_ws_client.py b/scripts/test_ws_client.py index caa495a19..2c64ae867 100644 --- a/scripts/test_ws_client.py +++ b/scripts/test_ws_client.py @@ -4,22 +4,31 @@ import socket import websockets +from freqtrade.enums import RPCMessageType +from freqtrade.rpc.api_server.ws.channel import WebSocketChannel + logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) async def _client(): + subscribe_topics = [RPCMessageType.WHITELIST] try: while True: try: url = "ws://localhost:8080/api/v1/message/ws?token=testtoken" async with websockets.connect(url) as ws: + channel = WebSocketChannel(ws) + logger.info("Connection successful") + # Tell the producer we only want these topics + await channel.send(subscribe_topics) + while True: try: data = await asyncio.wait_for( - ws.recv(), + channel.recv(), timeout=5 ) logger.info(f"Data received - {data}") @@ -27,14 +36,14 @@ async def _client(): # We haven't received data yet. Check the connection and continue. try: # ping - ping = await ws.ping() + ping = await channel.ping() await asyncio.wait_for(ping, timeout=2) logger.debug(f"Connection to {url} still alive...") continue except Exception: logger.info( f"Ping error {url} - retrying in 5s") - asyncio.sleep(2) + await asyncio.sleep(2) break except (socket.gaierror, ConnectionRefusedError): From 50e280866757e39dd4d229fd3f5f32e9f9e0ff25 Mon Sep 17 00:00:00 2001 From: th0rntwig <107926911+th0rntwig@users.noreply.github.com> Date: Tue, 30 Aug 2022 12:54:39 +0200 Subject: [PATCH 099/592] Fix bug in DI (#7321) --- freqtrade/freqai/data_kitchen.py | 15 +++++---------- 1 file changed, 5 insertions(+), 10 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 5091073aa..763a07375 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -529,7 +529,6 @@ class FreqaiDataKitchen: "outlier_protection_percentage", 30) outlier_pct = (dropped_pts.sum() / len(dropped_pts)) * 100 if outlier_pct >= outlier_protection_pct: - self.svm_model = None return outlier_pct else: return 0.0 @@ -579,6 +578,7 @@ class FreqaiDataKitchen: f"SVM detected {outlier_pct:.2f}% of the points as outliers. " f"Keeping original dataset." ) + self.svm_model = None return self.data_dictionary["train_features"] = self.data_dictionary["train_features"][ @@ -633,6 +633,8 @@ class FreqaiDataKitchen: from math import cos, sin if predict: + if not self.data['DBSCAN_eps']: + return train_ft_df = self.data_dictionary['train_features'] pred_ft_df = self.data_dictionary['prediction_features'] num_preds = len(pred_ft_df) @@ -702,6 +704,7 @@ class FreqaiDataKitchen: f"DBSCAN detected {outlier_pct:.2f}% of the points as outliers. " f"Keeping original dataset." ) + self.data['DBSCAN_eps'] = 0 return self.data_dictionary['train_features'] = self.data_dictionary['train_features'][ @@ -759,18 +762,10 @@ class FreqaiDataKitchen: 0, ) - outlier_pct = self.get_outlier_percentage(1 - do_predict) - if outlier_pct: - logger.warning( - f"DI detected {outlier_pct:.2f}% of the points as outliers. " - f"Keeping original dataset." - ) - return - if (len(do_predict) - do_predict.sum()) > 0: logger.info( f"DI tossed {len(do_predict) - do_predict.sum()} predictions for " - "being too far from training data" + "being too far from training data." ) self.do_predict += do_predict From d3cb211283ced68d082cfdbdac12f3d2ab90d63b Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Thu, 18 Aug 2022 14:44:49 +0200 Subject: [PATCH 100/592] Add inlier metric computation --- freqtrade/freqai/data_kitchen.py | 74 ++++++++++++++++++++++++++++++++ 1 file changed, 74 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 763a07375..62e353949 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -723,6 +723,80 @@ class FreqaiDataKitchen: ) return + + def compute_inlier_metric(self) -> None: + """ + + Compute inlier metric from backwards distance distributions. + This metric defines how well features from a timepoint fit + into previous timepoints. + """ + + import scipy.stats as ss + + nmb_previous_points = self.data['InlierMetric_nmb_points'] + weibull_percentile = self.data['InlierMetric_weib_perc'] + + train_ft_df = self.data_dictionary['train_features'] + train_ft_df_reindexed = train_ft_df.reindex( + index=np.flip(train_ft_df.index) + ) + + pairwise = pd.DataFrame( + np.triu( + pairwise_distances(train_ft_df_reindexed, n_jobs=self.thread_count) + ), + columns=train_ft_df_reindexed.index, + index=train_ft_df_reindexed.index + ) + pairwise = pairwise.round(5) + + column_labels = [ + '{}{}'.format('d', i) for i in range(1, nmb_previous_points+1) + ] + distances = pd.DataFrame( + columns=column_labels, index=train_ft_df.index + ) + for index in train_ft_df.index[nmb_previous_points]: + current_row = pairwise.loc[[index]] + current_row_no_zeros = current_row.loc[ + :, (current_row!=0).any(axis=0) + ] + distances.loc[[index]] = current_row_no_zeros.iloc[ + :, :nmb_previous_points + ] + distances = distances.replace([np.inf, -np.inf], np.nan) + drop_index = pd.isnull(distances).any(1) + distances = distances[drop_index==0] + + inliers = pd.DataFrame(index=distances.index) + for key in distances.keys(): + current_distances = distances[key].dropna() + fit_params = ss.weibull_min.fit(current_distances) + cutoff = ss.weibull_min.ppf(weibull_percentile, *fit_params) + is_inlier = np.where( + current_distances<=cutoff, 1, 0 + ) + df_inlier = pd.DataFrame( + {key+'_IsInlier':is_inlier}, index=distances.index + ) + inliers = pd.concat( + [inliers, df_inlier], axis=1 + ) + + self.data_dictionary['train_features'] = pd.DataFrame( + data=inliers.sum(axis=1)/nmb_previous_points, + columns=['inlier_metric'], + index = train_ft_df.index + ) + + percent_outliers = np.round( + 100*(1-self.data_dictionary['iniler_metric'].sum()/ + len(train_ft_df.index)), 2 + ) + logger.info('{percent_outliers}%% of data points were identified as outliers') + + return None def find_features(self, dataframe: DataFrame) -> None: """ From b11742a4c5a7130d7aabc0d20c343372f7911379 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Thu, 18 Aug 2022 19:15:29 +0200 Subject: [PATCH 101/592] integrate inlier metric function --- freqtrade/freqai/data_kitchen.py | 85 ++++++++++++++++++---------- freqtrade/freqai/freqai_interface.py | 36 ++++++++---- 2 files changed, 79 insertions(+), 42 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 62e353949..80919626c 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -723,81 +723,104 @@ class FreqaiDataKitchen: ) return - - def compute_inlier_metric(self) -> None: + + def compute_inlier_metric(self, set_='train') -> None: """ - - Compute inlier metric from backwards distance distributions. - This metric defines how well features from a timepoint fit + + Compute inlier metric from backwards distance distributions. + This metric defines how well features from a timepoint fit into previous timepoints. """ import scipy.stats as ss - - nmb_previous_points = self.data['InlierMetric_nmb_points'] - weibull_percentile = self.data['InlierMetric_weib_perc'] - train_ft_df = self.data_dictionary['train_features'] - train_ft_df_reindexed = train_ft_df.reindex( - index=np.flip(train_ft_df.index) + no_prev_pts = self.freqai_config["feature_parameters"]["inlier_metric_window"] + weib_pct = self.freqai_config["feature_parameters"]["inlier_metric_weibull_cutoff"] + + if set_ == 'train': + compute_df = copy.deepcopy(self.data_dictionary['train_features']) + elif set_ == 'test': + compute_df = copy.deepcopy(self.data_dictionary['test_features']) + else: + compute_df = copy.deepcopy(self.data_dictionary['prediction_features']) + + compute_df_reindexed = compute_df.reindex( + index=np.flip(compute_df.index) ) pairwise = pd.DataFrame( np.triu( - pairwise_distances(train_ft_df_reindexed, n_jobs=self.thread_count) + pairwise_distances(compute_df_reindexed, n_jobs=self.thread_count) ), - columns=train_ft_df_reindexed.index, - index=train_ft_df_reindexed.index + columns=compute_df_reindexed.index, + index=compute_df_reindexed.index ) pairwise = pairwise.round(5) column_labels = [ - '{}{}'.format('d', i) for i in range(1, nmb_previous_points+1) + '{}{}'.format('d', i) for i in range(1, no_prev_pts + 1) ] distances = pd.DataFrame( - columns=column_labels, index=train_ft_df.index + columns=column_labels, index=compute_df.index ) - for index in train_ft_df.index[nmb_previous_points]: + + for index in compute_df.index[no_prev_pts:]: current_row = pairwise.loc[[index]] current_row_no_zeros = current_row.loc[ - :, (current_row!=0).any(axis=0) + :, (current_row != 0).any(axis=0) ] distances.loc[[index]] = current_row_no_zeros.iloc[ - :, :nmb_previous_points + :, :no_prev_pts ] distances = distances.replace([np.inf, -np.inf], np.nan) drop_index = pd.isnull(distances).any(1) - distances = distances[drop_index==0] + distances = distances[drop_index == 0] inliers = pd.DataFrame(index=distances.index) for key in distances.keys(): current_distances = distances[key].dropna() fit_params = ss.weibull_min.fit(current_distances) - cutoff = ss.weibull_min.ppf(weibull_percentile, *fit_params) + cutoff = ss.weibull_min.ppf(weib_pct, *fit_params) is_inlier = np.where( - current_distances<=cutoff, 1, 0 + current_distances <= cutoff, 1, 0 ) df_inlier = pd.DataFrame( - {key+'_IsInlier':is_inlier}, index=distances.index + {key + '_IsInlier': is_inlier}, index=distances.index ) inliers = pd.concat( [inliers, df_inlier], axis=1 ) - self.data_dictionary['train_features'] = pd.DataFrame( - data=inliers.sum(axis=1)/nmb_previous_points, + inlier_metric = pd.DataFrame( + data=inliers.sum(axis=1) / no_prev_pts, columns=['inlier_metric'], - index = train_ft_df.index + index=compute_df.index ) - percent_outliers = np.round( - 100*(1-self.data_dictionary['iniler_metric'].sum()/ - len(train_ft_df.index)), 2 - ) - logger.info('{percent_outliers}%% of data points were identified as outliers') + inlier_metric = 2 * (inlier_metric - inlier_metric.min()) / \ + (inlier_metric.max() - inlier_metric.min()) - 1 + + if set_ in ('train', 'test'): + inlier_metric = inlier_metric.iloc[no_prev_pts:] + compute_df = compute_df.iloc[no_prev_pts:] + self.remove_beginning_points_from_data_dict(set_, no_prev_pts) + self.data_dictionary[f'{set_}_features'] = pd.concat( + [compute_df, inlier_metric], axis=1) + else: + self.data_dictionary['prediction_features'] = pd.concat( + [compute_df, inlier_metric], axis=1) + self.data_dictionary['prediction_features'].fillna(0, inplace=True) return None + def remove_beginning_points_from_data_dict(self, set_='train', no_prev_pts: int = 10): + features = self.data_dictionary[f'{set_}_features'] + weights = self.data_dictionary[f'{set_}_weights'] + labels = self.data_dictionary[f'{set_}_labels'] + self.data_dictionary[f'{set_}_weights'] = weights[no_prev_pts:] + self.data_dictionary[f'{set_}_features'] = features.iloc[no_prev_pts:] + self.data_dictionary[f'{set_}_labels'] = labels.iloc[no_prev_pts:] + def find_features(self, dataframe: DataFrame) -> None: """ Find features in the strategy provided dataframe diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 4106f24e0..e6e019b66 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -66,7 +66,6 @@ class IFreqaiModel(ABC): "data_split_parameters", {}) self.model_training_parameters: Dict[str, Any] = config.get("freqai", {}).get( "model_training_parameters", {}) - self.feature_parameters = config.get("freqai", {}).get("feature_parameters") self.retrain = False self.first = True self.set_full_path() @@ -74,11 +73,14 @@ class IFreqaiModel(ABC): self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode) self.identifier: str = self.freqai_info.get("identifier", "no_id_provided") self.scanning = False + self.ft_params = self.freqai_info["feature_parameters"] self.keras: bool = self.freqai_info.get("keras", False) - if self.keras and self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0): - self.freqai_info["feature_parameters"]["DI_threshold"] = 0 + if self.keras and self.ft_params.get("DI_threshold", 0): + self.ft_params["DI_threshold"] = 0 logger.warning("DI threshold is not configured for Keras models yet. Deactivating.") self.CONV_WIDTH = self.freqai_info.get("conv_width", 2) + if self.ft_params.get("inlier_metric_window", 0): + self.CONV_WIDTH = self.ft_params.get("inlier_metric_window", 0) * 2 self.pair_it = 0 self.pair_it_train = 0 self.total_pairs = len(self.config.get("exchange", {}).get("pair_whitelist")) @@ -403,18 +405,20 @@ class IFreqaiModel(ABC): example of how outlier data points are dropped from the dataframe used for training. """ - if self.freqai_info["feature_parameters"].get( + ft_params = self.freqai_info["feature_parameters"] + + if ft_params.get( "principal_component_analysis", False ): dk.principal_component_analysis() - if self.freqai_info["feature_parameters"].get("use_SVM_to_remove_outliers", False): + if ft_params.get("use_SVM_to_remove_outliers", False): dk.use_SVM_to_remove_outliers(predict=False) - if self.freqai_info["feature_parameters"].get("DI_threshold", 0): + if ft_params.get("DI_threshold", 0): dk.data["avg_mean_dist"] = dk.compute_distances() - if self.freqai_info["feature_parameters"].get("use_DBSCAN_to_remove_outliers", False): + if ft_params.get("use_DBSCAN_to_remove_outliers", False): if dk.pair in self.dd.old_DBSCAN_eps: eps = self.dd.old_DBSCAN_eps[dk.pair] else: @@ -422,6 +426,11 @@ class IFreqaiModel(ABC): dk.use_DBSCAN_to_remove_outliers(predict=False, eps=eps) self.dd.old_DBSCAN_eps[dk.pair] = dk.data['DBSCAN_eps'] + if ft_params.get('inlier_metric_window', 0): + dk.compute_inlier_metric(set_='train') + if self.freqai_info["data_split_parameters"]["test_size"] > 0: + dk.compute_inlier_metric(set_='test') + def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None: """ Base data cleaning method for predict. @@ -433,18 +442,23 @@ class IFreqaiModel(ABC): of how the do_predict vector is modified. do_predict is ultimately passed back to strategy for buy signals. """ - if self.freqai_info["feature_parameters"].get( + ft_params = self.freqai_info["feature_parameters"] + + if ft_params.get('inlier_metric_window', 0): + dk.compute_inlier_metric(set_='predict') + + if ft_params.get( "principal_component_analysis", False ): dk.pca_transform(dataframe) - if self.freqai_info["feature_parameters"].get("use_SVM_to_remove_outliers", False): + if ft_params.get("use_SVM_to_remove_outliers", False): dk.use_SVM_to_remove_outliers(predict=True) - if self.freqai_info["feature_parameters"].get("DI_threshold", 0): + if ft_params.get("DI_threshold", 0): dk.check_if_pred_in_training_spaces() - if self.freqai_info["feature_parameters"].get("use_DBSCAN_to_remove_outliers", False): + if ft_params.get("use_DBSCAN_to_remove_outliers", False): dk.use_DBSCAN_to_remove_outliers(predict=True) def model_exists( From a58dd0bbf9347a69fecde43e5735bc1851de3b9b Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 19 Aug 2022 18:35:24 +0200 Subject: [PATCH 102/592] add noise feature, improve docstrings --- freqtrade/freqai/data_kitchen.py | 11 +++++++++++ freqtrade/freqai/freqai_interface.py | 18 +++++++----------- 2 files changed, 18 insertions(+), 11 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 80919626c..0158996c7 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -821,6 +821,17 @@ class FreqaiDataKitchen: self.data_dictionary[f'{set_}_features'] = features.iloc[no_prev_pts:] self.data_dictionary[f'{set_}_labels'] = labels.iloc[no_prev_pts:] + def add_noise_to_training_features(self) -> None: + """ + Add noise to train features to reduce the risk of overfitting. + """ + mu = 0 # no shift + sigma = self.freqai_config["feature_parameters"]["noise_standard_deviation"] + compute_df = self.data_dictionary['train_features'] + noise = np.random.normal(mu, sigma, [compute_df.shape[0], compute_df.shape[1]]) + self.data_dictionary['train_features'] += noise + return + def find_features(self, dataframe: DataFrame) -> None: """ Find features in the strategy provided dataframe diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index e6e019b66..239cb1869 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -399,10 +399,9 @@ class IFreqaiModel(ABC): def data_cleaning_train(self, dk: FreqaiDataKitchen) -> None: """ - Base data cleaning method for train - Any function inside this method should drop training data points from the filtered_dataframe - based on user decided logic. See FreqaiDataKitchen::use_SVM_to_remove_outliers() for an - example of how outlier data points are dropped from the dataframe used for training. + Base data cleaning method for train. + Functions here improve/modify the input data by identifying outliers, + computing additional metrics, adding noise, reducing dimensionality etc. """ ft_params = self.freqai_info["feature_parameters"] @@ -431,16 +430,13 @@ class IFreqaiModel(ABC): if self.freqai_info["data_split_parameters"]["test_size"] > 0: dk.compute_inlier_metric(set_='test') + if self.freqai_info["feature_parameters"].get('noise_standard_deviation', 0): + dk.add_noise_to_training_features() + def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None: """ Base data cleaning method for predict. - These functions each modify dk.do_predict, which is a dataframe with equal length - to the number of candles coming from and returning to the strategy. Inside do_predict, - 1 allows prediction and < 0 signals to the strategy that the model is not confident in - the prediction. - See FreqaiDataKitchen::remove_outliers() for an example - of how the do_predict vector is modified. do_predict is ultimately passed back to strategy - for buy signals. + Functions here are complementary to the functions of data_cleaning_train. """ ft_params = self.freqai_info["feature_parameters"] From 7f52908e87a61ed60c7fe3f2b9b933b6211c60da Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 30 Aug 2022 18:55:58 +0200 Subject: [PATCH 103/592] ensure the lost points are prepended for FreqUI --- freqtrade/freqai/freqai_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 239cb1869..893f960ea 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -587,7 +587,7 @@ class IFreqaiModel(ABC): # # for keras type models, the conv_window needs to be prepended so # # viewing is correct in frequi - if self.freqai_info.get('keras', False): + if self.freqai_info.get('keras', False) or self.ft_params.get('inlier_metric_window', 0): n_lost_points = self.freqai_info.get('conv_width', 2) zeros_df = DataFrame(np.zeros((n_lost_points, len(hist_preds_df.columns))), columns=hist_preds_df.columns) From 418bd26a8097008ccb5ef747cc63ea087fadfea4 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 30 Aug 2022 11:04:16 -0600 Subject: [PATCH 104/592] minor fixes, rework consumer request, update requirements.txt --- freqtrade/enums/__init__.py | 2 +- freqtrade/enums/rpcmessagetype.py | 6 ++++++ freqtrade/rpc/api_server/api_ws.py | 23 +++++++---------------- freqtrade/rpc/api_server/webserver.py | 6 +----- freqtrade/rpc/rpc.py | 14 ++++++++++++-- freqtrade/rpc/rpc_manager.py | 2 +- freqtrade/rpc/telegram.py | 10 +++++++--- requirements-externalsignals.txt | 7 ------- requirements.txt | 5 +++++ scripts/test_ws_client.py | 11 +++++++++-- setup.py | 5 ++++- 11 files changed, 53 insertions(+), 38 deletions(-) delete mode 100644 requirements-externalsignals.txt diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index ffeb8cc12..406d847e6 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -6,7 +6,7 @@ from freqtrade.enums.exittype import ExitType from freqtrade.enums.externalsignal import ExternalSignalModeType, LeaderMessageType, WaitDataPolicy from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues -from freqtrade.enums.rpcmessagetype import RPCMessageType +from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType from freqtrade.enums.state import State diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index 8e4182b33..6283fb7cc 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -21,9 +21,15 @@ class RPCMessageType(str, Enum): STRATEGY_MSG = 'strategy_msg' WHITELIST = 'whitelist' + ANALYZED_DF = 'analyzed_df' def __repr__(self): return self.value def __str__(self): return self.value + + +# Enum for parsing requests from ws consumers +class RPCRequestType(str, Enum): + SUBSCRIBE = 'subscribe' diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 405beed79..c8d1b70fa 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -2,8 +2,7 @@ import logging from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect -from freqtrade.enums import RPCMessageType -from freqtrade.rpc.api_server.deps import get_channel_manager +from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc_optional from freqtrade.rpc.api_server.ws.utils import is_websocket_alive @@ -16,7 +15,8 @@ router = APIRouter() @router.websocket("/message/ws") async def message_endpoint( ws: WebSocket, - channel_manager=Depends(get_channel_manager) + channel_manager=Depends(get_channel_manager), + rpc=Depends(get_rpc_optional) ): try: if is_websocket_alive(ws): @@ -31,19 +31,10 @@ async def message_endpoint( while not channel.is_closed(): request = await channel.recv() - # This is where we'd parse the request. For now this should only - # be a list of topics to subscribe too. List[str] - # Maybe allow the consumer to update the topics subscribed - # during runtime? - - # If the request isn't a list then skip it - if not isinstance(request, list): - continue - - # Check if all topics listed are an RPCMessageType - if all([any(x.value == topic for x in RPCMessageType) for topic in request]): - logger.debug(f"{ws.client} subscribed to topics: {request}") - channel.set_subscriptions(request) + # Process the request here. Should this be a method of RPC? + if rpc: + logger.info(f"Request: {request}") + rpc._process_consumer_request(request, channel) except WebSocketDisconnect: # Handle client disconnects diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 94cb8cd45..f4af8c8ed 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -63,11 +63,7 @@ class ApiServer(RPCHandler): ApiServer.__initialized = False return ApiServer.__instance - def __init__( - self, - config: Dict[str, Any], - standalone: bool = False, - ) -> None: + def __init__(self, config: Dict[str, Any], standalone: bool = False) -> None: ApiServer._config = config if self.__initialized and (standalone or self._standalone): return diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 3c7558158..f684c7783 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -19,8 +19,8 @@ from freqtrade.configuration.timerange import TimeRange from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT from freqtrade.data.history import load_data from freqtrade.data.metrics import calculate_max_drawdown -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State, - TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RPCMessageType, RPCRequestType, + SignalDirection, State, TradingMode) from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler @@ -1089,6 +1089,16 @@ class RPC: 'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT), 'last_process_ts': int(last_p.timestamp()), } + + # We are passed a Channel object, we can only do sync functions on that channel object + def _process_consumer_request(self, request, channel): + # Should we ensure that request is Dict[str, Any]? + type, data = request.get('type'), request.get('data') + + if type == RPCRequestType.SUBSCRIBE: + if all([any(x.value == topic for x in RPCMessageType) for topic in data]): + logger.debug(f"{channel} subscribed to topics: {data}") + channel.set_subscriptions(data) # # # ------------------------------ EXTERNAL SIGNALS ----------------------- # diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index c5e93e3b4..b3cd5604c 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -64,7 +64,7 @@ class RPCManager: """ Stops all enabled rpc modules """ logger.info('Cleaning up rpc modules ...') while self.registered_modules: - mod = self.registered_modules.pop() + mod = self.registered_modules.pop() # popleft to cleanup API server last? logger.info('Cleaning up rpc.%s ...', mod.name) mod.cleanup() del mod diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py index 8ce2fa2e4..141368769 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -436,9 +436,13 @@ class Telegram(RPCHandler): # Notification disabled return - message = self.compose_message(msg, msg_type) - - self._send_msg(message, disable_notification=(noti == 'silent')) + # Would this be better than adding un-needed if statements to compose_message? + try: + message = self.compose_message(msg, msg_type) + self._send_msg(message, disable_notification=(noti == 'silent')) + except NotImplementedError: + # just skip it + return def _get_sell_emoji(self, msg): """ diff --git a/requirements-externalsignals.txt b/requirements-externalsignals.txt deleted file mode 100644 index 7920b34f6..000000000 --- a/requirements-externalsignals.txt +++ /dev/null @@ -1,7 +0,0 @@ -# Include all requirements to run the bot. --r requirements.txt - -# Required for follower -websockets -msgpack -janus diff --git a/requirements.txt b/requirements.txt index 77925f98b..4d97f500a 100644 --- a/requirements.txt +++ b/requirements.txt @@ -50,3 +50,8 @@ python-dateutil==2.8.2 #Futures schedule==1.1.0 + +#WS Messages +websockets~=10.3 +msgpack~=1.0.4 +janus==1.0.0 diff --git a/scripts/test_ws_client.py b/scripts/test_ws_client.py index 2c64ae867..872ff3ccf 100644 --- a/scripts/test_ws_client.py +++ b/scripts/test_ws_client.py @@ -1,6 +1,7 @@ import asyncio import logging import socket +from typing import Any import websockets @@ -12,8 +13,14 @@ logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) +def compose_consumer_request(type_: str, data: Any): + return {"type": type_, "data": data} + + async def _client(): - subscribe_topics = [RPCMessageType.WHITELIST] + # Trying to recreate multiple topic issue. Wait until first whitelist message, + # then CTRL-C to get the status message. + topics = [RPCMessageType.WHITELIST, RPCMessageType.STATUS] try: while True: try: @@ -23,7 +30,7 @@ async def _client(): logger.info("Connection successful") # Tell the producer we only want these topics - await channel.send(subscribe_topics) + await channel.send(compose_consumer_request("subscribe", topics)) while True: try: diff --git a/setup.py b/setup.py index 8f04e75f7..c7b1f1c7c 100644 --- a/setup.py +++ b/setup.py @@ -79,7 +79,10 @@ setup( 'psutil', 'pyjwt', 'aiofiles', - 'schedule' + 'schedule', + 'websockets', + 'msgpack', + 'janus' ], extras_require={ 'dev': all_extra, From 0b8482360f0ec1aea6e61ac08b3746584c03800a Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 30 Aug 2022 20:32:49 +0200 Subject: [PATCH 105/592] add documentation for inlier metric --- docs/freqai.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/docs/freqai.md b/docs/freqai.md index e4a451324..3fc76e9f0 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -115,6 +115,8 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. | `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` | `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False +| `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 +| `inlier_metric_weibull_cutoff` | If the `inlier_metric_window` is set, this value is used to determine the tail cutoff in the weibull distribution fit. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** float. Default: 0.95 | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. @@ -636,6 +638,20 @@ testing; the other points are used for training. The test data is used to evaluate the performance of the model after training. If the test score is high, the model is able to capture the behavior of the data well. If the test score is low, either the model either does not capture the complexity of the data, the test data is significantly different from the train data, or a different model should be used. +### Using the `inlier_metric` + +The `inlier_metric` is a metric aimed at quantifying how different a prediction data point is from the most recent historic data points. + +User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points). + +This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. If one of the distances falls in the tail of the respective weibull distribution, it is considered an "outlier." If the distance to the lookback point is not in the tail, it is considered an "inlier." Inliers receive a value of 1, and outliers receive a value of 0. + +FreqAI adds this `inlier_metric` score to the training features! Thus, your model is trained to recognize how this temporal inlier metric is evolving. + +Users can control the weibull threshold using the `inlier_metric_weibull_cutoff` + +This function does not currently remove outliers from the data set. + ### Controlling the model learning process Model training parameters are unique to the machine learning library selected by the user. FreqAI allows the user to set any parameter for any library using the `model_training_parameters` dictionary in the user configuration file. The example configuration file (found in `config_examples/config_freqai.example.json`) show some of the example parameters associated with `Catboost` and `LightGBM`, but the user can add any parameters available in those libraries. From 7e8e29e42d4c2b0eb058d9408c27ebd220eb9f68 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 30 Aug 2022 20:41:37 +0200 Subject: [PATCH 106/592] use continuous value for inlier_metric --- docs/freqai.md | 9 +++------ freqtrade/freqai/data_kitchen.py | 9 +++------ 2 files changed, 6 insertions(+), 12 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 3fc76e9f0..2c6efa3b9 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -116,7 +116,6 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` | `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False | `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 -| `inlier_metric_weibull_cutoff` | If the `inlier_metric_window` is set, this value is used to determine the tail cutoff in the weibull distribution fit. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** float. Default: 0.95 | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. @@ -644,13 +643,11 @@ The `inlier_metric` is a metric aimed at quantifying how different a prediction User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points). -This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. If one of the distances falls in the tail of the respective weibull distribution, it is considered an "outlier." If the distance to the lookback point is not in the tail, it is considered an "inlier." Inliers receive a value of 1, and outliers receive a value of 0. +This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. The cumulative distribution function for the weibull distribution is used to produce a quantile for each of the data points. The quantiles for each lookback point are averaged to create the `inlier_metric`. -FreqAI adds this `inlier_metric` score to the training features! Thus, your model is trained to recognize how this temporal inlier metric is evolving. +FreqAI adds this `inlier_metric` score to the training features! In other words, your model is trained to recognize how this temporal inlier metric is related to the user set labels. -Users can control the weibull threshold using the `inlier_metric_weibull_cutoff` - -This function does not currently remove outliers from the data set. +This function does **not** remove outliers from the data set. ### Controlling the model learning process diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 0158996c7..9d4a69287 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -735,7 +735,6 @@ class FreqaiDataKitchen: import scipy.stats as ss no_prev_pts = self.freqai_config["feature_parameters"]["inlier_metric_window"] - weib_pct = self.freqai_config["feature_parameters"]["inlier_metric_weibull_cutoff"] if set_ == 'train': compute_df = copy.deepcopy(self.data_dictionary['train_features']) @@ -780,12 +779,10 @@ class FreqaiDataKitchen: for key in distances.keys(): current_distances = distances[key].dropna() fit_params = ss.weibull_min.fit(current_distances) - cutoff = ss.weibull_min.ppf(weib_pct, *fit_params) - is_inlier = np.where( - current_distances <= cutoff, 1, 0 - ) + quantiles = ss.weibull_min.cdf(current_distances, *fit_params) + df_inlier = pd.DataFrame( - {key + '_IsInlier': is_inlier}, index=distances.index + {key: quantiles}, index=distances.index ) inliers = pd.concat( [inliers, df_inlier], axis=1 From c9aa09ec89d37d6f8fcea4c9f15c092021a82a93 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 30 Aug 2022 20:46:06 +0200 Subject: [PATCH 107/592] Simplify base fee handling --- freqtrade/freqtradebot.py | 32 ++++++++++------------ tests/test_freqtradebot.py | 56 ++++++++++++++++++++------------------ 2 files changed, 43 insertions(+), 45 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index ea9221213..5393e3d39 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1778,7 +1778,7 @@ class FreqtradeBot(LoggingMixin): self.rpc.send_msg(msg) def apply_fee_conditional(self, trade: Trade, trade_base_currency: str, - amount: float, fee_abs: float) -> float: + amount: float, fee_abs: float) -> Optional[float]: """ Applies the fee to amount (either from Order or from Trades). Can eat into dust if more than the required asset is available. @@ -1791,35 +1791,32 @@ class FreqtradeBot(LoggingMixin): logger.info(f"Fee amount for {trade} was in base currency - " f"Eating Fee {fee_abs} into dust.") elif fee_abs != 0: - real_amount = self.exchange.amount_to_precision(trade.pair, amount - fee_abs) - logger.info(f"Applying fee on amount for {trade} " - f"(from {amount} to {real_amount}).") - return real_amount - return amount + logger.info(f"Applying fee on amount for {trade}, fee={fee_abs}.") + return fee_abs + return None def handle_order_fee(self, trade: Trade, order_obj: Order, order: Dict[str, Any]) -> None: # Try update amount (binance-fix) try: - new_amount = self.get_real_amount(trade, order, order_obj) - if not isclose(safe_value_fallback(order, 'filled', 'amount'), new_amount, - abs_tol=constants.MATH_CLOSE_PREC): - order_obj.ft_fee_base = trade.amount - new_amount + fee_abs = self.get_real_amount(trade, order, order_obj) + if fee_abs is not None: + order_obj.ft_fee_base = fee_abs except DependencyException as exception: logger.warning("Could not update trade amount: %s", exception) - def get_real_amount(self, trade: Trade, order: Dict, order_obj: Order) -> float: + def get_real_amount(self, trade: Trade, order: Dict, order_obj: Order) -> Optional[float]: """ Detect and update trade fee. Calls trade.update_fee() upon correct detection. Returns modified amount if the fee was taken from the destination currency. Necessary for exchanges which charge fees in base currency (e.g. binance) - :return: identical (or new) amount for the trade + :return: Absolute fee to apply for this order or None """ # Init variables order_amount = safe_value_fallback(order, 'filled', 'amount') # Only run for closed orders if trade.fee_updated(order.get('side', '')) or order['status'] == 'open': - return order_amount + return None trade_base_currency = self.exchange.get_pair_base_currency(trade.pair) # use fee from order-dict if possible @@ -1837,12 +1834,12 @@ class FreqtradeBot(LoggingMixin): # Apply fee to amount return self.apply_fee_conditional(trade, trade_base_currency, amount=order_amount, fee_abs=fee_cost) - return order_amount + return None return self.fee_detection_from_trades( trade, order, order_obj, order_amount, order.get('trades', [])) def fee_detection_from_trades(self, trade: Trade, order: Dict, order_obj: Order, - order_amount: float, trades: List) -> float: + order_amount: float, trades: List) -> Optional[float]: """ fee-detection fallback to Trades. Either uses provided trades list or the result of fetch_my_trades to get correct fee. @@ -1853,7 +1850,7 @@ class FreqtradeBot(LoggingMixin): if len(trades) == 0: logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade) - return order_amount + return None fee_currency = None amount = 0 fee_abs = 0.0 @@ -1897,8 +1894,7 @@ class FreqtradeBot(LoggingMixin): if fee_abs != 0: return self.apply_fee_conditional(trade, trade_base_currency, amount=amount, fee_abs=fee_abs) - else: - return amount + return None def get_valid_price(self, custom_price: float, proposed_price: float) -> float: """ diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 138527053..902343c1e 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -1927,8 +1927,7 @@ def test_update_trade_state(mocker, default_conf_usdt, limit_order, is_short, ca mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True)) mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order) mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[]) - mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', - return_value=order['amount']) + mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=0.0) order_id = order['id'] trade = Trade( @@ -1960,11 +1959,11 @@ def test_update_trade_state(mocker, default_conf_usdt, limit_order, is_short, ca assert trade.amount == order['amount'] trade.open_order_id = order_id - mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81) - assert trade.amount != 90.81 + mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=0.01) + assert trade.amount == 30.0 # test amount modified by fee-logic freqtrade.update_trade_state(trade, order_id) - assert trade.amount == 90.81 + assert trade.amount == 29.99 assert trade.open_order_id is None trade.is_open = True @@ -4268,10 +4267,10 @@ def test_get_real_amount_quote(default_conf_usdt, trades_for_order, buy_order_fe caplog.clear() order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') # Amount is reduced by "fee" - assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount - (amount * 0.001) + assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == (amount * 0.001) assert log_has( 'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, is_short=False,' - ' leverage=1.0, open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).', + ' leverage=1.0, open_rate=0.24544100, open_since=closed), fee=0.008.', caplog ) @@ -4296,7 +4295,7 @@ def test_get_real_amount_quote_dust(default_conf_usdt, trades_for_order, buy_ord walletmock.reset_mock() order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') # Amount is kept as is - assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount + assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) is None assert walletmock.call_count == 1 assert log_has_re(r'Fee amount for Trade.* was in base currency ' '- Eating Fee 0.008 into dust', caplog) @@ -4319,7 +4318,7 @@ def test_get_real_amount_no_trade(default_conf_usdt, buy_order_fee, caplog, mock order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') # Amount is reduced by "fee" - assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount + assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) is None assert log_has( 'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, ' 'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) failed: ' @@ -4343,8 +4342,7 @@ def test_get_real_amount_no_trade(default_conf_usdt, buy_order_fee, caplog, mock # from order ({'cost': 0.004, 'currency': 'LTC'}, 0.004, False, ( 'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, ' - 'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) (from' - ' 8.0 to 7.996).' + 'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed), fee=0.004.' )), # invalid, no currency in from fee dict ({'cost': 0.008, 'currency': None}, 0, True, None), @@ -4376,7 +4374,11 @@ def test_get_real_amount( caplog.clear() order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') - assert freqtrade.get_real_amount(trade, buy_order, order_obj) == amount - fee_reduction_amount + res = freqtrade.get_real_amount(trade, buy_order, order_obj) + if fee_reduction_amount == 0: + assert res is None + else: + assert res == fee_reduction_amount if expected_log: assert log_has(expected_log, caplog) @@ -4422,14 +4424,14 @@ def test_get_real_amount_multi( return_value={'ask': 0.19, 'last': 0.2}) # Amount is reduced by "fee" - expected_amount = amount - (amount * fee_reduction_amount) + expected_amount = amount * fee_reduction_amount order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == expected_amount assert log_has( ( 'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, ' - 'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) ' - f'(from 8.0 to {expected_log_amount}).' + 'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed), ' + f'fee={expected_amount}.' ), caplog ) @@ -4462,7 +4464,7 @@ def test_get_real_amount_invalid_order(default_conf_usdt, trades_for_order, buy_ order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') # Amount does not change - assert freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj) == amount + assert freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj) is None def test_get_real_amount_fees_order(default_conf_usdt, market_buy_order_usdt_doublefee, @@ -4485,7 +4487,7 @@ def test_get_real_amount_fees_order(default_conf_usdt, market_buy_order_usdt_dou # Amount does not change assert trade.fee_open == 0.0025 order_obj = Order.parse_from_ccxt_object(market_buy_order_usdt_doublefee, 'LTC/ETH', 'buy') - assert freqtrade.get_real_amount(trade, market_buy_order_usdt_doublefee, order_obj) == 30.0 + assert freqtrade.get_real_amount(trade, market_buy_order_usdt_doublefee, order_obj) is None assert tfo_mock.call_count == 0 # Fetch fees from trades dict if available to get "proper" values assert round(trade.fee_open, 4) == 0.001 @@ -4537,7 +4539,7 @@ def test_get_real_amount_wrong_amount_rounding(default_conf_usdt, trades_for_ord order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') # Amount changes by fee amount. assert pytest.approx(freqtrade.get_real_amount( - trade, limit_buy_order_usdt, order_obj)) == amount - (amount * 0.001) + trade, limit_buy_order_usdt, order_obj)) == (amount * 0.001) def test_get_real_amount_open_trade_usdt(default_conf_usdt, fee, mocker): @@ -4559,7 +4561,7 @@ def test_get_real_amount_open_trade_usdt(default_conf_usdt, fee, mocker): } freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) order_obj = Order.parse_from_ccxt_object(order, 'LTC/ETH', 'buy') - assert freqtrade.get_real_amount(trade, order, order_obj) == amount + assert freqtrade.get_real_amount(trade, order, order_obj) is None def test_get_real_amount_in_point(default_conf_usdt, buy_order_fee, fee, mocker, caplog): @@ -4616,7 +4618,7 @@ def test_get_real_amount_in_point(default_conf_usdt, buy_order_fee, fee, mocker, order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy') res = freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj) - assert res == amount + assert res is None assert trade.fee_open_currency is None assert trade.fee_open_cost is None message = "Not updating buy-fee - rate: None, POINT." @@ -4624,7 +4626,7 @@ def test_get_real_amount_in_point(default_conf_usdt, buy_order_fee, fee, mocker, caplog.clear() freqtrade.config['exchange']['unknown_fee_rate'] = 1 res = freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj) - assert res == amount + assert res is None assert trade.fee_open_currency == 'POINT' assert pytest.approx(trade.fee_open_cost) == 0.3046651026 assert trade.fee_open == 0.002 @@ -4633,12 +4635,12 @@ def test_get_real_amount_in_point(default_conf_usdt, buy_order_fee, fee, mocker, @pytest.mark.parametrize('amount,fee_abs,wallet,amount_exp', [ - (8.0, 0.0, 10, 8), - (8.0, 0.0, 0, 8), - (8.0, 0.1, 0, 7.9), - (8.0, 0.1, 10, 8), - (8.0, 0.1, 8.0, 8.0), - (8.0, 0.1, 7.9, 7.9), + (8.0, 0.0, 10, None), + (8.0, 0.0, 0, None), + (8.0, 0.1, 0, 0.1), + (8.0, 0.1, 10, None), + (8.0, 0.1, 8.0, None), + (8.0, 0.1, 7.9, 0.1), ]) def test_apply_fee_conditional(default_conf_usdt, fee, mocker, amount, fee_abs, wallet, amount_exp): From 10e0d538603338d0df0ffc57fa27b93c04647a19 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 30 Aug 2022 20:49:53 +0200 Subject: [PATCH 108/592] Simplify 2 more tests --- tests/test_freqtradebot.py | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 902343c1e..e6c6e7978 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -1051,8 +1051,6 @@ def test_add_stoploss_on_exchange(mocker, default_conf_usdt, limit_order, is_sho mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True)) mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order) mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[]) - mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', - return_value=order['amount']) stoploss = MagicMock(return_value={'id': 13434334}) mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss) @@ -1875,8 +1873,6 @@ def test_exit_positions(mocker, default_conf_usdt, limit_order, is_short, caplog mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_order[entry_side(is_short)]) mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[]) - mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', - return_value=limit_order[entry_side(is_short)]['amount']) trade = MagicMock() trade.is_short = is_short @@ -1886,14 +1882,13 @@ def test_exit_positions(mocker, default_conf_usdt, limit_order, is_short, caplog n = freqtrade.exit_positions(trades) assert n == 0 # Test amount not modified by fee-logic - assert not log_has( - 'Applying fee to amount for Trade {} from 30.0 to 90.81'.format(trade), caplog - ) + assert not log_has_re(r'Applying fee to amount for Trade .*', caplog) - mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81) + gra = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=0.0) # test amount modified by fee-logic n = freqtrade.exit_positions(trades) assert n == 0 + assert gra.call_count == 0 @pytest.mark.parametrize("is_short", [False, True]) From 346e73dd75503f9170d6f6759a517d0f421e6fc6 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 30 Aug 2022 19:21:34 -0600 Subject: [PATCH 109/592] client implementation, minor fixes --- config_examples/config_full.example.json | 13 +- freqtrade/constants.py | 26 +- freqtrade/data/dataprovider.py | 10 +- freqtrade/enums/__init__.py | 2 +- freqtrade/enums/externalmessages.py | 7 + freqtrade/enums/externalsignal.py | 18 - freqtrade/freqtradebot.py | 17 +- freqtrade/rpc/api_server/api_ws.py | 2 +- freqtrade/rpc/api_server/webserver.py | 29 +- freqtrade/rpc/api_server/ws/channel.py | 3 - freqtrade/rpc/emc.py | 229 ++++++++++ freqtrade/rpc/external_signal/__init__.py | 5 - freqtrade/rpc/external_signal/channel.py | 145 ------- freqtrade/rpc/external_signal/controller.py | 449 -------------------- freqtrade/rpc/external_signal/proxy.py | 61 --- freqtrade/rpc/external_signal/serializer.py | 65 --- freqtrade/rpc/external_signal/types.py | 8 - freqtrade/rpc/external_signal/utils.py | 10 - freqtrade/rpc/rpc.py | 62 --- freqtrade/rpc/rpc_manager.py | 4 +- freqtrade/strategy/interface.py | 43 +- scripts/test_ws_client.py | 74 ---- 22 files changed, 323 insertions(+), 959 deletions(-) create mode 100644 freqtrade/enums/externalmessages.py delete mode 100644 freqtrade/enums/externalsignal.py create mode 100644 freqtrade/rpc/emc.py delete mode 100644 freqtrade/rpc/external_signal/__init__.py delete mode 100644 freqtrade/rpc/external_signal/channel.py delete mode 100644 freqtrade/rpc/external_signal/controller.py delete mode 100644 freqtrade/rpc/external_signal/proxy.py delete mode 100644 freqtrade/rpc/external_signal/serializer.py delete mode 100644 freqtrade/rpc/external_signal/types.py delete mode 100644 freqtrade/rpc/external_signal/utils.py delete mode 100644 scripts/test_ws_client.py diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 74457d2b6..ec988687f 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -172,7 +172,18 @@ "jwt_secret_key": "somethingrandom", "CORS_origins": [], "username": "freqtrader", - "password": "SuperSecurePassword" + "password": "SuperSecurePassword", + "ws_token": "a_secret_ws_token", + "enable_message_ws": false + }, + "external_message_consumer": { + "enabled": false, + "producers": [ + { + "url": "ws://some.freqtrade.bot/api/v1/message/ws", + "ws_token": "a_secret_ws_token" + } + ] }, "bot_name": "freqtrade", "db_url": "sqlite:///tradesv3.sqlite", diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 96f8413b0..c7f2acc84 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -61,7 +61,6 @@ USERPATH_FREQAIMODELS = 'freqaimodels' TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent'] WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw'] -FOLLOWER_MODE_OPTIONS = ['follower', 'leader'] WAIT_DATA_POLICY_OPTIONS = ['none', 'first', 'all'] ENV_VAR_PREFIX = 'FREQTRADE__' @@ -246,7 +245,7 @@ CONF_SCHEMA = { 'exchange': {'$ref': '#/definitions/exchange'}, 'edge': {'$ref': '#/definitions/edge'}, 'freqai': {'$ref': '#/definitions/freqai'}, - 'external_signal': {'$ref': '#/definitions/external_signal'}, + 'external_message_consumer': {'$ref': '#/definitions/external_message_consumer'}, 'experimental': { 'type': 'object', 'properties': { @@ -404,7 +403,8 @@ CONF_SCHEMA = { }, 'username': {'type': 'string'}, 'password': {'type': 'string'}, - 'api_token': {'type': 'string'}, + 'ws_token': {'type': 'string'}, + 'enable_message_ws': {'type': 'boolean', 'default': False}, 'jwt_secret_key': {'type': 'string'}, 'CORS_origins': {'type': 'array', 'items': {'type': 'string'}}, 'verbosity': {'type': 'string', 'enum': ['error', 'info']}, @@ -489,35 +489,31 @@ CONF_SCHEMA = { }, 'required': ['process_throttle_secs', 'allowed_risk'] }, - 'external_signal': { + 'external_message_consumer': { 'type': 'object', 'properties': { 'enabled': {'type': 'boolean', 'default': False}, - 'mode': { - 'type': 'string', - 'enum': FOLLOWER_MODE_OPTIONS - }, - 'api_token': {'type': 'string', 'default': ''}, - 'leaders': { + 'producers': { 'type': 'array', 'items': { 'type': 'object', 'properties': { 'url': {'type': 'string', 'default': ''}, - 'api_token': {'type': 'string', 'default': ''}, + 'ws_token': {'type': 'string', 'default': ''}, } } }, - 'follower_reply_timeout': {'type': 'integer'}, - 'follower_sleep_time': {'type': 'integer'}, - 'follower_ping_timeout': {'type': 'integer'}, + 'reply_timeout': {'type': 'integer'}, + 'sleep_time': {'type': 'integer'}, + 'ping_timeout': {'type': 'integer'}, 'wait_data_policy': { 'type': 'string', 'enum': WAIT_DATA_POLICY_OPTIONS }, + 'wait_data_timeout': {'type': 'integer', 'default': 5}, 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False} }, - 'required': ['mode'] + 'required': ['producers'] }, "freqai": { "type": "object", diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index cd70db9a3..430ee0932 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -48,11 +48,13 @@ class DataProvider: self.__msg_cache = PeriodicCache( maxsize=1000, ttl=timeframe_to_seconds(self._config.get('timeframe', '1h'))) - self._num_sources = len(self._config.get('external_signal', {}).get('leader_list', [])) - self._wait_data_policy = self._config.get('external_signal', {}).get( + self._num_sources = len( + self._config.get('external_message_consumer', {}).get('producers', []) + ) + self._wait_data_policy = self._config.get('external_message_consumer', {}).get( 'wait_data_policy', WaitDataPolicy.all) - self._wait_data_timeout = self._config.get( - 'external_signal', {}).get('wait_data_timeout', 5) + self._wait_data_timeout = self._config.get('external_message_consumer', {}).get( + 'wait_data_timeout', 5) def _set_dataframe_max_index(self, limit_index: int): """ diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index 406d847e6..229d770ce 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -3,7 +3,7 @@ from freqtrade.enums.backteststate import BacktestState from freqtrade.enums.candletype import CandleType from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType -from freqtrade.enums.externalsignal import ExternalSignalModeType, LeaderMessageType, WaitDataPolicy +from freqtrade.enums.externalmessages import WaitDataPolicy from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType diff --git a/freqtrade/enums/externalmessages.py b/freqtrade/enums/externalmessages.py new file mode 100644 index 000000000..e43899ab5 --- /dev/null +++ b/freqtrade/enums/externalmessages.py @@ -0,0 +1,7 @@ +from enum import Enum + + +class WaitDataPolicy(str, Enum): + none = "none" + one = "one" + all = "all" diff --git a/freqtrade/enums/externalsignal.py b/freqtrade/enums/externalsignal.py deleted file mode 100644 index 05dc604a2..000000000 --- a/freqtrade/enums/externalsignal.py +++ /dev/null @@ -1,18 +0,0 @@ -from enum import Enum - - -class ExternalSignalModeType(str, Enum): - leader = "leader" - follower = "follower" - - -class LeaderMessageType(str, Enum): - default = "default" - pairlist = "pairlist" - analyzed_df = "analyzed_df" - - -class WaitDataPolicy(str, Enum): - none = "none" - one = "one" - all = "all" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index c9caaace6..c0d658c61 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -30,6 +30,7 @@ from freqtrade.plugins.pairlistmanager import PairListManager from freqtrade.plugins.protectionmanager import ProtectionManager from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.rpc import RPCManager +from freqtrade.rpc.emc import ExternalMessageConsumer from freqtrade.strategy.interface import IStrategy from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.util import FtPrecise @@ -90,11 +91,17 @@ class FreqtradeBot(LoggingMixin): self.strategy.dp = self.dataprovider # Attach Wallets to strategy instance self.strategy.wallets = self.wallets + # Attach rpc to strategy instance + self.strategy.rpc = self.rpc # Initializing Edge only if enabled self.edge = Edge(self.config, self.exchange, self.strategy) if \ self.config.get('edge', {}).get('enabled', False) else None + # Init ExternalMessageConsumer if enabled + self.emc = ExternalMessageConsumer(self.rpc._rpc, self.config) if \ + self.config.get('external_message_consumer', {}).get('enabled', False) else None + self.active_pair_whitelist = self._refresh_active_whitelist() # Set initial bot state from config @@ -150,6 +157,8 @@ class FreqtradeBot(LoggingMixin): self.check_for_open_trades() self.rpc.cleanup() + if self.emc: + self.emc.shutdown() Trade.commit() self.exchange.close() @@ -192,7 +201,11 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - self.strategy.analyze(self.active_pair_whitelist) + if self.emc: + leader_pairs = self.pairlists._whitelist + self.strategy.analyze_external(self.active_pair_whitelist, leader_pairs) + else: + self.strategy.analyze(self.active_pair_whitelist) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace @@ -255,7 +268,7 @@ class FreqtradeBot(LoggingMixin): self.pairlists.refresh_pairlist() _whitelist = self.pairlists.whitelist - self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'msg': _whitelist}) + self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'data': _whitelist}) # Calculating Edge positioning if self.edge: diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index c8d1b70fa..88bae099a 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -26,7 +26,7 @@ async def message_endpoint( # Return a channel ID, pass that instead of ws to the rest of the methods channel = await channel_manager.on_connect(ws) - # Keep connection open until explicitly closed, and sleep + # Keep connection open until explicitly closed, and process requests try: while not channel.is_closed(): request = await channel.recv() diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index f4af8c8ed..e391e66af 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -112,9 +112,6 @@ class ApiServer(RPCHandler): # Cancel the queue task self._background_task.cancel() - # Finally stop the loop - self._loop.call_soon_threadsafe(self._loop.stop) - self._thread.join() @classmethod @@ -127,7 +124,6 @@ class ApiServer(RPCHandler): def send_msg(self, msg: Dict[str, str]) -> None: if self._queue: - logger.info(f"Adding message to queue: {msg}") sync_q = self._queue.sync_q sync_q.put(msg) @@ -155,9 +151,11 @@ class ApiServer(RPCHandler): app.include_router(api_backtest, prefix="/api/v1", dependencies=[Depends(http_basic_or_jwt_token)], ) - app.include_router(ws_router, prefix="/api/v1", - dependencies=[Depends(get_ws_token)] - ) + if self._config.get('api_server', {}).get('enable_message_ws', False): + logger.info("Enabling Message WebSocket") + app.include_router(ws_router, prefix="/api/v1", + dependencies=[Depends(get_ws_token)] + ) app.include_router(router_login, prefix="/api/v1", tags=["auth"]) # UI Router MUST be last! app.include_router(router_ui, prefix='') @@ -194,17 +192,19 @@ class ApiServer(RPCHandler): try: while True: - logger.debug("Getting queue data...") + logger.debug("Getting queue messages...") # Get data from queue - data = await async_queue.get() - logger.debug(f"Found data: {data}") + message = await async_queue.get() + logger.debug(f"Found message of type: {message.get('type')}") # Broadcast it - await self._channel_manager.broadcast(data) + await self._channel_manager.broadcast(message) # Sleep, make this configurable? await asyncio.sleep(0.1) except asyncio.CancelledError: - # Silently stop - pass + # Disconnect channels and stop the loop on cancel + await self._channel_manager.disconnect_all() + self._loop.stop() + # For testing, shouldn't happen when stable except Exception as e: logger.info(f"Exception happened in background task: {e}") @@ -246,7 +246,8 @@ class ApiServer(RPCHandler): if self._standalone: self._server.run() else: - self.start_message_queue() + if self._config.get('api_server', {}).get('enable_message_ws', False): + self.start_message_queue() self._server.run_in_thread() except Exception: logger.exception("Api server failed to start.") diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index f24713a77..6bc5b9d6b 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -116,8 +116,6 @@ class ChannelManager: with self._lock: channel = self.channels.get(websocket) if channel: - logger.debug(f"Disconnecting channel - {channel}") - if not channel.is_closed(): await channel.close() @@ -142,7 +140,6 @@ class ChannelManager: """ with self._lock: message_type = data.get('type') - logger.debug(f"Broadcasting data: {message_type} - {data}") for websocket, channel in self.channels.items(): try: if channel.subscribed_to(message_type): diff --git a/freqtrade/rpc/emc.py b/freqtrade/rpc/emc.py new file mode 100644 index 000000000..48ad78266 --- /dev/null +++ b/freqtrade/rpc/emc.py @@ -0,0 +1,229 @@ +""" +ExternalMessageConsumer module + +Main purpose is to connect to external bot's message websocket to consume data +from it +""" +import asyncio +import logging +import socket +from threading import Thread +from typing import Any, Dict + +import websockets + +from freqtrade.enums import RPCMessageType, RPCRequestType +from freqtrade.misc import json_to_dataframe, remove_entry_exit_signals +from freqtrade.rpc import RPC +from freqtrade.rpc.api_server.ws.channel import WebSocketChannel + + +logger = logging.getLogger(__name__) + + +class ExternalMessageConsumer: + """ + The main controller class for consuming external messages from + other FreqTrade bot's + """ + + def __init__( + self, + rpc: RPC, + config: Dict[str, Any], + ): + self._rpc = rpc + self._config = config + + self._running = False + self._thread = None + self._loop = None + self._main_task = None + self._sub_tasks = None + + self._emc_config = self._config.get('external_message_consumer', {}) + + self.enabled = self._emc_config.get('enabled', False) + self.producers = self._emc_config.get('producers', []) + + if self.enabled and len(self.producers) < 1: + raise ValueError("You must specify at least 1 Producer to connect to.") + + self.reply_timeout = self._emc_config.get('reply_timeout', 10) + self.ping_timeout = self._emc_config.get('ping_timeout', 2) + self.sleep_time = self._emc_config.get('sleep_time', 5) + + # Setting these explicitly as they probably shouldn't be changed by a user + # Unless we somehow integrate this with the strategy to allow creating + # callbacks for the messages + self.topics = [RPCMessageType.WHITELIST, RPCMessageType.ANALYZED_DF] + + self.start() + + def start(self): + """ + Start the main internal loop in another thread to run coroutines + """ + self._loop = asyncio.new_event_loop() + + if not self._thread: + logger.info("Starting ExternalMessageConsumer") + + self._thread = Thread(target=self._loop.run_forever) + self._thread.start() + self._running = True + else: + raise RuntimeError("A loop is already running") + + self._main_task = asyncio.run_coroutine_threadsafe(self._main(), loop=self._loop) + + def shutdown(self): + """ + Shutdown the loop, thread, and tasks + """ + if self._thread and self._loop: + logger.info("Stopping ExternalMessageConsumer") + + if self._sub_tasks: + # Cancel sub tasks + for task in self._sub_tasks: + task.cancel() + + if self._main_task: + # Cancel the main task + self._main_task.cancel() + + self._thread.join() + + async def _main(self): + """ + The main task coroutine + """ + rpc_lock = asyncio.Lock() + + try: + # Create a connection to each producer + self._sub_tasks = [ + self._loop.create_task(self._handle_producer_connection(producer, rpc_lock)) + for producer in self.producers + ] + + await asyncio.gather(*self._sub_tasks) + except asyncio.CancelledError: + pass + finally: + # Stop the loop once we are done + self._loop.stop() + + async def _handle_producer_connection(self, producer, lock): + """ + Main connection loop for the consumer + """ + try: + while True: + try: + url, token = producer['url'], producer['ws_token'] + ws_url = f"{url}?token={token}" + + async with websockets.connect(ws_url) as ws: + logger.info("Connection successful") + channel = WebSocketChannel(ws) + + # Tell the producer we only want these topics + # Should always be the first thing we send + await channel.send( + self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) + ) + + # Now receive data, if none is within the time limit, ping + while True: + try: + message = await asyncio.wait_for( + channel.recv(), + timeout=5 + ) + + async with lock: + # Handle the data here + # We use a lock because it will call RPC methods + self.handle_producer_message(message) + + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Check the connection and continue. + try: + # ping + ping = await channel.ping() + + await asyncio.wait_for(ping, timeout=self.ping_timeout) + logger.debug(f"Connection to {url} still alive...") + + continue + except Exception: + logger.info( + f"Ping error {url} - retrying in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + + break + except ( + socket.gaierror, + ConnectionRefusedError, + websockets.exceptions.InvalidStatusCode + ) as e: + logger.error(f"Connection Refused - {e} retrying in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + + continue + + except asyncio.CancelledError: + # Exit silently + pass + + def compose_consumer_request(self, type_: str, data: Any) -> Dict[str, Any]: + """ + Create a request for sending to a producer + + :param type_: The RPCRequestType + :param data: The data to send + :returns: Dict[str, Any] + """ + return {'type': type_, 'data': data} + + # How we do things here isn't set in stone. There seems to be some interest + # in figuring out a better way, but we shall do this for now. + def handle_producer_message(self, message: Dict[str, Any]): + """ + Handles external messages from a Producer + """ + # Should we have a default message type? + message_type = message.get('type', RPCMessageType.STATUS) + message_data = message.get('data') + + logger.debug(f"Received message of type {message_type}") + + # Handle Whitelists + if message_type == RPCMessageType.WHITELIST: + pairlist = message_data + + # Add the pairlist data to the ExternalPairlist plugin + external_pairlist = self._rpc._freqtrade.pairlists._pairlist_handlers[0] + external_pairlist.add_pairlist_data(pairlist) + + # Handle analyzed dataframes + elif message_type == RPCMessageType.ANALYZED_DF: + # This shouldn't happen + if message_data is None: + return + + key, value = message_data.get('key'), message_data.get('data') + pair, timeframe, candle_type = key + + # Convert the JSON to a pandas DataFrame + dataframe = json_to_dataframe(value) + + # If set, remove the Entry and Exit signals from the Producer + if self._emc_config.get('remove_entry_exit_signals', False): + dataframe = remove_entry_exit_signals(dataframe) + + # Add the dataframe to the dataprovider + dataprovider = self._rpc._freqtrade.dataprovider + dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) diff --git a/freqtrade/rpc/external_signal/__init__.py b/freqtrade/rpc/external_signal/__init__.py deleted file mode 100644 index decc51551..000000000 --- a/freqtrade/rpc/external_signal/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -# # flake8: noqa: F401 -# from freqtrade.rpc.external_signal.controller import ExternalSignalController -# -# -# __all__ = ('ExternalSignalController') diff --git a/freqtrade/rpc/external_signal/channel.py b/freqtrade/rpc/external_signal/channel.py deleted file mode 100644 index 5b278dfed..000000000 --- a/freqtrade/rpc/external_signal/channel.py +++ /dev/null @@ -1,145 +0,0 @@ -# import logging -# from threading import RLock -# from typing import Type -# -# from freqtrade.rpc.external_signal.proxy import WebSocketProxy -# from freqtrade.rpc.external_signal.serializer import MsgPackWebSocketSerializer -# from freqtrade.rpc.external_signal.types import WebSocketType -# -# -# logger = logging.getLogger(__name__) -# -# -# class WebSocketChannel: -# """ -# Object to help facilitate managing a websocket connection -# """ -# -# def __init__( -# self, -# websocket: WebSocketType, -# serializer_cls: Type[WebSocketSerializer] = MsgPackWebSocketSerializer -# ): -# # The WebSocket object -# self._websocket = WebSocketProxy(websocket) -# # The Serializing class for the WebSocket object -# self._serializer_cls = serializer_cls -# -# # Internal event to signify a closed websocket -# self._closed = False -# -# # Wrap the WebSocket in the Serializing class -# self._wrapped_ws = self._serializer_cls(self._websocket) -# -# async def send(self, data): -# """ -# Send data on the wrapped websocket -# """ -# # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") -# await self._wrapped_ws.send(data) -# -# async def recv(self): -# """ -# Receive data on the wrapped websocket -# """ -# return await self._wrapped_ws.recv() -# -# async def ping(self): -# """ -# Ping the websocket -# """ -# return await self._websocket.ping() -# -# async def close(self): -# """ -# Close the WebSocketChannel -# """ -# -# self._closed = True -# -# def is_closed(self): -# return self._closed -# -# -# class ChannelManager: -# def __init__(self): -# self.channels = dict() -# self._lock = RLock() # Re-entrant Lock -# -# async def on_connect(self, websocket: WebSocketType): -# """ -# Wrap websocket connection into Channel and add to list -# -# :param websocket: The WebSocket object to attach to the Channel -# """ -# if hasattr(websocket, "accept"): -# try: -# await websocket.accept() -# except RuntimeError: -# # The connection was closed before we could accept it -# return -# -# ws_channel = WebSocketChannel(websocket) -# -# with self._lock: -# self.channels[websocket] = ws_channel -# -# return ws_channel -# -# async def on_disconnect(self, websocket: WebSocketType): -# """ -# Call close on the channel if it's not, and remove from channel list -# -# :param websocket: The WebSocket objet attached to the Channel -# """ -# with self._lock: -# channel = self.channels.get(websocket) -# if channel: -# logger.debug(f"Disconnecting channel - {channel}") -# -# if not channel.is_closed(): -# await channel.close() -# -# del self.channels[websocket] -# -# async def disconnect_all(self): -# """ -# Disconnect all Channels -# """ -# with self._lock: -# for websocket, channel in self.channels.items(): -# if not channel.is_closed(): -# await channel.close() -# -# self.channels = dict() -# -# async def broadcast(self, data): -# """ -# Broadcast data on all Channels -# -# :param data: The data to send -# """ -# with self._lock: -# for websocket, channel in self.channels.items(): -# try: -# await channel.send(data) -# except RuntimeError: -# # Handle cannot send after close cases -# await self.on_disconnect(websocket) -# -# async def send_direct(self, channel, data): -# """ -# Send data directly through direct_channel only -# -# :param direct_channel: The WebSocketChannel object to send data through -# :param data: The data to send -# """ -# # We iterate over the channels to get reference to the websocket object -# # so we can disconnect incase of failure -# await channel.send(data) -# -# def has_channels(self): -# """ -# Flag for more than 0 channels -# """ -# return len(self.channels) > 0 diff --git a/freqtrade/rpc/external_signal/controller.py b/freqtrade/rpc/external_signal/controller.py deleted file mode 100644 index 616ea7801..000000000 --- a/freqtrade/rpc/external_signal/controller.py +++ /dev/null @@ -1,449 +0,0 @@ -# """ -# This module manages replicate mode communication -# """ -# import asyncio -# import logging -# import secrets -# import socket -# from threading import Thread -# from typing import Any, Callable, Coroutine, Dict, Union -# -# import websockets -# from fastapi import Depends -# from fastapi import WebSocket as FastAPIWebSocket -# from fastapi import WebSocketDisconnect, status -# from janus import Queue as ThreadedQueue -# -# from freqtrade.enums import ExternalSignalModeType, LeaderMessageType, RPCMessageType -# from freqtrade.rpc import RPC, RPCHandler -# from freqtrade.rpc.external_signal.channel import ChannelManager -# from freqtrade.rpc.external_signal.types import MessageType -# from freqtrade.rpc.external_signal.utils import is_websocket_alive -# -# -# logger = logging.getLogger(__name__) -# -# -# class ExternalSignalController(RPCHandler): -# """ This class handles all websocket communication """ -# -# def __init__( -# self, -# rpc: RPC, -# config: Dict[str, Any], -# api_server: Union[Any, None] = None -# ) -> None: -# """ -# Init the ExternalSignalController class, and init the super class RPCHandler -# :param rpc: instance of RPC Helper class -# :param config: Configuration object -# :param api_server: The ApiServer object -# :return: None -# """ -# super().__init__(rpc, config) -# -# self.freqtrade = rpc._freqtrade -# self.api_server = api_server -# -# if not self.api_server: -# raise RuntimeError("The API server must be enabled for external signals to work") -# -# self._loop = None -# self._running = False -# self._thread = None -# self._queue = None -# -# self._main_task = None -# self._sub_tasks = None -# -# self._message_handlers = { -# LeaderMessageType.pairlist: self._rpc._handle_pairlist_message, -# LeaderMessageType.analyzed_df: self._rpc._handle_analyzed_df_message, -# LeaderMessageType.default: self._rpc._handle_default_message -# } -# -# self.channel_manager = ChannelManager() -# self.external_signal_config = config.get('external_signal', {}) -# -# # What the config should look like -# # "external_signal": { -# # "enabled": true, -# # "mode": "follower", -# # "leaders": [ -# # { -# # "url": "ws://localhost:8080/signals/ws", -# # "api_token": "test" -# # } -# # ] -# # } -# -# # "external_signal": { -# # "enabled": true, -# # "mode": "leader", -# # "api_token": "test" -# # } -# -# self.mode = ExternalSignalModeType[ -# self.external_signal_config.get('mode', 'leader').lower() -# ] -# -# self.leaders_list = self.external_signal_config.get('leaders', []) -# self.push_throttle_secs = self.external_signal_config.get('push_throttle_secs', 0.1) -# -# self.reply_timeout = self.external_signal_config.get('follower_reply_timeout', 10) -# self.ping_timeout = self.external_signal_config.get('follower_ping_timeout', 2) -# self.sleep_time = self.external_signal_config.get('follower_sleep_time', 5) -# -# # Validate external_signal_config here? -# -# if self.mode == ExternalSignalModeType.follower and len(self.leaders_list) == 0: -# raise ValueError("You must specify at least 1 leader in follower mode.") -# -# # This is only used by the leader, the followers use the tokens specified -# # in each of the leaders -# # If you do not specify an API key in the config, one will be randomly -# # generated and logged on startup -# default_api_key = secrets.token_urlsafe(16) -# self.secret_api_key = self.external_signal_config.get('api_token', default_api_key) -# -# self.start() -# -# def is_leader(self): -# """ -# Leader flag -# """ -# return self.enabled() and self.mode == ExternalSignalModeType.leader -# -# def enabled(self): -# """ -# Enabled flag -# """ -# return self.external_signal_config.get('enabled', False) -# -# def num_leaders(self): -# """ -# The number of leaders we should be connected to -# """ -# return len(self.leaders_list) -# -# def start_threaded_loop(self): -# """ -# Start the main internal loop in another thread to run coroutines -# """ -# self._loop = asyncio.new_event_loop() -# -# if not self._thread: -# self._thread = Thread(target=self._loop.run_forever) -# self._thread.start() -# self._running = True -# else: -# raise RuntimeError("A loop is already running") -# -# def submit_coroutine(self, coroutine: Coroutine): -# """ -# Submit a coroutine to the threaded loop -# """ -# if not self._running: -# raise RuntimeError("Cannot schedule new futures after shutdown") -# -# if not self._loop or not self._loop.is_running(): -# raise RuntimeError("Loop must be started before any function can" -# " be submitted") -# -# return asyncio.run_coroutine_threadsafe(coroutine, self._loop) -# -# def start(self): -# """ -# Start the controller main loop -# """ -# self.start_threaded_loop() -# self._main_task = self.submit_coroutine(self.main()) -# -# async def shutdown(self): -# """ -# Shutdown all tasks and close up -# """ -# logger.info("Stopping rpc.externalsignalcontroller") -# -# # Flip running flag -# self._running = False -# -# # Cancel sub tasks -# for task in self._sub_tasks: -# task.cancel() -# -# # Then disconnect all channels -# await self.channel_manager.disconnect_all() -# -# def cleanup(self) -> None: -# """ -# Cleanup pending module resources. -# """ -# if self._thread: -# if self._loop.is_running(): -# self._main_task.cancel() -# self._thread.join() -# -# async def main(self): -# """ -# Main coro -# -# Start the loop based on what mode we're in -# """ -# try: -# if self.mode == ExternalSignalModeType.leader: -# logger.info("Starting rpc.externalsignalcontroller in Leader mode") -# -# await self.run_leader_mode() -# elif self.mode == ExternalSignalModeType.follower: -# logger.info("Starting rpc.externalsignalcontroller in Follower mode") -# -# await self.run_follower_mode() -# -# except asyncio.CancelledError: -# # We're cancelled -# await self.shutdown() -# except Exception as e: -# # Log the error -# logger.error(f"Exception occurred in main task: {e}") -# logger.exception(e) -# finally: -# # This coroutine is the last thing to be ended, so it should stop the loop -# self._loop.stop() -# -# def log_api_token(self): -# """ -# Log the API token -# """ -# logger.info("-" * 15) -# logger.info(f"API_KEY: {self.secret_api_key}") -# logger.info("-" * 15) -# -# def send_msg(self, msg: MessageType) -> None: -# """ -# Support RPC calls -# """ -# if msg["type"] == RPCMessageType.EMIT_DATA: -# message = msg.get("message") -# if message: -# self.send_message(message) -# else: -# logger.error(f"Message is empty! {msg}") -# -# def send_message(self, msg: MessageType) -> None: -# """ -# Broadcast message over all channels if there are any -# """ -# -# if self.channel_manager.has_channels(): -# self._send_message(msg) -# else: -# logger.debug("No listening followers, skipping...") -# pass -# -# def _send_message(self, msg: MessageType): -# """ -# Add data to the internal queue to be broadcasted. This func will block -# if the queue is full. This is meant to be called in the main thread. -# """ -# if self._queue: -# queue = self._queue.sync_q -# queue.put(msg) # This will block if the queue is full -# else: -# logger.warning("Can not send data, leader loop has not started yet!") -# -# async def send_initial_data(self, channel): -# logger.info("Sending initial data through channel") -# -# data = self._rpc._initial_leader_data() -# -# for message in data: -# await channel.send(message) -# -# async def _handle_leader_message(self, message: MessageType): -# """ -# Handle message received from a Leader -# """ -# type = message.get("data_type", LeaderMessageType.default) -# data = message.get("data") -# -# handler: Callable = self._message_handlers[type] -# handler(type, data) -# -# # ---------------------------------------------------------------------- -# -# async def run_leader_mode(self): -# """ -# Main leader coroutine -# -# This starts all of the leader coros and registers the endpoint on -# the ApiServer -# """ -# self.register_leader_endpoint() -# self.log_api_token() -# -# self._sub_tasks = [ -# self._loop.create_task(self._broadcast_queue_data()) -# ] -# -# return await asyncio.gather(*self._sub_tasks) -# -# async def run_follower_mode(self): -# """ -# Main follower coroutine -# -# This starts all of the follower connection coros -# """ -# -# rpc_lock = asyncio.Lock() -# -# self._sub_tasks = [ -# self._loop.create_task(self._handle_leader_connection(leader, rpc_lock)) -# for leader in self.leaders_list -# ] -# -# return await asyncio.gather(*self._sub_tasks) -# -# async def _broadcast_queue_data(self): -# """ -# Loop over queue data and broadcast it -# """ -# # Instantiate the queue in this coroutine so it's attached to our loop -# self._queue = ThreadedQueue() -# async_queue = self._queue.async_q -# -# try: -# while self._running: -# # Get data from queue -# data = await async_queue.get() -# -# # Broadcast it to everyone -# await self.channel_manager.broadcast(data) -# -# # Sleep -# await asyncio.sleep(self.push_throttle_secs) -# -# except asyncio.CancelledError: -# # Silently stop -# pass -# -# async def get_api_token( -# self, -# websocket: FastAPIWebSocket, -# token: Union[str, None] = None -# ): -# """ -# Extract the API key from query param. Must match the -# set secret_api_key or the websocket connection will be closed. -# """ -# if token == self.secret_api_key: -# return token -# else: -# logger.info("Denying websocket request...") -# await websocket.close(code=status.WS_1008_POLICY_VIOLATION) -# -# def register_leader_endpoint(self, path: str = "/signals/ws"): -# """ -# Attach and start the main leader loop to the ApiServer -# -# :param path: The endpoint path -# """ -# if not self.api_server: -# raise RuntimeError("The leader needs the ApiServer to be active") -# -# # The endpoint function for running the main leader loop -# @self.api_server.app.websocket(path) -# async def leader_endpoint( -# websocket: FastAPIWebSocket, -# api_key: str = Depends(self.get_api_token) -# ): -# await self.leader_endpoint_loop(websocket) -# -# async def leader_endpoint_loop(self, websocket: FastAPIWebSocket): -# """ -# The WebSocket endpoint served by the ApiServer. This handles connections, -# and adding them to the channel manager. -# """ -# try: -# if is_websocket_alive(websocket): -# logger.info(f"Follower connected - {websocket.client}") -# channel = await self.channel_manager.on_connect(websocket) -# -# # Send initial data here -# # Data is being broadcasted right away as soon as startup, -# # we may not have to send initial data at all. Further testing -# # required. -# await self.send_initial_data(channel) -# -# # Keep connection open until explicitly closed, and sleep -# try: -# while not channel.is_closed(): -# request = await channel.recv() -# logger.info(f"Follower request - {request}") -# -# except WebSocketDisconnect: -# # Handle client disconnects -# logger.info(f"Follower disconnected - {websocket.client}") -# await self.channel_manager.on_disconnect(websocket) -# except Exception as e: -# logger.info(f"Follower connection failed - {websocket.client}") -# logger.exception(e) -# # Handle cases like - -# # RuntimeError('Cannot call "send" once a closed message has been sent') -# await self.channel_manager.on_disconnect(websocket) -# -# except Exception: -# logger.error(f"Failed to serve - {websocket.client}") -# await self.channel_manager.on_disconnect(websocket) -# -# async def _handle_leader_connection(self, leader, lock): -# """ -# Given a leader, connect and wait on data. If connection is lost, -# it will attempt to reconnect. -# """ -# try: -# url, token = leader["url"], leader["api_token"] -# websocket_url = f"{url}?token={token}" -# -# logger.info(f"Attempting to connect to Leader at: {url}") -# while True: -# try: -# async with websockets.connect(websocket_url) as ws: -# channel = await self.channel_manager.on_connect(ws) -# logger.info(f"Connection to Leader at {url} successful") -# while True: -# try: -# data = await asyncio.wait_for( -# channel.recv(), -# timeout=self.reply_timeout -# ) -# except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): -# # We haven't received data yet. Check the connection and continue. -# try: -# # ping -# ping = await channel.ping() -# await asyncio.wait_for(ping, timeout=self.ping_timeout) -# logger.debug(f"Connection to {url} still alive...") -# continue -# except Exception: -# logger.info( -# f"Ping error {url} - retrying in {self.sleep_time}s") -# asyncio.sleep(self.sleep_time) -# break -# -# async with lock: -# # Acquire lock so only 1 coro handling at a time -# # as we call the RPC module in the main thread -# await self._handle_leader_message(data) -# -# except (socket.gaierror, ConnectionRefusedError): -# logger.info(f"Connection Refused - retrying connection in {self.sleep_time}s") -# await asyncio.sleep(self.sleep_time) -# continue -# except websockets.exceptions.InvalidStatusCode as e: -# logger.error(f"Connection Refused - {e}") -# await asyncio.sleep(self.sleep_time) -# continue -# -# except asyncio.CancelledError: -# pass diff --git a/freqtrade/rpc/external_signal/proxy.py b/freqtrade/rpc/external_signal/proxy.py deleted file mode 100644 index df2a07da0..000000000 --- a/freqtrade/rpc/external_signal/proxy.py +++ /dev/null @@ -1,61 +0,0 @@ -# from typing import Union -# -# from fastapi import WebSocket as FastAPIWebSocket -# from websockets import WebSocketClientProtocol as WebSocket -# -# from freqtrade.rpc.external_signal.types import WebSocketType -# -# -# class WebSocketProxy: -# """ -# WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol -# under the same API -# """ -# -# def __init__(self, websocket: WebSocketType): -# self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket -# -# async def send(self, data): -# """ -# Send data on the wrapped websocket -# """ -# if isinstance(data, str): -# data = data.encode() -# -# if hasattr(self._websocket, "send_bytes"): -# await self._websocket.send_bytes(data) -# else: -# await self._websocket.send(data) -# -# async def recv(self): -# """ -# Receive data on the wrapped websocket -# """ -# if hasattr(self._websocket, "receive_bytes"): -# return await self._websocket.receive_bytes() -# else: -# return await self._websocket.recv() -# -# async def ping(self): -# """ -# Ping the websocket, not supported by FastAPI WebSockets -# """ -# if hasattr(self._websocket, "ping"): -# return await self._websocket.ping() -# return False -# -# async def close(self, code: int = 1000): -# """ -# Close the websocket connection, only supported by FastAPI WebSockets -# """ -# if hasattr(self._websocket, "close"): -# return await self._websocket.close(code) -# pass -# -# async def accept(self): -# """ -# Accept the WebSocket connection, only support by FastAPI WebSockets -# """ -# if hasattr(self._websocket, "accept"): -# return await self._websocket.accept() -# pass diff --git a/freqtrade/rpc/external_signal/serializer.py b/freqtrade/rpc/external_signal/serializer.py deleted file mode 100644 index a23469ef4..000000000 --- a/freqtrade/rpc/external_signal/serializer.py +++ /dev/null @@ -1,65 +0,0 @@ -# import json -# import logging -# from abc import ABC, abstractmethod -# -# import msgpack -# import orjson -# -# from freqtrade.rpc.external_signal.proxy import WebSocketProxy -# -# -# logger = logging.getLogger(__name__) -# -# -# class WebSocketSerializer(ABC): -# def __init__(self, websocket: WebSocketProxy): -# self._websocket: WebSocketProxy = websocket -# -# @abstractmethod -# def _serialize(self, data): -# raise NotImplementedError() -# -# @abstractmethod -# def _deserialize(self, data): -# raise NotImplementedError() -# -# async def send(self, data: bytes): -# await self._websocket.send(self._serialize(data)) -# -# async def recv(self) -> bytes: -# data = await self._websocket.recv() -# -# return self._deserialize(data) -# -# async def close(self, code: int = 1000): -# await self._websocket.close(code) -# -# # Going to explore using MsgPack as the serialization, -# # as that might be the best method for sending pandas -# # dataframes over the wire -# -# -# class JSONWebSocketSerializer(WebSocketSerializer): -# def _serialize(self, data): -# return json.dumps(data) -# -# def _deserialize(self, data): -# return json.loads(data) -# -# -# class ORJSONWebSocketSerializer(WebSocketSerializer): -# ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY -# -# def _serialize(self, data): -# return orjson.dumps(data, option=self.ORJSON_OPTIONS) -# -# def _deserialize(self, data): -# return orjson.loads(data, option=self.ORJSON_OPTIONS) -# -# -# class MsgPackWebSocketSerializer(WebSocketSerializer): -# def _serialize(self, data): -# return msgpack.packb(data, use_bin_type=True) -# -# def _deserialize(self, data): -# return msgpack.unpackb(data, raw=False) diff --git a/freqtrade/rpc/external_signal/types.py b/freqtrade/rpc/external_signal/types.py deleted file mode 100644 index 38e43f667..000000000 --- a/freqtrade/rpc/external_signal/types.py +++ /dev/null @@ -1,8 +0,0 @@ -# from typing import Any, Dict, TypeVar -# -# from fastapi import WebSocket as FastAPIWebSocket -# from websockets import WebSocketClientProtocol as WebSocket -# -# -# WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) -# MessageType = Dict[str, Any] diff --git a/freqtrade/rpc/external_signal/utils.py b/freqtrade/rpc/external_signal/utils.py deleted file mode 100644 index 72c8d2ef8..000000000 --- a/freqtrade/rpc/external_signal/utils.py +++ /dev/null @@ -1,10 +0,0 @@ -# from starlette.websockets import WebSocket, WebSocketState -# -# -# async def is_websocket_alive(ws: WebSocket) -> bool: -# if ( -# ws.application_state == WebSocketState.CONNECTED and -# ws.client_state == WebSocketState.CONNECTED -# ): -# return True -# return False diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index f684c7783..a41d08d55 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1099,65 +1099,3 @@ class RPC: if all([any(x.value == topic for x in RPCMessageType) for topic in data]): logger.debug(f"{channel} subscribed to topics: {data}") channel.set_subscriptions(data) - # - # # ------------------------------ EXTERNAL SIGNALS ----------------------- - # - # def _initial_leader_data(self): - # # We create a list of Messages to send to the follower on connect - # data = [] - # - # # Send Pairlist data - # data.append({ - # "data_type": LeaderMessageType.pairlist, - # "data": self._freqtrade.pairlists._whitelist - # }) - # - # return data - # - # def _handle_pairlist_message(self, type, data): - # """ - # Handles the emitted pairlists from the Leaders - # - # :param type: The data_type of the data - # :param data: The data - # """ - # pairlist = data - # - # logger.debug(f"Handling Pairlist message: {pairlist}") - # - # external_pairlist = self._freqtrade.pairlists._pairlist_handlers[0] - # external_pairlist.add_pairlist_data(pairlist) - # - # def _handle_analyzed_df_message(self, type, data): - # """ - # Handles the analyzed dataframes from the Leaders - # - # :param type: The data_type of the data - # :param data: The data - # """ - # key, value = data["key"], data["value"] - # pair, timeframe, candle_type = key - # - # # Skip any pairs that we don't have in the pairlist? - # # leader_pairlist = self._freqtrade.pairlists._whitelist - # # if pair not in leader_pairlist: - # # return - # - # dataframe = json_to_dataframe(value) - # - # if self._config.get('external_signal', {}).get('remove_signals_analyzed_df', False): - # dataframe = remove_entry_exit_signals(dataframe) - # - # logger.debug(f"Handling analyzed dataframe for {pair}") - # logger.debug(dataframe.tail()) - # - # # Add the dataframe to the dataprovider - # dataprovider = self._freqtrade.dataprovider - # dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) - # - # def _handle_default_message(self, type, data): - # """ - # Default leader message handler, just logs it. We should never have to - # run this unless the leader sends us some weird message. - # """ - # logger.debug(f"Received message from Leader of type {type}: {data}") diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index b3cd5604c..3488a6e3c 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -78,7 +78,9 @@ class RPCManager: 'status': 'stopping bot' } """ - logger.info('Sending rpc message: %s', msg) + # Removed actually showing the message because the logs would be + # completely spammed of the json dataframe + logger.info('Sending rpc message of type: %s', msg.get('type')) if 'pair' in msg: msg.update({ 'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair']) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 22a10b4d3..7120928ff 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -5,19 +5,21 @@ This module defines the interface to apply for strategies import logging from abc import ABC, abstractmethod from datetime import datetime, timedelta, timezone -from typing import Callable, Dict, List, Optional, Tuple, Union +from typing import Dict, List, Optional, Tuple, Union import arrow from pandas import DataFrame from freqtrade.constants import ListPairsWithTimeframes from freqtrade.data.dataprovider import DataProvider -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, SignalTagType, - SignalType, TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RPCMessageType, SignalDirection, + SignalTagType, SignalType, TradingMode) from freqtrade.enums.runmode import RunMode from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds +from freqtrade.misc import dataframe_to_json, remove_entry_exit_signals from freqtrade.persistence import Order, PairLocks, Trade +from freqtrade.rpc import RPCManager from freqtrade.strategy.hyper import HyperStrategyMixin from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators, _create_and_merge_informative_pair, @@ -111,6 +113,7 @@ class IStrategy(ABC, HyperStrategyMixin): # and wallets - access to the current balance. dp: DataProvider wallets: Optional[Wallets] = None + rpc: RPCManager # Filled from configuration stake_currency: str # container variable for strategy source code @@ -702,8 +705,7 @@ class IStrategy(ABC, HyperStrategyMixin): self, dataframe: DataFrame, metadata: dict, - external_data: bool = False, - finish_callback: Optional[Callable] = None, + external_data: bool = False ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame @@ -729,17 +731,20 @@ class IStrategy(ABC, HyperStrategyMixin): candle_type = self.config.get('candle_type_def', CandleType.SPOT) self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) - if finish_callback: - finish_callback(pair, dataframe, self.timeframe, candle_type) + if not external_data: + self.rpc.send_msg( + { + 'type': RPCMessageType.ANALYZED_DF, + 'data': { + 'key': (pair, self.timeframe, candle_type), + 'value': dataframe_to_json(dataframe) + } + } + ) else: logger.debug("Skipping TA Analysis for already analyzed candle") - dataframe[SignalType.ENTER_LONG.value] = 0 - dataframe[SignalType.EXIT_LONG.value] = 0 - dataframe[SignalType.ENTER_SHORT.value] = 0 - dataframe[SignalType.EXIT_SHORT.value] = 0 - dataframe[SignalTagType.ENTER_TAG.value] = None - dataframe[SignalTagType.EXIT_TAG.value] = None + dataframe = remove_entry_exit_signals(dataframe) logger.debug("Loop Analysis Launched") @@ -748,8 +753,7 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze_pair( self, pair: str, - external_data: bool = False, - finish_callback: Optional[Callable] = None, + external_data: bool = False ) -> None: """ Fetch data for this pair from dataprovider and analyze. @@ -773,7 +777,7 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = strategy_safe_wrapper( self._analyze_ticker_internal, message="" - )(dataframe, {'pair': pair}, external_data, finish_callback) + )(dataframe, {'pair': pair}, external_data) self.assert_df(dataframe, df_len, df_close, df_date) except StrategyError as error: @@ -786,15 +790,14 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze( self, - pairs: List[str], - finish_callback: Optional[Callable] = None + pairs: List[str] ) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze """ for pair in pairs: - self.analyze_pair(pair, finish_callback=finish_callback) + self.analyze_pair(pair) def analyze_external(self, pairs: List[str], leader_pairs: List[str]) -> None: """ @@ -808,10 +811,10 @@ class IStrategy(ABC, HyperStrategyMixin): # them normally. # List order is not preserved when doing this! # We use ^ instead of - for symmetric difference - # What do we do with these? extra_pairs = list(set(pairs) ^ set(leader_pairs)) # These would be the pairs that we have trades in, which means # we would have to analyze them normally + # Eventually maybe request data from the Leader if we don't have it? for pair in leader_pairs: # Analyze the pairs, but get the dataframe from the external data diff --git a/scripts/test_ws_client.py b/scripts/test_ws_client.py deleted file mode 100644 index 872ff3ccf..000000000 --- a/scripts/test_ws_client.py +++ /dev/null @@ -1,74 +0,0 @@ -import asyncio -import logging -import socket -from typing import Any - -import websockets - -from freqtrade.enums import RPCMessageType -from freqtrade.rpc.api_server.ws.channel import WebSocketChannel - - -logging.basicConfig(level=logging.DEBUG) -logger = logging.getLogger(__name__) - - -def compose_consumer_request(type_: str, data: Any): - return {"type": type_, "data": data} - - -async def _client(): - # Trying to recreate multiple topic issue. Wait until first whitelist message, - # then CTRL-C to get the status message. - topics = [RPCMessageType.WHITELIST, RPCMessageType.STATUS] - try: - while True: - try: - url = "ws://localhost:8080/api/v1/message/ws?token=testtoken" - async with websockets.connect(url) as ws: - channel = WebSocketChannel(ws) - - logger.info("Connection successful") - # Tell the producer we only want these topics - await channel.send(compose_consumer_request("subscribe", topics)) - - while True: - try: - data = await asyncio.wait_for( - channel.recv(), - timeout=5 - ) - logger.info(f"Data received - {data}") - except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): - # We haven't received data yet. Check the connection and continue. - try: - # ping - ping = await channel.ping() - await asyncio.wait_for(ping, timeout=2) - logger.debug(f"Connection to {url} still alive...") - continue - except Exception: - logger.info( - f"Ping error {url} - retrying in 5s") - await asyncio.sleep(2) - break - - except (socket.gaierror, ConnectionRefusedError): - logger.info("Connection Refused - retrying connection in 5s") - await asyncio.sleep(2) - continue - except websockets.exceptions.InvalidStatusCode as e: - logger.error(f"Connection Refused - {e}") - await asyncio.sleep(2) - continue - - except (asyncio.CancelledError, KeyboardInterrupt): - pass - - -def main(): - asyncio.run(_client()) - - -if __name__ == "__main__": - main() From ddc45ce2ebe57c670a6419a724cc10b7b127e7ad Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 30 Aug 2022 19:30:14 -0600 Subject: [PATCH 110/592] message handling fix, data waiting fix --- freqtrade/data/dataprovider.py | 5 ++++- freqtrade/rpc/emc.py | 25 +++++++++++++++---------- 2 files changed, 19 insertions(+), 11 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 430ee0932..2d473683c 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -168,7 +168,10 @@ class DataProvider: timeout_str = f"for {timeout} seconds" if timeout > 0 else "indefinitely" logger.debug(f"Waiting for external data on {pair} for {timeout_str}") - pair_event.wait(timeout=timeout) + if timeout > 0: + pair_event.wait(timeout=timeout) + else: + pair_event.wait() def add_pairlisthandler(self, pairlists) -> None: """ diff --git a/freqtrade/rpc/emc.py b/freqtrade/rpc/emc.py index 48ad78266..ee4d9e6b8 100644 --- a/freqtrade/rpc/emc.py +++ b/freqtrade/rpc/emc.py @@ -164,6 +164,9 @@ class ExternalMessageConsumer: await asyncio.sleep(self.sleep_time) break + except Exception as e: + logger.exception(e) + continue except ( socket.gaierror, ConnectionRefusedError, @@ -214,16 +217,18 @@ class ExternalMessageConsumer: if message_data is None: return - key, value = message_data.get('key'), message_data.get('data') - pair, timeframe, candle_type = key + key, value = message_data.get('key'), message_data.get('value') - # Convert the JSON to a pandas DataFrame - dataframe = json_to_dataframe(value) + if key and value: + pair, timeframe, candle_type = key - # If set, remove the Entry and Exit signals from the Producer - if self._emc_config.get('remove_entry_exit_signals', False): - dataframe = remove_entry_exit_signals(dataframe) + # Convert the JSON to a pandas DataFrame + dataframe = json_to_dataframe(value) - # Add the dataframe to the dataprovider - dataprovider = self._rpc._freqtrade.dataprovider - dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) + # If set, remove the Entry and Exit signals from the Producer + if self._emc_config.get('remove_entry_exit_signals', False): + dataframe = remove_entry_exit_signals(dataframe) + + # Add the dataframe to the dataprovider + dataprovider = self._rpc._freqtrade.dataprovider + dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) From 115a901773c63cb4d207e6039e9bed05f260ef7f Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 30 Aug 2022 19:34:43 -0600 Subject: [PATCH 111/592] minor fix for conditional in handle func --- freqtrade/rpc/emc.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/rpc/emc.py b/freqtrade/rpc/emc.py index ee4d9e6b8..42061079a 100644 --- a/freqtrade/rpc/emc.py +++ b/freqtrade/rpc/emc.py @@ -201,6 +201,10 @@ class ExternalMessageConsumer: message_type = message.get('type', RPCMessageType.STATUS) message_data = message.get('data') + # We shouldn't get empty messages + if message_data is None: + return + logger.debug(f"Received message of type {message_type}") # Handle Whitelists @@ -213,10 +217,6 @@ class ExternalMessageConsumer: # Handle analyzed dataframes elif message_type == RPCMessageType.ANALYZED_DF: - # This shouldn't happen - if message_data is None: - return - key, value = message_data.get('key'), message_data.get('value') if key and value: From 4aec2db14dadb7e2fec6a6d883a6a7f3e48dd311 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 31 Aug 2022 08:18:28 +0000 Subject: [PATCH 112/592] Remove isClose from tests in favor of pytest.approx --- tests/data/test_btanalysis.py | 5 ++- tests/exchange/test_exchange.py | 45 ++++++++++++------------- tests/leverage/test_interest.py | 6 ++-- tests/strategy/test_strategy_helpers.py | 4 +-- tests/test_persistence.py | 7 ++-- 5 files changed, 30 insertions(+), 37 deletions(-) diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index 977140ebb..72084d067 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -1,4 +1,3 @@ -from math import isclose from pathlib import Path from unittest.mock import MagicMock @@ -269,7 +268,7 @@ def test_create_cum_profit(testdatadir): "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 - assert isclose(cum_profits.iloc[-1]['cum_profits'], 8.723007518796964e-06) + assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 8.723007518796964e-06 def test_create_cum_profit1(testdatadir): @@ -287,7 +286,7 @@ def test_create_cum_profit1(testdatadir): "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 - assert isclose(cum_profits.iloc[-1]['cum_profits'], 8.723007518796964e-06) + assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 8.723007518796964e-06 with pytest.raises(ValueError, match='Trade dataframe empty.'): create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'NOTAPAIR'], diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 800aa5381..5456b3098 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2,7 +2,6 @@ import copy import logging from copy import deepcopy from datetime import datetime, timedelta, timezone -from math import isclose from random import randint from unittest.mock import MagicMock, Mock, PropertyMock, patch @@ -407,10 +406,10 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: # min result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) expected_result = 2 * (1 + 0.05) / (1 - abs(stoploss)) - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss, 3.0) - assert isclose(result, expected_result / 3) + assert pytest.approx(result) == expected_result / 3 # max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 10000 @@ -426,10 +425,10 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) expected_result = 2 * 2 * (1 + 0.05) / (1 - abs(stoploss)) - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 5.0) - assert isclose(result, expected_result / 5) + assert pytest.approx(result) == expected_result / 5 # max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 20000 @@ -445,10 +444,10 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) expected_result = max(2, 2 * 2) * (1 + 0.05) / (1 - abs(stoploss)) - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 10) - assert isclose(result, expected_result / 10) + assert pytest.approx(result) == expected_result / 10 # min amount and cost are set (amount is minial) markets["ETH/BTC"]["limits"] = { @@ -461,20 +460,20 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) expected_result = max(8, 2 * 2) * (1 + 0.05) / (1 - abs(stoploss)) - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 7.0) - assert isclose(result, expected_result / 7.0) + assert pytest.approx(result) == expected_result / 7.0 # Max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 1000 result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -0.4) expected_result = max(8, 2 * 2) * 1.5 - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -0.4, 8.0) - assert isclose(result, expected_result / 8.0) + assert pytest.approx(result) == expected_result / 8.0 # Max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 1000 @@ -482,10 +481,10 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: # Really big stoploss result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1) expected_result = max(8, 2 * 2) * 1.5 - assert isclose(result, expected_result) + assert pytest.approx(result) == expected_result # With Leverage result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1, 12.0) - assert isclose(result, expected_result / 12) + assert pytest.approx(result) == expected_result / 12 # Max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 1000 @@ -501,7 +500,7 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: # Contract size 0.01 result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1) - assert isclose(result, expected_result * 0.01) + assert pytest.approx(result) == expected_result * 0.01 # Max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 10 @@ -513,7 +512,7 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None: ) # With Leverage, Contract size 10 result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1, 12.0) - assert isclose(result, (expected_result / 12) * 10.0) + assert pytest.approx(result) == (expected_result / 12) * 10.0 # Max result = exchange.get_max_pair_stake_amount('ETH/BTC', 2) assert result == 10000 @@ -3239,7 +3238,7 @@ def test_get_trades_for_order(default_conf, mocker, exchange_name, trading_mode, orders = exchange.get_trades_for_order(order_id, 'ETH/USDT:USDT', since) assert len(orders) == 1 assert orders[0]['price'] == 165 - assert isclose(orders[0]['amount'], amount) + assert pytest.approx(orders[0]['amount']) == amount assert api_mock.fetch_my_trades.call_count == 1 # since argument should be assert isinstance(api_mock.fetch_my_trades.call_args[0][1], int) @@ -3776,8 +3775,8 @@ def test__get_funding_fees_from_exchange(default_conf, mocker, exchange_name): since=unix_time ) - assert (isclose(expected_fees, fees_from_datetime)) - assert (isclose(expected_fees, fees_from_unix_time)) + assert pytest.approx(expected_fees) == fees_from_datetime + assert pytest.approx(expected_fees) == fees_from_unix_time ccxt_exceptionhandlers( mocker, @@ -4514,7 +4513,7 @@ def test_liquidation_price( default_conf['liquidation_buffer'] = 0.0 exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(mm_ratio, maintenance_amt)) - assert isclose(round(exchange.get_liquidation_price( + assert pytest.approx(round(exchange.get_liquidation_price( pair='DOGE/USDT', open_rate=open_rate, is_short=is_short, @@ -4523,7 +4522,7 @@ def test_liquidation_price( upnl_ex_1=upnl_ex_1, amount=amount, stake_amount=open_rate * amount, - ), 2), expected) + ), 2)) == expected def test_get_max_pair_stake_amount( @@ -4868,8 +4867,8 @@ def test_get_max_leverage_futures(default_conf, mocker, leverage_tiers): assert exchange.get_max_leverage("BNB/BUSD", 1.0) == 20.0 assert exchange.get_max_leverage("BNB/USDT", 100.0) == 75.0 assert exchange.get_max_leverage("BTC/USDT", 170.30) == 125.0 - assert isclose(exchange.get_max_leverage("BNB/BUSD", 99999.9), 5.000005) - assert isclose(exchange.get_max_leverage("BNB/USDT", 1500), 33.333333333333333) + assert pytest.approx(exchange.get_max_leverage("BNB/BUSD", 99999.9)) == 5.000005 + assert pytest.approx(exchange.get_max_leverage("BNB/USDT", 1500)) == 33.333333333333333 assert exchange.get_max_leverage("BTC/USDT", 300000000) == 2.0 assert exchange.get_max_leverage("BTC/USDT", 600000000) == 1.0 # Last tier @@ -5145,7 +5144,7 @@ def test_get_liquidation_price( else: buffer_amount = liquidation_buffer * abs(open_rate - expected_liq) expected_liq = expected_liq - buffer_amount if is_short else expected_liq + buffer_amount - assert isclose(expected_liq, liq) + assert pytest.approx(expected_liq) == liq @pytest.mark.parametrize('contract_size,order_amount', [ diff --git a/tests/leverage/test_interest.py b/tests/leverage/test_interest.py index 7bdf4c2f0..64e99b6b4 100644 --- a/tests/leverage/test_interest.py +++ b/tests/leverage/test_interest.py @@ -1,5 +1,3 @@ -from math import isclose - import pytest from freqtrade.leverage import interest @@ -30,9 +28,9 @@ twentyfive_hours = FtPrecise(25.0) def test_interest(exchange, interest_rate, hours, expected): borrowed = FtPrecise(60.0) - assert isclose(interest( + assert pytest.approx(float(interest( exchange_name=exchange, borrowed=borrowed, rate=FtPrecise(interest_rate), hours=hours - ), expected) + ))) == expected diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py index 244fd3919..a7c2da26a 100644 --- a/tests/strategy/test_strategy_helpers.py +++ b/tests/strategy/test_strategy_helpers.py @@ -1,5 +1,3 @@ -from math import isclose - import numpy as np import pandas as pd import pytest @@ -165,7 +163,7 @@ def test_stoploss_from_open(): or (side == 'short' and expected_stop_price < current_price)): assert stoploss == 0 else: - assert isclose(stop_price, expected_stop_price, rel_tol=0.00001) + assert pytest.approx(stop_price) == expected_stop_price def test_stoploss_from_absolute(): diff --git a/tests/test_persistence.py b/tests/test_persistence.py index 2460fde68..f16c8b054 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -1,7 +1,6 @@ # pragma pylint: disable=missing-docstring, C0103 import logging from datetime import datetime, timedelta, timezone -from math import isclose from pathlib import Path from types import FunctionType from unittest.mock import MagicMock @@ -630,9 +629,9 @@ def test_calc_open_close_trade_price( trade.open_rate = 2.0 trade.close_rate = 2.2 trade.recalc_open_trade_value() - assert isclose(trade._calc_open_trade_value(trade.amount, trade.open_rate), open_value) - assert isclose(trade.calc_close_trade_value(trade.close_rate), close_value) - assert isclose(trade.calc_profit(trade.close_rate), round(profit, 8)) + assert pytest.approx(trade._calc_open_trade_value(trade.amount, trade.open_rate)) == open_value + assert pytest.approx(trade.calc_close_trade_value(trade.close_rate)) == close_value + assert pytest.approx(trade.calc_profit(trade.close_rate)) == round(profit, 8) assert pytest.approx(trade.calc_profit_ratio(trade.close_rate)) == profit_ratio From 7ba4fda5d7c4f472bb61bf03fe91e7f2b1564762 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 31 Aug 2022 10:26:47 +0000 Subject: [PATCH 113/592] Implement PR feedback --- freqtrade/freqai/utils.py | 12 ++++-------- tests/freqai/test_freqai_backtesting.py | 6 ------ 2 files changed, 4 insertions(+), 14 deletions(-) diff --git a/freqtrade/freqai/utils.py b/freqtrade/freqai/utils.py index d56702049..6081b6ce5 100644 --- a/freqtrade/freqai/utils.py +++ b/freqtrade/freqai/utils.py @@ -22,21 +22,17 @@ def download_all_data_for_training(dp: DataProvider, config: dict) -> None: :param dp: DataProvider instance attached to the strategy """ - if dp._exchange is not None: - markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) - or config.get('include_inactive')] - else: - # This should not occur: + if dp._exchange is None: raise OperationalException('No exchange object found.') + markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m) + or config.get('include_inactive')] all_pairs = dynamic_expand_pairlist(config, markets) timerange = get_required_data_timerange(config) new_pairs_days = int((timerange.stopts - timerange.startts) / 86400) - if not dp._exchange: - # Not realistic - this is only called in live mode. - raise OperationalException("Dataprovider did not have an exchange attached.") + refresh_backtest_ohlcv_data( dp._exchange, pairs=all_pairs, diff --git a/tests/freqai/test_freqai_backtesting.py b/tests/freqai/test_freqai_backtesting.py index c8a51edb0..ea127fa99 100644 --- a/tests/freqai/test_freqai_backtesting.py +++ b/tests/freqai/test_freqai_backtesting.py @@ -48,10 +48,4 @@ def test_freqai_backtest_load_data(freqai_conf, mocker, caplog): assert log_has_re('Increasing startup_candle_count for freqai to.*', caplog) - # del freqai_conf['freqai']['startup_candles'] - # backtesting = Backtesting(freqai_conf) - # with pytest.raises(OperationalException, - # match=r'FreqAI backtesting module.*startup_candles in config.'): - # backtesting.load_bt_data() - Backtesting.cleanup() From 13ccd940d5e9d9bacedb896cbe4859217f487dde Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 31 Aug 2022 10:26:58 +0000 Subject: [PATCH 114/592] Remove startup_candle_count from freqai sample config to avoid confusion --- config_examples/config_freqai.example.json | 8 +++++--- freqtrade/templates/FreqaiHybridExampleStrategy.py | 1 - 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index 7112fc225..13c7a94ea 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -9,7 +9,6 @@ "dry_run": true, "timeframe": "3m", "dry_run_wallet": 1000, - "startup_candle_count": 20, "cancel_open_orders_on_exit": true, "unfilledtimeout": { "entry": 10, @@ -76,7 +75,10 @@ "principal_component_analysis": false, "use_SVM_to_remove_outliers": true, "indicator_max_period_candles": 20, - "indicator_periods_candles": [10, 20] + "indicator_periods_candles": [ + 10, + 20 + ] }, "data_split_parameters": { "test_size": 0.33, @@ -92,4 +94,4 @@ "internals": { "process_throttle_secs": 5 } -} +} \ No newline at end of file diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index 0a91455f5..5d1e149dd 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -45,7 +45,6 @@ class FreqaiExampleHybridStrategy(IStrategy): "weight_factor": 0.9, "principal_component_analysis": false, "use_SVM_to_remove_outliers": true, - "indicator_max_period_candles": 20, "indicator_periods_candles": [10, 20] }, "data_split_parameters": { From 57ff6f8ac592678c5399e83e75656c66076bd863 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 31 Aug 2022 10:28:31 +0000 Subject: [PATCH 115/592] Init timerange object properly --- freqtrade/freqai/utils.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqai/utils.py b/freqtrade/freqai/utils.py index 6081b6ce5..6a70f050f 100644 --- a/freqtrade/freqai/utils.py +++ b/freqtrade/freqai/utils.py @@ -55,7 +55,6 @@ def get_required_data_timerange( for auto data-download in FreqAI """ time = datetime.now(tz=timezone.utc).timestamp() - data_load_timerange = TimeRange() timeframes = config["freqai"]["feature_parameters"].get("include_timeframes") @@ -75,12 +74,13 @@ def get_required_data_timerange( additional_seconds = max_period * max_tf_seconds - data_load_timerange.startts = int( + startts = int( time - config["freqai"].get("train_period_days", 0) * 86400 - additional_seconds ) - data_load_timerange.stopts = int(time) + stopts = int(time) + data_load_timerange = TimeRange('date', 'date', startts, stopts) return data_load_timerange From df51da22ee699e9a362d980747dba28e578d6c47 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 31 Aug 2022 11:23:48 -0300 Subject: [PATCH 116/592] refactoring freqai backtesting --- freqtrade/freqai/data_kitchen.py | 37 ++++++++++- freqtrade/freqai/freqai_interface.py | 98 ++++++++++++++++++++++++---- 2 files changed, 119 insertions(+), 16 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 763a07375..80b795b8e 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1,6 +1,7 @@ import copy import datetime import logging +import os import shutil from pathlib import Path from typing import Any, Dict, List, Tuple @@ -780,9 +781,10 @@ class FreqaiDataKitchen: weights = np.exp(-np.arange(num_weights) / (wfactor * num_weights))[::-1] return weights - def append_predictions(self, predictions: DataFrame, do_predict: npt.ArrayLike) -> None: + def get_predictions_to_append(self, predictions: DataFrame, + do_predict: npt.ArrayLike) -> DataFrame: """ - Append backtest prediction from current backtest period to all previous periods + Get backtest prediction from current backtest period """ append_df = DataFrame() @@ -797,12 +799,19 @@ class FreqaiDataKitchen: if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0: append_df["DI_values"] = self.DI_values + return append_df + + def append_predictions(self, append_df: DataFrame) -> None: + """ + Append backtest prediction from current backtest period to all previous periods + """ + if self.full_df.empty: self.full_df = append_df else: self.full_df = pd.concat([self.full_df, append_df], axis=0) - return + return append_df def fill_predictions(self, dataframe): """ @@ -1089,3 +1098,25 @@ class FreqaiDataKitchen: if self.unique_classes: for label in self.unique_classes: self.unique_class_list += list(self.unique_classes[label]) + + def save_backtesting_prediction( + self, file_name: str, root_folder: str, append_df: DataFrame + ) -> None: + + """ + Save prediction dataframe from backtesting to h5 file format + :param file_name: h5 file name + :param root_folder: folder to save h5 file + """ + os.makedirs(root_folder, exist_ok=True) + append_df.to_hdf(file_name, key='append_df', mode='w') + + def get_backtesting_prediction(self, prediction_file_name: str) -> DataFrame: + """ + Retrive from disk the prediction dataframe + :param prediction_file_name: prediction file full path + :return: + :Dataframe: Backtesting prediction from current backtesting period + """ + append_df = pd.read_hdf(prediction_file_name) + return append_df diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 4106f24e0..d396113e8 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -224,28 +224,50 @@ class IFreqaiModel(ABC): "trains" ) + trained_timestamp_int = int(trained_timestamp.stopts) dk.data_path = Path( dk.full_path / - f"sub-train-{metadata['pair'].split('/')[0]}_{int(trained_timestamp.stopts)}" + f"sub-train-{metadata['pair'].split('/')[0]}_{trained_timestamp_int}" ) - if not self.model_exists( - metadata["pair"], dk, trained_timestamp=int(trained_timestamp.stopts) + + if self.backtest_prediction_exists( + metadata["pair"], dk, trained_timestamp=trained_timestamp_int ): - dk.find_features(dataframe_train) - self.model = self.train(dataframe_train, metadata["pair"], dk) - self.dd.pair_dict[metadata["pair"]]["trained_timestamp"] = int( - trained_timestamp.stopts) - dk.set_new_model_names(metadata["pair"], trained_timestamp) - self.dd.save_data(self.model, metadata["pair"], dk) + prediction_filename, _ = self.get_backtesting_prediction_file_name( + metadata["pair"], + dk, + trained_timestamp=int(trained_timestamp.stopts)) + + append_df = dk.get_backtesting_prediction(prediction_filename) + dk.append_predictions(append_df) else: - self.model = self.dd.load_data(metadata["pair"], dk) + if not self.model_exists( + metadata["pair"], dk, trained_timestamp=trained_timestamp_int + ): + dk.find_features(dataframe_train) + self.model = self.train(dataframe_train, metadata["pair"], dk) + self.dd.pair_dict[metadata["pair"]]["trained_timestamp"] = int( + trained_timestamp.stopts) + dk.set_new_model_names(metadata["pair"], trained_timestamp) + self.dd.save_data(self.model, metadata["pair"], dk) + else: + self.model = self.dd.load_data(metadata["pair"], dk) - self.check_if_feature_list_matches_strategy(dataframe_train, dk) + self.check_if_feature_list_matches_strategy(dataframe_train, dk) - pred_df, do_preds = self.predict(dataframe_backtest, dk) + pred_df, do_preds = self.predict(dataframe_backtest, dk) + append_df = dk.get_predictions_to_append(pred_df, do_preds) + dk.append_predictions(append_df) - dk.append_predictions(pred_df, do_preds) + prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name( + metadata["pair"], + dk, + trained_timestamp_int) + + dk.save_backtesting_prediction(prediction_file_name, + root_prediction, + append_df) dk.fill_predictions(dataframe) @@ -643,6 +665,56 @@ class IFreqaiModel(ABC): self.train_time = 0 return + def backtest_prediction_exists( + self, + pair: str, + dk: FreqaiDataKitchen, + trained_timestamp: int, + scanning: bool = False, + ) -> bool: + """ + Given a pair and path, check if a backtesting prediction already exists + :param pair: pair e.g. BTC/USD + :param path: path to prediction + :return: + :boolean: whether the prediction file exists or not. + """ + if not self.live: + prediction_file_name, _ = self.get_backtesting_prediction_file_name( + pair, dk, trained_timestamp + ) + path_to_predictionfile = Path(prediction_file_name) + + file_exists = path_to_predictionfile.is_file() + if file_exists and not scanning: + logger.info("Found backtesting prediction file at %s", prediction_file_name) + elif not scanning: + logger.info( + "Could not find backtesting prediction file at %s", prediction_file_name + ) + return file_exists + else: + return False + + def get_backtesting_prediction_file_name( + self, pair: str, dk: FreqaiDataKitchen, trained_timestamp: int + ): + """ + Given a pair, path and a trained timestamp, + returns the path and name of the predictions file + :param pair: pair e.g. BTC/USD + :param dk: FreqaiDataKitchen + :trained_timestamp: current backtesting timestamp period + :return: + :str: prediction file name + :str: prediction root path + """ + coin, _ = pair.split("/") + prediction_base_filename = f"{coin.lower()}_{trained_timestamp}" + root_prediction = f'{dk.full_path}/backtesting_predictions' + prediction_file_name = f"{root_prediction}/{prediction_base_filename}_predictions.h5" + return prediction_file_name, root_prediction + # Following methods which are overridden by user made prediction models. # See freqai/prediction_models/CatboostPredictionModel.py for an example. From 510cf4f30507ed4763d13e12a41e12ceb59a6748 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 31 Aug 2022 10:40:26 -0600 Subject: [PATCH 117/592] remove data waiting, remove explicit analyzing of external df --- freqtrade/data/dataprovider.py | 107 +++++++++---------- freqtrade/enums/__init__.py | 1 - freqtrade/enums/externalmessages.py | 7 -- freqtrade/freqtradebot.py | 16 ++- freqtrade/rpc/api_server/api_ws.py | 37 +++++-- freqtrade/rpc/emc.py | 153 +++++++++++++++------------- freqtrade/rpc/rpc.py | 14 +-- freqtrade/strategy/interface.py | 54 ++-------- 8 files changed, 182 insertions(+), 207 deletions(-) delete mode 100644 freqtrade/enums/externalmessages.py diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 2d473683c..9376c0b33 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -7,7 +7,6 @@ Common Interface for bot and strategy to access data. import logging from collections import deque from datetime import datetime, timezone -from threading import Event from typing import Any, Dict, List, Optional, Tuple from pandas import DataFrame @@ -15,9 +14,11 @@ from pandas import DataFrame from freqtrade.configuration import TimeRange from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe from freqtrade.data.history import load_pair_history -from freqtrade.enums import CandleType, RunMode, WaitDataPolicy +from freqtrade.enums import CandleType, RPCMessageType, RunMode from freqtrade.exceptions import ExchangeError, OperationalException from freqtrade.exchange import Exchange, timeframe_to_seconds +from freqtrade.misc import dataframe_to_json +from freqtrade.rpc import RPCManager from freqtrade.util import PeriodicCache @@ -33,16 +34,18 @@ class DataProvider: self, config: dict, exchange: Optional[Exchange], + rpc: Optional[RPCManager] = None, pairlists=None ) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists + self.__rpc = rpc self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} self.__slice_index: Optional[int] = None self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {} self.__external_pairs_df: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} - self.__external_pairs_event: Dict[PairWithTimeframe, Tuple[int, Event]] = {} + self.__producer_pairs: List[str] = [] self._msg_queue: deque = deque() self.__msg_cache = PeriodicCache( @@ -51,10 +54,7 @@ class DataProvider: self._num_sources = len( self._config.get('external_message_consumer', {}).get('producers', []) ) - self._wait_data_policy = self._config.get('external_message_consumer', {}).get( - 'wait_data_policy', WaitDataPolicy.all) - self._wait_data_timeout = self._config.get('external_message_consumer', {}).get( - 'wait_data_timeout', 5) + self.external_data_enabled = self._num_sources > 0 def _set_dataframe_max_index(self, limit_index: int): """ @@ -83,6 +83,46 @@ class DataProvider: self.__cached_pairs[pair_key] = ( dataframe, datetime.now(timezone.utc)) + # For multiple producers we will want to merge the pairlists instead of overwriting + def set_producer_pairs(self, pairlist: List[str]): + """ + Set the pairs received to later be used. + This only supports 1 Producer right now. + + :param pairlist: List of pairs + """ + self.__producer_pairs = pairlist.copy() + + def get_producer_pairs(self) -> List[str]: + """ + Get the pairs cached from the producer + + :returns: List of pairs + """ + return self.__producer_pairs + + def emit_df( + self, + pair_key: PairWithTimeframe, + dataframe: DataFrame + ) -> None: + """ + Send this dataframe as an ANALYZED_DF message to RPC + + :param pair_key: PairWithTimeframe tuple + :param data: Tuple containing the DataFrame and the datetime it was cached + """ + if self.__rpc: + self.__rpc.send_msg( + { + 'type': RPCMessageType.ANALYZED_DF, + 'data': { + 'key': pair_key, + 'value': dataframe_to_json(dataframe) + } + } + ) + def add_external_df( self, pair: str, @@ -101,7 +141,6 @@ class DataProvider: # For multiple leaders, if the data already exists, we'd merge self.__external_pairs_df[pair_key] = (dataframe, datetime.now(timezone.utc)) - self._set_data_event(pair_key) def get_external_df( self, @@ -120,59 +159,11 @@ class DataProvider: pair_key = (pair, timeframe, candle_type) if pair_key not in self.__external_pairs_df: - self._wait_on_data(pair_key) - - if pair_key not in self.__external_pairs_df: - return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) + return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) return self.__external_pairs_df[pair_key] - def _set_data_event(self, key: PairWithTimeframe): - """ - Depending on the WaitDataPolicy, if an event exists for this PairWithTimeframe - then set the event to release main thread from waiting. - - :param key: PairWithTimeframe - """ - pair_event = self.__external_pairs_event.get(key) - - if pair_event: - num_concat, event = pair_event - self.__external_pairs_event[key] = (num_concat + 1, event) - - if self._wait_data_policy == WaitDataPolicy.one: - logger.debug("Setting Data as policy is One") - event.set() - elif self._wait_data_policy == WaitDataPolicy.all and num_concat == self._num_sources: - logger.debug("Setting Data as policy is all, and is complete") - event.set() - - del self.__external_pairs_event[key] - - def _wait_on_data(self, key: PairWithTimeframe): - """ - Depending on the WaitDataPolicy, we will create and wait on an event until - set that determines the full amount of data is available - - :param key: PairWithTimeframe - """ - if self._wait_data_policy is not WaitDataPolicy.none: - pair, timeframe, candle_type = key - - pair_event = Event() - self.__external_pairs_event[key] = (0, pair_event) - - timeout = self._wait_data_timeout \ - if self._wait_data_policy is not WaitDataPolicy.all else 0 - - timeout_str = f"for {timeout} seconds" if timeout > 0 else "indefinitely" - logger.debug(f"Waiting for external data on {pair} for {timeout_str}") - - if timeout > 0: - pair_event.wait(timeout=timeout) - else: - pair_event.wait() - def add_pairlisthandler(self, pairlists) -> None: """ Allow adding pairlisthandler after initialization diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py index 229d770ce..d32e04e17 100644 --- a/freqtrade/enums/__init__.py +++ b/freqtrade/enums/__init__.py @@ -3,7 +3,6 @@ from freqtrade.enums.backteststate import BacktestState from freqtrade.enums.candletype import CandleType from freqtrade.enums.exitchecktuple import ExitCheckTuple from freqtrade.enums.exittype import ExitType -from freqtrade.enums.externalmessages import WaitDataPolicy from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.ordertypevalue import OrderTypeValues from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType diff --git a/freqtrade/enums/externalmessages.py b/freqtrade/enums/externalmessages.py deleted file mode 100644 index e43899ab5..000000000 --- a/freqtrade/enums/externalmessages.py +++ /dev/null @@ -1,7 +0,0 @@ -from enum import Enum - - -class WaitDataPolicy(str, Enum): - none = "none" - one = "one" - all = "all" diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index c0d658c61..f7b7ad80b 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -85,21 +85,19 @@ class FreqtradeBot(LoggingMixin): # Keep this at the end of this initialization method. self.rpc: RPCManager = RPCManager(self) - self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists) + self.dataprovider = DataProvider(self.config, self.exchange, self.rpc, self.pairlists) # Attach Dataprovider to strategy instance self.strategy.dp = self.dataprovider # Attach Wallets to strategy instance self.strategy.wallets = self.wallets - # Attach rpc to strategy instance - self.strategy.rpc = self.rpc # Initializing Edge only if enabled self.edge = Edge(self.config, self.exchange, self.strategy) if \ self.config.get('edge', {}).get('enabled', False) else None # Init ExternalMessageConsumer if enabled - self.emc = ExternalMessageConsumer(self.rpc._rpc, self.config) if \ + self.emc = ExternalMessageConsumer(self.config, self.dataprovider) if \ self.config.get('external_message_consumer', {}).get('enabled', False) else None self.active_pair_whitelist = self._refresh_active_whitelist() @@ -201,11 +199,11 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - if self.emc: - leader_pairs = self.pairlists._whitelist - self.strategy.analyze_external(self.active_pair_whitelist, leader_pairs) - else: - self.strategy.analyze(self.active_pair_whitelist) + # This just means we won't broadcast dataframes if we're listening to a producer + # Doesn't necessarily NEED to be this way, as maybe we'd like to broadcast + # even if we are using external dataframes in the future. + self.strategy.analyze(self.active_pair_whitelist, + external_data=self.dataprovider.external_data_enabled) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 88bae099a..d7c7239d1 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -1,22 +1,48 @@ import logging +from typing import Any, Dict from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect -from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc_optional +from freqtrade.enums import RPCMessageType, RPCRequestType +from freqtrade.rpc.api_server.deps import get_channel_manager +from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws.utils import is_websocket_alive +# from typing import Any, Dict + + logger = logging.getLogger(__name__) # Private router, protected by API Key authentication router = APIRouter() +# We are passed a Channel object, we can only do sync functions on that channel object +def _process_consumer_request(request: Dict[str, Any], channel: WebSocketChannel): + type, data = request.get('type'), request.get('data') + + # If the request is empty, do nothing + if not data: + return + + # If we have a request of type SUBSCRIBE, set the topics in this channel + if type == RPCRequestType.SUBSCRIBE: + if isinstance(data, list): + logger.error(f"Improper request from channel: {channel} - {request}") + return + + # If all topics passed are a valid RPCMessageType, set subscriptions on channel + if all([any(x.value == topic for x in RPCMessageType) for topic in data]): + + logger.debug(f"{channel} subscribed to topics: {data}") + channel.set_subscriptions(data) + + @router.websocket("/message/ws") async def message_endpoint( ws: WebSocket, - channel_manager=Depends(get_channel_manager), - rpc=Depends(get_rpc_optional) + channel_manager=Depends(get_channel_manager) ): try: if is_websocket_alive(ws): @@ -32,9 +58,8 @@ async def message_endpoint( request = await channel.recv() # Process the request here. Should this be a method of RPC? - if rpc: - logger.info(f"Request: {request}") - rpc._process_consumer_request(request, channel) + logger.info(f"Request: {request}") + _process_consumer_request(request, channel) except WebSocketDisconnect: # Handle client disconnects diff --git a/freqtrade/rpc/emc.py b/freqtrade/rpc/emc.py index 42061079a..3d78bc257 100644 --- a/freqtrade/rpc/emc.py +++ b/freqtrade/rpc/emc.py @@ -12,9 +12,9 @@ from typing import Any, Dict import websockets +from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.misc import json_to_dataframe, remove_entry_exit_signals -from freqtrade.rpc import RPC from freqtrade.rpc.api_server.ws.channel import WebSocketChannel @@ -29,11 +29,11 @@ class ExternalMessageConsumer: def __init__( self, - rpc: RPC, config: Dict[str, Any], + dataprovider: DataProvider ): - self._rpc = rpc self._config = config + self._dp = dataprovider self._running = False self._thread = None @@ -99,12 +99,12 @@ class ExternalMessageConsumer: """ The main task coroutine """ - rpc_lock = asyncio.Lock() + lock = asyncio.Lock() try: # Create a connection to each producer self._sub_tasks = [ - self._loop.create_task(self._handle_producer_connection(producer, rpc_lock)) + self._loop.create_task(self._handle_producer_connection(producer, lock)) for producer in self.producers ] @@ -115,73 +115,90 @@ class ExternalMessageConsumer: # Stop the loop once we are done self._loop.stop() - async def _handle_producer_connection(self, producer, lock): + async def _handle_producer_connection(self, producer: Dict[str, Any], lock: asyncio.Lock): """ Main connection loop for the consumer + + :param producer: Dictionary containing producer info: {'url': '', 'ws_token': ''} + :param lock: An asyncio Lock """ try: - while True: - try: - url, token = producer['url'], producer['ws_token'] - ws_url = f"{url}?token={token}" - - async with websockets.connect(ws_url) as ws: - logger.info("Connection successful") - channel = WebSocketChannel(ws) - - # Tell the producer we only want these topics - # Should always be the first thing we send - await channel.send( - self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) - ) - - # Now receive data, if none is within the time limit, ping - while True: - try: - message = await asyncio.wait_for( - channel.recv(), - timeout=5 - ) - - async with lock: - # Handle the data here - # We use a lock because it will call RPC methods - self.handle_producer_message(message) - - except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): - # We haven't received data yet. Check the connection and continue. - try: - # ping - ping = await channel.ping() - - await asyncio.wait_for(ping, timeout=self.ping_timeout) - logger.debug(f"Connection to {url} still alive...") - - continue - except Exception: - logger.info( - f"Ping error {url} - retrying in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - - break - except Exception as e: - logger.exception(e) - continue - except ( - socket.gaierror, - ConnectionRefusedError, - websockets.exceptions.InvalidStatusCode - ) as e: - logger.error(f"Connection Refused - {e} retrying in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - - continue - + await self._create_connection(producer, lock) except asyncio.CancelledError: # Exit silently pass - def compose_consumer_request(self, type_: str, data: Any) -> Dict[str, Any]: + async def _create_connection(self, producer: Dict[str, Any], lock: asyncio.Lock): + """ + Actually creates and handles the websocket connection, pinging on timeout + and handling connection errors. + + :param producer: Dictionary containing producer info: {'url': '', 'ws_token': ''} + :param lock: An asyncio Lock + """ + while self._running: + try: + url, token = producer['url'], producer['ws_token'] + ws_url = f"{url}?token={token}" + + # This will raise InvalidURI if the url is bad + async with websockets.connect(ws_url) as ws: + logger.info("Connection successful") + channel = WebSocketChannel(ws) + + # Tell the producer we only want these topics + # Should always be the first thing we send + await channel.send( + self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) + ) + + # Now receive data, if none is within the time limit, ping + while True: + try: + message = await asyncio.wait_for( + channel.recv(), + timeout=self.reply_timeout + ) + + async with lock: + # Handle the message + self.handle_producer_message(message) + + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Check the connection and continue. + try: + # ping + ping = await channel.ping() + + await asyncio.wait_for(ping, timeout=self.ping_timeout) + logger.debug(f"Connection to {url} still alive...") + + continue + except Exception: + logger.info( + f"Ping error {url} - retrying in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + + break + except Exception as e: + logger.exception(e) + continue + except ( + socket.gaierror, + ConnectionRefusedError, + websockets.exceptions.InvalidStatusCode + ) as e: + logger.error(f"Connection Refused - {e} retrying in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + + continue + + # Catch invalid ws_url, and break the loop + except websockets.exceptions.InvalidURI as e: + logger.error(f"{ws_url} is an invalid WebSocket URL - {e}") + break + + def compose_consumer_request(self, type_: RPCRequestType, data: Any) -> Dict[str, Any]: """ Create a request for sending to a producer @@ -211,9 +228,8 @@ class ExternalMessageConsumer: if message_type == RPCMessageType.WHITELIST: pairlist = message_data - # Add the pairlist data to the ExternalPairlist plugin - external_pairlist = self._rpc._freqtrade.pairlists._pairlist_handlers[0] - external_pairlist.add_pairlist_data(pairlist) + # Add the pairlist data to the DataProvider + self._dp.set_producer_pairs(pairlist) # Handle analyzed dataframes elif message_type == RPCMessageType.ANALYZED_DF: @@ -230,5 +246,4 @@ class ExternalMessageConsumer: dataframe = remove_entry_exit_signals(dataframe) # Add the dataframe to the dataprovider - dataprovider = self._rpc._freqtrade.dataprovider - dataprovider.add_external_df(pair, timeframe, dataframe, candle_type) + self._dp.add_external_df(pair, timeframe, dataframe, candle_type) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index a41d08d55..ed7f13a96 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -19,8 +19,8 @@ from freqtrade.configuration.timerange import TimeRange from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT from freqtrade.data.history import load_data from freqtrade.data.metrics import calculate_max_drawdown -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RPCMessageType, RPCRequestType, - SignalDirection, State, TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State, + TradingMode) from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler @@ -1089,13 +1089,3 @@ class RPC: 'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT), 'last_process_ts': int(last_p.timestamp()), } - - # We are passed a Channel object, we can only do sync functions on that channel object - def _process_consumer_request(self, request, channel): - # Should we ensure that request is Dict[str, Any]? - type, data = request.get('type'), request.get('data') - - if type == RPCRequestType.SUBSCRIBE: - if all([any(x.value == topic for x in RPCMessageType) for topic in data]): - logger.debug(f"{channel} subscribed to topics: {data}") - channel.set_subscriptions(data) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 7120928ff..a06b6506e 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -12,14 +12,13 @@ from pandas import DataFrame from freqtrade.constants import ListPairsWithTimeframes from freqtrade.data.dataprovider import DataProvider -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RPCMessageType, SignalDirection, - SignalTagType, SignalType, TradingMode) +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, SignalTagType, + SignalType, TradingMode) from freqtrade.enums.runmode import RunMode from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds -from freqtrade.misc import dataframe_to_json, remove_entry_exit_signals +from freqtrade.misc import remove_entry_exit_signals from freqtrade.persistence import Order, PairLocks, Trade -from freqtrade.rpc import RPCManager from freqtrade.strategy.hyper import HyperStrategyMixin from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators, _create_and_merge_informative_pair, @@ -113,7 +112,6 @@ class IStrategy(ABC, HyperStrategyMixin): # and wallets - access to the current balance. dp: DataProvider wallets: Optional[Wallets] = None - rpc: RPCManager # Filled from configuration stake_currency: str # container variable for strategy source code @@ -731,16 +729,8 @@ class IStrategy(ABC, HyperStrategyMixin): candle_type = self.config.get('candle_type_def', CandleType.SPOT) self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) - if not external_data: - self.rpc.send_msg( - { - 'type': RPCMessageType.ANALYZED_DF, - 'data': { - 'key': (pair, self.timeframe, candle_type), - 'value': dataframe_to_json(dataframe) - } - } - ) + if populate_indicators: + self.dp.emit_df((pair, self.timeframe, candle_type), dataframe) else: logger.debug("Skipping TA Analysis for already analyzed candle") @@ -763,10 +753,7 @@ class IStrategy(ABC, HyperStrategyMixin): """ candle_type = self.config.get('candle_type_def', CandleType.SPOT) - if not external_data: - dataframe = self.dp.ohlcv(pair, self.timeframe, candle_type) - else: - dataframe, _ = self.dp.get_external_df(pair, self.timeframe, candle_type) + dataframe = self.dp.ohlcv(pair, self.timeframe, candle_type) if not isinstance(dataframe, DataFrame) or dataframe.empty: logger.warning('Empty candle (OHLCV) data for pair %s', pair) @@ -790,38 +777,15 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze( self, - pairs: List[str] + pairs: List[str], + external_data: bool = False ) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze """ for pair in pairs: - self.analyze_pair(pair) - - def analyze_external(self, pairs: List[str], leader_pairs: List[str]) -> None: - """ - Analyze the pre-populated dataframes from the Leader - - :param pairs: The active pair whitelist - :param leader_pairs: The list of pairs from the Leaders - """ - - # Get the extra pairs not listed in Leader pairs, and process - # them normally. - # List order is not preserved when doing this! - # We use ^ instead of - for symmetric difference - extra_pairs = list(set(pairs) ^ set(leader_pairs)) - # These would be the pairs that we have trades in, which means - # we would have to analyze them normally - # Eventually maybe request data from the Leader if we don't have it? - - for pair in leader_pairs: - # Analyze the pairs, but get the dataframe from the external data - self.analyze_pair(pair, external_data=True) - - for pair in extra_pairs: - self.analyze_pair(pair) + self.analyze_pair(pair, external_data) @ staticmethod def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]: From 865b34cd6f91972cb252fff97d7d3ca1248976bd Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 31 Aug 2022 11:43:02 -0600 Subject: [PATCH 118/592] add producer names --- freqtrade/constants.py | 1 + freqtrade/data/dataprovider.py | 36 ++++++++++++------- freqtrade/freqtradebot.py | 7 ++-- .../{emc.py => external_message_consumer.py} | 10 +++--- freqtrade/strategy/interface.py | 21 +++++------ tests/rpc/test_rpc_telegram.py | 7 ++-- 6 files changed, 46 insertions(+), 36 deletions(-) rename freqtrade/rpc/{emc.py => external_message_consumer.py} (95%) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index c7f2acc84..2e580acf5 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -498,6 +498,7 @@ CONF_SCHEMA = { 'items': { 'type': 'object', 'properties': { + 'name': {'type': 'string'}, 'url': {'type': 'string', 'default': ''}, 'ws_token': {'type': 'string', 'default': ''}, } diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 9376c0b33..947387f75 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -34,8 +34,8 @@ class DataProvider: self, config: dict, exchange: Optional[Exchange], - rpc: Optional[RPCManager] = None, - pairlists=None + pairlists=None, + rpc: Optional[RPCManager] = None ) -> None: self._config = config self._exchange = exchange @@ -44,8 +44,9 @@ class DataProvider: self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} self.__slice_index: Optional[int] = None self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {} - self.__external_pairs_df: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} - self.__producer_pairs: List[str] = [] + self.__producer_pairs_df: Dict[str, + Dict[PairWithTimeframe, Tuple[DataFrame, datetime]]] = {} + self.__producer_pairs: Dict[str, List[str]] = {} self._msg_queue: deque = deque() self.__msg_cache = PeriodicCache( @@ -84,22 +85,22 @@ class DataProvider: dataframe, datetime.now(timezone.utc)) # For multiple producers we will want to merge the pairlists instead of overwriting - def set_producer_pairs(self, pairlist: List[str]): + def set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"): """ Set the pairs received to later be used. This only supports 1 Producer right now. :param pairlist: List of pairs """ - self.__producer_pairs = pairlist.copy() + self.__producer_pairs[producer_name] = pairlist.copy() - def get_producer_pairs(self) -> List[str]: + def get_producer_pairs(self, producer_name: str = "default") -> List[str]: """ Get the pairs cached from the producer :returns: List of pairs """ - return self.__producer_pairs + return self.__producer_pairs.get(producer_name, []) def emit_df( self, @@ -129,6 +130,7 @@ class DataProvider: timeframe: str, dataframe: DataFrame, candle_type: CandleType, + producer_name: str = "default" ) -> None: """ Add the pair data to this class from an external source. @@ -139,15 +141,19 @@ class DataProvider: """ pair_key = (pair, timeframe, candle_type) + if producer_name not in self.__producer_pairs_df: + self.__producer_pairs_df[producer_name] = {} + # For multiple leaders, if the data already exists, we'd merge - self.__external_pairs_df[pair_key] = (dataframe, datetime.now(timezone.utc)) + self.__producer_pairs_df[producer_name][pair_key] = (dataframe, datetime.now(timezone.utc)) def get_external_df( self, pair: str, timeframe: str, - candle_type: CandleType - ) -> DataFrame: + candle_type: CandleType, + producer_name: str = "default" + ) -> Tuple[DataFrame, datetime]: """ Get the pair data from the external sources. Will wait if the policy is set to, and data is not available. @@ -158,11 +164,15 @@ class DataProvider: """ pair_key = (pair, timeframe, candle_type) - if pair_key not in self.__external_pairs_df: + if producer_name not in self.__producer_pairs_df: # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) - return self.__external_pairs_df[pair_key] + if pair_key not in self.__producer_pairs_df: + # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) + return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + + return self.__producer_pairs_df[producer_name][pair_key] def add_pairlisthandler(self, pairlists) -> None: """ diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index f7b7ad80b..19c77d403 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -30,7 +30,7 @@ from freqtrade.plugins.pairlistmanager import PairListManager from freqtrade.plugins.protectionmanager import ProtectionManager from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.rpc import RPCManager -from freqtrade.rpc.emc import ExternalMessageConsumer +from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer from freqtrade.strategy.interface import IStrategy from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.util import FtPrecise @@ -85,7 +85,7 @@ class FreqtradeBot(LoggingMixin): # Keep this at the end of this initialization method. self.rpc: RPCManager = RPCManager(self) - self.dataprovider = DataProvider(self.config, self.exchange, self.rpc, self.pairlists) + self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists, self.rpc) # Attach Dataprovider to strategy instance self.strategy.dp = self.dataprovider @@ -202,8 +202,9 @@ class FreqtradeBot(LoggingMixin): # This just means we won't broadcast dataframes if we're listening to a producer # Doesn't necessarily NEED to be this way, as maybe we'd like to broadcast # even if we are using external dataframes in the future. + self.strategy.analyze(self.active_pair_whitelist, - external_data=self.dataprovider.external_data_enabled) + emit_df=self.dataprovider.external_data_enabled) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace diff --git a/freqtrade/rpc/emc.py b/freqtrade/rpc/external_message_consumer.py similarity index 95% rename from freqtrade/rpc/emc.py rename to freqtrade/rpc/external_message_consumer.py index 3d78bc257..ae72089b5 100644 --- a/freqtrade/rpc/emc.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -162,7 +162,7 @@ class ExternalMessageConsumer: async with lock: # Handle the message - self.handle_producer_message(message) + self.handle_producer_message(producer, message) except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): # We haven't received data yet. Check the connection and continue. @@ -210,10 +210,11 @@ class ExternalMessageConsumer: # How we do things here isn't set in stone. There seems to be some interest # in figuring out a better way, but we shall do this for now. - def handle_producer_message(self, message: Dict[str, Any]): + def handle_producer_message(self, producer: Dict[str, Any], message: Dict[str, Any]): """ Handles external messages from a Producer """ + producer_name = producer.get('name', 'default') # Should we have a default message type? message_type = message.get('type', RPCMessageType.STATUS) message_data = message.get('data') @@ -229,7 +230,7 @@ class ExternalMessageConsumer: pairlist = message_data # Add the pairlist data to the DataProvider - self._dp.set_producer_pairs(pairlist) + self._dp.set_producer_pairs(pairlist, producer_name=producer_name) # Handle analyzed dataframes elif message_type == RPCMessageType.ANALYZED_DF: @@ -246,4 +247,5 @@ class ExternalMessageConsumer: dataframe = remove_entry_exit_signals(dataframe) # Add the dataframe to the dataprovider - self._dp.add_external_df(pair, timeframe, dataframe, candle_type) + self._dp.add_external_df(pair, timeframe, dataframe, + candle_type, producer_name=producer_name) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index a06b6506e..34e475ed7 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -682,8 +682,7 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze_ticker( self, dataframe: DataFrame, - metadata: dict, - populate_indicators: bool = True + metadata: dict ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame @@ -693,8 +692,7 @@ class IStrategy(ABC, HyperStrategyMixin): :return: DataFrame of candle (OHLCV) data with indicator data and signals added """ logger.debug("TA Analysis Launched") - if populate_indicators: - dataframe = self.advise_indicators(dataframe, metadata) + dataframe = self.advise_indicators(dataframe, metadata) dataframe = self.advise_entry(dataframe, metadata) dataframe = self.advise_exit(dataframe, metadata) return dataframe @@ -703,7 +701,7 @@ class IStrategy(ABC, HyperStrategyMixin): self, dataframe: DataFrame, metadata: dict, - external_data: bool = False + emit_df: bool = False ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame @@ -720,16 +718,15 @@ class IStrategy(ABC, HyperStrategyMixin): if (not self.process_only_new_candles or self._last_candle_seen_per_pair.get(pair, None) != dataframe.iloc[-1]['date']): - populate_indicators = not external_data # Defs that only make change on new candle data. - dataframe = self.analyze_ticker(dataframe, metadata, populate_indicators) + dataframe = self.analyze_ticker(dataframe, metadata) self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date'] candle_type = self.config.get('candle_type_def', CandleType.SPOT) self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) - if populate_indicators: + if emit_df: self.dp.emit_df((pair, self.timeframe, candle_type), dataframe) else: @@ -743,7 +740,7 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze_pair( self, pair: str, - external_data: bool = False + emit_df: bool = False ) -> None: """ Fetch data for this pair from dataprovider and analyze. @@ -764,7 +761,7 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = strategy_safe_wrapper( self._analyze_ticker_internal, message="" - )(dataframe, {'pair': pair}, external_data) + )(dataframe, {'pair': pair}, emit_df) self.assert_df(dataframe, df_len, df_close, df_date) except StrategyError as error: @@ -778,14 +775,14 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze( self, pairs: List[str], - external_data: bool = False + emit_df: bool = False ) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze """ for pair in pairs: - self.analyze_pair(pair, external_data) + self.analyze_pair(pair, emit_df) @ staticmethod def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]: diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py index a30115bd9..c7ae7cb74 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -2138,10 +2138,9 @@ def test_send_msg_strategy_msg_notification(default_conf, mocker) -> None: def test_send_msg_unknown_type(default_conf, mocker) -> None: telegram, _, _ = get_telegram_testobject(mocker, default_conf) - with pytest.raises(NotImplementedError, match=r'Unknown message type: None'): - telegram.send_msg({ - 'type': None, - }) + telegram.send_msg({ + 'type': None, + }) @pytest.mark.parametrize('message_type,enter,enter_signal,leverage', [ From 6e8abf8674b143fcee50e38c8ecb44081f31d347 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 31 Aug 2022 11:58:58 -0600 Subject: [PATCH 119/592] add producer name to required fields in config --- freqtrade/constants.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 2e580acf5..6bacaf961 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -501,17 +501,13 @@ CONF_SCHEMA = { 'name': {'type': 'string'}, 'url': {'type': 'string', 'default': ''}, 'ws_token': {'type': 'string', 'default': ''}, - } + }, + 'required': ['name', 'url', 'ws_token'] } }, 'reply_timeout': {'type': 'integer'}, 'sleep_time': {'type': 'integer'}, 'ping_timeout': {'type': 'integer'}, - 'wait_data_policy': { - 'type': 'string', - 'enum': WAIT_DATA_POLICY_OPTIONS - }, - 'wait_data_timeout': {'type': 'integer', 'default': 5}, 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False} }, 'required': ['producers'] From c72a2c26c7c3be0f9da2582886cd8bcca87efb5b Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 31 Aug 2022 12:06:24 -0600 Subject: [PATCH 120/592] remove external pairlist --- .../plugins/pairlist/ExternalPairList.py | 103 ------------------ 1 file changed, 103 deletions(-) delete mode 100644 freqtrade/plugins/pairlist/ExternalPairList.py diff --git a/freqtrade/plugins/pairlist/ExternalPairList.py b/freqtrade/plugins/pairlist/ExternalPairList.py deleted file mode 100644 index 27a328060..000000000 --- a/freqtrade/plugins/pairlist/ExternalPairList.py +++ /dev/null @@ -1,103 +0,0 @@ -""" -External Pair List provider - -Provides pair list from Leader data -""" -import logging -from typing import Any, Dict, List - -from freqtrade.plugins.pairlist.IPairList import IPairList - - -logger = logging.getLogger(__name__) - - -class ExternalPairList(IPairList): - """ - PairList plugin for use with external signal follower mode. - Will use pairs given from leader data. - - Usage: - "pairlists": [ - { - "method": "ExternalPairList", - "number_assets": 5, # We can limit the amount of pairs to use from leader - } - ], - """ - - def __init__(self, exchange, pairlistmanager, - config: Dict[str, Any], pairlistconfig: Dict[str, Any], - pairlist_pos: int) -> None: - super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) - - # Not sure how to enforce ExternalPairList as the only PairList - - self._num_assets = self._pairlistconfig.get('number_assets') - - self._leader_pairs: List[str] = [] - - def _clamped_pairlist(self): - """ - Return the self._leader_pairs pairlist limited to the maximum set num_assets - or the length of it. - """ - length = len(self._leader_pairs) - if self._num_assets: - return self._leader_pairs[:min(length, self._num_assets)] - else: - return self._leader_pairs - - @property - def needstickers(self) -> bool: - """ - Boolean property defining if tickers are necessary. - If no Pairlist requires tickers, an empty Dict is passed - as tickers argument to filter_pairlist - """ - return False - - def short_desc(self) -> str: - """ - Short whitelist method description - used for startup-messages - -> Please overwrite in subclasses - """ - return f"{self.name}" - - def add_pairlist_data(self, pairlist: List[str]): - """ - Add pairs from Leader - - :param pairlist: List of pairs - """ - - # If some pairs were removed on Leader, remove them here - for pair in self._leader_pairs: - if pair not in pairlist: - logger.debug(f"Leader removed pair: {pair}") - self._leader_pairs.remove(pair) - - # Only add new pairs - seen = set(self._leader_pairs) - for pair in pairlist: - if pair in seen: - continue - self._leader_pairs.append(pair) - - def gen_pairlist(self, tickers: Dict) -> List[str]: - """ - Generate the pairlist - :param tickers: Tickers (from exchange.get_tickers()). May be cached. - :return: List of pairs - """ - return self._clamped_pairlist() - - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: - """ - Filters and sorts pairlist and returns the whitelist again. - Called on each bot iteration - please use internal caching if necessary - :param pairlist: pairlist to filter or sort - :param tickers: Tickers (from exchange.get_tickers()). May be cached. - :return: new whitelist - """ - return self._clamped_pairlist() From 7bed0450d2c6ae90dd00d98a51b18701be6c4874 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 31 Aug 2022 15:36:29 -0300 Subject: [PATCH 121/592] pr review - refactoring backtesting freqai --- freqtrade/freqai/data_kitchen.py | 19 ++++++++++++++----- freqtrade/freqai/freqai_interface.py | 12 ++++++------ tests/freqai/test_freqai_interface.py | 8 ++++---- 3 files changed, 24 insertions(+), 15 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 80b795b8e..8dc94e9ec 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1,7 +1,6 @@ import copy import datetime import logging -import os import shutil from pathlib import Path from typing import Any, Dict, List, Tuple @@ -1108,15 +1107,25 @@ class FreqaiDataKitchen: :param file_name: h5 file name :param root_folder: folder to save h5 file """ - os.makedirs(root_folder, exist_ok=True) - append_df.to_hdf(file_name, key='append_df', mode='w') + backtesting_root = Path( + self.full_path + / root_folder + ) + if not backtesting_root.is_dir(): + backtesting_root.mkdir(parents=True, exist_ok=True) - def get_backtesting_prediction(self, prediction_file_name: str) -> DataFrame: + full_file_path = Path(self.full_path / root_folder / file_name) + append_df.to_hdf(full_file_path, key='append_df', mode='w') + + def get_backtesting_prediction( + self, root_prediction: str, prediction_file_name: str + ) -> DataFrame: """ Retrive from disk the prediction dataframe :param prediction_file_name: prediction file full path :return: :Dataframe: Backtesting prediction from current backtesting period """ - append_df = pd.read_hdf(prediction_file_name) + prediction_path = Path(self.full_path / root_prediction / prediction_file_name) + append_df = pd.read_hdf(prediction_path) return append_df diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index d396113e8..ad64588a7 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -234,12 +234,12 @@ class IFreqaiModel(ABC): if self.backtest_prediction_exists( metadata["pair"], dk, trained_timestamp=trained_timestamp_int ): - prediction_filename, _ = self.get_backtesting_prediction_file_name( + prediction_filename, root_prediction = self.get_backtesting_prediction_file_name( metadata["pair"], dk, trained_timestamp=int(trained_timestamp.stopts)) - append_df = dk.get_backtesting_prediction(prediction_filename) + append_df = dk.get_backtesting_prediction(root_prediction, prediction_filename) dk.append_predictions(append_df) else: if not self.model_exists( @@ -680,10 +680,10 @@ class IFreqaiModel(ABC): :boolean: whether the prediction file exists or not. """ if not self.live: - prediction_file_name, _ = self.get_backtesting_prediction_file_name( + prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name( pair, dk, trained_timestamp ) - path_to_predictionfile = Path(prediction_file_name) + path_to_predictionfile = Path(dk.full_path / root_prediction / prediction_file_name) file_exists = path_to_predictionfile.is_file() if file_exists and not scanning: @@ -711,8 +711,8 @@ class IFreqaiModel(ABC): """ coin, _ = pair.split("/") prediction_base_filename = f"{coin.lower()}_{trained_timestamp}" - root_prediction = f'{dk.full_path}/backtesting_predictions' - prediction_file_name = f"{root_prediction}/{prediction_base_filename}_predictions.h5" + root_prediction = 'backtesting_predictions' + prediction_file_name = f"{prediction_base_filename}_predictions.h5" return prediction_file_name, root_prediction # Following methods which are overridden by user made prediction models. diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 792ffc467..09f5d27ff 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -192,7 +192,7 @@ def test_start_backtesting(mocker, freqai_conf): freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] - assert len(model_folders) == 5 + assert len(model_folders) == 6 shutil.rmtree(Path(freqai.dk.full_path)) @@ -217,7 +217,7 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] - assert len(model_folders) == 8 + assert len(model_folders) == 9 shutil.rmtree(Path(freqai.dk.full_path)) @@ -242,7 +242,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] - assert len(model_folders) == 5 + assert len(model_folders) == 6 # without deleting the exiting folder structure, re-run @@ -263,7 +263,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): freqai.start_backtesting(df, metadata, freqai.dk) assert log_has_re( - "Found model at ", + "Found backtesting prediction ", caplog, ) From 57e9078727fe03ca682fee3ee38ff1c8c93a29b1 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 31 Aug 2022 14:44:52 -0600 Subject: [PATCH 122/592] update example config --- config_examples/config_full.example.json | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index ec988687f..d0efa5bb6 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -180,10 +180,15 @@ "enabled": false, "producers": [ { + "name": "default", "url": "ws://some.freqtrade.bot/api/v1/message/ws", "ws_token": "a_secret_ws_token" } - ] + ], + "reply_timeout": 10, + "ping_timeout": 5, + "sleep_time": 5, + "remove_entry_exit_signals": false }, "bot_name": "freqtrade", "db_url": "sqlite:///tradesv3.sqlite", From ba2eb7cf0f9f517f526a44b3efc792674911a5da Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 1 Sep 2022 06:35:24 +0200 Subject: [PATCH 123/592] Fix BNB fee bug when selling thanks @epigramx, for reporting and for the detailed data. --- freqtrade/freqtradebot.py | 16 +++++++++++----- tests/test_freqtradebot.py | 8 +++++++- 2 files changed, 18 insertions(+), 6 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 5393e3d39..37bc6dfed 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1778,7 +1778,7 @@ class FreqtradeBot(LoggingMixin): self.rpc.send_msg(msg) def apply_fee_conditional(self, trade: Trade, trade_base_currency: str, - amount: float, fee_abs: float) -> Optional[float]: + amount: float, fee_abs: float, order_obj: Order) -> Optional[float]: """ Applies the fee to amount (either from Order or from Trades). Can eat into dust if more than the required asset is available. @@ -1786,7 +1786,12 @@ class FreqtradeBot(LoggingMixin): never in base currency. """ self.wallets.update() - if fee_abs != 0 and self.wallets.get_free(trade_base_currency) >= amount: + amount_ = amount + if order_obj.ft_order_side == trade.exit_side or order_obj.ft_order_side == 'stoploss': + # check against remaining amount! + amount_ = trade.amount - amount + + if fee_abs != 0 and self.wallets.get_free(trade_base_currency) >= amount_: # Eat into dust if we own more than base currency logger.info(f"Fee amount for {trade} was in base currency - " f"Eating Fee {fee_abs} into dust.") @@ -1833,7 +1838,8 @@ class FreqtradeBot(LoggingMixin): if trade_base_currency == fee_currency: # Apply fee to amount return self.apply_fee_conditional(trade, trade_base_currency, - amount=order_amount, fee_abs=fee_cost) + amount=order_amount, fee_abs=fee_cost, + order_obj=order_obj) return None return self.fee_detection_from_trades( trade, order, order_obj, order_amount, order.get('trades', [])) @@ -1892,8 +1898,8 @@ class FreqtradeBot(LoggingMixin): raise DependencyException("Half bought? Amounts don't match") if fee_abs != 0: - return self.apply_fee_conditional(trade, trade_base_currency, - amount=amount, fee_abs=fee_abs) + return self.apply_fee_conditional( + trade, trade_base_currency, amount=amount, fee_abs=fee_abs, order_obj=order_obj) return None def get_valid_price(self, custom_price: float, proposed_price: float) -> float: diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index e6c6e7978..aff0504b3 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -4650,11 +4650,17 @@ def test_apply_fee_conditional(default_conf_usdt, fee, mocker, fee_close=fee.return_value, open_order_id="123456" ) + order = Order( + ft_order_side='buy', + order_id='100', + ft_pair=trade.pair, + ft_is_open=True, + ) freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) walletmock.reset_mock() # Amount is kept as is - assert freqtrade.apply_fee_conditional(trade, 'LTC', amount, fee_abs) == amount_exp + assert freqtrade.apply_fee_conditional(trade, 'LTC', amount, fee_abs, order) == amount_exp assert walletmock.call_count == 1 From f3c73189d55be454845a4e9cc7d8b084a2b0853c Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 1 Sep 2022 06:49:51 +0200 Subject: [PATCH 124/592] Remove pointless default on wallet_balance argument --- freqtrade/exchange/exchange.py | 2 +- tests/exchange/test_exchange.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 9d08d3d19..c3dca43a8 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2600,7 +2600,7 @@ class Exchange: is_short: bool, amount: float, # Absolute value of position size stake_amount: float, - wallet_balance: float = 0.0, + wallet_balance: float, mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 5456b3098..3352019a9 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4985,6 +4985,7 @@ def test_get_liquidation_price1(mocker, default_conf): is_short=False, amount=0.8, stake_amount=18.884 * 0.8, + wallet_balance=18.884 * 0.8, ) assert liq_price == 17.47 @@ -4996,6 +4997,7 @@ def test_get_liquidation_price1(mocker, default_conf): is_short=False, amount=0.8, stake_amount=18.884 * 0.8, + wallet_balance=18.884 * 0.8, ) assert liq_price == 17.540699999999998 @@ -5007,6 +5009,7 @@ def test_get_liquidation_price1(mocker, default_conf): is_short=False, amount=0.8, stake_amount=18.884 * 0.8, + wallet_balance=18.884 * 0.8, ) assert liq_price is None default_conf['trading_mode'] = 'margin' @@ -5019,6 +5022,7 @@ def test_get_liquidation_price1(mocker, default_conf): is_short=False, amount=0.8, stake_amount=18.884 * 0.8, + wallet_balance=18.884 * 0.8, ) From d6e115178a117e6f22f648b1d0def25b90eec471 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Thu, 1 Sep 2022 07:09:23 -0300 Subject: [PATCH 125/592] refactoring freqai backtesting - remove duplicate code --- freqtrade/freqai/data_kitchen.py | 32 ++++++-------- freqtrade/freqai/freqai_interface.py | 62 ++++++---------------------- 2 files changed, 24 insertions(+), 70 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 361d9872d..f88e20223 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -69,6 +69,8 @@ class FreqaiDataKitchen: self.label_list: List = [] self.training_features_list: List = [] self.model_filename: str = "" + self.backtesting_results_path = Path() + self.backtesting_prediction_folder: str = "backtesting_predictions" self.live = live self.pair = pair @@ -808,8 +810,6 @@ class FreqaiDataKitchen: else: self.full_df = pd.concat([self.full_df, append_df], axis=0) - return append_df - def fill_predictions(self, dataframe): """ Back fill values to before the backtesting range so that the dataframe matches size @@ -1070,33 +1070,25 @@ class FreqaiDataKitchen: self.unique_class_list += list(self.unique_classes[label]) def save_backtesting_prediction( - self, file_name: str, root_folder: str, append_df: DataFrame + self, append_df: DataFrame ) -> None: """ Save prediction dataframe from backtesting to h5 file format - :param file_name: h5 file name - :param root_folder: folder to save h5 file + :param append_df: dataframe for backtesting period """ - backtesting_root = Path( - self.full_path - / root_folder - ) - if not backtesting_root.is_dir(): - backtesting_root.mkdir(parents=True, exist_ok=True) + full_predictions_folder = Path(self.full_path / self.backtesting_prediction_folder) + if not full_predictions_folder.is_dir(): + full_predictions_folder.mkdir(parents=True, exist_ok=True) - full_file_path = Path(self.full_path / root_folder / file_name) - append_df.to_hdf(full_file_path, key='append_df', mode='w') + append_df.to_hdf(self.backtesting_results_path, key='append_df', mode='w') def get_backtesting_prediction( - self, root_prediction: str, prediction_file_name: str + self ) -> DataFrame: + """ - Retrive from disk the prediction dataframe - :param prediction_file_name: prediction file full path - :return: - :Dataframe: Backtesting prediction from current backtesting period + Get prediction dataframe from h5 file format """ - prediction_path = Path(self.full_path / root_prediction / prediction_file_name) - append_df = pd.read_hdf(prediction_path) + append_df = pd.read_hdf(self.backtesting_results_path) return append_df diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 2297811b4..0a63e36ea 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -231,15 +231,11 @@ class IFreqaiModel(ABC): f"sub-train-{metadata['pair'].split('/')[0]}_{trained_timestamp_int}" ) - if self.backtest_prediction_exists( - metadata["pair"], dk, trained_timestamp=trained_timestamp_int - ): - prediction_filename, root_prediction = self.get_backtesting_prediction_file_name( - metadata["pair"], - dk, - trained_timestamp=int(trained_timestamp.stopts)) + coin, _ = metadata["pair"].split("/") + dk.model_filename = f"cb_{coin.lower()}_{trained_timestamp_int}" - append_df = dk.get_backtesting_prediction(root_prediction, prediction_filename) + if self.backtest_prediction_exists(dk): + append_df = dk.get_backtesting_prediction() dk.append_predictions(append_df) else: if not self.model_exists( @@ -259,15 +255,7 @@ class IFreqaiModel(ABC): pred_df, do_preds = self.predict(dataframe_backtest, dk) append_df = dk.get_predictions_to_append(pred_df, do_preds) dk.append_predictions(append_df) - - prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name( - metadata["pair"], - dk, - trained_timestamp_int) - - dk.save_backtesting_prediction(prediction_file_name, - root_prediction, - append_df) + dk.save_backtesting_prediction(append_df) dk.fill_predictions(dataframe) @@ -478,11 +466,6 @@ class IFreqaiModel(ABC): :return: :boolean: whether the model file exists or not. """ - coin, _ = pair.split("/") - - if not self.live: - dk.model_filename = model_filename = f"cb_{coin.lower()}_{trained_timestamp}" - path_to_modelfile = Path(dk.data_path / f"{model_filename}_model.joblib") file_exists = path_to_modelfile.is_file() if file_exists and not scanning: @@ -661,23 +644,21 @@ class IFreqaiModel(ABC): def backtest_prediction_exists( self, - pair: str, dk: FreqaiDataKitchen, - trained_timestamp: int, scanning: bool = False, ) -> bool: """ - Given a pair and path, check if a backtesting prediction already exists - :param pair: pair e.g. BTC/USD - :param path: path to prediction + Check if a backtesting prediction already exists + :param dk: FreqaiDataKitchen :return: :boolean: whether the prediction file exists or not. """ if not self.live: - prediction_file_name, root_prediction = self.get_backtesting_prediction_file_name( - pair, dk, trained_timestamp - ) - path_to_predictionfile = Path(dk.full_path / root_prediction / prediction_file_name) + prediction_file_name = dk.model_filename + path_to_predictionfile = Path(dk.full_path / + dk.backtesting_prediction_folder / + f"{prediction_file_name}_prediction.h5") + dk.backtesting_results_path = path_to_predictionfile file_exists = path_to_predictionfile.is_file() if file_exists and not scanning: @@ -690,25 +671,6 @@ class IFreqaiModel(ABC): else: return False - def get_backtesting_prediction_file_name( - self, pair: str, dk: FreqaiDataKitchen, trained_timestamp: int - ): - """ - Given a pair, path and a trained timestamp, - returns the path and name of the predictions file - :param pair: pair e.g. BTC/USD - :param dk: FreqaiDataKitchen - :trained_timestamp: current backtesting timestamp period - :return: - :str: prediction file name - :str: prediction root path - """ - coin, _ = pair.split("/") - prediction_base_filename = f"{coin.lower()}_{trained_timestamp}" - root_prediction = 'backtesting_predictions' - prediction_file_name = f"{prediction_base_filename}_predictions.h5" - return prediction_file_name, root_prediction - # Following methods which are overridden by user made prediction models. # See freqai/prediction_models/CatboostPredictionModel.py for an example. From 61d5fc0e0836aa880ce00bf60981027a0bce7f40 Mon Sep 17 00:00:00 2001 From: epigramx Date: Thu, 1 Sep 2022 17:22:34 +0300 Subject: [PATCH 126/592] Make the recommendation for Binance/Kucoin blacklisting more accurate. Now that a recent bug regarding selling BNB is fixed, it should be safe to trade it, but with a warning that the user may have to manually maintain extra BNB. Also the old text implied those features are always unabled so this texts makes it clear those fee-related features can be also disabled. I'm not sure if it's still true that an "eaten by fees" position becomes unsellable but I left that as it is. --- docs/exchanges.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/exchanges.md b/docs/exchanges.md index 407a67d70..b55eaac74 100644 --- a/docs/exchanges.md +++ b/docs/exchanges.md @@ -61,8 +61,8 @@ Binance supports [time_in_force](configuration.md#understand-order_time_in_force ### Binance Blacklist -For Binance, please add `"BNB/"` to your blacklist to avoid issues. -Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore. +For Binance, it is suggested to add `"BNB/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `BNB` on the account or, unless you're willing to disable using `BNB` for fees. +Binance accounts may use `BNB` for fees, and if a trade happens to be on `BNB`, further trades may consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore. ### Binance Futures @@ -205,8 +205,8 @@ Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force) ### Kucoin Blacklists -For Kucoin, please add `"KCS/"` to your blacklist to avoid issues. -Accounts having KCS accounts use this to pay for fees - if your first trade happens to be on `KCS`, further trades will consume this position and make the initial KCS trade unsellable as the expected amount is not there anymore. +For Kucoin, it is suggested to add `"KCS/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `KCS` on the account or, unless you're willing to disable using `KCS` for fees. +Kucoin accounts may use `KCS` for fees, and if a trade happens to be on `KCS`, further trades may consume this position and make the initial `KCS` trade unsellable as the expected amount is not there anymore. ## Huobi From 11fbfd3402996db93870b5d4beadc2b0840bc37c Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 1 Sep 2022 19:39:20 +0200 Subject: [PATCH 127/592] Remove unnecessary assignment --- freqtrade/persistence/trade_model.py | 1 - 1 file changed, 1 deletion(-) diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 23997f835..1f14f110e 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -648,7 +648,6 @@ class LocalTrade(): """ self.close_rate = rate self.close_date = self.close_date or datetime.utcnow() - self.close_profit_abs = self.calc_profit(rate) + self.realized_profit self.is_open = False self.exit_order_status = 'closed' self.open_order_id = None From 3f8400df10abd51f814b566a2c17ea5423963f34 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Thu, 1 Sep 2022 21:51:33 +0200 Subject: [PATCH 128/592] Normalise PCA space --- freqtrade/freqai/data_kitchen.py | 64 ++++++++++++++++++++++---------- 1 file changed, 45 insertions(+), 19 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index f38c69fae..2a3d00cc5 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -287,19 +287,26 @@ class FreqaiDataKitchen: :returns: :data_dictionary: updated dictionary with standardized values. """ + + df_train_features = data_dictionary["train_features"] # standardize the data by training stats - train_max = data_dictionary["train_features"].max() - train_min = data_dictionary["train_features"].min() - data_dictionary["train_features"] = ( - 2 * (data_dictionary["train_features"] - train_min) / (train_max - train_min) - 1 + train_max = df_train_features.max() + train_min = df_train_features.min() + df_train_features = ( + 2 * (df_train_features - train_min) / (train_max - train_min) - 1 ) data_dictionary["test_features"] = ( 2 * (data_dictionary["test_features"] - train_min) / (train_max - train_min) - 1 ) for item in train_max.keys(): - self.data[item + "_max"] = train_max[item] - self.data[item + "_min"] = train_min[item] + if not [col for col in df_train_features.columns if col.startwith('PC')]: + self.data[item + "_max"] = train_max[item] + self.data[item + "_min"] = train_min[item] + else: + # if PCA is enabled and has transformed the training features + self.data[item + "_pca_max"] = train_max[item] + self.data[item + "_pca_min"] = train_min[item] for item in data_dictionary["train_labels"].keys(): if data_dictionary["train_labels"][item].dtype == object: @@ -320,8 +327,14 @@ class FreqaiDataKitchen: - 1 ) - self.data[f"{item}_max"] = train_labels_max # .to_dict() - self.data[f"{item}_min"] = train_labels_min # .to_dict() + if not [col for col in df_train_features.columns if col.startwith('PC')]: + self.data[f"{item}_max"] = train_labels_max # .to_dict() + self.data[f"{item}_min"] = train_labels_min # .to_dict() + else: + # if PCA is enabled and has transformed the training features + self.data[f"{item}_pca_max"] = train_labels_max # .to_dict() + self.data[f"{item}_pca_min"] = train_labels_min # .to_dict() + return data_dictionary def normalize_data_from_metadata(self, df: DataFrame) -> DataFrame: @@ -331,11 +344,17 @@ class FreqaiDataKitchen: :param df: Dataframe to be standardized """ + if not [col for col in df.columns if col.startwith('PC')]: + id_str = '' + else: + # if PCA is enabled + id_str = '_pca' + for item in df.keys(): df[item] = ( 2 - * (df[item] - self.data[f"{item}_min"]) - / (self.data[f"{item}_max"] - self.data[f"{item}_min"]) + * (df[item] - self.data[f"{item}{id_str}_min"]) + / (self.data[f"{item}{id_str}_max"] - self.data[f"{item}{id_str}_min"]) - 1 ) @@ -450,22 +469,23 @@ class FreqaiDataKitchen: from sklearn.decomposition import PCA # avoid importing if we dont need it - n_components = self.data_dictionary["train_features"].shape[1] - pca = PCA(n_components=n_components) + pca = PCA(0.999) pca = pca.fit(self.data_dictionary["train_features"]) - n_keep_components = np.argmin(pca.explained_variance_ratio_.cumsum() < 0.999) - pca2 = PCA(n_components=n_keep_components) + n_keep_components = pca.n_components_ self.data["n_kept_components"] = n_keep_components - pca2 = pca2.fit(self.data_dictionary["train_features"]) + n_components = self.data_dictionary["train_features"].shape[1] logger.info("reduced feature dimension by %s", n_components - n_keep_components) - logger.info("explained variance %f", np.sum(pca2.explained_variance_ratio_)) - train_components = pca2.transform(self.data_dictionary["train_features"]) + logger.info("explained variance %f", np.sum(pca.explained_variance_ratio_)) + train_components = pca.transform(self.data_dictionary["train_features"]) self.data_dictionary["train_features"] = pd.DataFrame( data=train_components, columns=["PC" + str(i) for i in range(0, n_keep_components)], index=self.data_dictionary["train_features"].index, ) + # normalsing transformed training features + self.data_dictionary["train_features"] = self.normalize_data( + self.data_dictionary["train_features"]) # keeping a copy of the non-transformed features so we can check for errors during # model load from disk @@ -473,15 +493,18 @@ class FreqaiDataKitchen: self.training_features_list = self.data_dictionary["train_features"].columns if self.freqai_config.get('data_split_parameters', {}).get('test_size', 0.1) != 0: - test_components = pca2.transform(self.data_dictionary["test_features"]) + test_components = pca.transform(self.data_dictionary["test_features"]) self.data_dictionary["test_features"] = pd.DataFrame( data=test_components, columns=["PC" + str(i) for i in range(0, n_keep_components)], index=self.data_dictionary["test_features"].index, ) + # normalise transformed test feature to transformed training features + self.data_dictionary["test_features"] = self.normalize_data_from_metadata( + self.data_dictionary["test_features"]) self.data["n_kept_components"] = n_keep_components - self.pca = pca2 + self.pca = pca logger.info(f"PCA reduced total features from {n_components} to {n_keep_components}") @@ -502,6 +525,9 @@ class FreqaiDataKitchen: columns=["PC" + str(i) for i in range(0, self.data["n_kept_components"])], index=filtered_dataframe.index, ) + # normalise transformed predictions to transformed training features + self.data_dictionary["prediction_features"] = self.normalize_data_from_metadata( + self.data_dictionary["prediction_features"]) def compute_distances(self) -> float: """ From 11b2bc269ed1e4851f9cb51331b21a3faefe68a5 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Thu, 1 Sep 2022 22:37:32 +0200 Subject: [PATCH 129/592] Added missing s --- freqtrade/freqai/data_kitchen.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 2a3d00cc5..69ce5272d 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -300,7 +300,7 @@ class FreqaiDataKitchen: ) for item in train_max.keys(): - if not [col for col in df_train_features.columns if col.startwith('PC')]: + if not [col for col in df_train_features.columns if col.startswith('PC')]: self.data[item + "_max"] = train_max[item] self.data[item + "_min"] = train_min[item] else: @@ -327,7 +327,7 @@ class FreqaiDataKitchen: - 1 ) - if not [col for col in df_train_features.columns if col.startwith('PC')]: + if not [col for col in df_train_features.columns if col.startswith('PC')]: self.data[f"{item}_max"] = train_labels_max # .to_dict() self.data[f"{item}_min"] = train_labels_min # .to_dict() else: @@ -344,7 +344,7 @@ class FreqaiDataKitchen: :param df: Dataframe to be standardized """ - if not [col for col in df.columns if col.startwith('PC')]: + if not [col for col in df.columns if col.startswith('PC')]: id_str = '' else: # if PCA is enabled From 00f35f48707a600fb13fd723d376502fd1e4ddd8 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 1 Sep 2022 20:06:36 -0600 Subject: [PATCH 130/592] remove old constant, add initial_data requesting, minor changes --- freqtrade/constants.py | 3 - freqtrade/data/dataprovider.py | 1 - freqtrade/enums/rpcmessagetype.py | 1 + freqtrade/freqtradebot.py | 10 +-- freqtrade/rpc/api_server/api_ws.py | 39 +++++++++--- freqtrade/rpc/api_server/webserver.py | 8 +-- freqtrade/rpc/external_message_consumer.py | 73 +++++++++++++++------- freqtrade/rpc/rpc.py | 51 ++++++++++++--- freqtrade/rpc/rpc_manager.py | 2 + freqtrade/strategy/interface.py | 4 +- 10 files changed, 136 insertions(+), 56 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 6bacaf961..63222f2ff 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -61,8 +61,6 @@ USERPATH_FREQAIMODELS = 'freqaimodels' TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent'] WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw'] -WAIT_DATA_POLICY_OPTIONS = ['none', 'first', 'all'] - ENV_VAR_PREFIX = 'FREQTRADE__' NON_OPEN_EXCHANGE_STATES = ('cancelled', 'canceled', 'closed', 'expired') @@ -404,7 +402,6 @@ CONF_SCHEMA = { 'username': {'type': 'string'}, 'password': {'type': 'string'}, 'ws_token': {'type': 'string'}, - 'enable_message_ws': {'type': 'boolean', 'default': False}, 'jwt_secret_key': {'type': 'string'}, 'CORS_origins': {'type': 'array', 'items': {'type': 'string'}}, 'verbosity': {'type': 'string', 'enum': ['error', 'info']}, diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 947387f75..90302f88e 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -144,7 +144,6 @@ class DataProvider: if producer_name not in self.__producer_pairs_df: self.__producer_pairs_df[producer_name] = {} - # For multiple leaders, if the data already exists, we'd merge self.__producer_pairs_df[producer_name][pair_key] = (dataframe, datetime.now(timezone.utc)) def get_external_df( diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index 6283fb7cc..c213826ae 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -33,3 +33,4 @@ class RPCMessageType(str, Enum): # Enum for parsing requests from ws consumers class RPCRequestType(str, Enum): SUBSCRIBE = 'subscribe' + INITIAL_DATA = 'initial_data' diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 19c77d403..888994ffb 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -203,8 +203,7 @@ class FreqtradeBot(LoggingMixin): # Doesn't necessarily NEED to be this way, as maybe we'd like to broadcast # even if we are using external dataframes in the future. - self.strategy.analyze(self.active_pair_whitelist, - emit_df=self.dataprovider.external_data_enabled) + self.strategy.analyze(self.active_pair_whitelist) with self._exit_lock: # Check for exchange cancelations, timeouts and user requested replace @@ -264,11 +263,10 @@ class FreqtradeBot(LoggingMixin): pairs that have open trades. """ # Refresh whitelist + _prev_whitelist = self.pairlists.whitelist self.pairlists.refresh_pairlist() _whitelist = self.pairlists.whitelist - self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'data': _whitelist}) - # Calculating Edge positioning if self.edge: self.edge.calculate(_whitelist) @@ -279,6 +277,10 @@ class FreqtradeBot(LoggingMixin): # It ensures that candle (OHLCV) data are downloaded for open trades as well _whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist]) + # Called last to include the included pairs + if _prev_whitelist != _whitelist: + self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'data': _whitelist}) + return _whitelist def get_free_open_trades(self) -> int: diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index d7c7239d1..52507106d 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -4,9 +4,10 @@ from typing import Any, Dict from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect from freqtrade.enums import RPCMessageType, RPCRequestType -from freqtrade.rpc.api_server.deps import get_channel_manager +from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws.utils import is_websocket_alive +from freqtrade.rpc.rpc import RPC # from typing import Any, Dict @@ -18,17 +19,20 @@ logger = logging.getLogger(__name__) router = APIRouter() -# We are passed a Channel object, we can only do sync functions on that channel object -def _process_consumer_request(request: Dict[str, Any], channel: WebSocketChannel): +async def _process_consumer_request( + request: Dict[str, Any], + channel: WebSocketChannel, + rpc: RPC +): type, data = request.get('type'), request.get('data') - # If the request is empty, do nothing - if not data: - return - # If we have a request of type SUBSCRIBE, set the topics in this channel if type == RPCRequestType.SUBSCRIBE: - if isinstance(data, list): + # If the request is empty, do nothing + if not data: + return + + if not isinstance(data, list): logger.error(f"Improper request from channel: {channel} - {request}") return @@ -38,11 +42,26 @@ def _process_consumer_request(request: Dict[str, Any], channel: WebSocketChannel logger.debug(f"{channel} subscribed to topics: {data}") channel.set_subscriptions(data) + elif type == RPCRequestType.INITIAL_DATA: + # Acquire the data + initial_data = rpc._ws_initial_data() + + # We now loop over it sending it in pieces + whitelist_data, analyzed_df = initial_data.get('whitelist'), initial_data.get('analyzed_df') + + if whitelist_data: + await channel.send({"type": RPCMessageType.WHITELIST, "data": whitelist_data}) + + if analyzed_df: + for pair, message in analyzed_df.items(): + await channel.send({"type": RPCMessageType.ANALYZED_DF, "data": message}) + @router.websocket("/message/ws") async def message_endpoint( ws: WebSocket, - channel_manager=Depends(get_channel_manager) + rpc: RPC = Depends(get_rpc), + channel_manager=Depends(get_channel_manager), ): try: if is_websocket_alive(ws): @@ -59,7 +78,7 @@ async def message_endpoint( # Process the request here. Should this be a method of RPC? logger.info(f"Request: {request}") - _process_consumer_request(request, channel) + await _process_consumer_request(request, channel, rpc) except WebSocketDisconnect: # Handle client disconnects diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index e391e66af..150c83890 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -151,11 +151,9 @@ class ApiServer(RPCHandler): app.include_router(api_backtest, prefix="/api/v1", dependencies=[Depends(http_basic_or_jwt_token)], ) - if self._config.get('api_server', {}).get('enable_message_ws', False): - logger.info("Enabling Message WebSocket") - app.include_router(ws_router, prefix="/api/v1", - dependencies=[Depends(get_ws_token)] - ) + app.include_router(ws_router, prefix="/api/v1", + dependencies=[Depends(get_ws_token)] + ) app.include_router(router_login, prefix="/api/v1", tags=["auth"]) # UI Router MUST be last! app.include_router(router_ui, prefix='') diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index ae72089b5..4544afc29 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -8,7 +8,7 @@ import asyncio import logging import socket from threading import Thread -from typing import Any, Dict +from typing import Any, Dict, Optional import websockets @@ -58,6 +58,11 @@ class ExternalMessageConsumer: # callbacks for the messages self.topics = [RPCMessageType.WHITELIST, RPCMessageType.ANALYZED_DF] + self._message_handlers = { + RPCMessageType.WHITELIST: self._consume_whitelist_message, + RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message, + } + self.start() def start(self): @@ -152,6 +157,11 @@ class ExternalMessageConsumer: self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) ) + # Now request the initial data from this Producer + await channel.send( + self.compose_consumer_request(RPCRequestType.INITIAL_DATA) + ) + # Now receive data, if none is within the time limit, ping while True: try: @@ -198,7 +208,11 @@ class ExternalMessageConsumer: logger.error(f"{ws_url} is an invalid WebSocket URL - {e}") break - def compose_consumer_request(self, type_: RPCRequestType, data: Any) -> Dict[str, Any]: + def compose_consumer_request( + self, + type_: RPCRequestType, + data: Optional[Any] = None + ) -> Dict[str, Any]: """ Create a request for sending to a producer @@ -208,8 +222,6 @@ class ExternalMessageConsumer: """ return {'type': type_, 'data': data} - # How we do things here isn't set in stone. There seems to be some interest - # in figuring out a better way, but we shall do this for now. def handle_producer_message(self, producer: Dict[str, Any], message: Dict[str, Any]): """ Handles external messages from a Producer @@ -225,27 +237,44 @@ class ExternalMessageConsumer: logger.debug(f"Received message of type {message_type}") - # Handle Whitelists - if message_type == RPCMessageType.WHITELIST: - pairlist = message_data + message_handler = self._message_handlers.get(message_type) - # Add the pairlist data to the DataProvider - self._dp.set_producer_pairs(pairlist, producer_name=producer_name) + if not message_handler: + logger.info(f"Received unhandled message: {message_data}, ignoring...") + return - # Handle analyzed dataframes - elif message_type == RPCMessageType.ANALYZED_DF: - key, value = message_data.get('key'), message_data.get('value') + message_handler(producer_name, message_data) - if key and value: - pair, timeframe, candle_type = key + def _consume_whitelist_message(self, producer_name: str, message_data: Any): + # We expect List[str] + if not isinstance(message_data, list): + return - # Convert the JSON to a pandas DataFrame - dataframe = json_to_dataframe(value) + # Add the pairlist data to the DataProvider + self._dp.set_producer_pairs(message_data, producer_name=producer_name) - # If set, remove the Entry and Exit signals from the Producer - if self._emc_config.get('remove_entry_exit_signals', False): - dataframe = remove_entry_exit_signals(dataframe) + logger.debug(f"Consumed message from {producer_name} of type RPCMessageType.WHITELIST") - # Add the dataframe to the dataprovider - self._dp.add_external_df(pair, timeframe, dataframe, - candle_type, producer_name=producer_name) + def _consume_analyzed_df_message(self, producer_name: str, message_data: Any): + # We expect a Dict[str, Any] + if not isinstance(message_data, dict): + return + + key, value = message_data.get('key'), message_data.get('value') + + if key and value: + pair, timeframe, candle_type = key + + # Convert the JSON to a pandas DataFrame + dataframe = json_to_dataframe(value) + + # If set, remove the Entry and Exit signals from the Producer + if self._emc_config.get('remove_entry_exit_signals', False): + dataframe = remove_entry_exit_signals(dataframe) + + # Add the dataframe to the dataprovider + self._dp.add_external_df(pair, timeframe, dataframe, + candle_type, producer_name=producer_name) + + logger.debug( + f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index ed7f13a96..c4752c570 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -24,7 +24,7 @@ from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirecti from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler -from freqtrade.misc import decimals_per_coin, shorten_date +from freqtrade.misc import dataframe_to_json, decimals_per_coin, shorten_date from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1035,16 +1035,51 @@ class RPC: def _rpc_analysed_dataframe(self, pair: str, timeframe: str, limit: Optional[int]) -> Dict[str, Any]: + """ Analyzed dataframe in Dict form """ - _data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe( - pair, timeframe) - _data = _data.copy() - if limit: - _data = _data.iloc[-limit:] + _data, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) return self._convert_dataframe_to_dict(self._freqtrade.config['strategy'], pair, timeframe, _data, last_analyzed) - @staticmethod + def __rpc_analysed_dataframe_raw(self, pair: str, timeframe: str, + limit: Optional[int]) -> Tuple[DataFrame, datetime]: + """ Get the dataframe and last analyze from the dataprovider """ + _data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe( + pair, timeframe) + _data = _data.copy() + + if limit: + _data = _data.iloc[-limit:] + return _data, last_analyzed + + def _ws_all_analysed_dataframes( + self, + pairlist: List[str], + limit: Optional[int] + ) -> Dict[str, Any]: + """ Get the analysed dataframes of each pair in the pairlist """ + timeframe = self._freqtrade.config['timeframe'] + candle_type = self._freqtrade.config.get('candle_type_def', CandleType.SPOT) + _data = {} + + for pair in pairlist: + dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) + _data[pair] = { + "key": (pair, timeframe, candle_type), + "value": dataframe_to_json(dataframe) + } + + return _data + + def _ws_initial_data(self): + """ Websocket friendly initial data, whitelists and all analyzed dataframes """ + whitelist = self._freqtrade.active_pair_whitelist + # We only get the last 500 candles, should we remove the limit? + analyzed_df = self._ws_all_analysed_dataframes(whitelist, 500) + + return {"whitelist": whitelist, "analyzed_df": analyzed_df} + + @ staticmethod def _rpc_analysed_history_full(config, pair: str, timeframe: str, timerange: str, exchange) -> Dict[str, Any]: timerange_parsed = TimeRange.parse_timerange(timerange) @@ -1075,7 +1110,7 @@ class RPC: self._freqtrade.strategy.plot_config['subplots'] = {} return self._freqtrade.strategy.plot_config - @staticmethod + @ staticmethod def _rpc_sysinfo() -> Dict[str, Any]: return { "cpu_pct": psutil.cpu_percent(interval=1, percpu=True), diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 3488a6e3c..d6374566c 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -81,6 +81,8 @@ class RPCManager: # Removed actually showing the message because the logs would be # completely spammed of the json dataframe logger.info('Sending rpc message of type: %s', msg.get('type')) + # Log actual message in debug? + # logger.debug(msg) if 'pair' in msg: msg.update({ 'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair']) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 34e475ed7..7fcae870a 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -725,9 +725,7 @@ class IStrategy(ABC, HyperStrategyMixin): candle_type = self.config.get('candle_type_def', CandleType.SPOT) self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) - - if emit_df: - self.dp.emit_df((pair, self.timeframe, candle_type), dataframe) + self.dp.emit_df((pair, self.timeframe, candle_type), dataframe) else: logger.debug("Skipping TA Analysis for already analyzed candle") From b53791fef20990d2a46b9dbf6795fb8cfc490c2f Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 07:11:20 +0200 Subject: [PATCH 131/592] Futures volumepairlist to account for contract size --- freqtrade/plugins/pairlist/VolumePairList.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py index 8138a5fb6..d7cc6e5ec 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -186,6 +186,7 @@ class VolumePairList(IPairList): needed_pairs, since_ms=since_ms, cache=False ) for i, p in enumerate(filtered_tickers): + contract_size = self._exchange.markets[p['symbol']].get('contractSize', 1.0) or 1.0 pair_candles = candles[ (p['symbol'], self._lookback_timeframe, self._def_candletype) ] if ( @@ -199,6 +200,7 @@ class VolumePairList(IPairList): pair_candles['quoteVolume'] = ( pair_candles['volume'] * pair_candles['typical_price'] + * contract_size ) else: # Exchange ohlcv data is in quote volume already. From dccde88c83c4e8dfa7c8b70a6c4a7f9459ce177c Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 1 Sep 2022 23:15:03 -0600 Subject: [PATCH 132/592] fix dataframe serializing --- freqtrade/data/dataprovider.py | 3 +- freqtrade/misc.py | 3 +- freqtrade/rpc/api_server/ws/channel.py | 4 +-- freqtrade/rpc/api_server/ws/serializer.py | 37 +++++++++++++++------- freqtrade/rpc/external_message_consumer.py | 9 +++--- freqtrade/rpc/rpc.py | 7 ++-- 6 files changed, 37 insertions(+), 26 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 90302f88e..ef3067f38 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -17,7 +17,6 @@ from freqtrade.data.history import load_pair_history from freqtrade.enums import CandleType, RPCMessageType, RunMode from freqtrade.exceptions import ExchangeError, OperationalException from freqtrade.exchange import Exchange, timeframe_to_seconds -from freqtrade.misc import dataframe_to_json from freqtrade.rpc import RPCManager from freqtrade.util import PeriodicCache @@ -119,7 +118,7 @@ class DataProvider: 'type': RPCMessageType.ANALYZED_DF, 'data': { 'key': pair_key, - 'value': dataframe_to_json(dataframe) + 'value': dataframe } } ) diff --git a/freqtrade/misc.py b/freqtrade/misc.py index ceace4ed8..6a93b6f26 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -269,7 +269,8 @@ def json_to_dataframe(data: str) -> pandas.DataFrame: :returns: A pandas DataFrame from the JSON string """ dataframe = pandas.read_json(data) - dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True) + if 'date' in dataframe.columns: + dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True) return dataframe diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 6bc5b9d6b..b47fe7550 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -3,7 +3,7 @@ from threading import RLock from typing import List, Type from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy -from freqtrade.rpc.api_server.ws.serializer import ORJSONWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.api_server.ws.serializer import RapidJSONWebSocketSerializer, WebSocketSerializer from freqtrade.rpc.api_server.ws.types import WebSocketType @@ -18,7 +18,7 @@ class WebSocketChannel: def __init__( self, websocket: WebSocketType, - serializer_cls: Type[WebSocketSerializer] = ORJSONWebSocketSerializer + serializer_cls: Type[WebSocketSerializer] = RapidJSONWebSocketSerializer ): # The WebSocket object self._websocket = WebSocketProxy(websocket) diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index ae2857f0b..c11ca9a99 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -3,8 +3,10 @@ import logging from abc import ABC, abstractmethod import msgpack -import orjson +import rapidjson +from pandas import DataFrame +from freqtrade.misc import dataframe_to_json, json_to_dataframe from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy @@ -34,27 +36,23 @@ class WebSocketSerializer(ABC): async def close(self, code: int = 1000): await self._websocket.close(code) -# Going to explore using MsgPack as the serialization, -# as that might be the best method for sending pandas -# dataframes over the wire - class JSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data): - return json.dumps(data) + return json.dumps(data, default=_json_default) def _deserialize(self, data): - return json.loads(data) + return json.loads(data, object_hook=_json_object_hook) -class ORJSONWebSocketSerializer(WebSocketSerializer): - ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY +# ORJSON does not support .loads(object_hook=x) parameter, so we must use RapidJSON +class RapidJSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data): - return orjson.dumps(data, option=self.ORJSON_OPTIONS) + return rapidjson.dumps(data, default=_json_default) def _deserialize(self, data): - return orjson.loads(data) + return rapidjson.loads(data, object_hook=_json_object_hook) class MsgPackWebSocketSerializer(WebSocketSerializer): @@ -63,3 +61,20 @@ class MsgPackWebSocketSerializer(WebSocketSerializer): def _deserialize(self, data): return msgpack.unpackb(data, raw=False) + + +# Support serializing pandas DataFrames +def _json_default(z): + if isinstance(z, DataFrame): + return { + '__type__': 'dataframe', + '__value__': dataframe_to_json(z) + } + raise TypeError + + +# Support deserializing JSON to pandas DataFrames +def _json_object_hook(z): + if z.get('__type__') == 'dataframe': + return json_to_dataframe(z.get('__value__')) + return z diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 4544afc29..4c7f6570d 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -10,11 +10,12 @@ import socket from threading import Thread from typing import Any, Dict, Optional +import pandas import websockets from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RPCMessageType, RPCRequestType -from freqtrade.misc import json_to_dataframe, remove_entry_exit_signals +from freqtrade.misc import remove_entry_exit_signals from freqtrade.rpc.api_server.ws.channel import WebSocketChannel @@ -262,11 +263,9 @@ class ExternalMessageConsumer: key, value = message_data.get('key'), message_data.get('value') - if key and value: + if key and isinstance(value, pandas.DataFrame): pair, timeframe, candle_type = key - - # Convert the JSON to a pandas DataFrame - dataframe = json_to_dataframe(value) + dataframe = value # If set, remove the Entry and Exit signals from the Producer if self._emc_config.get('remove_entry_exit_signals', False): diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index c4752c570..96b43f36b 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -24,7 +24,7 @@ from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirecti from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler -from freqtrade.misc import dataframe_to_json, decimals_per_coin, shorten_date +from freqtrade.misc import decimals_per_coin, shorten_date from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1064,10 +1064,7 @@ class RPC: for pair in pairlist: dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) - _data[pair] = { - "key": (pair, timeframe, candle_type), - "value": dataframe_to_json(dataframe) - } + _data[pair] = {"key": (pair, timeframe, candle_type), "value": dataframe} return _data From eb4cd6ba82b8d348b02a37d65c1567f0678f056d Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 1 Sep 2022 23:52:13 -0600 Subject: [PATCH 133/592] split initial data into separate requests --- freqtrade/enums/rpcmessagetype.py | 4 +++- freqtrade/rpc/api_server/api_ws.py | 22 +++++++++---------- freqtrade/rpc/external_message_consumer.py | 25 +++++++++++++--------- freqtrade/rpc/rpc.py | 11 +++++----- 4 files changed, 35 insertions(+), 27 deletions(-) diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index c213826ae..929f6d083 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -33,4 +33,6 @@ class RPCMessageType(str, Enum): # Enum for parsing requests from ws consumers class RPCRequestType(str, Enum): SUBSCRIBE = 'subscribe' - INITIAL_DATA = 'initial_data' + + WHITELIST = 'whitelist' + ANALYZED_DF = 'analyzed_df' diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 52507106d..cf5b6cde0 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -33,7 +33,7 @@ async def _process_consumer_request( return if not isinstance(data, list): - logger.error(f"Improper request from channel: {channel} - {request}") + logger.error(f"Improper subscribe request from channel: {channel} - {request}") return # If all topics passed are a valid RPCMessageType, set subscriptions on channel @@ -42,19 +42,19 @@ async def _process_consumer_request( logger.debug(f"{channel} subscribed to topics: {data}") channel.set_subscriptions(data) - elif type == RPCRequestType.INITIAL_DATA: - # Acquire the data - initial_data = rpc._ws_initial_data() + elif type == RPCRequestType.WHITELIST: + # They requested the whitelist + whitelist = rpc._ws_request_whitelist() - # We now loop over it sending it in pieces - whitelist_data, analyzed_df = initial_data.get('whitelist'), initial_data.get('analyzed_df') + await channel.send({"type": RPCMessageType.WHITELIST, "data": whitelist}) - if whitelist_data: - await channel.send({"type": RPCMessageType.WHITELIST, "data": whitelist_data}) + elif type == RPCRequestType.ANALYZED_DF: + # They requested the full historical analyzed dataframes + analyzed_df = rpc._ws_request_analyzed_df() - if analyzed_df: - for pair, message in analyzed_df.items(): - await channel.send({"type": RPCMessageType.ANALYZED_DF, "data": message}) + # For every dataframe, send as a separate message + for _, message in analyzed_df.items(): + await channel.send({"type": RPCMessageType.ANALYZED_DF, "data": message}) @router.websocket("/message/ws") diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 4c7f6570d..c925624f8 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -158,10 +158,12 @@ class ExternalMessageConsumer: self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) ) - # Now request the initial data from this Producer - await channel.send( - self.compose_consumer_request(RPCRequestType.INITIAL_DATA) - ) + # Now request the initial data from this Producer for every topic + # we've subscribed to + for topic in self.topics: + # without .upper() we get KeyError + request_type = RPCRequestType[topic.upper()] + await channel.send(self.compose_consumer_request(request_type)) # Now receive data, if none is within the time limit, ping while True: @@ -191,9 +193,12 @@ class ExternalMessageConsumer: await asyncio.sleep(self.sleep_time) break - except Exception as e: - logger.exception(e) - continue + + # Catch invalid ws_url, and break the loop + except websockets.exceptions.InvalidURI as e: + logger.error(f"{ws_url} is an invalid WebSocket URL - {e}") + break + except ( socket.gaierror, ConnectionRefusedError, @@ -204,9 +209,9 @@ class ExternalMessageConsumer: continue - # Catch invalid ws_url, and break the loop - except websockets.exceptions.InvalidURI as e: - logger.error(f"{ws_url} is an invalid WebSocket URL - {e}") + except Exception as e: + # An unforseen error has occurred, log and stop + logger.exception(e) break def compose_consumer_request( diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 96b43f36b..378677e44 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1068,13 +1068,14 @@ class RPC: return _data - def _ws_initial_data(self): - """ Websocket friendly initial data, whitelists and all analyzed dataframes """ + def _ws_request_analyzed_df(self): + """ Historical Analyzed Dataframes for WebSocket """ whitelist = self._freqtrade.active_pair_whitelist - # We only get the last 500 candles, should we remove the limit? - analyzed_df = self._ws_all_analysed_dataframes(whitelist, 500) + return self._ws_all_analysed_dataframes(whitelist, 500) - return {"whitelist": whitelist, "analyzed_df": analyzed_df} + def _ws_request_whitelist(self): + """ Whitelist data for WebSocket """ + return self._freqtrade.active_pair_whitelist @ staticmethod def _rpc_analysed_history_full(config, pair: str, timeframe: str, From 5b0b802f311f0999412482a1722e87afe306892d Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 2 Sep 2022 00:05:36 -0600 Subject: [PATCH 134/592] hybrid json ws serializer --- freqtrade/rpc/api_server/ws/channel.py | 5 +++-- freqtrade/rpc/api_server/ws/serializer.py | 9 +++++++++ 2 files changed, 12 insertions(+), 2 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index b47fe7550..8891d3296 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -3,7 +3,8 @@ from threading import RLock from typing import List, Type from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy -from freqtrade.rpc.api_server.ws.serializer import RapidJSONWebSocketSerializer, WebSocketSerializer +from freqtrade.rpc.api_server.ws.serializer import (HybridJSONWebSocketSerializer, + WebSocketSerializer) from freqtrade.rpc.api_server.ws.types import WebSocketType @@ -18,7 +19,7 @@ class WebSocketChannel: def __init__( self, websocket: WebSocketType, - serializer_cls: Type[WebSocketSerializer] = RapidJSONWebSocketSerializer + serializer_cls: Type[WebSocketSerializer] = HybridJSONWebSocketSerializer ): # The WebSocket object self._websocket = WebSocketProxy(websocket) diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index c11ca9a99..109708cc9 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -3,6 +3,7 @@ import logging from abc import ABC, abstractmethod import msgpack +import orjson import rapidjson from pandas import DataFrame @@ -55,6 +56,14 @@ class RapidJSONWebSocketSerializer(WebSocketSerializer): return rapidjson.loads(data, object_hook=_json_object_hook) +class HybridJSONWebSocketSerializer(WebSocketSerializer): + def _serialize(self, data): + return orjson.dumps(data, default=_json_default) + + def _deserialize(self, data): + return rapidjson.loads(data, object_hook=_json_object_hook) + + class MsgPackWebSocketSerializer(WebSocketSerializer): def _serialize(self, data): return msgpack.packb(data, use_bin_type=True) From a948e51389108d7b827d4ad4551fd861b88bdb71 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 19:56:12 +0200 Subject: [PATCH 135/592] Update futures docs to define pair namings #7334, #7136, ... --- docs/leverage.md | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/docs/leverage.md b/docs/leverage.md index 491e6eda0..429aff86c 100644 --- a/docs/leverage.md +++ b/docs/leverage.md @@ -13,7 +13,7 @@ Please only use advanced trading modes when you know how freqtrade (and your strategy) works. Also, never risk more than what you can afford to lose. -Please read the [strategy migration guide](strategy_migration.md#strategy-migration-between-v2-and-v3) to migrate your strategy from a freqtrade v2 strategy, to v3 strategy that can short and trade futures. +If you already have an existing strategy, please read the [strategy migration guide](strategy_migration.md#strategy-migration-between-v2-and-v3) to migrate your strategy from a freqtrade v2 strategy, to strategy of version 3 which can short and trade futures. ## Shorting @@ -62,6 +62,13 @@ You will also have to pick a "margin mode" (explanation below) - with freqtrade "margin_mode": "isolated" ``` +##### Pair namings + +Freqtrade follows the [ccxt naming conventions for futures](https://docs.ccxt.com/en/latest/manual.html?#perpetual-swap-perpetual-future). +A futures pair will therefore have the naming of `base/quote:settle` (e.g. `ETH/USDT:USDT`). + +Binance is currently still an exception to this naming scheme, where pairs are named `ETH/USDT` also for futures markets, but will be aligned as soon as CCXT is ready. + ### Margin mode On top of `trading_mode` - you will also have to configure your `margin_mode`. From b26126cb57300cefb51222ddf185a4f929bdbba8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 20:08:38 +0200 Subject: [PATCH 136/592] Don't use ticker['symbol'] but use "pair" instead closes #7262 --- docs/exchanges.md | 4 ++-- freqtrade/plugins/pairlist/PrecisionFilter.py | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/exchanges.md b/docs/exchanges.md index b55eaac74..b5470f65a 100644 --- a/docs/exchanges.md +++ b/docs/exchanges.md @@ -61,7 +61,7 @@ Binance supports [time_in_force](configuration.md#understand-order_time_in_force ### Binance Blacklist -For Binance, it is suggested to add `"BNB/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `BNB` on the account or, unless you're willing to disable using `BNB` for fees. +For Binance, it is suggested to add `"BNB/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `BNB` on the account or unless you're willing to disable using `BNB` for fees. Binance accounts may use `BNB` for fees, and if a trade happens to be on `BNB`, further trades may consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore. ### Binance Futures @@ -205,7 +205,7 @@ Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force) ### Kucoin Blacklists -For Kucoin, it is suggested to add `"KCS/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `KCS` on the account or, unless you're willing to disable using `KCS` for fees. +For Kucoin, it is suggested to add `"KCS/"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `KCS` on the account or unless you're willing to disable using `KCS` for fees. Kucoin accounts may use `KCS` for fees, and if a trade happens to be on `KCS`, further trades may consume this position and make the initial `KCS` trade unsellable as the expected amount is not there anymore. ## Huobi diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py index dcd153d8e..61150f03d 100644 --- a/freqtrade/plugins/pairlist/PrecisionFilter.py +++ b/freqtrade/plugins/pairlist/PrecisionFilter.py @@ -52,7 +52,7 @@ class PrecisionFilter(IPairList): :return: True if the pair can stay, false if it should be removed """ if ticker.get('last', None) is None: - self.log_once(f"Removed {ticker['symbol']} from whitelist, because " + self.log_once(f"Removed {pair} from whitelist, because " "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) return False @@ -62,10 +62,10 @@ class PrecisionFilter(IPairList): sp = self._exchange.price_to_precision(pair, stop_price) stop_gap_price = self._exchange.price_to_precision(pair, stop_price * 0.99) - logger.debug(f"{ticker['symbol']} - {sp} : {stop_gap_price}") + logger.debug(f"{pair} - {sp} : {stop_gap_price}") if sp <= stop_gap_price: - self.log_once(f"Removed {ticker['symbol']} from whitelist, because " + self.log_once(f"Removed {pair} from whitelist, because " f"stop price {sp} would be <= stop limit {stop_gap_price}", logger.info) return False From cf917ad2f5b983f11ca1032a7f3f9b4742c88ca0 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 2 Sep 2022 15:05:16 -0600 Subject: [PATCH 137/592] initial candle request limit, better error reporting, split up _handle_producer_connection --- freqtrade/constants.py | 8 +- freqtrade/rpc/api_server/api_ws.py | 27 ++++-- freqtrade/rpc/api_server/ws/channel.py | 14 ++- freqtrade/rpc/api_server/ws/proxy.py | 10 +- freqtrade/rpc/external_message_consumer.py | 106 ++++++++++++++------- freqtrade/rpc/rpc.py | 4 +- 6 files changed, 119 insertions(+), 50 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 63222f2ff..352e48148 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -505,7 +505,13 @@ CONF_SCHEMA = { 'reply_timeout': {'type': 'integer'}, 'sleep_time': {'type': 'integer'}, 'ping_timeout': {'type': 'integer'}, - 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False} + 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False}, + 'initial_candle_limit': { + 'type': 'integer', + 'minimum': 100, + 'maximum': 1500, + 'default': 500 + } }, 'required': ['producers'] }, diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index cf5b6cde0..95cfd031a 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -26,6 +26,8 @@ async def _process_consumer_request( ): type, data = request.get('type'), request.get('data') + logger.debug(f"Request of type {type} from {channel}") + # If we have a request of type SUBSCRIBE, set the topics in this channel if type == RPCRequestType.SUBSCRIBE: # If the request is empty, do nothing @@ -49,8 +51,16 @@ async def _process_consumer_request( await channel.send({"type": RPCMessageType.WHITELIST, "data": whitelist}) elif type == RPCRequestType.ANALYZED_DF: + limit = None + + if data: + # Limit the amount of candles per dataframe to 'limit' or 1500 + limit = max(data.get('limit', 500), 1500) + # They requested the full historical analyzed dataframes - analyzed_df = rpc._ws_request_analyzed_df() + analyzed_df = rpc._ws_request_analyzed_df(limit) + + logger.debug(f"ANALYZED_DF RESULT: {analyzed_df}") # For every dataframe, send as a separate message for _, message in analyzed_df.items(): @@ -65,32 +75,33 @@ async def message_endpoint( ): try: if is_websocket_alive(ws): - logger.info(f"Consumer connected - {ws.client}") - # TODO: # Return a channel ID, pass that instead of ws to the rest of the methods channel = await channel_manager.on_connect(ws) + logger.info(f"Consumer connected - {channel}") + # Keep connection open until explicitly closed, and process requests try: while not channel.is_closed(): request = await channel.recv() - # Process the request here. Should this be a method of RPC? - logger.info(f"Request: {request}") + # Process the request here await _process_consumer_request(request, channel, rpc) except WebSocketDisconnect: # Handle client disconnects - logger.info(f"Consumer disconnected - {ws.client}") + logger.info(f"Consumer disconnected - {channel}") await channel_manager.on_disconnect(ws) except Exception as e: - logger.info(f"Consumer connection failed - {ws.client}") + logger.info(f"Consumer connection failed - {channel}") logger.exception(e) # Handle cases like - # RuntimeError('Cannot call "send" once a closed message has been sent') await channel_manager.on_disconnect(ws) - except Exception: + except Exception as e: logger.error(f"Failed to serve - {ws.client}") + # Log tracebacks to keep track of what errors are happening + logger.exception(e) await channel_manager.on_disconnect(ws) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 8891d3296..1f0cd9c7a 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -1,6 +1,7 @@ import logging from threading import RLock -from typing import List, Type +from typing import List, Optional, Type +from uuid import uuid4 from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy from freqtrade.rpc.api_server.ws.serializer import (HybridJSONWebSocketSerializer, @@ -19,8 +20,12 @@ class WebSocketChannel: def __init__( self, websocket: WebSocketType, + channel_id: Optional[str] = None, serializer_cls: Type[WebSocketSerializer] = HybridJSONWebSocketSerializer ): + + self.channel_id = channel_id if channel_id else uuid4().hex[:8] + # The WebSocket object self._websocket = WebSocketProxy(websocket) # The Serializing class for the WebSocket object @@ -34,6 +39,13 @@ class WebSocketChannel: # Wrap the WebSocket in the Serializing class self._wrapped_ws = self._serializer_cls(self._websocket) + def __repr__(self): + return f"WebSocketChannel({self.channel_id}, {self.remote_addr})" + + @property + def remote_addr(self): + return self._websocket.remote_addr + async def send(self, data): """ Send data on the wrapped websocket diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py index 6acc1d363..73d1481b9 100644 --- a/freqtrade/rpc/api_server/ws/proxy.py +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -1,4 +1,4 @@ -from typing import Union +from typing import Any, Tuple, Union from fastapi import WebSocket as FastAPIWebSocket from websockets import WebSocketClientProtocol as WebSocket @@ -15,6 +15,14 @@ class WebSocketProxy: def __init__(self, websocket: WebSocketType): self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket + @property + def remote_addr(self) -> Tuple[Any, ...]: + if hasattr(self._websocket, "remote_address"): + return self._websocket.remote_address + elif hasattr(self._websocket, "client"): + return tuple(self._websocket.client) + return ("unknown", 0) + async def send(self, data): """ Send data on the wrapped websocket diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index c925624f8..3b39b02c8 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -8,7 +8,7 @@ import asyncio import logging import socket from threading import Thread -from typing import Any, Dict, Optional +from typing import Any, Dict, List, Optional import pandas import websockets @@ -54,11 +54,25 @@ class ExternalMessageConsumer: self.ping_timeout = self._emc_config.get('ping_timeout', 2) self.sleep_time = self._emc_config.get('sleep_time', 5) + self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 500) + # Setting these explicitly as they probably shouldn't be changed by a user # Unless we somehow integrate this with the strategy to allow creating # callbacks for the messages self.topics = [RPCMessageType.WHITELIST, RPCMessageType.ANALYZED_DF] + # Allow setting data for each initial request + self._initial_requests: List[Dict[str, Any]] = [ + { + "type": RPCRequestType.WHITELIST, + "data": None + }, + { + "type": RPCRequestType.ANALYZED_DF, + "data": {"limit": self.initial_candle_limit} + } + ] + self._message_handlers = { RPCMessageType.WHITELIST: self._consume_whitelist_message, RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message, @@ -145,12 +159,14 @@ class ExternalMessageConsumer: while self._running: try: url, token = producer['url'], producer['ws_token'] + name = producer["name"] ws_url = f"{url}?token={token}" # This will raise InvalidURI if the url is bad async with websockets.connect(ws_url) as ws: - logger.info("Connection successful") - channel = WebSocketChannel(ws) + channel = WebSocketChannel(ws, channel_id=name) + + logger.info(f"Producer connection success - {channel}") # Tell the producer we only want these topics # Should always be the first thing we send @@ -158,41 +174,16 @@ class ExternalMessageConsumer: self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) ) - # Now request the initial data from this Producer for every topic - # we've subscribed to - for topic in self.topics: - # without .upper() we get KeyError - request_type = RPCRequestType[topic.upper()] - await channel.send(self.compose_consumer_request(request_type)) + # Now request the initial data from this Producer + for request in self._initial_requests: + request_type = request.get('type', 'none') # Default to string + request_data = request.get('data') + await channel.send( + self.compose_consumer_request(request_type, request_data) + ) # Now receive data, if none is within the time limit, ping - while True: - try: - message = await asyncio.wait_for( - channel.recv(), - timeout=self.reply_timeout - ) - - async with lock: - # Handle the message - self.handle_producer_message(producer, message) - - except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): - # We haven't received data yet. Check the connection and continue. - try: - # ping - ping = await channel.ping() - - await asyncio.wait_for(ping, timeout=self.ping_timeout) - logger.debug(f"Connection to {url} still alive...") - - continue - except Exception: - logger.info( - f"Ping error {url} - retrying in {self.sleep_time}s") - await asyncio.sleep(self.sleep_time) - - break + await self._receive_messages(channel, producer, lock) # Catch invalid ws_url, and break the loop except websockets.exceptions.InvalidURI as e: @@ -214,6 +205,47 @@ class ExternalMessageConsumer: logger.exception(e) break + async def _receive_messages( + self, + channel: WebSocketChannel, + producer: Dict[str, Any], + lock: asyncio.Lock + ): + """ + Loop to handle receiving messages from a Producer + + :param channel: The WebSocketChannel object for the WebSocket + :param producer: Dictionary containing producer info + :param lock: An asyncio Lock + """ + while True: + try: + message = await asyncio.wait_for( + channel.recv(), + timeout=self.reply_timeout + ) + + async with lock: + # Handle the message + self.handle_producer_message(producer, message) + + except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): + # We haven't received data yet. Check the connection and continue. + try: + # ping + ping = await channel.ping() + + await asyncio.wait_for(ping, timeout=self.ping_timeout) + logger.debug(f"Connection to {channel} still alive...") + + continue + except Exception: + logger.info( + f"Ping error {channel} - retrying in {self.sleep_time}s") + await asyncio.sleep(self.sleep_time) + + break + def compose_consumer_request( self, type_: RPCRequestType, @@ -241,7 +273,7 @@ class ExternalMessageConsumer: if message_data is None: return - logger.debug(f"Received message of type {message_type}") + logger.debug(f"Received message of type {message_type} from `{producer_name}`") message_handler = self._message_handlers.get(message_type) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 378677e44..7b29665eb 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1068,10 +1068,10 @@ class RPC: return _data - def _ws_request_analyzed_df(self): + def _ws_request_analyzed_df(self, limit: Optional[int]): """ Historical Analyzed Dataframes for WebSocket """ whitelist = self._freqtrade.active_pair_whitelist - return self._ws_all_analysed_dataframes(whitelist, 500) + return self._ws_all_analysed_dataframes(whitelist, limit) def _ws_request_whitelist(self): """ Whitelist data for WebSocket """ From 05cbcf834ce8cec8b858c89725cc5086bad7c970 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 2 Sep 2022 16:01:33 -0600 Subject: [PATCH 138/592] minor logging changes --- freqtrade/rpc/external_message_consumer.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 3b39b02c8..d3b82cadf 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -54,6 +54,7 @@ class ExternalMessageConsumer: self.ping_timeout = self._emc_config.get('ping_timeout', 2) self.sleep_time = self._emc_config.get('sleep_time', 5) + # The amount of candles per dataframe on the initial request self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 500) # Setting these explicitly as they probably shouldn't be changed by a user @@ -73,6 +74,7 @@ class ExternalMessageConsumer: } ] + # Specify which function to use for which RPCMessageType self._message_handlers = { RPCMessageType.WHITELIST: self._consume_whitelist_message, RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message, @@ -139,7 +141,7 @@ class ExternalMessageConsumer: """ Main connection loop for the consumer - :param producer: Dictionary containing producer info: {'url': '', 'ws_token': ''} + :param producer: Dictionary containing producer info :param lock: An asyncio Lock """ try: @@ -153,7 +155,7 @@ class ExternalMessageConsumer: Actually creates and handles the websocket connection, pinging on timeout and handling connection errors. - :param producer: Dictionary containing producer info: {'url': '', 'ws_token': ''} + :param producer: Dictionary containing producer info :param lock: An asyncio Lock """ while self._running: @@ -176,10 +178,8 @@ class ExternalMessageConsumer: # Now request the initial data from this Producer for request in self._initial_requests: - request_type = request.get('type', 'none') # Default to string - request_data = request.get('data') await channel.send( - self.compose_consumer_request(request_type, request_data) + self.compose_consumer_request(request['type'], request['data']) ) # Now receive data, if none is within the time limit, ping @@ -218,7 +218,7 @@ class ExternalMessageConsumer: :param producer: Dictionary containing producer info :param lock: An asyncio Lock """ - while True: + while self._running: try: message = await asyncio.wait_for( channel.recv(), @@ -273,7 +273,7 @@ class ExternalMessageConsumer: if message_data is None: return - logger.debug(f"Received message of type {message_type} from `{producer_name}`") + logger.info(f"Received message of type {message_type} from `{producer_name}`") message_handler = self._message_handlers.get(message_type) From af5460cebf2b17ea440f1d7f037a7b8c88681d6a Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Fri, 2 Sep 2022 22:01:53 -0300 Subject: [PATCH 139/592] Add option to keep models only in memory for backtest --- config_examples/config_freqai.example.json | 3 ++- docs/freqai.md | 1 + freqtrade/freqai/freqai_interface.py | 4 +++- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index 13c7a94ea..846d37a82 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -56,6 +56,7 @@ "purge_old_models": true, "train_period_days": 15, "backtest_period_days": 7, + "backtest_save_model": true, "live_retrain_hours": 0, "identifier": "uniqe-id", "feature_parameters": { @@ -94,4 +95,4 @@ "internals": { "process_throttle_secs": 5 } -} \ No newline at end of file +} diff --git a/docs/freqai.md b/docs/freqai.md index 482a56d2b..6ee124b9b 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -93,6 +93,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `purge_old_models` | Delete obsolete models (otherwise, all historic models will remain on disk).
    **Datatype:** Boolean. Default: `False`. | `train_period_days` | **Required.**
    Number of days to use for the training data (width of the sliding window).
    **Datatype:** Positive integer. | `backtest_period_days` | **Required.**
    Number of days to inference from the trained model before sliding the window defined above, and retraining the model. This can be fractional days, but beware that the user-provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
    **Datatype:** Float. +| `backtest_save_model` | Saves models to disk when running backtesting.
    **Datatype:** Boolean. Default: `True`. | `identifier` | **Required.**
    A unique name for the current model. This can be reused to reload pre-trained models/data.
    **Datatype:** String. | `live_retrain_hours` | Frequency of retraining during dry/live runs.
    Default set to 0, which means the model will retrain as often as possible.
    **Datatype:** Float > 0. | `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
    Defaults set to 0, which means models never expire.
    **Datatype:** Positive integer. diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 0a63e36ea..9c7ef05a7 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -71,6 +71,7 @@ class IFreqaiModel(ABC): self.first = True self.set_full_path() self.follow_mode: bool = self.freqai_info.get("follow_mode", False) + self.backtest_save_model: bool = self.freqai_info.get("backtest_save_model", True) self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode) self.identifier: str = self.freqai_info.get("identifier", "no_id_provided") self.scanning = False @@ -246,7 +247,8 @@ class IFreqaiModel(ABC): self.dd.pair_dict[metadata["pair"]]["trained_timestamp"] = int( trained_timestamp.stopts) dk.set_new_model_names(metadata["pair"], trained_timestamp) - self.dd.save_data(self.model, metadata["pair"], dk) + if self.backtest_save_model: + self.dd.save_data(self.model, metadata["pair"], dk) else: self.model = self.dd.load_data(metadata["pair"], dk) From 966de1961180e39061277ffef00fdf78f1d86bdf Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 08:16:33 +0200 Subject: [PATCH 140/592] Improve test resiliance by properly setting Order object --- tests/plugins/test_protections.py | 2 ++ tests/test_persistence.py | 2 ++ 2 files changed, 4 insertions(+) diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py index acfe124a8..820eced20 100644 --- a/tests/plugins/test_protections.py +++ b/tests/plugins/test_protections.py @@ -37,6 +37,7 @@ def generate_mock_trade(pair: str, fee: float, is_open: bool, trade.orders.append(Order( ft_order_side=trade.entry_side, order_id=f'{pair}-{trade.entry_side}-{trade.open_date}', + ft_is_open=False, ft_pair=pair, amount=trade.amount, filled=trade.amount, @@ -51,6 +52,7 @@ def generate_mock_trade(pair: str, fee: float, is_open: bool, trade.orders.append(Order( ft_order_side=trade.exit_side, order_id=f'{pair}-{trade.exit_side}-{trade.close_date}', + ft_is_open=False, ft_pair=pair, amount=trade.amount, filled=trade.amount, diff --git a/tests/test_persistence.py b/tests/test_persistence.py index f16c8b054..3ce8a0a2c 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -654,6 +654,7 @@ def test_trade_close(fee): trade.orders.append(Order( ft_order_side=trade.entry_side, order_id=f'{trade.pair}-{trade.entry_side}-{trade.open_date}', + ft_is_open=False, ft_pair=trade.pair, amount=trade.amount, filled=trade.amount, @@ -667,6 +668,7 @@ def test_trade_close(fee): trade.orders.append(Order( ft_order_side=trade.exit_side, order_id=f'{trade.pair}-{trade.exit_side}-{trade.open_date}', + ft_is_open=False, ft_pair=trade.pair, amount=trade.amount, filled=trade.amount, From be192fae910612b745c9b062788d54903bf1c95c Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 10:53:51 +0200 Subject: [PATCH 141/592] Test should use proper Order objects --- tests/test_persistence.py | 34 ++++++++++++++++++---------------- 1 file changed, 18 insertions(+), 16 deletions(-) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index 3ce8a0a2c..23ccc67f3 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -581,25 +581,25 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee, @pytest.mark.parametrize( 'exchange,is_short,lev,open_value,close_value,profit,profit_ratio,trading_mode,funding_fees', [ ("binance", False, 1, 60.15, 65.835, 5.685, 0.09451371, spot, 0.0), - ("binance", True, 1, 59.850, 66.1663784375, -6.3163784375, -0.1055368, margin, 0.0), + ("binance", True, 1, 65.835, 60.151253125, 5.68374687, 0.08633321, margin, 0.0), ("binance", False, 3, 60.15, 65.83416667, 5.68416667, 0.28349958, margin, 0.0), - ("binance", True, 3, 59.85, 66.1663784375, -6.3163784375, -0.31661044, margin, 0.0), + ("binance", True, 3, 65.835, 60.151253125, 5.68374687, 0.25899963, margin, 0.0), ("kraken", False, 1, 60.15, 65.835, 5.685, 0.09451371, spot, 0.0), - ("kraken", True, 1, 59.850, 66.231165, -6.381165, -0.1066192, margin, 0.0), + ("kraken", True, 1, 65.835, 60.21015, 5.62485, 0.0854386, margin, 0.0), ("kraken", False, 3, 60.15, 65.795, 5.645, 0.28154613, margin, 0.0), - ("kraken", True, 3, 59.850, 66.231165, -6.381165, -0.3198578, margin, 0.0), + ("kraken", True, 3, 65.835, 60.21015, 5.62485, 0.25631579, margin, 0.0), ("binance", False, 1, 60.15, 65.835, 5.685, 0.09451371, futures, 0.0), ("binance", False, 1, 60.15, 66.835, 6.685, 0.11113881, futures, 1.0), - ("binance", True, 1, 59.85, 66.165, -6.315, -0.10551378, futures, 0.0), - ("binance", True, 1, 59.85, 67.165, -7.315, -0.12222222, futures, -1.0), + ("binance", True, 1, 65.835, 60.15, 5.685, 0.08635224, futures, 0.0), + ("binance", True, 1, 65.835, 61.15, 4.685, 0.07116276, futures, -1.0), + ("binance", True, 3, 65.835, 59.15, 6.685, 0.3046252, futures, 1.0), ("binance", False, 3, 60.15, 64.835, 4.685, 0.23366583, futures, -1.0), - ("binance", True, 3, 59.85, 65.165, -5.315, -0.26641604, futures, 1.0), ]) @pytest.mark.usefixtures("init_persistence") def test_calc_open_close_trade_price( - limit_buy_order_usdt, limit_sell_order_usdt, fee, exchange, is_short, lev, + limit_order, fee, exchange, is_short, lev, open_value, close_value, profit, profit_ratio, trading_mode, funding_fees ): trade: Trade = Trade( @@ -617,22 +617,24 @@ def test_calc_open_close_trade_price( trading_mode=trading_mode, funding_fees=funding_fees ) - + entry_order = limit_order[trade.entry_side] + exit_order = limit_order[trade.exit_side] trade.open_order_id = f'something-{is_short}-{lev}-{exchange}' - oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, 'ADA/USDT', 'buy') + oobj = Order.parse_from_ccxt_object(entry_order, 'ADA/USDT', trade.entry_side) + trade.orders.append(oobj) trade.update_trade(oobj) - oobj = Order.parse_from_ccxt_object(limit_sell_order_usdt, 'ADA/USDT', 'sell') + oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', trade.exit_side) + trade.orders.append(oobj) trade.update_trade(oobj) - trade.open_rate = 2.0 - trade.close_rate = 2.2 - trade.recalc_open_trade_value() + assert trade.is_open is False + assert pytest.approx(trade._calc_open_trade_value(trade.amount, trade.open_rate)) == open_value assert pytest.approx(trade.calc_close_trade_value(trade.close_rate)) == close_value - assert pytest.approx(trade.calc_profit(trade.close_rate)) == round(profit, 8) - assert pytest.approx(trade.calc_profit_ratio(trade.close_rate)) == profit_ratio + assert pytest.approx(trade.close_profit_abs) == profit + assert pytest.approx(trade.close_profit) == profit_ratio @pytest.mark.usefixtures("init_persistence") From 599c1c79fb8170a7ea4bf9d250a4a3db0a3234ba Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 3 Sep 2022 14:00:01 +0200 Subject: [PATCH 142/592] reorganized backtest utilities, test new functionality, improve/update doc --- config_examples/config_freqai.example.json | 2 - docs/freqai.md | 32 +++++++------ freqtrade/freqai/data_kitchen.py | 27 ++++++++++- freqtrade/freqai/freqai_interface.py | 50 +++++--------------- freqtrade/templates/FreqaiExampleStrategy.py | 2 +- tests/freqai/test_freqai_interface.py | 9 +++- 6 files changed, 63 insertions(+), 59 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index 846d37a82..12eb30128 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -56,7 +56,6 @@ "purge_old_models": true, "train_period_days": 15, "backtest_period_days": 7, - "backtest_save_model": true, "live_retrain_hours": 0, "identifier": "uniqe-id", "feature_parameters": { @@ -75,7 +74,6 @@ "weight_factor": 0.9, "principal_component_analysis": false, "use_SVM_to_remove_outliers": true, - "indicator_max_period_candles": 20, "indicator_periods_candles": [ 10, 20 diff --git a/docs/freqai.md b/docs/freqai.md index 6ee124b9b..3646362c3 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -89,11 +89,10 @@ Mandatory parameters are marked as **Required**, which means that they are requi |------------|-------------| | | **General configuration parameters** | `freqai` | **Required.**
    The parent dictionary containing all the parameters for controlling FreqAI.
    **Datatype:** Dictionary. -| `startup_candles` | Number of candles needed for *backtesting only* to ensure all indicators are non NaNs at the start of the first train period.
    **Datatype:** Positive integer. | `purge_old_models` | Delete obsolete models (otherwise, all historic models will remain on disk).
    **Datatype:** Boolean. Default: `False`. | `train_period_days` | **Required.**
    Number of days to use for the training data (width of the sliding window).
    **Datatype:** Positive integer. | `backtest_period_days` | **Required.**
    Number of days to inference from the trained model before sliding the window defined above, and retraining the model. This can be fractional days, but beware that the user-provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
    **Datatype:** Float. -| `backtest_save_model` | Saves models to disk when running backtesting.
    **Datatype:** Boolean. Default: `True`. +| `save_backtest_models` | Backtesting operates most efficiently by saving the prediction data and reusing them directly for subsequent runs (when users wish to tune entry/exit parameters). If a user wishes to save models to disk when running backtesting, they should activate `save_backtest_models`. A user may wish to do this if they plan to use the same model files for starting a dry/live instance with the same `identifier`.
    **Datatype:** Boolean. Default: `False`. | `identifier` | **Required.**
    A unique name for the current model. This can be reused to reload pre-trained models/data.
    **Datatype:** String. | `live_retrain_hours` | Frequency of retraining during dry/live runs.
    Default set to 0, which means the model will retrain as often as possible.
    **Datatype:** Float > 0. | `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
    Defaults set to 0, which means models never expire.
    **Datatype:** Positive integer. @@ -280,6 +279,17 @@ The FreqAI strategy requires the user to include the following lines of code in Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](#feature-engineering)) and labels ([more information](#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. +### Setting the `startup_candle_count` +Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md/#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). + +!!! Note + Typically it is best for users to be safe and multiply their expected `startup_candle_count` by 2. There are instances where the talib functions actually require more data than just the passed `period`. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Look out for this log message to confirm that your data is clean: + + ``` + 2022-08-31 15:14:04 - freqtrade.freqai.data_kitchen - INFO - dropped 0 training points due to NaNs in populated dataset 4319. + ``` + + ## Creating a dynamic target The `&*_std/mean` return values describe the statistical fit of the user defined label *during the most recent training*. This value allows the user to know the rarity of a given prediction. For example, `templates/FreqaiExampleStrategy.py`, creates a `target_roi` which is based on filtering out predictions that are below a given z-score of 1.25. @@ -505,7 +515,7 @@ and if a full `live_retrain_hours` has elapsed since the end of the loaded model The FreqAI backtesting module can be executed with the following command: ```bash -freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 +freqtrade backtesting --strategy FreqaiExampleStrategy --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 ``` Backtesting mode requires the user to have the data pre-downloaded (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). @@ -532,20 +542,14 @@ the user is asking FreqAI to use a training period of 30 days and backtest on th This means that if the user sets `--timerange 20210501-20210701`, FreqAI will train have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). After the training of the model, FreqAI will backtest the subsequent 7 days. The "sliding window" then moves one week forward (emulating FreqAI retraining once per week in live mode) and the new model uses the previous 30 days (including the 7 days used for backtesting by the previous model) to train. This is repeated until the end of `--timerange`. -In live mode, the required training data is automatically computed and downloaded. However, in backtesting mode, -the user must manually enter the required number of `startup_candles` in the config. This value -is used to increase the data to FreqAI, which should be sufficient to enable all indicators -to be NaN free at the beginning of the first training. This is done by identifying the -longest timeframe (`4h` in presented example config) and the longest indicator period (`20` days in presented example config) -and adding this to the `train_period_days`. The units need to be in the base candle time frame: -`startup_candles` = ( 4 hours * 20 max period * 60 minutes/hour + 30 day train_period_days * 1440 minutes per day ) / 5 min (base time frame) = 9360. - -!!! Note - In dry/live mode, this is all precomputed and handled automatically. Thus, `startup_candle` has no influence on dry/live mode. - !!! Note Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run. +### Downloading data for backtesting +Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download/#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by taking subtracting `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. + +As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). + ### Defining model expirations During dry/live mode, FreqAI trains each coin pair sequentially (on separate threads/GPU from the main Freqtrade bot). This means that there is always an age discrepancy between models. If a user is training on 50 pairs, and each pair requires 5 minutes to train, the oldest model will be over 4 hours old. This may be undesirable if the characteristic time scale (the trade duration target) for a strategy is less than 4 hours. The user can decide to only make trade entries if the model is less than diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index f88e20223..13af1e0d2 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -70,7 +70,7 @@ class FreqaiDataKitchen: self.training_features_list: List = [] self.model_filename: str = "" self.backtesting_results_path = Path() - self.backtesting_prediction_folder: str = "backtesting_predictions" + self.backtest_predictions_folder: str = "backtesting_predictions" self.live = live self.pair = pair @@ -1077,7 +1077,7 @@ class FreqaiDataKitchen: Save prediction dataframe from backtesting to h5 file format :param append_df: dataframe for backtesting period """ - full_predictions_folder = Path(self.full_path / self.backtesting_prediction_folder) + full_predictions_folder = Path(self.full_path / self.backtest_predictions_folder) if not full_predictions_folder.is_dir(): full_predictions_folder.mkdir(parents=True, exist_ok=True) @@ -1092,3 +1092,26 @@ class FreqaiDataKitchen: """ append_df = pd.read_hdf(self.backtesting_results_path) return append_df + + def check_if_backtest_prediction_exists( + self + ) -> bool: + """ + Check if a backtesting prediction already exists + :param dk: FreqaiDataKitchen + :return: + :boolean: whether the prediction file exists or not. + """ + path_to_predictionfile = Path(self.full_path / + self.backtest_predictions_folder / + f"{self.model_filename}_prediction.h5") + self.backtesting_results_path = path_to_predictionfile + + file_exists = path_to_predictionfile.is_file() + if file_exists: + logger.info(f"Found backtesting prediction file at {path_to_predictionfile}") + else: + logger.info( + f"Could not find backtesting prediction file at {path_to_predictionfile}" + ) + return file_exists diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 9c7ef05a7..399568c7d 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -71,7 +71,9 @@ class IFreqaiModel(ABC): self.first = True self.set_full_path() self.follow_mode: bool = self.freqai_info.get("follow_mode", False) - self.backtest_save_model: bool = self.freqai_info.get("backtest_save_model", True) + self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", False) + if self.save_backtest_models: + logger.info('Backtesting module configured to save all models.') self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode) self.identifier: str = self.freqai_info.get("identifier", "no_id_provided") self.scanning = False @@ -125,10 +127,9 @@ class IFreqaiModel(ABC): elif not self.follow_mode: self.dk = FreqaiDataKitchen(self.config, self.live, metadata["pair"]) logger.info(f"Training {len(self.dk.training_timeranges)} timeranges") - with self.analysis_lock: - dataframe = self.dk.use_strategy_to_populate_indicators( - strategy, prediction_dataframe=dataframe, pair=metadata["pair"] - ) + dataframe = self.dk.use_strategy_to_populate_indicators( + strategy, prediction_dataframe=dataframe, pair=metadata["pair"] + ) dk = self.start_backtesting(dataframe, metadata, self.dk) dataframe = dk.remove_features_from_df(dk.return_dataframe) @@ -232,10 +233,9 @@ class IFreqaiModel(ABC): f"sub-train-{metadata['pair'].split('/')[0]}_{trained_timestamp_int}" ) - coin, _ = metadata["pair"].split("/") - dk.model_filename = f"cb_{coin.lower()}_{trained_timestamp_int}" + dk.set_new_model_names(metadata["pair"], trained_timestamp) - if self.backtest_prediction_exists(dk): + if dk.check_if_backtest_prediction_exists(): append_df = dk.get_backtesting_prediction() dk.append_predictions(append_df) else: @@ -246,8 +246,9 @@ class IFreqaiModel(ABC): self.model = self.train(dataframe_train, metadata["pair"], dk) self.dd.pair_dict[metadata["pair"]]["trained_timestamp"] = int( trained_timestamp.stopts) - dk.set_new_model_names(metadata["pair"], trained_timestamp) - if self.backtest_save_model: + + if self.save_backtest_models: + logger.info('Saving backtest model to disk.') self.dd.save_data(self.model, metadata["pair"], dk) else: self.model = self.dd.load_data(metadata["pair"], dk) @@ -644,35 +645,6 @@ class IFreqaiModel(ABC): self.train_time = 0 return - def backtest_prediction_exists( - self, - dk: FreqaiDataKitchen, - scanning: bool = False, - ) -> bool: - """ - Check if a backtesting prediction already exists - :param dk: FreqaiDataKitchen - :return: - :boolean: whether the prediction file exists or not. - """ - if not self.live: - prediction_file_name = dk.model_filename - path_to_predictionfile = Path(dk.full_path / - dk.backtesting_prediction_folder / - f"{prediction_file_name}_prediction.h5") - dk.backtesting_results_path = path_to_predictionfile - - file_exists = path_to_predictionfile.is_file() - if file_exists and not scanning: - logger.info("Found backtesting prediction file at %s", prediction_file_name) - elif not scanning: - logger.info( - "Could not find backtesting prediction file at %s", prediction_file_name - ) - return file_exists - else: - return False - # Following methods which are overridden by user made prediction models. # See freqai/prediction_models/CatboostPredictionModel.py for an example. diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index aa584bfbc..0e822a028 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -44,7 +44,7 @@ class FreqaiExampleStrategy(IStrategy): stoploss = -0.05 use_exit_signal = True # this is the maximum period fed to talib (timeframe independent) - startup_candle_count: int = 20 + startup_candle_count: int = 40 can_short = False linear_roi_offset = DecimalParameter( diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 09f5d27ff..5441b3c24 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -174,6 +174,7 @@ def test_train_model_in_series_LightGBMClassifier(mocker, freqai_conf): def test_start_backtesting(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180130"}) + freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) @@ -200,6 +201,7 @@ def test_start_backtesting(mocker, freqai_conf): def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180124"}) freqai_conf.get("freqai", {}).update({"backtest_period_days": 0.5}) + freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) @@ -224,6 +226,7 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): freqai_conf.update({"timerange": "20180120-20180130"}) + freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) @@ -263,10 +266,14 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): freqai.start_backtesting(df, metadata, freqai.dk) assert log_has_re( - "Found backtesting prediction ", + "Found backtesting prediction file ", caplog, ) + path = (freqai.dd.full_path / freqai.dk.backtest_predictions_folder) + prediction_files = [x for x in path.iterdir() if x.is_file()] + assert len(prediction_files) == 5 + shutil.rmtree(Path(freqai.dk.full_path)) From 80b5f035aba23f382363dc81499477977cea1e27 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 15:01:28 +0200 Subject: [PATCH 143/592] Remove typo in log message --- freqtrade/freqai/freqai_interface.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 6b4ac183a..0bd88c64f 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -613,8 +613,8 @@ class IFreqaiModel(ABC): logger.info( f'Total time spent inferencing pairlist {self.inference_time:.2f} seconds') if self.inference_time > 0.25 * self.base_tf_seconds: - logger.warning('Inference took over 25/% of the candle time. Reduce pairlist to' - ' avoid blinding open trades and degrading performance.') + logger.warning("Inference took over 25% of the candle time. Reduce pairlist to" + " avoid blinding open trades and degrading performance.") self.pair_it = 0 self.inference_time = 0 return From df50b1928d6d58b130d1d2b40dcaad334800bcc3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 06:51:30 +0200 Subject: [PATCH 144/592] Fix funding fee calculation for backtesting --- freqtrade/optimize/backtesting.py | 2 +- freqtrade/persistence/trade_model.py | 34 +++++++++++++++++++++++++--- 2 files changed, 32 insertions(+), 4 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 77bf3d8ad..8f6b6b332 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -686,7 +686,7 @@ class Backtesting: self.futures_data[trade.pair], amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc, + open_date=trade.date_last_filled_utc, close_date=exit_candle_time, ) diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 1f14f110e..9c9c7f381 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -65,6 +65,8 @@ class Order(_DECL_BASE): order_filled_date = Column(DateTime, nullable=True) order_update_date = Column(DateTime, nullable=True) + funding_fee = Column(Float, nullable=True) + ft_fee_base = Column(Float, nullable=True) @property @@ -72,6 +74,13 @@ class Order(_DECL_BASE): """ Order-date with UTC timezoneinfo""" return self.order_date.replace(tzinfo=timezone.utc) + @property + def order_filled_utc(self) -> Optional[datetime]: + """ last order-date with UTC timezoneinfo""" + return ( + self.order_filled_date.replace(tzinfo=timezone.utc) if self.order_filled_date else None + ) + @property def safe_price(self) -> float: return self.average or self.price @@ -179,6 +188,10 @@ class Order(_DECL_BASE): self.remaining = 0 self.status = 'closed' self.ft_is_open = False + # Assign funding fees to Order. + # Assumes backtesting will use date_last_filled_utc to calculate future funding fees. + self.funding_fee = trade.funding_fees + if (self.ft_order_side == trade.entry_side): trade.open_rate = self.price trade.recalc_trade_from_orders() @@ -346,6 +359,12 @@ class LocalTrade(): else: return self.amount + @property + def date_last_filled_utc(self): + """ Date of the last filled order""" + return max([self.open_date_utc, + max(o.order_filled_utc for o in self.orders if o.filled and not o.ft_is_open)]) + @property def open_date_utc(self): return self.open_date.replace(tzinfo=timezone.utc) @@ -843,10 +862,14 @@ class LocalTrade(): close_profit = 0.0 close_profit_abs = 0.0 profit = None - for o in self.orders: + # Reset funding fees + self.funding_fees = 0.0 + funding_fees = 0.0 + ordercount = len(self.orders) - 1 + for i, o in enumerate(self.orders): if o.ft_is_open or not o.filled: continue - + funding_fees += (o.funding_fee or 0.0) tmp_amount = FtPrecise(o.safe_amount_after_fee) tmp_price = FtPrecise(o.safe_price) @@ -861,7 +884,11 @@ class LocalTrade(): avg_price = current_stake / current_amount if is_exit: - # Process partial exits + # Process exits + if i == ordercount and is_closing: + # Apply funding fees only to the last order + self.funding_fees = funding_fees + exit_rate = o.safe_price exit_amount = o.safe_amount_after_fee profit = self.calc_profit(rate=exit_rate, amount=exit_amount, @@ -871,6 +898,7 @@ class LocalTrade(): exit_rate, amount=exit_amount, open_rate=avg_price) else: total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price) + self.funding_fees = funding_fees if close_profit: self.close_profit = close_profit From 0c6a02687a49b48c433ec841200911b21efc8f24 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 20:55:13 +0200 Subject: [PATCH 145/592] Don't calculate funding fees if we're not going to use them. --- freqtrade/freqtradebot.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 37bc6dfed..95b42155f 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -726,10 +726,11 @@ class FreqtradeBot(LoggingMixin): fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker') base_currency = self.exchange.get_pair_base_currency(pair) open_date = datetime.now(timezone.utc) - funding_fees = self.exchange.get_funding_fees( - pair=pair, amount=amount, is_short=is_short, open_date=open_date) + # This is a new trade if trade is None: + funding_fees = self.exchange.get_funding_fees( + pair=pair, amount=amount, is_short=is_short, open_date=open_date) trade = Trade( pair=pair, base_currency=base_currency, From 0f483ee31f043ceafaa7a5c19eaa77ade2e1d323 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 10:06:23 +0200 Subject: [PATCH 146/592] Use "since last order" approach for live as well. --- freqtrade/freqtradebot.py | 4 ++-- freqtrade/persistence/trade_model.py | 12 +++++++++--- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 95b42155f..5323a5fc0 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -281,7 +281,7 @@ class FreqtradeBot(LoggingMixin): pair=trade.pair, amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc + open_date=trade.date_last_filled_utc ) trade.funding_fees = funding_fees else: @@ -1485,7 +1485,7 @@ class FreqtradeBot(LoggingMixin): pair=trade.pair, amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc, + open_date=trade.date_last_filled_utc, ) exit_type = 'exit' exit_reason = exit_tag or exit_check.exit_reason diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 9c9c7f381..c2a87daaa 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -128,6 +128,10 @@ class Order(_DECL_BASE): self.ft_is_open = True if self.status in NON_OPEN_EXCHANGE_STATES: self.ft_is_open = False + if self.trade: + # Assign funding fee up to this point + # (represents the funding fee since the last order) + self.funding_fee = self.trade.funding_fees if (order.get('filled', 0.0) or 0.0) > 0: self.order_filled_date = datetime.now(timezone.utc) self.order_update_date = datetime.now(timezone.utc) @@ -360,10 +364,12 @@ class LocalTrade(): return self.amount @property - def date_last_filled_utc(self): + def date_last_filled_utc(self) -> datetime: """ Date of the last filled order""" - return max([self.open_date_utc, - max(o.order_filled_utc for o in self.orders if o.filled and not o.ft_is_open)]) + orders = self.select_filled_orders() + if not orders: + return self.open_date_utc + return max([self.open_date_utc, max(o.order_filled_utc for o in orders)]) @property def open_date_utc(self): From b95b3d8391f4df3bb3510173711349d7356a08ec Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 15:09:50 +0200 Subject: [PATCH 147/592] Update test to actually test funding fee appliance --- tests/test_persistence.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index 23ccc67f3..cdca3bc4d 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -615,21 +615,25 @@ def test_calc_open_close_trade_price( is_short=is_short, leverage=lev, trading_mode=trading_mode, - funding_fees=funding_fees ) entry_order = limit_order[trade.entry_side] exit_order = limit_order[trade.exit_side] trade.open_order_id = f'something-{is_short}-{lev}-{exchange}' oobj = Order.parse_from_ccxt_object(entry_order, 'ADA/USDT', trade.entry_side) - trade.orders.append(oobj) + oobj.trade = trade + oobj.update_from_ccxt_object(entry_order) trade.update_trade(oobj) + trade.funding_fees = funding_fees + oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', trade.exit_side) - trade.orders.append(oobj) + oobj.trade = trade + oobj.update_from_ccxt_object(exit_order) trade.update_trade(oobj) assert trade.is_open is False + assert trade.funding_fees == funding_fees assert pytest.approx(trade._calc_open_trade_value(trade.amount, trade.open_rate)) == open_value assert pytest.approx(trade.calc_close_trade_value(trade.close_rate)) == close_value From ed4cc18cddaaff7bdb95738ee4a3d5093530b0e0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 15:18:09 +0200 Subject: [PATCH 148/592] Migration to check order funding fee --- freqtrade/persistence/migrations.py | 10 ++++++---- freqtrade/persistence/trade_model.py | 2 +- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index 1131c88b4..1f1330ba7 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -212,17 +212,18 @@ def migrate_orders_table(engine, table_back_name: str, cols_order: List): ft_fee_base = get_column_def(cols_order, 'ft_fee_base', 'null') average = get_column_def(cols_order, 'average', 'null') stop_price = get_column_def(cols_order, 'stop_price', 'null') + funding_fee = get_column_def(cols_order, 'funding_fee', '0.0') # sqlite does not support literals for booleans with engine.begin() as connection: connection.execute(text(f""" insert into orders (id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, average, remaining, cost, - stop_price, order_date, order_filled_date, order_update_date, ft_fee_base) + stop_price, order_date, order_filled_date, order_update_date, ft_fee_base, funding_fee) select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, {average} average, remaining, cost, {stop_price} stop_price, order_date, order_filled_date, - order_update_date, {ft_fee_base} ft_fee_base + order_update_date, {ft_fee_base} ft_fee_base {funding_fee} funding_fee from {table_back_name} """)) @@ -307,9 +308,10 @@ def check_migrate(engine, decl_base, previous_tables) -> None: # Check if migration necessary # Migrates both trades and orders table! # if ('orders' not in previous_tables - # or not has_column(cols_orders, 'stop_price')): + # or not has_column(cols_orders, 'funding_fee')): migrating = False - if not has_column(cols_trades, 'contract_size'): + if not has_column(cols_orders, 'funding_fee'): + # if not has_column(cols_trades, 'contract_size'): migrating = True logger.info(f"Running database migration for trades - " f"backup: {table_back_name}, {order_table_bak_name}") diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index c2a87daaa..6127c502d 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -892,7 +892,7 @@ class LocalTrade(): if is_exit: # Process exits if i == ordercount and is_closing: - # Apply funding fees only to the last order + # Apply funding fees only to the last closing order self.funding_fees = funding_fees exit_rate = o.safe_price From c9be66b5b639f151abb1d9a5e76267d752eddb3b Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 3 Sep 2022 15:52:29 +0200 Subject: [PATCH 149/592] increase test coverage for dk, improve function naming, extra cleaning --- freqtrade/freqai/data_kitchen.py | 30 ++++++----- freqtrade/freqai/freqai_interface.py | 10 ++-- tests/freqai/conftest.py | 32 +++++++++++ tests/freqai/test_freqai_datakitchen.py | 72 ++++++++++++++++++++++++- tests/freqai/test_freqai_interface.py | 34 ++++++------ 5 files changed, 143 insertions(+), 35 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 9d4a69287..fce9e8480 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1,7 +1,7 @@ import copy -import datetime import logging import shutil +from datetime import datetime, timezone from pathlib import Path from typing import Any, Dict, List, Tuple @@ -345,7 +345,7 @@ class FreqaiDataKitchen: def denormalize_labels_from_metadata(self, df: DataFrame) -> DataFrame: """ - Normalize a set of data using the mean and standard deviation from + Denormalize a set of data using the mean and standard deviation from the associated training data. :param df: Dataframe of predictions to be denormalized """ @@ -384,7 +384,7 @@ class FreqaiDataKitchen: config_timerange = TimeRange.parse_timerange(self.config["timerange"]) if config_timerange.stopts == 0: config_timerange.stopts = int( - datetime.datetime.now(tz=datetime.timezone.utc).timestamp() + datetime.now(tz=timezone.utc).timestamp() ) timerange_train = copy.deepcopy(full_timerange) timerange_backtest = copy.deepcopy(full_timerange) @@ -401,8 +401,8 @@ class FreqaiDataKitchen: timerange_train.stopts = timerange_train.startts + train_period_days first = False - start = datetime.datetime.utcfromtimestamp(timerange_train.startts) - stop = datetime.datetime.utcfromtimestamp(timerange_train.stopts) + start = datetime.utcfromtimestamp(timerange_train.startts) + stop = datetime.utcfromtimestamp(timerange_train.stopts) tr_training_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")) tr_training_list_timerange.append(copy.deepcopy(timerange_train)) @@ -415,8 +415,8 @@ class FreqaiDataKitchen: if timerange_backtest.stopts > config_timerange.stopts: timerange_backtest.stopts = config_timerange.stopts - start = datetime.datetime.utcfromtimestamp(timerange_backtest.startts) - stop = datetime.datetime.utcfromtimestamp(timerange_backtest.stopts) + start = datetime.utcfromtimestamp(timerange_backtest.startts) + stop = datetime.utcfromtimestamp(timerange_backtest.stopts) tr_backtesting_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")) tr_backtesting_list_timerange.append(copy.deepcopy(timerange_backtest)) @@ -436,8 +436,8 @@ class FreqaiDataKitchen: it is sliced down to just the present training period. """ - start = datetime.datetime.fromtimestamp(timerange.startts, tz=datetime.timezone.utc) - stop = datetime.datetime.fromtimestamp(timerange.stopts, tz=datetime.timezone.utc) + start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) + stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc) df = df.loc[df["date"] >= start, :] df = df.loc[df["date"] <= stop, :] @@ -808,6 +808,8 @@ class FreqaiDataKitchen: [compute_df, inlier_metric], axis=1) self.data_dictionary['prediction_features'].fillna(0, inplace=True) + logger.info('Inlier metric computed and added to features.') + return None def remove_beginning_points_from_data_dict(self, set_='train', no_prev_pts: int = 10): @@ -948,14 +950,14 @@ class FreqaiDataKitchen: "Please indicate the end date of your desired backtesting. " "timerange.") # backtest_timerange.stopts = int( - # datetime.datetime.now(tz=datetime.timezone.utc).timestamp() + # datetime.now(tz=timezone.utc).timestamp() # ) backtest_timerange.startts = ( backtest_timerange.startts - backtest_period_days * SECONDS_IN_DAY ) - start = datetime.datetime.utcfromtimestamp(backtest_timerange.startts) - stop = datetime.datetime.utcfromtimestamp(backtest_timerange.stopts) + start = datetime.utcfromtimestamp(backtest_timerange.startts) + stop = datetime.utcfromtimestamp(backtest_timerange.stopts) full_timerange = start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d") self.full_path = Path( @@ -981,7 +983,7 @@ class FreqaiDataKitchen: :return: bool = If the model is expired or not. """ - time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() + time = datetime.now(tz=timezone.utc).timestamp() elapsed_time = (time - trained_timestamp) / 3600 # hours max_time = self.freqai_config.get("expiration_hours", 0) if max_time > 0: @@ -993,7 +995,7 @@ class FreqaiDataKitchen: self, trained_timestamp: int ) -> Tuple[bool, TimeRange, TimeRange]: - time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp() + time = datetime.now(tz=timezone.utc).timestamp() trained_timerange = TimeRange() data_load_timerange = TimeRange() diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 893f960ea..fd0554248 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -1,10 +1,10 @@ # import contextlib -import datetime import logging import shutil import threading import time from abc import ABC, abstractmethod +from datetime import datetime from pathlib import Path from threading import Lock from typing import Any, Dict, Tuple @@ -174,7 +174,7 @@ class IFreqaiModel(ABC): if retrain: self.train_timer('start') - self.train_model_in_series( + self.extract_data_and_train_model( new_trained_timerange, pair, strategy, dk, data_load_timerange ) self.train_timer('stop') @@ -214,10 +214,10 @@ class IFreqaiModel(ABC): dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe) trained_timestamp = tr_train - tr_train_startts_str = datetime.datetime.utcfromtimestamp(tr_train.startts).strftime( + tr_train_startts_str = datetime.utcfromtimestamp(tr_train.startts).strftime( "%Y-%m-%d %H:%M:%S" ) - tr_train_stopts_str = datetime.datetime.utcfromtimestamp(tr_train.stopts).strftime( + tr_train_stopts_str = datetime.utcfromtimestamp(tr_train.stopts).strftime( "%Y-%m-%d %H:%M:%S" ) logger.info( @@ -495,7 +495,7 @@ class IFreqaiModel(ABC): Path(self.full_path, Path(self.config["config_files"][0]).name), ) - def train_model_in_series( + def extract_data_and_train_model( self, new_trained_timerange: TimeRange, pair: str, diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index dd148da77..6528347e8 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -82,6 +82,38 @@ def get_patched_freqaimodel(mocker, freqaiconf): return freqaimodel +def make_unfiltered_dataframe(mocker, freqai_conf): + freqai_conf.update({"timerange": "20180110-20180130"}) + + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange) + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = True + freqai.dk = FreqaiDataKitchen(freqai_conf) + freqai.dk.pair = "ADA/BTC" + timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(timerange, freqai.dk) + + freqai.dd.pair_dict = MagicMock() + + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") + + corr_dataframes, base_dataframes = freqai.dd.get_base_and_corr_dataframes( + data_load_timerange, freqai.dk.pair, freqai.dk + ) + + unfiltered_dataframe = freqai.dk.use_strategy_to_populate_indicators( + strategy, corr_dataframes, base_dataframes, freqai.dk.pair + ) + + unfiltered_dataframe = freqai.dk.slice_dataframe(new_timerange, unfiltered_dataframe) + + return freqai, unfiltered_dataframe + + def make_data_dictionary(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 9ef955695..2204e94c6 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -6,7 +6,8 @@ import pytest from freqtrade.exceptions import OperationalException from tests.conftest import log_has_re -from tests.freqai.conftest import get_patched_data_kitchen, make_data_dictionary +from tests.freqai.conftest import (get_patched_data_kitchen, make_data_dictionary, + make_unfiltered_dataframe) @pytest.mark.parametrize( @@ -94,3 +95,72 @@ def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, "SVM detected 8.46%", caplog, ) + + +def test_compute_inlier_metric(mocker, freqai_conf, caplog): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai_conf['freqai']['feature_parameters'].update({"inlier_metric_window": 10}) + freqai.dk.compute_inlier_metric(set_='train') + assert log_has_re( + "Inlier metric computed and added to features.", + caplog, + ) + + +def test_add_noise_to_training_features(mocker, freqai_conf): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai_conf['freqai']['feature_parameters'].update({"noise_standard_deviation": 0.1}) + freqai.dk.add_noise_to_training_features() + + +def test_remove_beginning_points_from_data_dict(mocker, freqai_conf): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai.dk.remove_beginning_points_from_data_dict(set_='train') + + +def test_principal_component_analysis(mocker, freqai_conf, caplog): + freqai = make_data_dictionary(mocker, freqai_conf) + freqai.dk.principal_component_analysis() + assert log_has_re( + "reduced feature dimension by", + caplog, + ) + + +def test_normalize_data(mocker, freqai_conf): + freqai = make_data_dictionary(mocker, freqai_conf) + data_dict = freqai.dk.data_dictionary + freqai.dk.normalize_data(data_dict) + assert len(freqai.dk.data) == 56 + + +def test_filter_features(mocker, freqai_conf): + freqai, unfiltered_dataframe = make_unfiltered_dataframe(mocker, freqai_conf) + freqai.dk.find_features(unfiltered_dataframe) + + filtered_df, labels = freqai.dk.filter_features( + unfiltered_dataframe, + freqai.dk.training_features_list, + freqai.dk.label_list, + training_filter=True, + ) + + assert len(filtered_df.columns) == 26 + + +def test_make_train_test_datasets(mocker, freqai_conf): + freqai, unfiltered_dataframe = make_unfiltered_dataframe(mocker, freqai_conf) + freqai.dk.find_features(unfiltered_dataframe) + + features_filtered, labels_filtered = freqai.dk.filter_features( + unfiltered_dataframe, + freqai.dk.training_features_list, + freqai.dk.label_list, + training_filter=True, + ) + + data_dictionary = freqai.dk.make_train_test_datasets(features_filtered, labels_filtered) + + assert data_dictionary + assert len(data_dictionary) == 7 + assert len(data_dictionary['train_features'].index) == 1916 diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 792ffc467..927af2a02 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -17,7 +17,7 @@ def is_arm() -> bool: return "arm" in machine or "aarch64" in machine -def test_train_model_in_series_LightGBM(mocker, freqai_conf): +def test_extract_data_and_train_model_LightGBM(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) @@ -35,7 +35,8 @@ def test_train_model_in_series_LightGBM(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() @@ -45,7 +46,7 @@ def test_train_model_in_series_LightGBM(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf): +def test_extract_data_and_train_model_LightGBMMultiModel(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"strategy": "freqai_test_multimodel_strat"}) freqai_conf.update({"freqaimodel": "LightGBMRegressorMultiTarget"}) @@ -64,7 +65,8 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert len(freqai.dk.label_list) == 2 assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() @@ -77,7 +79,7 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf): @pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") -def test_train_model_in_series_Catboost(mocker, freqai_conf): +def test_extract_data_and_train_model_Catboost(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "CatboostRegressor"}) # freqai_conf.get('freqai', {}).update( @@ -98,8 +100,8 @@ def test_train_model_in_series_Catboost(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", + strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() @@ -110,7 +112,7 @@ def test_train_model_in_series_Catboost(mocker, freqai_conf): @pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") -def test_train_model_in_series_CatboostClassifier(mocker, freqai_conf): +def test_extract_data_and_train_model_CatboostClassifier(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "CatboostClassifier"}) freqai_conf.update({"strategy": "freqai_test_classifier"}) @@ -130,8 +132,8 @@ def test_train_model_in_series_CatboostClassifier(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", + strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() @@ -141,7 +143,7 @@ def test_train_model_in_series_CatboostClassifier(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_train_model_in_series_LightGBMClassifier(mocker, freqai_conf): +def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "LightGBMClassifier"}) freqai_conf.update({"strategy": "freqai_test_classifier"}) @@ -161,8 +163,8 @@ def test_train_model_in_series_LightGBMClassifier(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", + strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() @@ -289,7 +291,8 @@ def test_follow_mode(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() @@ -338,7 +341,8 @@ def test_principal_component_analysis(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_pca_object.pkl") From fa8d5b9834ab1ba872e5ca2397e24ed3df9968a7 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 3 Sep 2022 16:05:18 +0200 Subject: [PATCH 150/592] add documentation for noise_standard_deviation` --- docs/freqai.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/freqai.md b/docs/freqai.md index 2c6efa3b9..d504c93d6 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -116,6 +116,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` | `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False | `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 +| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5%. Good for preventing overfitting.
    **Datatype:** int. Default: 0 | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. From c21808ff9830b8f0e98b93fdc1e998b4ee37b4c0 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 3 Sep 2022 16:54:30 +0200 Subject: [PATCH 151/592] remove metadata redundancy, fix pca bug --- freqtrade/freqai/data_kitchen.py | 55 +++++++++++++++----------------- 1 file changed, 26 insertions(+), 29 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 69ce5272d..ff8f72490 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -288,25 +288,20 @@ class FreqaiDataKitchen: :data_dictionary: updated dictionary with standardized values. """ - df_train_features = data_dictionary["train_features"] + df = data_dictionary["train_features"] # standardize the data by training stats - train_max = df_train_features.max() - train_min = df_train_features.min() - df_train_features = ( - 2 * (df_train_features - train_min) / (train_max - train_min) - 1 + train_max = df.max() + train_min = df.min() + df = ( + 2 * (df - train_min) / (train_max - train_min) - 1 ) data_dictionary["test_features"] = ( 2 * (data_dictionary["test_features"] - train_min) / (train_max - train_min) - 1 ) for item in train_max.keys(): - if not [col for col in df_train_features.columns if col.startswith('PC')]: - self.data[item + "_max"] = train_max[item] - self.data[item + "_min"] = train_min[item] - else: - # if PCA is enabled and has transformed the training features - self.data[item + "_pca_max"] = train_max[item] - self.data[item + "_pca_min"] = train_min[item] + self.data[item + "_max"] = train_max[item] + self.data[item + "_min"] = train_min[item] for item in data_dictionary["train_labels"].keys(): if data_dictionary["train_labels"][item].dtype == object: @@ -327,16 +322,24 @@ class FreqaiDataKitchen: - 1 ) - if not [col for col in df_train_features.columns if col.startswith('PC')]: - self.data[f"{item}_max"] = train_labels_max # .to_dict() - self.data[f"{item}_min"] = train_labels_min # .to_dict() - else: - # if PCA is enabled and has transformed the training features - self.data[f"{item}_pca_max"] = train_labels_max # .to_dict() - self.data[f"{item}_pca_min"] = train_labels_min # .to_dict() - + self.data[f"{item}_max"] = train_labels_max + self.data[f"{item}_min"] = train_labels_min return data_dictionary + def normalize_single_dataframe(self, df: DataFrame) -> DataFrame: + + train_max = df.max() + train_min = df.min() + df = ( + 2 * (df - train_min) / (train_max - train_min) - 1 + ) + + for item in train_max.keys(): + self.data[item + "_max"] = train_max[item] + self.data[item + "_min"] = train_min[item] + + return df + def normalize_data_from_metadata(self, df: DataFrame) -> DataFrame: """ Normalize a set of data using the mean and standard deviation from @@ -344,17 +347,11 @@ class FreqaiDataKitchen: :param df: Dataframe to be standardized """ - if not [col for col in df.columns if col.startswith('PC')]: - id_str = '' - else: - # if PCA is enabled - id_str = '_pca' - for item in df.keys(): df[item] = ( 2 - * (df[item] - self.data[f"{item}{id_str}_min"]) - / (self.data[f"{item}{id_str}_max"] - self.data[f"{item}{id_str}_min"]) + * (df[item] - self.data[f"{item}_min"]) + / (self.data[f"{item}_max"] - self.data[f"{item}_min"]) - 1 ) @@ -484,7 +481,7 @@ class FreqaiDataKitchen: index=self.data_dictionary["train_features"].index, ) # normalsing transformed training features - self.data_dictionary["train_features"] = self.normalize_data( + self.data_dictionary["train_features"] = self.normalize_single_dataframe( self.data_dictionary["train_features"]) # keeping a copy of the non-transformed features so we can check for errors during From 5cfb4154ebce933997cd45b0e1d3c57876271e5f Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 3 Sep 2022 19:48:30 +0200 Subject: [PATCH 152/592] revert all changes in normalize_data() --- freqtrade/freqai/data_kitchen.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index ff8f72490..3335503d3 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -288,12 +288,11 @@ class FreqaiDataKitchen: :data_dictionary: updated dictionary with standardized values. """ - df = data_dictionary["train_features"] # standardize the data by training stats - train_max = df.max() - train_min = df.min() - df = ( - 2 * (df - train_min) / (train_max - train_min) - 1 + train_max = data_dictionary["train_features"].max() + train_min = data_dictionary["train_features"].min() + data_dictionary["train_features"] = ( + 2 * (data_dictionary["train_features"] - train_min) / (train_max - train_min) - 1 ) data_dictionary["test_features"] = ( 2 * (data_dictionary["test_features"] - train_min) / (train_max - train_min) - 1 @@ -322,8 +321,8 @@ class FreqaiDataKitchen: - 1 ) - self.data[f"{item}_max"] = train_labels_max - self.data[f"{item}_min"] = train_labels_min + self.data[f"{item}_max"] = train_labels_max + self.data[f"{item}_min"] = train_labels_min return data_dictionary def normalize_single_dataframe(self, df: DataFrame) -> DataFrame: From 16573b19e3d478b3a5625a81d2504823dee4cdf8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 19:34:38 +0200 Subject: [PATCH 153/592] Fix migration syntax error --- freqtrade/persistence/migrations.py | 4 ++-- freqtrade/persistence/trade_model.py | 3 ++- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index 1f1330ba7..a54c5570f 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -223,7 +223,7 @@ def migrate_orders_table(engine, table_back_name: str, cols_order: List): select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, {average} average, remaining, cost, {stop_price} stop_price, order_date, order_filled_date, - order_update_date, {ft_fee_base} ft_fee_base {funding_fee} funding_fee + order_update_date, {ft_fee_base} ft_fee_base, {funding_fee} funding_fee from {table_back_name} """)) @@ -310,8 +310,8 @@ def check_migrate(engine, decl_base, previous_tables) -> None: # if ('orders' not in previous_tables # or not has_column(cols_orders, 'funding_fee')): migrating = False - if not has_column(cols_orders, 'funding_fee'): # if not has_column(cols_trades, 'contract_size'): + if not has_column(cols_orders, 'funding_fee'): migrating = True logger.info(f"Running database migration for trades - " f"backup: {table_back_name}, {order_table_bak_name}") diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 6127c502d..ea60796a4 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -369,7 +369,8 @@ class LocalTrade(): orders = self.select_filled_orders() if not orders: return self.open_date_utc - return max([self.open_date_utc, max(o.order_filled_utc for o in orders)]) + return max([self.open_date_utc, + max(o.order_filled_utc for o in orders if o.order_filled_utc)]) @property def open_date_utc(self): From dae3b3d86adde0f6c7065ce1d083d9ceac62e5ef Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 3 Sep 2022 13:24:14 -0600 Subject: [PATCH 154/592] support shutting down freqai --- freqtrade/freqai/freqai_interface.py | 37 +++++++++++++++++++--------- freqtrade/freqtradebot.py | 2 ++ freqtrade/strategy/interface.py | 10 ++++++++ 3 files changed, 38 insertions(+), 11 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index eac5cba07..a9c21fb65 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -7,7 +7,7 @@ import time from abc import ABC, abstractmethod from pathlib import Path from threading import Lock -from typing import Any, Dict, Tuple +from typing import Any, Dict, List, Tuple import numpy as np import pandas as pd @@ -27,13 +27,6 @@ pd.options.mode.chained_assignment = None logger = logging.getLogger(__name__) -def threaded(fn): - def wrapper(*args, **kwargs): - threading.Thread(target=fn, args=args, kwargs=kwargs).start() - - return wrapper - - class IFreqaiModel(ABC): """ Class containing all tools for training and prediction in the strategy. @@ -94,6 +87,9 @@ class IFreqaiModel(ABC): self.begin_time_train: float = 0 self.base_tf_seconds = timeframe_to_seconds(self.config['timeframe']) + self._threads: List[threading.Thread] = [] + self._stop_event = threading.Event() + def assert_config(self, config: Dict[str, Any]) -> None: if not config.get("freqai", {}): @@ -147,15 +143,34 @@ class IFreqaiModel(ABC): self.model = None self.dk = None - @threaded - def start_scanning(self, strategy: IStrategy) -> None: + def shutdown(self): + """ + Cleans up threads on Shutdown, set stop event. Join threads to wait + for current training iteration. + """ + logger.info("Stopping FreqAI") + self._stop_event.set() + + logger.info("Waiting on Training iteration") + for _thread in self._threads: + _thread.join() + + def start_scanning(self, *args, **kwargs) -> None: + """ + Start `self._start_scanning` in a separate thread + """ + _thread = threading.Thread(target=self._start_scanning, args=args, kwargs=kwargs) + self._threads.append(_thread) + _thread.start() + + def _start_scanning(self, strategy: IStrategy) -> None: """ Function designed to constantly scan pairs for retraining on a separate thread (intracandle) to improve model youth. This function is agnostic to data preparation/collection/storage, it simply trains on what ever data is available in the self.dd. :param strategy: IStrategy = The user defined strategy class """ - while 1: + while not self._stop_event.is_set(): time.sleep(1) for pair in self.config.get("exchange", {}).get("pair_whitelist"): diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 37bc6dfed..883417219 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -148,6 +148,8 @@ class FreqtradeBot(LoggingMixin): self.check_for_open_trades() + self.strategy.ft_bot_cleanup() + self.rpc.cleanup() Trade.commit() self.exchange.close() diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index c7ea95bda..562a16b18 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -168,6 +168,10 @@ class IStrategy(ABC, HyperStrategyMixin): raise OperationalException( 'freqAI is not enabled. ' 'Please enable it in your config to use this strategy.') + + def cleanup(self, *args, **kwargs): + pass + self.freqai = DummyClass() # type: ignore def ft_bot_start(self, **kwargs) -> None: @@ -181,6 +185,12 @@ class IStrategy(ABC, HyperStrategyMixin): self.ft_load_hyper_params(self.config.get('runmode') == RunMode.HYPEROPT) + def ft_bot_cleanup(self) -> None: + """ + Clean up FreqAI and child threads + """ + self.freqai.shutdown() + @abstractmethod def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ From 3b5e5fc57b7a11402c76f13bddede071bd9eaf9e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 3 Sep 2022 14:10:23 -0600 Subject: [PATCH 155/592] fix method name in dummy class --- freqtrade/strategy/interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 562a16b18..70cc7fdb3 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -169,7 +169,7 @@ class IStrategy(ABC, HyperStrategyMixin): 'freqAI is not enabled. ' 'Please enable it in your config to use this strategy.') - def cleanup(self, *args, **kwargs): + def shutdown(self, *args, **kwargs): pass self.freqai = DummyClass() # type: ignore From ec76214d023a6c53ffab0af8d43bc5b72b1d66af Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 4 Sep 2022 15:56:07 +0200 Subject: [PATCH 156/592] backup historical predictions pickle and load the backup in case of corruption --- freqtrade/freqai/data_drawer.py | 27 ++++++++++++++++++++------- 1 file changed, 20 insertions(+), 7 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index b6a1a15d7..9eeabef8f 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -76,6 +76,8 @@ class FreqaiDataDrawer: self.full_path / f"follower_dictionary-{self.follower_name}.json" ) self.historic_predictions_path = Path(self.full_path / "historic_predictions.pkl") + self.historic_predictions_bkp_path = Path( + self.full_path / "historic_predictions.backup.pkl") self.pair_dictionary_path = Path(self.full_path / "pair_dictionary.json") self.follow_mode = follow_mode if follow_mode: @@ -118,13 +120,21 @@ class FreqaiDataDrawer: """ exists = self.historic_predictions_path.is_file() if exists: - with open(self.historic_predictions_path, "rb") as fp: - self.historic_predictions = cloudpickle.load(fp) - logger.info( - f"Found existing historic predictions at {self.full_path}, but beware " - "that statistics may be inaccurate if the bot has been offline for " - "an extended period of time." - ) + try: + with open(self.historic_predictions_path, "rb") as fp: + self.historic_predictions = cloudpickle.load(fp) + logger.info( + f"Found existing historic predictions at {self.full_path}, but beware " + "that statistics may be inaccurate if the bot has been offline for " + "an extended period of time." + ) + except EOFError: + logger.warning( + 'Historical prediction file was corrupted. Trying to load backup file.') + with open(self.historic_predictions_bkp_path, "rb") as fp: + self.historic_predictions = cloudpickle.load(fp) + logger.warning('FreqAI successfully loaded the backup historical predictions file.') + elif not self.follow_mode: logger.info("Could not find existing historic_predictions, starting from scratch") else: @@ -142,6 +152,9 @@ class FreqaiDataDrawer: with open(self.historic_predictions_path, "wb") as fp: cloudpickle.dump(self.historic_predictions, fp, protocol=cloudpickle.DEFAULT_PROTOCOL) + # create a backup + shutil.copy(self.historic_predictions_path, self.historic_predictions_bkp_path) + def save_drawer_to_disk(self): """ Save data drawer full of all pair model metadata in present model folder. From 160186885404b4b15be4251a80b4ac054d930954 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 4 Sep 2022 09:42:43 -0600 Subject: [PATCH 157/592] dataprovider fix, updated config example --- config_examples/config_full.example.json | 3 +-- freqtrade/data/dataprovider.py | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index d0efa5bb6..2ebad4924 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -173,8 +173,7 @@ "CORS_origins": [], "username": "freqtrader", "password": "SuperSecurePassword", - "ws_token": "a_secret_ws_token", - "enable_message_ws": false + "ws_token": "a_secret_ws_token" }, "external_message_consumer": { "enabled": false, diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index ef3067f38..af0f2a70a 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -166,7 +166,7 @@ class DataProvider: # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) - if pair_key not in self.__producer_pairs_df: + if pair_key not in self.__producer_pairs_df[producer_name]: # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) From 07f806a314ec6e963a33b79782e8b658782b235d Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 4 Sep 2022 10:22:10 -0600 Subject: [PATCH 158/592] minor improvements, fixes, old config+constant removal --- .gitignore | 2 -- config_examples/config_full.example.json | 5 +++- freqtrade/constants.py | 3 +- freqtrade/data/dataprovider.py | 33 +++++++++++++++------- freqtrade/freqtradebot.py | 4 --- freqtrade/rpc/api_server/api_auth.py | 1 + freqtrade/rpc/api_server/api_ws.py | 15 +++++++--- freqtrade/rpc/api_server/webserver.py | 5 ++-- freqtrade/rpc/external_message_consumer.py | 6 ++-- freqtrade/strategy/interface.py | 15 ++++------ 10 files changed, 51 insertions(+), 38 deletions(-) diff --git a/.gitignore b/.gitignore index 6a47a7f81..e400c01f5 100644 --- a/.gitignore +++ b/.gitignore @@ -113,5 +113,3 @@ target/ !config_examples/config_full.example.json !config_examples/config_kraken.example.json !config_examples/config_freqai.example.json -!config_examples/config_leader.example.json -!config_examples/config_follower.example.json diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 2ebad4924..99d695406 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -175,12 +175,15 @@ "password": "SuperSecurePassword", "ws_token": "a_secret_ws_token" }, + // The ExternalMessageConsumer config should only be enabled on an instance + // that listens to outside data from another instance. This should not be enabled + // in your producer of data. "external_message_consumer": { "enabled": false, "producers": [ { "name": "default", - "url": "ws://some.freqtrade.bot/api/v1/message/ws", + "url": "ws://localhost:8081/api/v1/message/ws", "ws_token": "a_secret_ws_token" } ], diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 352e48148..bc00d7cfc 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -33,8 +33,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss', AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'AgeFilter', 'OffsetFilter', 'PerformanceFilter', 'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter', - 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter', - 'ExternalPairList'] + 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter'] AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard'] AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5'] BACKTEST_BREAKDOWNS = ['day', 'week', 'month'] diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index af0f2a70a..32152f2f5 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -48,8 +48,11 @@ class DataProvider: self.__producer_pairs: Dict[str, List[str]] = {} self._msg_queue: deque = deque() + self._default_candle_type = self._config.get('candle_type_def', CandleType.SPOT) + self._default_timeframe = self._config.get('timeframe', '1h') + self.__msg_cache = PeriodicCache( - maxsize=1000, ttl=timeframe_to_seconds(self._config.get('timeframe', '1h'))) + maxsize=1000, ttl=timeframe_to_seconds(self._default_timeframe)) self._num_sources = len( self._config.get('external_message_consumer', {}).get('producers', []) @@ -84,7 +87,7 @@ class DataProvider: dataframe, datetime.now(timezone.utc)) # For multiple producers we will want to merge the pairlists instead of overwriting - def set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"): + def _set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"): """ Set the pairs received to later be used. This only supports 1 Producer right now. @@ -101,7 +104,7 @@ class DataProvider: """ return self.__producer_pairs.get(producer_name, []) - def emit_df( + def _emit_df( self, pair_key: PairWithTimeframe, dataframe: DataFrame @@ -123,12 +126,12 @@ class DataProvider: } ) - def add_external_df( + def _add_external_df( self, pair: str, - timeframe: str, dataframe: DataFrame, - candle_type: CandleType, + timeframe: Optional[str] = None, + candle_type: Optional[CandleType] = None, producer_name: str = "default" ) -> None: """ @@ -138,18 +141,22 @@ class DataProvider: :param timeframe: Timeframe to get data for :param candle_type: Any of the enum CandleType (must match trading mode!) """ - pair_key = (pair, timeframe, candle_type) + _timeframe = self._default_timeframe if not timeframe else timeframe + _candle_type = self._default_candle_type if not candle_type else candle_type + + pair_key = (pair, _timeframe, _candle_type) if producer_name not in self.__producer_pairs_df: self.__producer_pairs_df[producer_name] = {} self.__producer_pairs_df[producer_name][pair_key] = (dataframe, datetime.now(timezone.utc)) + logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.") def get_external_df( self, pair: str, - timeframe: str, - candle_type: CandleType, + timeframe: Optional[str] = None, + candle_type: Optional[CandleType] = None, producer_name: str = "default" ) -> Tuple[DataFrame, datetime]: """ @@ -160,16 +167,22 @@ class DataProvider: :param timeframe: Timeframe to get data for :param candle_type: Any of the enum CandleType (must match trading mode!) """ - pair_key = (pair, timeframe, candle_type) + _timeframe = self._default_timeframe if not timeframe else timeframe + _candle_type = self._default_candle_type if not candle_type else candle_type + pair_key = (pair, _timeframe, _candle_type) + + # If we have no data from this Producer yet if producer_name not in self.__producer_pairs_df: # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + # If we do have data from that Producer, but no data on this pair_key if pair_key not in self.__producer_pairs_df[producer_name]: # We don't have this data yet, return empty DataFrame and datetime (01-01-1970) return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) + # We have it, return this data return self.__producer_pairs_df[producer_name][pair_key] def add_pairlisthandler(self, pairlists) -> None: diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 888994ffb..ce01fc872 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -199,10 +199,6 @@ class FreqtradeBot(LoggingMixin): strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() - # This just means we won't broadcast dataframes if we're listening to a producer - # Doesn't necessarily NEED to be this way, as maybe we'd like to broadcast - # even if we are using external dataframes in the future. - self.strategy.analyze(self.active_pair_whitelist) with self._exit_lock: diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index fd90918e1..6655dbf86 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -50,6 +50,7 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access"): # This should be reimplemented to better realign with the existing tools provided # by FastAPI regarding API Tokens +# https://github.com/tiangolo/fastapi/blob/master/fastapi/security/api_key.py async def get_ws_token( ws: WebSocket, token: Union[str, None] = None, diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 95cfd031a..d11d1acfe 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -2,23 +2,30 @@ import logging from typing import Any, Dict from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect +# fastapi does not make this available through it, so import directly from starlette +from starlette.websockets import WebSocketState from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel -from freqtrade.rpc.api_server.ws.utils import is_websocket_alive from freqtrade.rpc.rpc import RPC -# from typing import Any, Dict - - logger = logging.getLogger(__name__) # Private router, protected by API Key authentication router = APIRouter() +async def is_websocket_alive(ws: WebSocket) -> bool: + if ( + ws.application_state == WebSocketState.CONNECTED and + ws.client_state == WebSocketState.CONNECTED + ): + return True + return False + + async def _process_consumer_request( request: Dict[str, Any], channel: WebSocketChannel, diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 150c83890..ad93e77a7 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -205,7 +205,7 @@ class ApiServer(RPCHandler): # For testing, shouldn't happen when stable except Exception as e: - logger.info(f"Exception happened in background task: {e}") + logger.exception(f"Exception happened in background task: {e}") def start_api(self): """ @@ -244,8 +244,7 @@ class ApiServer(RPCHandler): if self._standalone: self._server.run() else: - if self._config.get('api_server', {}).get('enable_message_ws', False): - self.start_message_queue() + self.start_message_queue() self._server.run_in_thread() except Exception: logger.exception("Api server failed to start.") diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index d3b82cadf..7f2ac01fb 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -289,7 +289,7 @@ class ExternalMessageConsumer: return # Add the pairlist data to the DataProvider - self._dp.set_producer_pairs(message_data, producer_name=producer_name) + self._dp._set_producer_pairs(message_data, producer_name=producer_name) logger.debug(f"Consumed message from {producer_name} of type RPCMessageType.WHITELIST") @@ -309,8 +309,8 @@ class ExternalMessageConsumer: dataframe = remove_entry_exit_signals(dataframe) # Add the dataframe to the dataprovider - self._dp.add_external_df(pair, timeframe, dataframe, - candle_type, producer_name=producer_name) + self._dp._add_external_df(pair, dataframe, timeframe, + candle_type, producer_name=producer_name) logger.debug( f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 7fcae870a..73948a37a 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -700,8 +700,7 @@ class IStrategy(ABC, HyperStrategyMixin): def _analyze_ticker_internal( self, dataframe: DataFrame, - metadata: dict, - emit_df: bool = False + metadata: dict ) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame @@ -725,7 +724,7 @@ class IStrategy(ABC, HyperStrategyMixin): candle_type = self.config.get('candle_type_def', CandleType.SPOT) self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type) - self.dp.emit_df((pair, self.timeframe, candle_type), dataframe) + self.dp._emit_df((pair, self.timeframe, candle_type), dataframe) else: logger.debug("Skipping TA Analysis for already analyzed candle") @@ -737,8 +736,7 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze_pair( self, - pair: str, - emit_df: bool = False + pair: str ) -> None: """ Fetch data for this pair from dataprovider and analyze. @@ -759,7 +757,7 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = strategy_safe_wrapper( self._analyze_ticker_internal, message="" - )(dataframe, {'pair': pair}, emit_df) + )(dataframe, {'pair': pair}) self.assert_df(dataframe, df_len, df_close, df_date) except StrategyError as error: @@ -772,15 +770,14 @@ class IStrategy(ABC, HyperStrategyMixin): def analyze( self, - pairs: List[str], - emit_df: bool = False + pairs: List[str] ) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze """ for pair in pairs: - self.analyze_pair(pair, emit_df) + self.analyze_pair(pair) @ staticmethod def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]: From 8a08f8ff8d1d53a13bd7ba47a2fd09426aa9cacf Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 4 Sep 2022 10:27:34 -0600 Subject: [PATCH 159/592] revert rpc manager --- freqtrade/rpc/rpc_manager.py | 18 ++---------------- 1 file changed, 2 insertions(+), 16 deletions(-) diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index d6374566c..3ba2f9d4d 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -49,17 +49,6 @@ class RPCManager: apiserver.add_rpc_handler(self._rpc) self.registered_modules.append(apiserver) - # Enable External Signals mode - # For this to be enabled, the API server must also be enabled - # if config.get('external_signal', {}).get('enabled', False): - # logger.info('Enabling RPC.ExternalSignalController') - # from freqtrade.rpc.external_signal import ExternalSignalController - # external_signals = ExternalSignalController(self._rpc, config, apiserver) - # self.registered_modules.append(external_signals) - # - # # Attach the controller to FreqTrade - # freqtrade.external_signal_controller = external_signals - def cleanup(self) -> None: """ Stops all enabled rpc modules """ logger.info('Cleaning up rpc modules ...') @@ -78,11 +67,8 @@ class RPCManager: 'status': 'stopping bot' } """ - # Removed actually showing the message because the logs would be - # completely spammed of the json dataframe - logger.info('Sending rpc message of type: %s', msg.get('type')) - # Log actual message in debug? - # logger.debug(msg) + if msg.get('type') is not RPCMessageType.ANALYZED_DF: + logger.info('Sending rpc message: %s', msg) if 'pair' in msg: msg.update({ 'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair']) From d43ed186fcc375f9087b059a00d2fb3b5ec6fdfe Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Sun, 4 Sep 2022 16:55:47 -0300 Subject: [PATCH 160/592] fix issue with freqai backtesting at slice dataframe --- freqtrade/freqai/data_kitchen.py | 15 +++++++++++++++ freqtrade/freqai/freqai_interface.py | 4 ++-- 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7595942fe..d525ae4ac 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -458,6 +458,21 @@ class FreqaiDataKitchen: return df + def slice_dataframe_backtesting(self, timerange: TimeRange, df: DataFrame) -> DataFrame: + """ + Given a full dataframe, extract the user desired window + :param tr: timerange string that we wish to extract from df + :param df: Dataframe containing all candles to run the entire backtest. Here + it is sliced down to just the present training period. + """ + + start = datetime.datetime.fromtimestamp(timerange.startts, tz=datetime.timezone.utc) + stop = datetime.datetime.fromtimestamp(timerange.stopts, tz=datetime.timezone.utc) + df = df.loc[df["date"] >= start, :] + df = df.loc[df["date"] < stop, :] + + return df + def principal_component_analysis(self) -> None: """ Performs Principal Component Analysis on the data for dimensionality reduction diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index a9c21fb65..b17f8c9ab 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -225,8 +225,8 @@ class IFreqaiModel(ABC): train_it += 1 total_trains = len(dk.backtesting_timeranges) self.training_timerange = tr_train - dataframe_train = dk.slice_dataframe(tr_train, dataframe) - dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe) + dataframe_train = dk.slice_dataframe_backtesting(tr_train, dataframe) + dataframe_backtest = dk.slice_dataframe_backtesting(tr_backtest, dataframe) trained_timestamp = tr_train tr_train_startts_str = datetime.datetime.utcfromtimestamp(tr_train.startts).strftime( From 78d01810ed1dd3ecee954b914e9066267d5e969a Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 00:07:05 +0200 Subject: [PATCH 161/592] reduce code redundancy, ensure live always gets the latest data --- freqtrade/freqai/data_kitchen.py | 18 ++---------------- freqtrade/freqai/freqai_interface.py | 4 ++-- 2 files changed, 4 insertions(+), 18 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index d525ae4ac..828734520 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -454,22 +454,8 @@ class FreqaiDataKitchen: start = datetime.datetime.fromtimestamp(timerange.startts, tz=datetime.timezone.utc) stop = datetime.datetime.fromtimestamp(timerange.stopts, tz=datetime.timezone.utc) df = df.loc[df["date"] >= start, :] - df = df.loc[df["date"] <= stop, :] - - return df - - def slice_dataframe_backtesting(self, timerange: TimeRange, df: DataFrame) -> DataFrame: - """ - Given a full dataframe, extract the user desired window - :param tr: timerange string that we wish to extract from df - :param df: Dataframe containing all candles to run the entire backtest. Here - it is sliced down to just the present training period. - """ - - start = datetime.datetime.fromtimestamp(timerange.startts, tz=datetime.timezone.utc) - stop = datetime.datetime.fromtimestamp(timerange.stopts, tz=datetime.timezone.utc) - df = df.loc[df["date"] >= start, :] - df = df.loc[df["date"] < stop, :] + if not self.live: + df = df.loc[df["date"] < stop, :] return df diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index b17f8c9ab..a9c21fb65 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -225,8 +225,8 @@ class IFreqaiModel(ABC): train_it += 1 total_trains = len(dk.backtesting_timeranges) self.training_timerange = tr_train - dataframe_train = dk.slice_dataframe_backtesting(tr_train, dataframe) - dataframe_backtest = dk.slice_dataframe_backtesting(tr_backtest, dataframe) + dataframe_train = dk.slice_dataframe(tr_train, dataframe) + dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe) trained_timestamp = tr_train tr_train_startts_str = datetime.datetime.utcfromtimestamp(tr_train.startts).strftime( From c8a9ac900c2bdec9620c6d2745ee78a3d78cfbdc Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 00:52:26 +0200 Subject: [PATCH 162/592] fix broken CI --- tests/freqai/test_freqai_datakitchen.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 9ef955695..44c721515 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -74,7 +74,7 @@ def test_use_DBSCAN_to_remove_outliers(mocker, freqai_conf, caplog): # freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 1}) freqai.dk.use_DBSCAN_to_remove_outliers(predict=False) assert log_has_re( - "DBSCAN found eps of 2.42.", + "DBSCAN found eps of 2.36.", caplog, ) @@ -83,7 +83,7 @@ def test_compute_distances(mocker, freqai_conf): freqai = make_data_dictionary(mocker, freqai_conf) freqai_conf['freqai']['feature_parameters'].update({"DI_threshold": 1}) avg_mean_dist = freqai.dk.compute_distances() - assert round(avg_mean_dist, 2) == 2.56 + assert round(avg_mean_dist, 2) == 2.54 def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, caplog): @@ -91,6 +91,6 @@ def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 0.1}) freqai.dk.use_SVM_to_remove_outliers(predict=False) assert log_has_re( - "SVM detected 8.46%", + "SVM detected 8.09%", caplog, ) From a035a69a61e344fa5b7a7a01e2f01cfad46de7af Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:09:53 +0000 Subject: [PATCH 163/592] Bump arrow from 1.2.2 to 1.2.3 Bumps [arrow](https://github.com/arrow-py/arrow) from 1.2.2 to 1.2.3. - [Release notes](https://github.com/arrow-py/arrow/releases) - [Changelog](https://github.com/arrow-py/arrow/blob/master/CHANGELOG.rst) - [Commits](https://github.com/arrow-py/arrow/compare/1.2.2...1.2.3) --- updated-dependencies: - dependency-name: arrow dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..99139f92b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,7 @@ cryptography==37.0.4 aiohttp==3.8.1 SQLAlchemy==1.4.40 python-telegram-bot==13.13 -arrow==1.2.2 +arrow==1.2.3 cachetools==4.2.2 requests==2.28.1 urllib3==1.26.12 From 7cc8ac0a3429f0fd40c2be30974457f32259d744 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:10:02 +0000 Subject: [PATCH 164/592] Bump psutil from 5.9.1 to 5.9.2 Bumps [psutil](https://github.com/giampaolo/psutil) from 5.9.1 to 5.9.2. - [Release notes](https://github.com/giampaolo/psutil/releases) - [Changelog](https://github.com/giampaolo/psutil/blob/master/HISTORY.rst) - [Commits](https://github.com/giampaolo/psutil/compare/release-5.9.1...release-5.9.2) --- updated-dependencies: - dependency-name: psutil dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..240eb0057 100644 --- a/requirements.txt +++ b/requirements.txt @@ -38,7 +38,7 @@ fastapi==0.81.0 uvicorn==0.18.3 pyjwt==2.4.0 aiofiles==0.8.0 -psutil==5.9.1 +psutil==5.9.2 # Support for colorized terminal output colorama==0.4.5 From af7e4d7bf0a5ce6f47e7a46d6f55dd814a43e22d Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:10:11 +0000 Subject: [PATCH 165/592] Bump pytest from 7.1.2 to 7.1.3 Bumps [pytest](https://github.com/pytest-dev/pytest) from 7.1.2 to 7.1.3. - [Release notes](https://github.com/pytest-dev/pytest/releases) - [Changelog](https://github.com/pytest-dev/pytest/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pytest-dev/pytest/compare/7.1.2...7.1.3) --- updated-dependencies: - dependency-name: pytest dependency-type: direct:development update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements-dev.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-dev.txt b/requirements-dev.txt index 26df7115c..40ca4e154 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -10,7 +10,7 @@ flake8==5.0.4 flake8-tidy-imports==4.8.0 mypy==0.971 pre-commit==2.20.0 -pytest==7.1.2 +pytest==7.1.3 pytest-asyncio==0.19.0 pytest-cov==3.0.0 pytest-mock==3.8.2 From 3d038568457a7cfadfc0765ecc1e2ca5867f04e1 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:10:31 +0000 Subject: [PATCH 166/592] Bump ccxt from 1.92.84 to 1.93.3 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.92.84 to 1.93.3. - [Release notes](https://github.com/ccxt/ccxt/releases) - [Changelog](https://github.com/ccxt/ccxt/blob/master/exchanges.cfg) - [Commits](https://github.com/ccxt/ccxt/compare/1.92.84...1.93.3) --- updated-dependencies: - dependency-name: ccxt dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..d70eebdd8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ numpy==1.23.2 pandas==1.4.3 pandas-ta==0.3.14b -ccxt==1.92.84 +ccxt==1.93.3 # Pin cryptography for now due to rust build errors with piwheels cryptography==37.0.4 aiohttp==3.8.1 From 90fbb794712cce946ae65caeacafa0f8724ae691 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:10:44 +0000 Subject: [PATCH 167/592] Bump prompt-toolkit from 3.0.30 to 3.0.31 Bumps [prompt-toolkit](https://github.com/prompt-toolkit/python-prompt-toolkit) from 3.0.30 to 3.0.31. - [Release notes](https://github.com/prompt-toolkit/python-prompt-toolkit/releases) - [Changelog](https://github.com/prompt-toolkit/python-prompt-toolkit/blob/master/CHANGELOG) - [Commits](https://github.com/prompt-toolkit/python-prompt-toolkit/compare/3.0.30...3.0.31) --- updated-dependencies: - dependency-name: prompt-toolkit dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..ff1eabe38 100644 --- a/requirements.txt +++ b/requirements.txt @@ -44,7 +44,7 @@ psutil==5.9.1 colorama==0.4.5 # Building config files interactively questionary==1.10.0 -prompt-toolkit==3.0.30 +prompt-toolkit==3.0.31 # Extensions to datetime library python-dateutil==2.8.2 From 6f6afca0277de0ffeab2d104fb4b1068446dafc3 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:10:53 +0000 Subject: [PATCH 168/592] Bump fastapi from 0.81.0 to 0.82.0 Bumps [fastapi](https://github.com/tiangolo/fastapi) from 0.81.0 to 0.82.0. - [Release notes](https://github.com/tiangolo/fastapi/releases) - [Commits](https://github.com/tiangolo/fastapi/compare/0.81.0...0.82.0) --- updated-dependencies: - dependency-name: fastapi dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..2ddf3fbd9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -34,7 +34,7 @@ orjson==3.8.0 sdnotify==0.3.2 # API Server -fastapi==0.81.0 +fastapi==0.82.0 uvicorn==0.18.3 pyjwt==2.4.0 aiofiles==0.8.0 From f5500350f9364fd619415e56cd9d43eb42911f78 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:11:24 +0000 Subject: [PATCH 169/592] Bump pandas from 1.4.3 to 1.4.4 Bumps [pandas](https://github.com/pandas-dev/pandas) from 1.4.3 to 1.4.4. - [Release notes](https://github.com/pandas-dev/pandas/releases) - [Changelog](https://github.com/pandas-dev/pandas/blob/main/RELEASE.md) - [Commits](https://github.com/pandas-dev/pandas/compare/v1.4.3...v1.4.4) --- updated-dependencies: - dependency-name: pandas dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..6bd828059 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,5 @@ numpy==1.23.2 -pandas==1.4.3 +pandas==1.4.4 pandas-ta==0.3.14b ccxt==1.92.84 From 48dc1f2d88bf82f5721aba621b6768cc953f6ca9 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 13:11:29 +0000 Subject: [PATCH 170/592] Bump pycoingecko from 2.2.0 to 3.0.0 Bumps [pycoingecko](https://github.com/man-c/pycoingecko) from 2.2.0 to 3.0.0. - [Release notes](https://github.com/man-c/pycoingecko/releases) - [Changelog](https://github.com/man-c/pycoingecko/blob/master/CHANGELOG.md) - [Commits](https://github.com/man-c/pycoingecko/compare/2.2.0...3.0.0) --- updated-dependencies: - dependency-name: pycoingecko dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cbd5e31ba..20796bd26 100644 --- a/requirements.txt +++ b/requirements.txt @@ -16,7 +16,7 @@ jsonschema==4.14.0 TA-Lib==0.4.24 technical==1.3.0 tabulate==0.8.10 -pycoingecko==2.2.0 +pycoingecko==3.0.0 jinja2==3.1.2 tables==3.7.0 blosc==1.10.6 From 9f5642fd972affbf12f16859e391a3f243bc45ad Mon Sep 17 00:00:00 2001 From: Italo <45588475+italodamato@users.noreply.github.com> Date: Mon, 5 Sep 2022 18:12:19 +0200 Subject: [PATCH 171/592] fix hyperopt df preprocessing --- freqtrade/optimize/hyperopt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index fea2a672f..4c8613a7a 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -423,7 +423,7 @@ class Hyperopt: # Trim startup period from analyzed dataframe to get correct dates for output. processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) self.min_date, self.max_date = get_timerange(processed) - return processed + return preprocessed def prepare_hyperopt_data(self) -> None: HyperoptStateContainer.set_state(HyperoptState.DATALOAD) From 949f618d42530d4c4ca3e6a06eba5b99443a8bd1 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 16:30:43 +0000 Subject: [PATCH 172/592] Bump python-telegram-bot from 13.13 to 13.14 Bumps [python-telegram-bot](https://github.com/python-telegram-bot/python-telegram-bot) from 13.13 to 13.14. - [Release notes](https://github.com/python-telegram-bot/python-telegram-bot/releases) - [Changelog](https://github.com/python-telegram-bot/python-telegram-bot/blob/v13.14/CHANGES.rst) - [Commits](https://github.com/python-telegram-bot/python-telegram-bot/compare/v13.13...v13.14) --- updated-dependencies: - dependency-name: python-telegram-bot dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index c7d55ba78..3cb321b2b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,7 +7,7 @@ ccxt==1.93.3 cryptography==37.0.4 aiohttp==3.8.1 SQLAlchemy==1.4.40 -python-telegram-bot==13.13 +python-telegram-bot==13.14 arrow==1.2.3 cachetools==4.2.2 requests==2.28.1 From 4628bfa580c49d8f80bf1372b66c95f6557b683c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 17:30:55 +0000 Subject: [PATCH 173/592] Bump jsonschema from 4.14.0 to 4.15.0 Bumps [jsonschema](https://github.com/python-jsonschema/jsonschema) from 4.14.0 to 4.15.0. - [Release notes](https://github.com/python-jsonschema/jsonschema/releases) - [Changelog](https://github.com/python-jsonschema/jsonschema/blob/main/CHANGELOG.rst) - [Commits](https://github.com/python-jsonschema/jsonschema/compare/v4.14.0...v4.15.0) --- updated-dependencies: - dependency-name: jsonschema dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 8b994cb88..fdbe6ac28 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,7 +12,7 @@ arrow==1.2.3 cachetools==4.2.2 requests==2.28.1 urllib3==1.26.12 -jsonschema==4.14.0 +jsonschema==4.15.0 TA-Lib==0.4.24 technical==1.3.0 tabulate==0.8.10 From 36e5c18fa600a3dbf3c58f6e2e7ee149a5b71ede Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 5 Sep 2022 20:54:03 +0200 Subject: [PATCH 174/592] Don't raise exception when a message is not implemented in telegram --- freqtrade/rpc/telegram.py | 12 +++++++----- tests/rpc/test_rpc_telegram.py | 10 +++++----- 2 files changed, 12 insertions(+), 10 deletions(-) diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py index 8c988d570..4a759f6ec 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -6,6 +6,7 @@ This module manage Telegram communication import json import logging import re +from copy import deepcopy from dataclasses import dataclass from datetime import date, datetime, timedelta from functools import partial @@ -374,7 +375,7 @@ class Telegram(RPCHandler): message += f"\n*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`" return message - def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> str: + def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> Optional[str]: if msg_type in [RPCMessageType.ENTRY, RPCMessageType.ENTRY_FILL]: message = self._format_entry_msg(msg) @@ -411,7 +412,8 @@ class Telegram(RPCHandler): elif msg_type == RPCMessageType.STRATEGY_MSG: message = f"{msg['msg']}" else: - raise NotImplementedError(f"Unknown message type: {msg_type}") + logger.debug("Unknown message type: %s", msg_type) + return None return message def send_msg(self, msg: Dict[str, Any]) -> None: @@ -438,9 +440,9 @@ class Telegram(RPCHandler): # Notification disabled return - message = self.compose_message(msg, msg_type) - - self._send_msg(message, disable_notification=(noti == 'silent')) + message = self.compose_message(deepcopy(msg), msg_type) + if message: + self._send_msg(message, disable_notification=(noti == 'silent')) def _get_sell_emoji(self, msg): """ diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py index cde7025a7..f2e490dff 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -2138,11 +2138,11 @@ def test_send_msg_strategy_msg_notification(default_conf, mocker) -> None: def test_send_msg_unknown_type(default_conf, mocker) -> None: - telegram, _, _ = get_telegram_testobject(mocker, default_conf) - with pytest.raises(NotImplementedError, match=r'Unknown message type: None'): - telegram.send_msg({ - 'type': None, - }) + telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf) + telegram.send_msg({ + 'type': None, + }) + msg_mock.call_count == 0 @pytest.mark.parametrize('message_type,enter,enter_signal,leverage', [ From 689b193240a77dc2e9619583a9bef3c9c7f07b56 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 20:57:42 +0200 Subject: [PATCH 175/592] improve clarity on data download requirements --- docs/freqai.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 3646362c3..d04d2fa6b 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -280,7 +280,7 @@ The FreqAI strategy requires the user to include the following lines of code in Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](#feature-engineering)) and labels ([more information](#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. ### Setting the `startup_candle_count` -Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md/#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). +Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). !!! Note Typically it is best for users to be safe and multiply their expected `startup_candle_count` by 2. There are instances where the talib functions actually require more data than just the passed `period`. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Look out for this log message to confirm that your data is clean: @@ -515,10 +515,11 @@ and if a full `live_retrain_hours` has elapsed since the end of the loaded model The FreqAI backtesting module can be executed with the following command: ```bash -freqtrade backtesting --strategy FreqaiExampleStrategy --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 +freqtrade download-data --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates -t 3m 15m 1h --timerange 20210315-20210701 +freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 ``` -Backtesting mode requires the user to have the data pre-downloaded (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). +Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). If this command has never been executed with the existing config file, it will train a new model for each pair, for each backtesting window within the expanded `--timerange`. @@ -546,7 +547,7 @@ FreqAI will train have trained 8 separate models at the end of `--timerange` (be Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run. ### Downloading data for backtesting -Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download/#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by taking subtracting `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. +Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). From 9fb3517adc9b6d078fe3fc00d7393a79fcddae15 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 5 Sep 2022 21:08:01 +0200 Subject: [PATCH 176/592] Fix non-resolvable freqai test this test could never succeed in UI's as the name was constantly changing. --- tests/freqai/test_freqai_datakitchen.py | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 44c721515..908223c20 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -1,5 +1,5 @@ -import datetime import shutil +from datetime import datetime, timedelta, timezone from pathlib import Path import pytest @@ -56,16 +56,13 @@ def test_split_timerange( shutil.rmtree(Path(dk.full_path)) -@pytest.mark.parametrize( - "timestamp, expected", - [ - (datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - 7200, True), - (datetime.datetime.now(tz=datetime.timezone.utc).timestamp(), False), - ], -) -def test_check_if_model_expired(mocker, freqai_conf, timestamp, expected): +def test_check_if_model_expired(mocker, freqai_conf): + dk = get_patched_data_kitchen(mocker, freqai_conf) - assert dk.check_if_model_expired(timestamp) == expected + now = datetime.now(tz=timezone.utc).timestamp() + assert dk.check_if_model_expired(now) is False + now = (datetime.now(tz=timezone.utc) - timedelta(hours=2)).timestamp() + assert dk.check_if_model_expired(now) is True shutil.rmtree(Path(dk.full_path)) From 8f261d8edff162e26ad42876b2a4ce88beb08d45 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 5 Sep 2022 13:47:17 -0600 Subject: [PATCH 177/592] change from bytes to text in websocket, remove old logs --- freqtrade/rpc/api_server/api_ws.py | 2 -- freqtrade/rpc/api_server/ws/channel.py | 3 --- freqtrade/rpc/api_server/ws/proxy.py | 15 +++++++++------ freqtrade/rpc/api_server/ws/serializer.py | 2 ++ 4 files changed, 11 insertions(+), 11 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index d11d1acfe..aaa526401 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -67,8 +67,6 @@ async def _process_consumer_request( # They requested the full historical analyzed dataframes analyzed_df = rpc._ws_request_analyzed_df(limit) - logger.debug(f"ANALYZED_DF RESULT: {analyzed_df}") - # For every dataframe, send as a separate message for _, message in analyzed_df.items(): await channel.send({"type": RPCMessageType.ANALYZED_DF, "data": message}) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 1f0cd9c7a..952b3b9f5 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -50,7 +50,6 @@ class WebSocketChannel: """ Send data on the wrapped websocket """ - # logger.info(f"Serialized Send - {self._wrapped_ws._serialize(data)}") await self._wrapped_ws.send(data) async def recv(self): @@ -168,8 +167,6 @@ class ChannelManager: :param direct_channel: The WebSocketChannel object to send data through :param data: The data to send """ - # We iterate over the channels to get reference to the websocket object - # so we can disconnect incase of failure await channel.send(data) def has_channels(self): diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py index 73d1481b9..ea977a228 100644 --- a/freqtrade/rpc/api_server/ws/proxy.py +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -27,11 +27,14 @@ class WebSocketProxy: """ Send data on the wrapped websocket """ - if isinstance(data, str): - data = data.encode() - if hasattr(self._websocket, "send_bytes"): - await self._websocket.send_bytes(data) + if not isinstance(data, str): + # We use HybridJSONWebSocketSerializer, which when serialized returns + # bytes because of ORJSON, so we explicitly decode into a string + data = str(data, "utf-8") + + if hasattr(self._websocket, "send_text"): + await self._websocket.send_text(data) else: await self._websocket.send(data) @@ -39,8 +42,8 @@ class WebSocketProxy: """ Receive data on the wrapped websocket """ - if hasattr(self._websocket, "receive_bytes"): - return await self._websocket.receive_bytes() + if hasattr(self._websocket, "receive_text"): + return await self._websocket.receive_text() else: return await self._websocket.recv() diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index 109708cc9..8ff617f45 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -58,9 +58,11 @@ class RapidJSONWebSocketSerializer(WebSocketSerializer): class HybridJSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data): + # ORJSON returns bytes return orjson.dumps(data, default=_json_default) def _deserialize(self, data): + # RapidJSON expects strings return rapidjson.loads(data, object_hook=_json_object_hook) From 1ea703d527b341322a64d0f8e2327117a2bca7a8 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 22:20:38 +0200 Subject: [PATCH 178/592] remove download-data command --- docs/freqai.md | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/freqai.md b/docs/freqai.md index d04d2fa6b..303c2f151 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -515,7 +515,6 @@ and if a full `live_retrain_hours` has elapsed since the end of the loaded model The FreqAI backtesting module can be executed with the following command: ```bash -freqtrade download-data --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates -t 3m 15m 1h --timerange 20210315-20210701 freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 ``` From 5b826150dff2c2d0f04b4a93ab802a5ce8b50c63 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Mon, 5 Sep 2022 17:43:28 -0300 Subject: [PATCH 179/592] fix hyperopt - freqai --- freqtrade/freqai/data_drawer.py | 29 +++++++++++++++++++++++----- freqtrade/freqai/freqai_interface.py | 7 +++++++ 2 files changed, 31 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 9eeabef8f..a1ecb7654 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -93,6 +93,16 @@ class FreqaiDataDrawer: "model_filename": "", "trained_timestamp": 0, "priority": 1, "first": True, "data_path": "", "extras": {}} + def __getstate__(self): + """ + Return state values to be pickled. + It's necessary to allow serialization in hyperopt + """ + return ({ + "pair_dict": self.pair_dict, + "pair_dictionary_path": self.pair_dictionary_path + }) + def load_drawer_from_disk(self): """ Locate and load a previously saved data drawer full of all pair model metadata in @@ -155,14 +165,23 @@ class FreqaiDataDrawer: # create a backup shutil.copy(self.historic_predictions_path, self.historic_predictions_bkp_path) - def save_drawer_to_disk(self): + def save_drawer_to_disk(self, live=False): """ Save data drawer full of all pair model metadata in present model folder. """ - with self.save_lock: + if live: + with self.save_lock: + with open(self.pair_dictionary_path, 'w') as fp: + rapidjson.dump( + self.pair_dict, fp, default=self.np_encoder, + number_mode=rapidjson.NM_NATIVE + ) + else: + # save_lock it's not working with hyperopt with open(self.pair_dictionary_path, 'w') as fp: - rapidjson.dump(self.pair_dict, fp, default=self.np_encoder, - number_mode=rapidjson.NM_NATIVE) + rapidjson.dump( + self.pair_dict, fp, default=self.np_encoder, + number_mode=rapidjson.NM_NATIVE) def save_follower_dict_to_disk(self): """ @@ -437,7 +456,7 @@ class FreqaiDataDrawer: self.model_dictionary[coin] = model self.pair_dict[coin]["model_filename"] = dk.model_filename self.pair_dict[coin]["data_path"] = str(dk.data_path) - self.save_drawer_to_disk() + self.save_drawer_to_disk(dk.live) return diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index a9c21fb65..9a05e8383 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -90,6 +90,13 @@ class IFreqaiModel(ABC): self._threads: List[threading.Thread] = [] self._stop_event = threading.Event() + def __getstate__(self): + """ + Return state values to be pickled. + It's necessary to allow serialization in hyperopt + """ + return ({"dd": self.dd}) + def assert_config(self, config: Dict[str, Any]) -> None: if not config.get("freqai", {}): From 2c8e5b191bf84580684bf3a372121cef2e13d8f8 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Mon, 5 Sep 2022 17:43:55 -0300 Subject: [PATCH 180/592] fix hyperopt - freqai --- freqtrade/freqai/data_drawer.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index a1ecb7654..dff6b5942 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -174,8 +174,7 @@ class FreqaiDataDrawer: with open(self.pair_dictionary_path, 'w') as fp: rapidjson.dump( self.pair_dict, fp, default=self.np_encoder, - number_mode=rapidjson.NM_NATIVE - ) + number_mode=rapidjson.NM_NATIVE) else: # save_lock it's not working with hyperopt with open(self.pair_dictionary_path, 'w') as fp: From b949ea301c5828612f094c1c5040a67adcd3a47e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 5 Sep 2022 19:29:07 -0600 Subject: [PATCH 181/592] fix failed apiserver tests --- freqtrade/rpc/api_server/webserver.py | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index ad93e77a7..6ad3f143e 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -114,6 +114,10 @@ class ApiServer(RPCHandler): self._thread.join() + self._thread = None + self._loop = None + self._background_task = None + @classmethod def shutdown(cls): cls.__initialized = False @@ -169,15 +173,15 @@ class ApiServer(RPCHandler): app.add_exception_handler(RPCException, self.handle_rpc_exception) def start_message_queue(self): + if self._thread: + return + # Create a new loop, as it'll be just for the background thread self._loop = asyncio.new_event_loop() # Start the thread - if not self._thread: - self._thread = Thread(target=self._loop.run_forever) - self._thread.start() - else: - raise RuntimeError("Threaded loop is already running") + self._thread = Thread(target=self._loop.run_forever) + self._thread.start() # Finally, submit the coro to the thread self._background_task = asyncio.run_coroutine_threadsafe( From a0d774fdc4e3be40e4ca138782f38f0db37a88fb Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 5 Sep 2022 20:23:00 -0600 Subject: [PATCH 182/592] change default initial candle limit to 1500 --- freqtrade/constants.py | 3 +-- freqtrade/rpc/external_message_consumer.py | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 03030d930..2279acc13 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -508,9 +508,8 @@ CONF_SCHEMA = { 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False}, 'initial_candle_limit': { 'type': 'integer', - 'minimum': 100, 'maximum': 1500, - 'default': 500 + 'default': 1500 } }, 'required': ['producers'] diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 7f2ac01fb..f0b177647 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -55,7 +55,7 @@ class ExternalMessageConsumer: self.sleep_time = self._emc_config.get('sleep_time', 5) # The amount of candles per dataframe on the initial request - self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 500) + self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 1500) # Setting these explicitly as they probably shouldn't be changed by a user # Unless we somehow integrate this with the strategy to allow creating From 4dec19de9f9ca55565c7972c62eb65afa33d1f48 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 06:52:50 +0200 Subject: [PATCH 183/592] Add comment to explain why we use the non-trimmed DF --- freqtrade/optimize/hyperopt.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 4c8613a7a..3becf857f 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -421,8 +421,9 @@ class Hyperopt: preprocessed = self.backtesting.strategy.advise_all_indicators(data) # Trim startup period from analyzed dataframe to get correct dates for output. - processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) - self.min_date, self.max_date = get_timerange(processed) + trimmed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) + self.min_date, self.max_date = get_timerange(trimmed) + # Real trimming will happen as part of backtesting. return preprocessed def prepare_hyperopt_data(self) -> None: From d526dfb171a25b99059f21f23c40965ef7ab3837 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 07:03:31 +0200 Subject: [PATCH 184/592] Revert some more changes in rpc_manager --- freqtrade/rpc/rpc_manager.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 3ba2f9d4d..fa2178b1a 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -20,7 +20,6 @@ class RPCManager: def __init__(self, freqtrade) -> None: """ Initializes all enabled rpc modules """ self.registered_modules: List[RPCHandler] = [] - self._freqtrade = freqtrade self._rpc = RPC(freqtrade) config = freqtrade.config # Enable telegram @@ -53,7 +52,7 @@ class RPCManager: """ Stops all enabled rpc modules """ logger.info('Cleaning up rpc modules ...') while self.registered_modules: - mod = self.registered_modules.pop() # popleft to cleanup API server last? + mod = self.registered_modules.pop() logger.info('Cleaning up rpc.%s ...', mod.name) mod.cleanup() del mod From 38f14349e9a70e582e0e1e2acecbbf18ab921385 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 5 Sep 2022 23:25:25 -0600 Subject: [PATCH 185/592] move bytes decoding to serializer --- freqtrade/rpc/api_server/ws/proxy.py | 6 ------ freqtrade/rpc/api_server/ws/serializer.py | 7 +++---- 2 files changed, 3 insertions(+), 10 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py index ea977a228..e43ce6441 100644 --- a/freqtrade/rpc/api_server/ws/proxy.py +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -27,12 +27,6 @@ class WebSocketProxy: """ Send data on the wrapped websocket """ - - if not isinstance(data, str): - # We use HybridJSONWebSocketSerializer, which when serialized returns - # bytes because of ORJSON, so we explicitly decode into a string - data = str(data, "utf-8") - if hasattr(self._websocket, "send_text"): await self._websocket.send_text(data) else: diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index 8ff617f45..c0c24bb28 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -57,11 +57,10 @@ class RapidJSONWebSocketSerializer(WebSocketSerializer): class HybridJSONWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data): - # ORJSON returns bytes - return orjson.dumps(data, default=_json_default) + def _serialize(self, data) -> str: + return str(orjson.dumps(data, default=_json_default), "utf-8") - def _deserialize(self, data): + def _deserialize(self, data: str): # RapidJSON expects strings return rapidjson.loads(data, object_hook=_json_object_hook) From 8597b52e345abca6111869bb5da71c01ce7d4107 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 16:29:24 +0200 Subject: [PATCH 186/592] Slightly update docs to link to full sample --- docs/strategy-customization.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index a452b8f05..2b6e1fb2f 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -824,6 +824,8 @@ Options: - Merge the dataframe without lookahead bias - Forward-fill (optional) +For a full sample, please refer to the [complete data provider example](#complete-data-provider-sample) below. + All columns of the informative dataframe will be available on the returning dataframe in a renamed fashion: !!! Example "Column renaming" From 4b28d0495f46337700686f1b430827336285511a Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 6 Sep 2022 19:46:58 +0200 Subject: [PATCH 187/592] fix timestamping, move imports, add words to doc --- docs/freqai.md | 2 +- freqtrade/freqai/data_kitchen.py | 26 ++++++++++++-------------- freqtrade/freqai/freqai_interface.py | 15 +++++++-------- tests/freqai/conftest.py | 12 +++++------- 4 files changed, 25 insertions(+), 30 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index d504c93d6..a8379106a 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -116,7 +116,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` | `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False | `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 -| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5%. Good for preventing overfitting.
    **Datatype:** int. Default: 0 +| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5% (i.e. the percent of data falling within the first standard deviation). Good for preventing overfitting.
    **Datatype:** int. Default: 0 | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index fce9e8480..8ef2d6aea 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -2,12 +2,14 @@ import copy import logging import shutil from datetime import datetime, timezone +from math import cos, sin from pathlib import Path from typing import Any, Dict, List, Tuple import numpy as np import numpy.typing as npt import pandas as pd +import scipy.stats as stats from pandas import DataFrame from sklearn import linear_model from sklearn.cluster import DBSCAN @@ -401,8 +403,8 @@ class FreqaiDataKitchen: timerange_train.stopts = timerange_train.startts + train_period_days first = False - start = datetime.utcfromtimestamp(timerange_train.startts) - stop = datetime.utcfromtimestamp(timerange_train.stopts) + start = datetime.fromtimestamp(timerange_train.startts, tz=timezone.utc) + stop = datetime.fromtimestamp(timerange_train.stopts, tz=timezone.utc) tr_training_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")) tr_training_list_timerange.append(copy.deepcopy(timerange_train)) @@ -415,8 +417,8 @@ class FreqaiDataKitchen: if timerange_backtest.stopts > config_timerange.stopts: timerange_backtest.stopts = config_timerange.stopts - start = datetime.utcfromtimestamp(timerange_backtest.startts) - stop = datetime.utcfromtimestamp(timerange_backtest.stopts) + start = datetime.fromtimestamp(timerange_backtest.startts, tz=timezone.utc) + stop = datetime.fromtimestamp(timerange_backtest.stopts, tz=timezone.utc) tr_backtesting_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")) tr_backtesting_list_timerange.append(copy.deepcopy(timerange_backtest)) @@ -630,8 +632,6 @@ class FreqaiDataKitchen: is an outlier. """ - from math import cos, sin - if predict: if not self.data['DBSCAN_eps']: return @@ -732,8 +732,6 @@ class FreqaiDataKitchen: into previous timepoints. """ - import scipy.stats as ss - no_prev_pts = self.freqai_config["feature_parameters"]["inlier_metric_window"] if set_ == 'train': @@ -778,8 +776,8 @@ class FreqaiDataKitchen: inliers = pd.DataFrame(index=distances.index) for key in distances.keys(): current_distances = distances[key].dropna() - fit_params = ss.weibull_min.fit(current_distances) - quantiles = ss.weibull_min.cdf(current_distances, *fit_params) + fit_params = stats.weibull_min.fit(current_distances) + quantiles = stats.weibull_min.cdf(current_distances, *fit_params) df_inlier = pd.DataFrame( {key: quantiles}, index=distances.index @@ -794,8 +792,8 @@ class FreqaiDataKitchen: index=compute_df.index ) - inlier_metric = 2 * (inlier_metric - inlier_metric.min()) / \ - (inlier_metric.max() - inlier_metric.min()) - 1 + inlier_metric = (2 * (inlier_metric - inlier_metric.min()) / + (inlier_metric.max() - inlier_metric.min()) - 1) if set_ in ('train', 'test'): inlier_metric = inlier_metric.iloc[no_prev_pts:] @@ -956,8 +954,8 @@ class FreqaiDataKitchen: backtest_timerange.startts = ( backtest_timerange.startts - backtest_period_days * SECONDS_IN_DAY ) - start = datetime.utcfromtimestamp(backtest_timerange.startts) - stop = datetime.utcfromtimestamp(backtest_timerange.stopts) + start = datetime.fromtimestamp(backtest_timerange.startts, tz=timezone.utc) + stop = datetime.fromtimestamp(backtest_timerange.stopts, tz=timezone.utc) full_timerange = start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d") self.full_path = Path( diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index fd0554248..9b3e853ef 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -1,10 +1,9 @@ -# import contextlib import logging import shutil import threading import time from abc import ABC, abstractmethod -from datetime import datetime +from datetime import datetime, timezone from pathlib import Path from threading import Lock from typing import Any, Dict, Tuple @@ -214,12 +213,12 @@ class IFreqaiModel(ABC): dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe) trained_timestamp = tr_train - tr_train_startts_str = datetime.utcfromtimestamp(tr_train.startts).strftime( - "%Y-%m-%d %H:%M:%S" - ) - tr_train_stopts_str = datetime.utcfromtimestamp(tr_train.stopts).strftime( - "%Y-%m-%d %H:%M:%S" - ) + tr_train_startts_str = datetime.fromtimestamp( + tr_train.startts, + tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S") + tr_train_stopts_str = datetime.fromtimestamp( + tr_train.stopts, + tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S") logger.info( f"Training {metadata['pair']}, {self.pair_it}/{self.total_pairs} pairs" f" from {tr_train_startts_str} to {tr_train_stopts_str}, {train_it}/{total_trains} " diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 6528347e8..ffdc52ebc 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -93,12 +93,11 @@ def make_unfiltered_dataframe(mocker, freqai_conf): freqai.live = True freqai.dk = FreqaiDataKitchen(freqai_conf) freqai.dk.pair = "ADA/BTC" - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk) freqai.dd.pair_dict = MagicMock() - - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") corr_dataframes, base_dataframes = freqai.dd.get_base_and_corr_dataframes( @@ -125,12 +124,11 @@ def make_data_dictionary(mocker, freqai_conf): freqai.live = True freqai.dk = FreqaiDataKitchen(freqai_conf) freqai.dk.pair = "ADA/BTC" - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk) freqai.dd.pair_dict = MagicMock() - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") corr_dataframes, base_dataframes = freqai.dd.get_base_and_corr_dataframes( From f2f811a2feed0a8ff427d638ac773d6aea670eaa Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 19:55:18 +0200 Subject: [PATCH 188/592] Fix telegram bug with open partial exit orders --- freqtrade/rpc/rpc.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 11311f671..05599074c 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -261,11 +261,15 @@ class RPC: profit_str += f" ({fiat_profit:.2f})" fiat_profit_sum = fiat_profit if isnan(fiat_profit_sum) \ else fiat_profit_sum + fiat_profit + open_order = (trade.select_order_by_order_id( + trade.open_order_id) if trade.open_order_id else None) + detail_trade = [ f'{trade.id} {direction_str}', - trade.pair + ('*' if (trade.open_order_id is not None - and trade.close_rate_requested is None) else '') - + ('**' if (trade.close_rate_requested is not None) else ''), + trade.pair + ('*' if (open_order + and open_order.ft_order_side == trade.entry_side) else '') + + ('**' if (open_order and + open_order.ft_order_side == trade.exit_side is not None) else ''), shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)), profit_str ] From e83c9b276dab1659da3ea245792fe858b43ed054 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 6 Sep 2022 19:56:52 +0200 Subject: [PATCH 189/592] fix whitespace --- freqtrade/freqai/data_kitchen.py | 2 +- tests/freqai/conftest.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 8ef2d6aea..471634c85 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -9,7 +9,7 @@ from typing import Any, Dict, List, Tuple import numpy as np import numpy.typing as npt import pandas as pd -import scipy.stats as stats +from scipy import stats from pandas import DataFrame from sklearn import linear_model from sklearn.cluster import DBSCAN diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index ffdc52ebc..2bd744455 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -97,7 +97,7 @@ def make_unfiltered_dataframe(mocker, freqai_conf): freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk) freqai.dd.pair_dict = MagicMock() - + new_timerange = TimeRange.parse_timerange("20180120-20180130") corr_dataframes, base_dataframes = freqai.dd.get_base_and_corr_dataframes( From 90ec336c70e02e0ae8156a768bf69b4ac0fa55b5 Mon Sep 17 00:00:00 2001 From: th0rntwig <107926911+th0rntwig@users.noreply.github.com> Date: Tue, 6 Sep 2022 19:58:25 +0200 Subject: [PATCH 190/592] Update+correct descriptions and figure (#7323) --- docs/assets/freqai_weight-factor.jpg | Bin 195825 -> 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z#ZcWc=hoF_6!LuIsOU=Qo)8^PE!lgsT3|yYzvm_w`GjW=Y3hSwa#G3|s67E@hRXj1 qd;rIVUxwWG+`l!D;}0<(d0nwzph`z&{6c>~1k#EKXesjV^nU@S$(@M+ diff --git a/docs/freqai.md b/docs/freqai.md index 303c2f151..c0844bf32 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -112,15 +112,15 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `DI_threshold` | Activates the Dissimilarity Index for outlier detection when > 0. See details about how it works [here](#removing-outliers-with-the-dissimilarity-index).
    **Datatype:** Positive float (typically < 1). | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Dictionary. -| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. -| `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
    **Datatype:** float. Default: `30` -| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** bool. Default: False +| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. +| `outlier_protection_percentage` | If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact. If the outlier protection is triggered, no predictions will be made based on the training data.
    **Datatype:** Float. Default: `30` +| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** Boolean. Default: False | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. -| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
    +| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
    **Datatype:** Boolean. | | **Model training parameters** -| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
    **Datatype:** Dictionary.**Datatype:** Boolean. +| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
    **Datatype:** Dictionary. | `n_estimators` | The number of boosted trees to fit in regression.
    **Datatype:** Integer. | `learning_rate` | Boosting learning rate during regression.
    **Datatype:** Float. | `n_jobs`, `thread_count`, `task_type` | Set the number of threads for parallel processing and the `task_type` (`gpu` or `cpu`). Different model libraries use different parameter names.
    **Datatype:** Float. @@ -738,7 +738,7 @@ Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters ![dbscan](assets/freqai_dbscan.jpg) -FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as double the no. of user-defined features, and `eps` ($\varepsilon$) taken as the longest distance in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. +FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as 1/4 of the no. of time points in the feature set, and `eps` ($\varepsilon$) taken as the elbow point in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. ## Additional information @@ -763,5 +763,5 @@ Code review, software architecture brainstorming: @xmatthias Beta testing and bug reporting: -@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm +@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm, Juha Nykänen @suikula, Wagner Costa @wagnercosta From d44296783e6264e25a3c20cfc7f5e104883f8ce2 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 6 Sep 2022 20:10:12 +0200 Subject: [PATCH 191/592] isort datakitchen --- freqtrade/freqai/data_kitchen.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 471634c85..2ed0d73af 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -9,8 +9,8 @@ from typing import Any, Dict, List, Tuple import numpy as np import numpy.typing as npt import pandas as pd -from scipy import stats from pandas import DataFrame +from scipy import stats from sklearn import linear_model from sklearn.cluster import DBSCAN from sklearn.metrics.pairwise import pairwise_distances From 3535aa7724c4a202007841a1efa18c70fe728ab5 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 6 Sep 2022 12:12:05 -0600 Subject: [PATCH 192/592] add last_analyzed to emitted dataframe --- freqtrade/data/dataprovider.py | 10 ++++++++-- freqtrade/rpc/external_message_consumer.py | 21 +++++++++++++-------- freqtrade/rpc/rpc.py | 3 ++- 3 files changed, 23 insertions(+), 11 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 76e184296..44296ab40 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -121,7 +121,7 @@ class DataProvider: 'type': RPCMessageType.ANALYZED_DF, 'data': { 'key': pair_key, - 'value': dataframe + 'value': (dataframe, datetime.now(timezone.utc)) } } ) @@ -130,6 +130,7 @@ class DataProvider: self, pair: str, dataframe: DataFrame, + last_analyzed: Optional[str] = None, timeframe: Optional[str] = None, candle_type: Optional[CandleType] = None, producer_name: str = "default" @@ -149,7 +150,12 @@ class DataProvider: if producer_name not in self.__producer_pairs_df: self.__producer_pairs_df[producer_name] = {} - self.__producer_pairs_df[producer_name][pair_key] = (dataframe, datetime.now(timezone.utc)) + if not last_analyzed: + _last_analyzed = datetime.now(timezone.utc) + else: + _last_analyzed = datetime.fromisoformat(last_analyzed) + + self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed) logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.") def get_external_df( diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index f0b177647..28628c1f6 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -10,7 +10,6 @@ import socket from threading import Thread from typing import Any, Dict, List, Optional -import pandas import websockets from freqtrade.data.dataprovider import DataProvider @@ -225,9 +224,12 @@ class ExternalMessageConsumer: timeout=self.reply_timeout ) - async with lock: - # Handle the message - self.handle_producer_message(producer, message) + try: + async with lock: + # Handle the message + self.handle_producer_message(producer, message) + except Exception as e: + logger.exception(f"Error handling producer message: {e}") except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed): # We haven't received data yet. Check the connection and continue. @@ -300,17 +302,20 @@ class ExternalMessageConsumer: key, value = message_data.get('key'), message_data.get('value') - if key and isinstance(value, pandas.DataFrame): + if key and value: pair, timeframe, candle_type = key - dataframe = value + dataframe, last_analyzed = value # If set, remove the Entry and Exit signals from the Producer if self._emc_config.get('remove_entry_exit_signals', False): dataframe = remove_entry_exit_signals(dataframe) # Add the dataframe to the dataprovider - self._dp._add_external_df(pair, dataframe, timeframe, - candle_type, producer_name=producer_name) + self._dp._add_external_df(pair, dataframe, + last_analyzed=last_analyzed, + timeframe=timeframe, + candle_type=candle_type, + producer_name=producer_name) logger.debug( f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 3757c58c2..98dad278f 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1064,7 +1064,8 @@ class RPC: for pair in pairlist: dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) - _data[pair] = {"key": (pair, timeframe, candle_type), "value": dataframe} + _data[pair] = {"key": (pair, timeframe, candle_type), + "value": (dataframe, last_analyzed)} return _data From dc4a4bdf09cfc3ecb588cdabb3877e07b5762ab0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 20:25:46 +0200 Subject: [PATCH 193/592] Wrap cleanup in try/finally handler If a database has errors, the database cleanups would fail, causing cleanup to be incomplete. closes #7364 --- freqtrade/freqtradebot.py | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index f7dca1d75..1d171ae89 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -142,17 +142,20 @@ class FreqtradeBot(LoggingMixin): :return: None """ logger.info('Cleaning up modules ...') + try: + # Wrap db activities in shutdown to avoid problems if database is gone, + # and raises further exceptions. + if self.config['cancel_open_orders_on_exit']: + self.cancel_all_open_orders() - if self.config['cancel_open_orders_on_exit']: - self.cancel_all_open_orders() + self.check_for_open_trades() - self.check_for_open_trades() + finally: + self.strategy.ft_bot_cleanup() - self.strategy.ft_bot_cleanup() - - self.rpc.cleanup() - Trade.commit() - self.exchange.close() + self.rpc.cleanup() + Trade.commit() + self.exchange.close() def startup(self) -> None: """ From 97077ba18acd9ea0ad67ba45e917aca6bdcb3b0d Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 6 Sep 2022 20:30:37 +0200 Subject: [PATCH 194/592] add continual learning to catboost and friends --- docs/freqai.md | 1 + freqtrade/freqai/freqai_interface.py | 3 ++- .../prediction_models/BaseClassifierModel.py | 2 +- .../prediction_models/BaseRegressionModel.py | 2 +- .../prediction_models/BaseTensorFlowModel.py | 2 +- .../prediction_models/CatboostClassifier.py | 11 ++++++++--- .../freqai/prediction_models/CatboostRegressor.py | 15 ++++++++------- .../CatboostRegressorMultiTarget.py | 7 +++++-- .../prediction_models/LightGBMClassifier.py | 11 ++++++++--- .../freqai/prediction_models/LightGBMRegressor.py | 11 ++++++++--- .../LightGBMRegressorMultiTarget.py | 7 +++++-- 11 files changed, 48 insertions(+), 24 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index c0844bf32..e790bbb81 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -98,6 +98,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
    Defaults set to 0, which means models never expire.
    **Datatype:** Positive integer. | `fit_live_predictions_candles` | Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training data set.
    **Datatype:** Positive integer. | `follow_mode` | If true, this instance of FreqAI will look for models associated with `identifier` and load those for inferencing. A `follower` will **not** train new models.
    **Datatype:** Boolean. Default: `False`. +| `continual_learning` | If true, FreqAI will start training new models from the final state of the most recently trained model.
    **Datatype:** Boolean. Default: `False`. | | **Feature parameters** | `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](#feature-engineering).
    **Datatype:** Dictionary. | `include_timeframes` | A list of timeframes that all indicators in `populate_any_indicators` will be created for. The list is added as features to the base asset feature set.
    **Datatype:** List of timeframes (strings). diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index a9c21fb65..b6f3d8ebc 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -86,6 +86,7 @@ class IFreqaiModel(ABC): self.begin_time: float = 0 self.begin_time_train: float = 0 self.base_tf_seconds = timeframe_to_seconds(self.config['timeframe']) + self.continual_learning = self.freqai_info.get('continual_learning', False) self._threads: List[threading.Thread] = [] self._stop_event = threading.Event() @@ -674,7 +675,7 @@ class IFreqaiModel(ABC): """ @abstractmethod - def fit(self, data_dictionary: Dict[str, Any]) -> Any: + def fit(self, data_dictionary: Dict[str, Any], dk: FreqaiDataKitchen) -> Any: """ Most regressors use the same function names and arguments e.g. user can drop in LGBMRegressor in place of CatBoostRegressor and all data diff --git a/freqtrade/freqai/prediction_models/BaseClassifierModel.py b/freqtrade/freqai/prediction_models/BaseClassifierModel.py index 2edbf3b51..e51e26e0f 100644 --- a/freqtrade/freqai/prediction_models/BaseClassifierModel.py +++ b/freqtrade/freqai/prediction_models/BaseClassifierModel.py @@ -61,7 +61,7 @@ class BaseClassifierModel(IFreqaiModel): ) logger.info(f'Training model on {len(data_dictionary["train_features"])} data points') - model = self.fit(data_dictionary) + model = self.fit(data_dictionary, dk) logger.info(f"--------------------done training {pair}--------------------") diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py index 2ef175a2e..45f0c2937 100644 --- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py +++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py @@ -60,7 +60,7 @@ class BaseRegressionModel(IFreqaiModel): ) logger.info(f'Training model on {len(data_dictionary["train_features"])} data points') - model = self.fit(data_dictionary) + model = self.fit(data_dictionary, dk) logger.info(f"--------------------done training {pair}--------------------") diff --git a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py index 04eff045f..66e6ec1fc 100644 --- a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py +++ b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py @@ -57,7 +57,7 @@ class BaseTensorFlowModel(IFreqaiModel): ) logger.info(f'Training model on {len(data_dictionary["train_features"])} data points') - model = self.fit(data_dictionary) + model = self.fit(data_dictionary, dk) logger.info(f"--------------------done training {pair}--------------------") diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index b88b28b25..13395879a 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -2,7 +2,7 @@ import logging from typing import Any, Dict from catboost import CatBoostClassifier, Pool - +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel @@ -16,7 +16,7 @@ class CatboostClassifier(BaseClassifierModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ User sets up the training and test data to fit their desired model here :params: @@ -36,6 +36,11 @@ class CatboostClassifier(BaseClassifierModel): **self.model_training_parameters, ) - cbr.fit(train_data) + if dk.pair not in self.dd.model_dictionary or not self.continual_learning: + init_model = None + else: + init_model = self.dd.model_dictionary[dk.pair] + + cbr.fit(train_data, init_model=init_model) return cbr diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index d93569c91..0b8bc162b 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -3,6 +3,7 @@ import logging from typing import Any, Dict from catboost import CatBoostRegressor, Pool +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel @@ -17,7 +18,7 @@ class CatboostRegressor(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold @@ -38,16 +39,16 @@ class CatboostRegressor(BaseRegressionModel): weight=data_dictionary["test_weights"], ) + if dk.pair not in self.dd.model_dictionary or not self.continual_learning: + init_model = None + else: + init_model = self.dd.model_dictionary[dk.pair] + model = CatBoostRegressor( allow_writing_files=False, **self.model_training_parameters, ) - model.fit(X=train_data, eval_set=test_data) - - # some evidence that catboost pools have memory leaks: - # https://github.com/catboost/catboost/issues/1835 - del train_data, test_data - gc.collect() + model.fit(X=train_data, eval_set=test_data, init_model=init_model) return model diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index 9894decd1..9ed61488c 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -3,7 +3,7 @@ from typing import Any, Dict from catboost import CatBoostRegressor # , Pool from sklearn.multioutput import MultiOutputRegressor - +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel @@ -17,7 +17,7 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold @@ -34,6 +34,9 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) sample_weight = data_dictionary["train_weights"] + if self.continual_learning: + logger.warning('Continual learning not supported for MultiTarget models') + model = MultiOutputRegressor(estimator=cbr) model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) diff --git a/freqtrade/freqai/prediction_models/LightGBMClassifier.py b/freqtrade/freqai/prediction_models/LightGBMClassifier.py index 4ac2c448b..0023a9f69 100644 --- a/freqtrade/freqai/prediction_models/LightGBMClassifier.py +++ b/freqtrade/freqai/prediction_models/LightGBMClassifier.py @@ -4,7 +4,7 @@ from typing import Any, Dict from lightgbm import LGBMClassifier from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel - +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen logger = logging.getLogger(__name__) @@ -16,7 +16,7 @@ class LightGBMClassifier(BaseClassifierModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ User sets up the training and test data to fit their desired model here :params: @@ -35,9 +35,14 @@ class LightGBMClassifier(BaseClassifierModel): y = data_dictionary["train_labels"].to_numpy()[:, 0] train_weights = data_dictionary["train_weights"] + if dk.pair not in self.dd.model_dictionary or not self.continual_learning: + init_model = None + else: + init_model = self.dd.model_dictionary[dk.pair] + model = LGBMClassifier(**self.model_training_parameters) model.fit(X=X, y=y, eval_set=eval_set, sample_weight=train_weights, - eval_sample_weight=[test_weights]) + eval_sample_weight=[test_weights], init_model=init_model) return model diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressor.py b/freqtrade/freqai/prediction_models/LightGBMRegressor.py index 2431fd2ad..81f0e6d22 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressor.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressor.py @@ -4,7 +4,7 @@ from typing import Any, Dict from lightgbm import LGBMRegressor from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel - +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen logger = logging.getLogger(__name__) @@ -16,7 +16,7 @@ class LightGBMRegressor(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ Most regressors use the same function names and arguments e.g. user can drop in LGBMRegressor in place of CatBoostRegressor and all data @@ -35,9 +35,14 @@ class LightGBMRegressor(BaseRegressionModel): y = data_dictionary["train_labels"] train_weights = data_dictionary["train_weights"] + if dk.pair not in self.dd.model_dictionary or not self.continual_learning: + init_model = None + else: + init_model = self.dd.model_dictionary[dk.pair] + model = LGBMRegressor(**self.model_training_parameters) model.fit(X=X, y=y, eval_set=eval_set, sample_weight=train_weights, - eval_sample_weight=[eval_weights]) + eval_sample_weight=[eval_weights], init_model=init_model) return model diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py index ecd405369..2b25493e0 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py @@ -5,7 +5,7 @@ from lightgbm import LGBMRegressor from sklearn.multioutput import MultiOutputRegressor from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel - +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen logger = logging.getLogger(__name__) @@ -17,7 +17,7 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold @@ -31,6 +31,9 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel): eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) sample_weight = data_dictionary["train_weights"] + if self.continual_learning: + logger.warning('Continual learning not supported for MultiTarget models') + model = MultiOutputRegressor(estimator=lgb) model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) train_score = model.score(X, y) From b1c02674492993571c1cbc10144277eb29fda7a9 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 6 Sep 2022 12:40:58 -0600 Subject: [PATCH 195/592] mypy fixes --- freqtrade/rpc/api_server/ws/channel.py | 4 +++- freqtrade/rpc/api_server/ws/proxy.py | 10 ++++++---- freqtrade/rpc/api_server/ws/types.py | 2 +- freqtrade/rpc/external_message_consumer.py | 7 ++++++- 4 files changed, 16 insertions(+), 7 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 952b3b9f5..cffe3092d 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -3,6 +3,8 @@ from threading import RLock from typing import List, Optional, Type from uuid import uuid4 +from fastapi import WebSocket as FastAPIWebSocket + from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy from freqtrade.rpc.api_server.ws.serializer import (HybridJSONWebSocketSerializer, WebSocketSerializer) @@ -105,7 +107,7 @@ class ChannelManager: :param websocket: The WebSocket object to attach to the Channel """ - if hasattr(websocket, "accept"): + if isinstance(websocket, FastAPIWebSocket): try: await websocket.accept() except RuntimeError: diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py index e43ce6441..da3e04887 100644 --- a/freqtrade/rpc/api_server/ws/proxy.py +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -1,7 +1,7 @@ from typing import Any, Tuple, Union from fastapi import WebSocket as FastAPIWebSocket -from websockets import WebSocketClientProtocol as WebSocket +from websockets.client import WebSocketClientProtocol as WebSocket from freqtrade.rpc.api_server.ws.types import WebSocketType @@ -17,10 +17,12 @@ class WebSocketProxy: @property def remote_addr(self) -> Tuple[Any, ...]: - if hasattr(self._websocket, "remote_address"): + if isinstance(self._websocket, WebSocket): return self._websocket.remote_address - elif hasattr(self._websocket, "client"): - return tuple(self._websocket.client) + elif isinstance(self._websocket, FastAPIWebSocket): + if self._websocket.client: + client, port = self._websocket.client.host, self._websocket.client.port + return (client, port) return ("unknown", 0) async def send(self, data): diff --git a/freqtrade/rpc/api_server/ws/types.py b/freqtrade/rpc/api_server/ws/types.py index 814fe6649..9855f9e06 100644 --- a/freqtrade/rpc/api_server/ws/types.py +++ b/freqtrade/rpc/api_server/ws/types.py @@ -1,7 +1,7 @@ from typing import Any, Dict, TypeVar from fastapi import WebSocket as FastAPIWebSocket -from websockets import WebSocketClientProtocol as WebSocket +from websockets.client import WebSocketClientProtocol as WebSocket WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 28628c1f6..c1ad0512e 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -8,7 +8,7 @@ import asyncio import logging import socket from threading import Thread -from typing import Any, Dict, List, Optional +from typing import TYPE_CHECKING, Any, Dict, List, Optional import websockets @@ -18,6 +18,11 @@ from freqtrade.misc import remove_entry_exit_signals from freqtrade.rpc.api_server.ws.channel import WebSocketChannel +if TYPE_CHECKING: + import websockets.connect + import websockets.exceptions + + logger = logging.getLogger(__name__) From 8d16dd804dcc0b0cfe94e1b3389186bc23d8e957 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Tue, 6 Sep 2022 15:42:47 -0300 Subject: [PATCH 196/592] hyperopt - freqai - docs and refactoring --- docs/freqai.md | 11 +++ freqtrade/configuration/configuration.py | 10 +++ freqtrade/freqai/data_drawer.py | 28 ++----- freqtrade/freqai/freqai_interface.py | 5 +- freqtrade/templates/FreqaiExampleStrategy.py | 86 +------------------- 5 files changed, 29 insertions(+), 111 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 303c2f151..f8cf64d21 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -279,6 +279,8 @@ The FreqAI strategy requires the user to include the following lines of code in Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](#feature-engineering)) and labels ([more information](#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. +*Important*: The `self.freqai.start()` function cannot be called outside the `populate_indicators()`. + ### Setting the `startup_candle_count` Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). @@ -532,6 +534,15 @@ for each pair, for each backtesting window within the expanded `--timerange`. --- +### Hyperopt + +The [Hyperopt](hyperopt.md) module can be executed with some restrictions: + +- The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. +- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md###runninghyperoptwithsmallersearchspace). +- The [Backtesting](#backtesting) instructions also apply apply to Hyperopt. + + ### Deciding the size of the sliding training window and backtesting duration The user defines the backtesting timerange with the typical `--timerange` parameter in the diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index 7c68ac46c..d18b67ff2 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -285,6 +285,7 @@ class Configuration: logger.info('Parameter --stoplosses detected: %s ...', self.args["stoploss_range"]) # Hyperopt section + self._check_hyperopt_analyze_per_epoch_freqai() self._args_to_config(config, argname='hyperopt', logstring='Using Hyperopt class name: {}') @@ -537,3 +538,12 @@ class Configuration: config['pairs'] = load_file(pairs_file) if 'pairs' in config and isinstance(config['pairs'], list): config['pairs'].sort() + + def _check_hyperopt_analyze_per_epoch_freqai(self) -> None: + """ + Helper for block hyperopt with analyze-per-epoch param. + """ + if ("analyze_per_epoch" in self.args and + self.args["analyze_per_epoch"] and "freqaimodel" in self.args): + raise OperationalException('analyze-per-epoch parameter is \ + not allowed with a Freqai strategy.') diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index dff6b5942..9eeabef8f 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -93,16 +93,6 @@ class FreqaiDataDrawer: "model_filename": "", "trained_timestamp": 0, "priority": 1, "first": True, "data_path": "", "extras": {}} - def __getstate__(self): - """ - Return state values to be pickled. - It's necessary to allow serialization in hyperopt - """ - return ({ - "pair_dict": self.pair_dict, - "pair_dictionary_path": self.pair_dictionary_path - }) - def load_drawer_from_disk(self): """ Locate and load a previously saved data drawer full of all pair model metadata in @@ -165,22 +155,14 @@ class FreqaiDataDrawer: # create a backup shutil.copy(self.historic_predictions_path, self.historic_predictions_bkp_path) - def save_drawer_to_disk(self, live=False): + def save_drawer_to_disk(self): """ Save data drawer full of all pair model metadata in present model folder. """ - if live: - with self.save_lock: - with open(self.pair_dictionary_path, 'w') as fp: - rapidjson.dump( - self.pair_dict, fp, default=self.np_encoder, - number_mode=rapidjson.NM_NATIVE) - else: - # save_lock it's not working with hyperopt + with self.save_lock: with open(self.pair_dictionary_path, 'w') as fp: - rapidjson.dump( - self.pair_dict, fp, default=self.np_encoder, - number_mode=rapidjson.NM_NATIVE) + rapidjson.dump(self.pair_dict, fp, default=self.np_encoder, + number_mode=rapidjson.NM_NATIVE) def save_follower_dict_to_disk(self): """ @@ -455,7 +437,7 @@ class FreqaiDataDrawer: self.model_dictionary[coin] = model self.pair_dict[coin]["model_filename"] = dk.model_filename self.pair_dict[coin]["data_path"] = str(dk.data_path) - self.save_drawer_to_disk(dk.live) + self.save_drawer_to_disk() return diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 9a05e8383..f631c9126 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -92,10 +92,9 @@ class IFreqaiModel(ABC): def __getstate__(self): """ - Return state values to be pickled. - It's necessary to allow serialization in hyperopt + Return an empty state to be pickled in hyperopt """ - return ({"dd": self.dd}) + return ({}) def assert_config(self, config: Dict[str, Any]) -> None: diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index 0e822a028..78132b06d 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -6,9 +6,7 @@ import talib.abstract as ta from pandas import DataFrame from technical import qtpylib -from freqtrade.exchange import timeframe_to_prev_date -from freqtrade.persistence import Trade -from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, merge_informative_pair +from freqtrade.strategy import IStrategy, merge_informative_pair logger = logging.getLogger(__name__) @@ -47,11 +45,6 @@ class FreqaiExampleStrategy(IStrategy): startup_candle_count: int = 40 can_short = False - linear_roi_offset = DecimalParameter( - 0.00, 0.02, default=0.005, space="sell", optimize=False, load=True - ) - max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) - def informative_pairs(self): whitelist_pairs = self.dp.current_whitelist() corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] @@ -226,83 +219,6 @@ class FreqaiExampleStrategy(IStrategy): def get_ticker_indicator(self): return int(self.config["timeframe"][:-1]) - def custom_exit( - self, pair: str, trade: Trade, current_time, current_rate, current_profit, **kwargs - ): - - dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe) - - trade_date = timeframe_to_prev_date(self.config["timeframe"], trade.open_date_utc) - trade_candle = dataframe.loc[(dataframe["date"] == trade_date)] - - if trade_candle.empty: - return None - trade_candle = trade_candle.squeeze() - - follow_mode = self.config.get("freqai", {}).get("follow_mode", False) - - if not follow_mode: - pair_dict = self.freqai.dd.pair_dict - else: - pair_dict = self.freqai.dd.follower_dict - - entry_tag = trade.enter_tag - - if ( - "prediction" + entry_tag not in pair_dict[pair] - or pair_dict[pair]['extras']["prediction" + entry_tag] == 0 - ): - pair_dict[pair]['extras']["prediction" + entry_tag] = abs(trade_candle["&-s_close"]) - if not follow_mode: - self.freqai.dd.save_drawer_to_disk() - else: - self.freqai.dd.save_follower_dict_to_disk() - - roi_price = pair_dict[pair]['extras']["prediction" + entry_tag] - roi_time = self.max_roi_time_long.value - - roi_decay = roi_price * ( - 1 - ((current_time - trade.open_date_utc).seconds) / (roi_time * 60) - ) - if roi_decay < 0: - roi_decay = self.linear_roi_offset.value - else: - roi_decay += self.linear_roi_offset.value - - if current_profit > roi_decay: - return "roi_custom_win" - - if current_profit < -roi_decay: - return "roi_custom_loss" - - def confirm_trade_exit( - self, - pair: str, - trade: Trade, - order_type: str, - amount: float, - rate: float, - time_in_force: str, - exit_reason: str, - current_time, - **kwargs, - ) -> bool: - - entry_tag = trade.enter_tag - follow_mode = self.config.get("freqai", {}).get("follow_mode", False) - if not follow_mode: - pair_dict = self.freqai.dd.pair_dict - else: - pair_dict = self.freqai.dd.follower_dict - - pair_dict[pair]['extras']["prediction" + entry_tag] = 0 - if not follow_mode: - self.freqai.dd.save_drawer_to_disk() - else: - self.freqai.dd.save_follower_dict_to_disk() - - return True - def confirm_trade_entry( self, pair: str, From 5aba5de20f5dea1f61aa7ced19a966744b5c3e30 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Tue, 6 Sep 2022 16:17:10 -0300 Subject: [PATCH 197/592] fix link - hyperopt spaces --- docs/freqai.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/freqai.md b/docs/freqai.md index fa58feb07..7aabb0e56 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -539,7 +539,7 @@ for each pair, for each backtesting window within the expanded `--timerange`. The [Hyperopt](hyperopt.md) module can be executed with some restrictions: - The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. -- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md###runninghyperoptwithsmallersearchspace). +- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md#running-hyperopt-with-smaller-search-space). - The [Backtesting](#backtesting) instructions also apply apply to Hyperopt. From 95a33ab2e639d8510c45e731946c5ed2a9189493 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 06:34:03 +0200 Subject: [PATCH 198/592] Add amount_to_contract helper in the exchange --- freqtrade/exchange/exchange.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index c3dca43a8..af072d555 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -446,6 +446,15 @@ class Exchange: contract_size = self.get_contract_size(pair) return contracts_to_amount(num_contracts, contract_size) + def amount_to_contract_precision(self, pair: str, amount: float) -> float: + """ + Helper wrapper around amount_to_contract_precision + """ + contract_size = self.get_contract_size(pair) + + return amount_to_contract_precision(amount, self.get_precision_amount(pair), + self.precisionMode, contract_size) + def set_sandbox(self, api: ccxt.Exchange, exchange_config: dict, name: str) -> None: if exchange_config.get('sandbox'): if api.urls.get('test'): From 83d9f3aeba221bb7a1934a193de66bb4c3887019 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 06:35:58 +0200 Subject: [PATCH 199/592] Add test showing #7365 --- tests/test_integration.py | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/tests/test_integration.py b/tests/test_integration.py index dd3488f81..77ed822d1 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -485,7 +485,7 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non assert len(trade.orders) == 1 assert pytest.approx(trade.stake_amount) == 60 assert pytest.approx(trade.amount) == 30.0 - assert log_has_re("Remaining amount of 1.6.* would be too small.", caplog) + assert log_has_re("Remaining amount of 1.6.* would be smaller than the minimum of 10.", caplog) freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-20) @@ -504,9 +504,21 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-50) freqtrade.process() assert log_has_re("Adjusting amount to trade.amount as it is higher.*", caplog) - assert log_has_re("Remaining amount of 0.0 would be too small.", caplog) + assert log_has_re("Remaining amount of 0.0 would be smaller than the minimum of 10.", caplog) trade = Trade.get_trades().first() assert len(trade.orders) == 2 assert trade.orders[-1].ft_order_side == 'sell' assert pytest.approx(trade.stake_amount) == 40.198 assert trade.is_open + + # use amount that would trunc to 0.0 once selling + mocker.patch("freqtrade.exchange.Exchange.amount_to_contract_precision", + lambda s, p, v: round(v, 1)) + freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-0.01) + freqtrade.process() + trade = Trade.get_trades().first() + assert len(trade.orders) == 2 + assert trade.orders[-1].ft_order_side == 'sell' + assert pytest.approx(trade.stake_amount) == 40.198 + assert trade.is_open + assert log_has_re('Amount to sell is 0.0 due to exchange limits - not selling.', caplog) From 4d69df08dde96d067d9daebbf2db3a61a24dd44a Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 06:43:08 +0200 Subject: [PATCH 200/592] trunc to amount precision before checking valid partial exits closes #7368 --- freqtrade/freqtradebot.py | 11 +++++++++-- freqtrade/optimize/backtesting.py | 6 +++++- 2 files changed, 14 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 1d171ae89..a2f39afd6 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -583,7 +583,9 @@ class FreqtradeBot(LoggingMixin): if stake_amount is not None and stake_amount < 0.0: # We should decrease our position - amount = abs(float(FtPrecise(stake_amount) / FtPrecise(current_exit_rate))) + amount = self.exchange.amount_to_contract_precision( + trade.pair, + abs(float(FtPrecise(stake_amount) / FtPrecise(current_exit_rate)))) if amount > trade.amount: # This is currently ineffective as remaining would become < min tradable # Fixing this would require checking for 0.0 there - @@ -592,9 +594,14 @@ class FreqtradeBot(LoggingMixin): f"Adjusting amount to trade.amount as it is higher. {amount} > {trade.amount}") amount = trade.amount + if amount == 0.0: + logger.info("Amount to sell is 0.0 due to exchange limits - not selling.") + return + remaining = (trade.amount - amount) * current_exit_rate if remaining < min_exit_stake: - logger.info(f'Remaining amount of {remaining} would be too small.') + logger.info(f"Remaining amount of {remaining} would be smaller " + f"than the minimum of {min_exit_stake}.") return self.execute_trade_exit(trade, current_exit_rate, exit_check=ExitCheckTuple( diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 8f6b6b332..97418b72c 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -537,7 +537,11 @@ class Backtesting: return pos_trade if stake_amount is not None and stake_amount < 0.0: - amount = abs(stake_amount) / current_rate + amount = amount_to_contract_precision( + abs(stake_amount) / current_rate, trade.amount_precision, + self.precision_mode, trade.contract_size) + if amount == 0.0: + return trade if amount > trade.amount: # This is currently ineffective as remaining would become < min tradable amount = trade.amount From 3454a52b9523ed567f0c009cc7b3bf8c6100b75f Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 06:55:22 +0200 Subject: [PATCH 201/592] Explicitly test amount_to_contract_precision --- tests/exchange/test_exchange.py | 33 +++++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 3352019a9..3b903f8ee 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4456,6 +4456,39 @@ def test__amount_to_contracts( assert result_amount == param_amount +@pytest.mark.parametrize('pair,amount,expected_spot,expected_fut', [ + # Contract size of 0.01 + ('ADA/USDT:USDT', 40, 40, 40), + ('ADA/USDT:USDT', 10.4445555, 10.4, 10.444), + ('LTC/ETH', 30, 30, 30), + ('LTC/USD', 30, 30, 30), + # contract size of 10 + ('ETH/USDT:USDT', 10.111, 10.1, 10), + ('ETH/USDT:USDT', 10.188, 10.1, 10), + ('ETH/USDT:USDT', 10.988, 10.9, 10), +]) +def test_amount_to_contract_precision( + mocker, + default_conf, + pair, + amount, + expected_spot, + expected_fut, +): + api_mock = MagicMock() + default_conf['trading_mode'] = 'spot' + default_conf['margin_mode'] = 'isolated' + exchange = get_patched_exchange(mocker, default_conf, api_mock) + + result_size = exchange.amount_to_contract_precision(pair, amount) + assert result_size == expected_spot + + default_conf['trading_mode'] = 'futures' + exchange = get_patched_exchange(mocker, default_conf, api_mock) + result_size = exchange.amount_to_contract_precision(pair, amount) + assert result_size == expected_fut + + @pytest.mark.parametrize('exchange_name,open_rate,is_short,trading_mode,margin_mode', [ # Bittrex ('bittrex', 2.0, False, 'spot', None), From 972b6991057d00ea1d321403cebf8e2feefa57ff Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 7 Sep 2022 11:11:31 -0300 Subject: [PATCH 202/592] hyperopt - freqai - change validation to config_validation --- freqtrade/configuration/config_validation.py | 9 +++++++++ freqtrade/configuration/configuration.py | 10 ---------- 2 files changed, 9 insertions(+), 10 deletions(-) diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py index ee846e7e6..b37d44d0f 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -84,6 +84,7 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False) _validate_protections(conf) _validate_unlimited_amount(conf) _validate_ask_orderbook(conf) + _validate_freqai_hyperopt(conf) validate_migrated_strategy_settings(conf) # validate configuration before returning @@ -323,6 +324,14 @@ def _validate_pricing_rules(conf: Dict[str, Any]) -> None: del conf['ask_strategy'] +def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None: + freqaimodel = conf.get('freqaimodel') + analyze_per_epoch = conf.get('analyze_per_epoch', False) + if analyze_per_epoch and freqaimodel is not None: + raise OperationalException( + 'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.') + + def _strategy_settings(conf: Dict[str, Any]) -> None: process_deprecated_setting(conf, None, 'use_sell_signal', None, 'use_exit_signal') diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index d18b67ff2..7c68ac46c 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -285,7 +285,6 @@ class Configuration: logger.info('Parameter --stoplosses detected: %s ...', self.args["stoploss_range"]) # Hyperopt section - self._check_hyperopt_analyze_per_epoch_freqai() self._args_to_config(config, argname='hyperopt', logstring='Using Hyperopt class name: {}') @@ -538,12 +537,3 @@ class Configuration: config['pairs'] = load_file(pairs_file) if 'pairs' in config and isinstance(config['pairs'], list): config['pairs'].sort() - - def _check_hyperopt_analyze_per_epoch_freqai(self) -> None: - """ - Helper for block hyperopt with analyze-per-epoch param. - """ - if ("analyze_per_epoch" in self.args and - self.args["analyze_per_epoch"] and "freqaimodel" in self.args): - raise OperationalException('analyze-per-epoch parameter is \ - not allowed with a Freqai strategy.') From 2c9b7659539ddbf9063f69f4a06429c3790552fc Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 09:35:37 -0600 Subject: [PATCH 203/592] add suffix parameter --- freqtrade/strategy/strategy_helper.py | 14 ++++++++++++-- 1 file changed, 12 insertions(+), 2 deletions(-) diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py index 43728dc1f..55afbf7a8 100644 --- a/freqtrade/strategy/strategy_helper.py +++ b/freqtrade/strategy/strategy_helper.py @@ -1,3 +1,5 @@ +from typing import Optional + import pandas as pd from freqtrade.exchange import timeframe_to_minutes @@ -6,7 +8,8 @@ from freqtrade.exchange import timeframe_to_minutes def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, timeframe: str, timeframe_inf: str, ffill: bool = True, append_timeframe: bool = True, - date_column: str = 'date') -> pd.DataFrame: + date_column: str = 'date', + suffix: Optional[str] = None) -> pd.DataFrame: """ Correctly merge informative samples to the original dataframe, avoiding lookahead bias. @@ -50,10 +53,17 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, # Rename columns to be unique date_merge = 'date_merge' - if append_timeframe: + if append_timeframe and not suffix: date_merge = f'date_merge_{timeframe_inf}' informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns] + elif suffix: + date_merge = f'date_merge_{suffix}' + informative.columns = [f"{col}_{suffix}" for col in informative.columns] + + elif suffix and append_timeframe: + raise ValueError("You can not specify `append_timeframe` as True and a `suffix`.") + # Combine the 2 dataframes # all indicators on the informative sample MUST be calculated before this point if ffill: From 047ded1baa7c7e980b98c8289f689e2f900cf203 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Wed, 7 Sep 2022 17:47:27 +0200 Subject: [PATCH 204/592] Check for constant columns --- freqtrade/freqai/data_kitchen.py | 41 ++++++++++++++++++-------------- 1 file changed, 23 insertions(+), 18 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7670cfd45..0a2355c48 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -184,7 +184,7 @@ class FreqaiDataKitchen: def filter_features( self, - unfiltered_dataframe: DataFrame, + unfiltered_df: DataFrame, training_feature_list: List, label_list: List = list(), training_filter: bool = True, @@ -195,31 +195,36 @@ class FreqaiDataKitchen: 0s in the prediction dataset. However, prediction dataset do_predict will reflect any row that had a NaN and will shield user from that prediction. :params: - :unfiltered_dataframe: the full dataframe for the present training period + :unfiltered_df: the full dataframe for the present training period :training_feature_list: list, the training feature list constructed by self.build_feature_list() according to user specified parameters in the configuration file. :labels: the labels for the dataset :training_filter: boolean which lets the function know if it is training data or prediction data to be filtered. :returns: - :filtered_dataframe: dataframe cleaned of NaNs and only containing the user + :filtered_df: dataframe cleaned of NaNs and only containing the user requested feature set. :labels: labels cleaned of NaNs. """ - filtered_dataframe = unfiltered_dataframe.filter(training_feature_list, axis=1) - filtered_dataframe = filtered_dataframe.replace([np.inf, -np.inf], np.nan) + filtered_df = unfiltered_df.filter(training_feature_list, axis=1) + filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan) - drop_index = pd.isnull(filtered_dataframe).any(1) # get the rows that have NaNs, + const_cols = filtered_df[:, filtered_df.nunique(axis=0) == len(filtered_df.index)].columns + if const_cols: + filtered_df = filtered_df.filter(filtered_df.columns.difference(const_cols)) + logger.warning(f"Removed features {const_cols} with constant values.") + + drop_index = pd.isnull(filtered_df).any(1) # get the rows that have NaNs, drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement. if (training_filter): # we don't care about total row number (total no. datapoints) in training, we only care # about removing any row with NaNs # if labels has multiple columns (user wants to train multiple modelEs), we detect here - labels = unfiltered_dataframe.filter(label_list, axis=1) + labels = unfiltered_df.filter(label_list, axis=1) drop_index_labels = pd.isnull(labels).any(1) drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0) - dates = unfiltered_dataframe['date'] - filtered_dataframe = filtered_dataframe[ + dates = unfiltered_df['date'] + filtered_df = filtered_df[ (drop_index == 0) & (drop_index_labels == 0) ] # dropping values labels = labels[ @@ -229,13 +234,13 @@ class FreqaiDataKitchen: (drop_index == 0) & (drop_index_labels == 0) ] logger.info( - f"dropped {len(unfiltered_dataframe) - len(filtered_dataframe)} training points" - f" due to NaNs in populated dataset {len(unfiltered_dataframe)}." + f"dropped {len(unfiltered_df) - len(filtered_df)} training points" + f" due to NaNs in populated dataset {len(unfiltered_df)}." ) - if (1 - len(filtered_dataframe) / len(unfiltered_dataframe)) > 0.1 and self.live: - worst_indicator = str(unfiltered_dataframe.count().idxmin()) + if (1 - len(filtered_df) / len(unfiltered_df)) > 0.1 and self.live: + worst_indicator = str(unfiltered_df.count().idxmin()) logger.warning( - f" {(1 - len(filtered_dataframe)/len(unfiltered_dataframe)) * 100:.0f} percent " + f" {(1 - len(filtered_df)/len(unfiltered_df)) * 100:.0f} percent " " of training data dropped due to NaNs, model may perform inconsistent " f"with expectations. Verify {worst_indicator}" ) @@ -244,9 +249,9 @@ class FreqaiDataKitchen: else: # we are backtesting so we need to preserve row number to send back to strategy, # so now we use do_predict to avoid any prediction based on a NaN - drop_index = pd.isnull(filtered_dataframe).any(1) + drop_index = pd.isnull(filtered_df).any(1) self.data["filter_drop_index_prediction"] = drop_index - filtered_dataframe.fillna(0, inplace=True) + filtered_df.fillna(0, inplace=True) # replacing all NaNs with zeros to avoid issues in 'prediction', but any prediction # that was based on a single NaN is ultimately protected from buys with do_predict drop_index = ~drop_index @@ -255,11 +260,11 @@ class FreqaiDataKitchen: logger.info( "dropped %s of %s prediction data points due to NaNs.", len(self.do_predict) - self.do_predict.sum(), - len(filtered_dataframe), + len(filtered_df), ) labels = [] - return filtered_dataframe, labels + return filtered_df, labels def build_data_dictionary( self, From cdc72bf8cab4bf78b2da460690a3b71ab076bff4 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Wed, 7 Sep 2022 18:14:13 +0200 Subject: [PATCH 205/592] Correct indexing --- freqtrade/freqai/data_kitchen.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 0a2355c48..790b3c078 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -209,7 +209,7 @@ class FreqaiDataKitchen: filtered_df = unfiltered_df.filter(training_feature_list, axis=1) filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan) - const_cols = filtered_df[:, filtered_df.nunique(axis=0) == len(filtered_df.index)].columns + const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index) if const_cols: filtered_df = filtered_df.filter(filtered_df.columns.difference(const_cols)) logger.warning(f"Removed features {const_cols} with constant values.") @@ -1205,7 +1205,6 @@ class FreqaiDataKitchen: def save_backtesting_prediction( self, append_df: DataFrame ) -> None: - """ Save prediction dataframe from backtesting to h5 file format :param append_df: dataframe for backtesting period @@ -1219,7 +1218,6 @@ class FreqaiDataKitchen: def get_backtesting_prediction( self ) -> DataFrame: - """ Get prediction dataframe from h5 file format """ From 322f00e3e8c7c183e350e84e4c740e0d34130c68 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 18:19:25 +0200 Subject: [PATCH 206/592] Fix empty entry message if order doesn't fill immediately closes #7368 --- freqtrade/freqtradebot.py | 2 +- tests/test_freqtradebot.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index a2f39afd6..ec32cae0e 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -919,7 +919,7 @@ class FreqtradeBot(LoggingMixin): 'stake_amount': trade.stake_amount, 'stake_currency': self.config['stake_currency'], 'fiat_currency': self.config.get('fiat_display_currency', None), - 'amount': order.safe_amount_after_fee, + 'amount': order.safe_amount_after_fee if fill else order.amount, 'open_date': trade.open_date or datetime.utcnow(), 'current_rate': current_rate, 'sub_trade': sub_trade, diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index aff0504b3..30b0b75b6 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3655,6 +3655,7 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit( assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value assert rpc_mock.call_count == 3 assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.ENTRY + assert rpc_mock.call_args_list[0][0][0]['amount'] > 20 assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY_FILL assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.EXIT_FILL From ea7bdac9edc7b3f5c5e039e509b8d368f7045a3e Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 7 Sep 2022 18:45:16 +0200 Subject: [PATCH 207/592] ensure inlier metric can be combined with other cleaning methods --- freqtrade/freqai/freqai_interface.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 5ccc9d1b2..32e42e115 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -427,6 +427,11 @@ class IFreqaiModel(ABC): ft_params = self.freqai_info["feature_parameters"] + if ft_params.get('inlier_metric_window', 0): + dk.compute_inlier_metric(set_='train') + if self.freqai_info["data_split_parameters"]["test_size"] > 0: + dk.compute_inlier_metric(set_='test') + if ft_params.get( "principal_component_analysis", False ): @@ -446,11 +451,6 @@ class IFreqaiModel(ABC): dk.use_DBSCAN_to_remove_outliers(predict=False, eps=eps) self.dd.old_DBSCAN_eps[dk.pair] = dk.data['DBSCAN_eps'] - if ft_params.get('inlier_metric_window', 0): - dk.compute_inlier_metric(set_='train') - if self.freqai_info["data_split_parameters"]["test_size"] > 0: - dk.compute_inlier_metric(set_='test') - if self.freqai_info["feature_parameters"].get('noise_standard_deviation', 0): dk.add_noise_to_training_features() From 48cadbf933e829c8335a3ef593aa324b7d08a659 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 09:52:22 -0600 Subject: [PATCH 208/592] remove duplicate line, change window to timeperiod --- freqtrade/templates/FreqaiExampleStrategy.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index 0e822a028..b172ab805 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -92,12 +92,10 @@ class FreqaiExampleStrategy(IStrategy): t = int(t) informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) + informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, timeperiod=t) informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t) informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t) - informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - bollinger = qtpylib.bollinger_bands( qtpylib.typical_price(informative), window=t, stds=2.2 ) From 5d338e697c6df2d7d3d5109fb7ce29309f6dcdf0 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 09:59:46 -0600 Subject: [PATCH 209/592] change window to timeperiod in hybrid --- freqtrade/templates/FreqaiHybridExampleStrategy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/FreqaiHybridExampleStrategy.py b/freqtrade/templates/FreqaiHybridExampleStrategy.py index 5d1e149dd..286ff012f 100644 --- a/freqtrade/templates/FreqaiHybridExampleStrategy.py +++ b/freqtrade/templates/FreqaiHybridExampleStrategy.py @@ -135,7 +135,7 @@ class FreqaiExampleHybridStrategy(IStrategy): t = int(t) informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) + informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, timeperiod=t) informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t) informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t) informative[f"%-{coin}roc-period_{t}"] = ta.ROC(informative, timeperiod=t) From 4c9ac6b7c0959a7d596279a1388145f8a90bd8da Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 7 Sep 2022 18:58:55 +0200 Subject: [PATCH 210/592] add kwargs, reduce duplicated code --- freqtrade/freqai/freqai_interface.py | 15 ++++++++++++--- .../prediction_models/CatboostClassifier.py | 8 +++----- .../freqai/prediction_models/CatboostRegressor.py | 10 +++------- .../CatboostRegressorMultiTarget.py | 3 ++- .../prediction_models/LightGBMClassifier.py | 10 ++++------ .../freqai/prediction_models/LightGBMRegressor.py | 10 ++++------ .../LightGBMRegressorMultiTarget.py | 5 +++-- 7 files changed, 31 insertions(+), 30 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index b6f3d8ebc..101df88ec 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -661,11 +661,20 @@ class IFreqaiModel(ABC): self.train_time = 0 return + def get_init_model(self, pair: str) -> Any: + if pair not in self.dd.model_dictionary or not self.continual_learning: + init_model = None + else: + init_model = self.dd.model_dictionary[pair] + + return init_model + # Following methods which are overridden by user made prediction models. # See freqai/prediction_models/CatboostPredictionModel.py for an example. @abstractmethod - def train(self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen) -> Any: + def train(self, unfiltered_dataframe: DataFrame, pair: str, + dk: FreqaiDataKitchen, **kwargs) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datahandler for storing, saving, loading, and analyzing the data. @@ -675,7 +684,7 @@ class IFreqaiModel(ABC): """ @abstractmethod - def fit(self, data_dictionary: Dict[str, Any], dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict[str, Any], dk: FreqaiDataKitchen, **kwargs) -> Any: """ Most regressors use the same function names and arguments e.g. user can drop in LGBMRegressor in place of CatBoostRegressor and all data @@ -688,7 +697,7 @@ class IFreqaiModel(ABC): @abstractmethod def predict( - self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = True + self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = True, **kwargs ) -> Tuple[DataFrame, NDArray[np.int_]]: """ Filter the prediction features data and predict with it. diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 13395879a..cd7afd392 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -2,6 +2,7 @@ import logging from typing import Any, Dict from catboost import CatBoostClassifier, Pool + from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel @@ -16,7 +17,7 @@ class CatboostClassifier(BaseClassifierModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ User sets up the training and test data to fit their desired model here :params: @@ -36,10 +37,7 @@ class CatboostClassifier(BaseClassifierModel): **self.model_training_parameters, ) - if dk.pair not in self.dd.model_dictionary or not self.continual_learning: - init_model = None - else: - init_model = self.dd.model_dictionary[dk.pair] + init_model = self.get_init_model(dk.pair) cbr.fit(train_data, init_model=init_model) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index 0b8bc162b..1ce31b628 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -1,10 +1,9 @@ -import gc import logging from typing import Any, Dict from catboost import CatBoostRegressor, Pool -from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel @@ -18,7 +17,7 @@ class CatboostRegressor(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold @@ -39,10 +38,7 @@ class CatboostRegressor(BaseRegressionModel): weight=data_dictionary["test_weights"], ) - if dk.pair not in self.dd.model_dictionary or not self.continual_learning: - init_model = None - else: - init_model = self.dd.model_dictionary[dk.pair] + init_model = self.get_init_model(dk.pair) model = CatBoostRegressor( allow_writing_files=False, diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index 9ed61488c..bc52bfdd9 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -3,6 +3,7 @@ from typing import Any, Dict from catboost import CatBoostRegressor # , Pool from sklearn.multioutput import MultiOutputRegressor + from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel @@ -17,7 +18,7 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold diff --git a/freqtrade/freqai/prediction_models/LightGBMClassifier.py b/freqtrade/freqai/prediction_models/LightGBMClassifier.py index 0023a9f69..69867eae3 100644 --- a/freqtrade/freqai/prediction_models/LightGBMClassifier.py +++ b/freqtrade/freqai/prediction_models/LightGBMClassifier.py @@ -3,8 +3,9 @@ from typing import Any, Dict from lightgbm import LGBMClassifier -from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel + logger = logging.getLogger(__name__) @@ -16,7 +17,7 @@ class LightGBMClassifier(BaseClassifierModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ User sets up the training and test data to fit their desired model here :params: @@ -35,10 +36,7 @@ class LightGBMClassifier(BaseClassifierModel): y = data_dictionary["train_labels"].to_numpy()[:, 0] train_weights = data_dictionary["train_weights"] - if dk.pair not in self.dd.model_dictionary or not self.continual_learning: - init_model = None - else: - init_model = self.dd.model_dictionary[dk.pair] + init_model = self.get_init_model(dk.pair) model = LGBMClassifier(**self.model_training_parameters) diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressor.py b/freqtrade/freqai/prediction_models/LightGBMRegressor.py index 81f0e6d22..99e9ff887 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressor.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressor.py @@ -3,8 +3,9 @@ from typing import Any, Dict from lightgbm import LGBMRegressor -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel + logger = logging.getLogger(__name__) @@ -16,7 +17,7 @@ class LightGBMRegressor(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ Most regressors use the same function names and arguments e.g. user can drop in LGBMRegressor in place of CatBoostRegressor and all data @@ -35,10 +36,7 @@ class LightGBMRegressor(BaseRegressionModel): y = data_dictionary["train_labels"] train_weights = data_dictionary["train_weights"] - if dk.pair not in self.dd.model_dictionary or not self.continual_learning: - init_model = None - else: - init_model = self.dd.model_dictionary[dk.pair] + init_model = self.get_init_model(dk.pair) model = LGBMRegressor(**self.model_training_parameters) diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py index 2b25493e0..c34680dbe 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py @@ -4,8 +4,9 @@ from typing import Any, Dict from lightgbm import LGBMRegressor from sklearn.multioutput import MultiOutputRegressor -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel + logger = logging.getLogger(__name__) @@ -17,7 +18,7 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel): has its own DataHandler where data is held, saved, loaded, and managed. """ - def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any: + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold From e51d352777d9e06518da0f28c974dceabf4afd0c Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 7 Sep 2022 19:11:54 +0200 Subject: [PATCH 211/592] ensure pca is handling same DF as inlier --- freqtrade/freqai/freqai_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 32e42e115..c5ac17a3a 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -467,7 +467,7 @@ class IFreqaiModel(ABC): if ft_params.get( "principal_component_analysis", False ): - dk.pca_transform(dataframe) + dk.pca_transform(self.dk.data_dictionary['prediction_features']) if ft_params.get("use_SVM_to_remove_outliers", False): dk.use_SVM_to_remove_outliers(predict=True) From a9fd12b816d5a36a8233f508dec92d3f4bb4ab40 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 18:28:04 +0200 Subject: [PATCH 212/592] Allow more dynamic timeframes by disabling "choice" part of #7366 --- freqtrade/commands/cli_options.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index 3d094da36..4240a8014 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -455,8 +455,6 @@ AVAILABLE_CLI_OPTIONS = { '-t', '--timeframes', help='Specify which tickers to download. Space-separated list. ' 'Default: `1m 5m`.', - choices=['1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h', - '6h', '8h', '12h', '1d', '3d', '1w', '2w', '1M', '1y'], default=['1m', '5m'], nargs='+', ), From f8e7ed5d7d8f05cd470517a630431725cff48280 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 7 Sep 2022 18:28:14 +0200 Subject: [PATCH 213/592] Reduce shutdown verbosity of exchange --- freqtrade/exchange/exchange.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index af072d555..569dcad9b 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -205,7 +205,7 @@ class Exchange: logger.debug("Exchange object destroyed, closing async loop") if (self._api_async and inspect.iscoroutinefunction(self._api_async.close) and self._api_async.session): - logger.info("Closing async ccxt session.") + logger.debug("Closing async ccxt session.") self.loop.run_until_complete(self._api_async.close()) def validate_config(self, config): From bf3ee51167f183739b0a71677126b9c18d733560 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 7 Sep 2022 14:42:05 -0300 Subject: [PATCH 214/592] validate freqai hyperopt with freqai enabled param --- freqtrade/configuration/config_validation.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py index b37d44d0f..8d9112bef 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -325,9 +325,9 @@ def _validate_pricing_rules(conf: Dict[str, Any]) -> None: def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None: - freqaimodel = conf.get('freqaimodel') + freqai_enabled = conf.get('freqai', {}).get('enabled', False) analyze_per_epoch = conf.get('analyze_per_epoch', False) - if analyze_per_epoch and freqaimodel is not None: + if analyze_per_epoch and freqai_enabled: raise OperationalException( 'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.') From 5934495dda06c4c62950c8eebe77fb431d394eb9 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 15:08:01 -0600 Subject: [PATCH 215/592] add websocket request/message schemas --- freqtrade/data/dataprovider.py | 10 +- freqtrade/rpc/api_server/api_ws.py | 40 ++++++-- freqtrade/rpc/api_server/ws/schema.py | 78 +++++++++++++++ freqtrade/rpc/external_message_consumer.py | 111 +++++++++------------ freqtrade/rpc/rpc.py | 8 +- 5 files changed, 165 insertions(+), 82 deletions(-) create mode 100644 freqtrade/rpc/api_server/ws/schema.py diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 44296ab40..4b5494e97 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -121,7 +121,8 @@ class DataProvider: 'type': RPCMessageType.ANALYZED_DF, 'data': { 'key': pair_key, - 'value': (dataframe, datetime.now(timezone.utc)) + 'df': dataframe, + 'la': datetime.now(timezone.utc) } } ) @@ -130,7 +131,7 @@ class DataProvider: self, pair: str, dataframe: DataFrame, - last_analyzed: Optional[str] = None, + last_analyzed: Optional[datetime] = None, timeframe: Optional[str] = None, candle_type: Optional[CandleType] = None, producer_name: str = "default" @@ -150,10 +151,7 @@ class DataProvider: if producer_name not in self.__producer_pairs_df: self.__producer_pairs_df[producer_name] = {} - if not last_analyzed: - _last_analyzed = datetime.now(timezone.utc) - else: - _last_analyzed = datetime.fromisoformat(last_analyzed) + _last_analyzed = datetime.now(timezone.utc) if not last_analyzed else last_analyzed self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed) logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.") diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index aaa526401..64c1cebb5 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -8,6 +8,8 @@ from starlette.websockets import WebSocketState from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel +from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, + WSRequestSchema, WSWhitelistMessage) from freqtrade.rpc.rpc import RPC @@ -18,6 +20,9 @@ router = APIRouter() async def is_websocket_alive(ws: WebSocket) -> bool: + """ + Check if a FastAPI Websocket is still open + """ if ( ws.application_state == WebSocketState.CONNECTED and ws.client_state == WebSocketState.CONNECTED @@ -31,7 +36,17 @@ async def _process_consumer_request( channel: WebSocketChannel, rpc: RPC ): - type, data = request.get('type'), request.get('data') + """ + Validate and handle a request from a websocket consumer + """ + # Validate the request, makes sure it matches the schema + try: + websocket_request = WSRequestSchema.parse_obj(request) + except ValidationError as e: + logger.error(f"Invalid request from {channel}: {e}") + return + + type, data = websocket_request.type, websocket_request.data logger.debug(f"Request of type {type} from {channel}") @@ -41,35 +56,35 @@ async def _process_consumer_request( if not data: return - if not isinstance(data, list): - logger.error(f"Improper subscribe request from channel: {channel} - {request}") - return - # If all topics passed are a valid RPCMessageType, set subscriptions on channel if all([any(x.value == topic for x in RPCMessageType) for topic in data]): - - logger.debug(f"{channel} subscribed to topics: {data}") channel.set_subscriptions(data) + # We don't send a response for subscriptions + elif type == RPCRequestType.WHITELIST: - # They requested the whitelist + # Get whitelist whitelist = rpc._ws_request_whitelist() - await channel.send({"type": RPCMessageType.WHITELIST, "data": whitelist}) + # Format response + response = WSWhitelistMessage(data=whitelist) + # Send it back + await channel.send(response.dict(exclude_none=True)) elif type == RPCRequestType.ANALYZED_DF: limit = None if data: # Limit the amount of candles per dataframe to 'limit' or 1500 - limit = max(data.get('limit', 500), 1500) + limit = max(data.get('limit', 1500), 1500) # They requested the full historical analyzed dataframes analyzed_df = rpc._ws_request_analyzed_df(limit) # For every dataframe, send as a separate message for _, message in analyzed_df.items(): - await channel.send({"type": RPCMessageType.ANALYZED_DF, "data": message}) + response = WSAnalyzedDFMessage(data=message) + await channel.send(response.dict(exclude_none=True)) @router.websocket("/message/ws") @@ -78,6 +93,9 @@ async def message_endpoint( rpc: RPC = Depends(get_rpc), channel_manager=Depends(get_channel_manager), ): + """ + Message WebSocket endpoint, facilitates sending RPC messages + """ try: if is_websocket_alive(ws): # TODO: diff --git a/freqtrade/rpc/api_server/ws/schema.py b/freqtrade/rpc/api_server/ws/schema.py new file mode 100644 index 000000000..3221911de --- /dev/null +++ b/freqtrade/rpc/api_server/ws/schema.py @@ -0,0 +1,78 @@ +from datetime import datetime +from typing import Any, Dict, List, Optional + +from pandas import DataFrame +from pydantic import BaseModel, ValidationError + +from freqtrade.constants import PairWithTimeframe +from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType + + +__all__ = ('WSRequestSchema', 'WSMessageSchema', 'ValidationError') + + +class BaseArbitraryModel(BaseModel): + class Config: + arbitrary_types_allowed = True + + +class WSRequestSchema(BaseArbitraryModel): + type: RPCRequestType + data: Optional[Any] = None + + +class WSMessageSchema(BaseArbitraryModel): + type: RPCMessageType + data: Optional[Any] = None + + class Config: + extra = 'allow' + + +# ------------------------------ REQUEST SCHEMAS ---------------------------- + + +class WSSubscribeRequest(WSRequestSchema): + type: RPCRequestType = RPCRequestType.SUBSCRIBE + data: List[RPCMessageType] + + +class WSWhitelistRequest(WSRequestSchema): + type: RPCRequestType = RPCRequestType.WHITELIST + data: None = None + + +class WSAnalyzedDFRequest(WSRequestSchema): + type: RPCRequestType = RPCRequestType.ANALYZED_DF + data: Dict[str, Any] = {"limit": 1500} + + +# ------------------------------ MESSAGE SCHEMAS ---------------------------- + +class WSWhitelistMessage(WSMessageSchema): + type: RPCMessageType = RPCMessageType.WHITELIST + data: List[str] + + +class WSAnalyzedDFMessage(WSMessageSchema): + class AnalyzedDFData(BaseArbitraryModel): + key: PairWithTimeframe + df: DataFrame + la: datetime + + type: RPCMessageType = RPCMessageType.ANALYZED_DF + data: AnalyzedDFData + +# -------------------------------------------------------------------------- + + +if __name__ == "__main__": + message = WSAnalyzedDFMessage( + data={ + "key": ("1", "5m", "spot"), + "df": DataFrame(), + "la": datetime.now() + } + ) + + print(message) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index c1ad0512e..d1e970826 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -8,14 +8,18 @@ import asyncio import logging import socket from threading import Thread -from typing import TYPE_CHECKING, Any, Dict, List, Optional +from typing import TYPE_CHECKING, Any, Dict, List import websockets from freqtrade.data.dataprovider import DataProvider -from freqtrade.enums import RPCMessageType, RPCRequestType +from freqtrade.enums import RPCMessageType from freqtrade.misc import remove_entry_exit_signals from freqtrade.rpc.api_server.ws.channel import WebSocketChannel +from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, + WSAnalyzedDFRequest, WSMessageSchema, + WSRequestSchema, WSSubscribeRequest, + WSWhitelistMessage, WSWhitelistRequest) if TYPE_CHECKING: @@ -67,15 +71,10 @@ class ExternalMessageConsumer: self.topics = [RPCMessageType.WHITELIST, RPCMessageType.ANALYZED_DF] # Allow setting data for each initial request - self._initial_requests: List[Dict[str, Any]] = [ - { - "type": RPCRequestType.WHITELIST, - "data": None - }, - { - "type": RPCRequestType.ANALYZED_DF, - "data": {"limit": self.initial_candle_limit} - } + self._initial_requests: List[WSRequestSchema] = [ + WSSubscribeRequest(data=self.topics), + WSWhitelistRequest(), + WSAnalyzedDFRequest() ] # Specify which function to use for which RPCMessageType @@ -174,16 +173,10 @@ class ExternalMessageConsumer: logger.info(f"Producer connection success - {channel}") - # Tell the producer we only want these topics - # Should always be the first thing we send - await channel.send( - self.compose_consumer_request(RPCRequestType.SUBSCRIBE, self.topics) - ) - # Now request the initial data from this Producer for request in self._initial_requests: await channel.send( - self.compose_consumer_request(request['type'], request['data']) + request.dict(exclude_none=True) ) # Now receive data, if none is within the time limit, ping @@ -253,74 +246,66 @@ class ExternalMessageConsumer: break - def compose_consumer_request( - self, - type_: RPCRequestType, - data: Optional[Any] = None - ) -> Dict[str, Any]: - """ - Create a request for sending to a producer - - :param type_: The RPCRequestType - :param data: The data to send - :returns: Dict[str, Any] - """ - return {'type': type_, 'data': data} - def handle_producer_message(self, producer: Dict[str, Any], message: Dict[str, Any]): """ Handles external messages from a Producer """ producer_name = producer.get('name', 'default') - # Should we have a default message type? - message_type = message.get('type', RPCMessageType.STATUS) - message_data = message.get('data') + + try: + producer_message = WSMessageSchema.parse_obj(message) + except ValidationError as e: + logger.error(f"Invalid message from {producer_name}: {e}") + return # We shouldn't get empty messages - if message_data is None: + if producer_message.data is None: return - logger.info(f"Received message of type {message_type} from `{producer_name}`") + logger.info(f"Received message of type {producer_message.type} from `{producer_name}`") - message_handler = self._message_handlers.get(message_type) + message_handler = self._message_handlers.get(producer_message.type) if not message_handler: - logger.info(f"Received unhandled message: {message_data}, ignoring...") + logger.info(f"Received unhandled message: {producer_message.data}, ignoring...") return - message_handler(producer_name, message_data) + message_handler(producer_name, producer_message) - def _consume_whitelist_message(self, producer_name: str, message_data: Any): - # We expect List[str] - if not isinstance(message_data, list): + def _consume_whitelist_message(self, producer_name: str, message: Any): + try: + # Validate the message + message = WSWhitelistMessage.parse_obj(message) + except ValidationError: return # Add the pairlist data to the DataProvider - self._dp._set_producer_pairs(message_data, producer_name=producer_name) + self._dp._set_producer_pairs(message.data, producer_name=producer_name) - logger.debug(f"Consumed message from {producer_name} of type RPCMessageType.WHITELIST") + logger.debug(f"Consumed message from {producer_name} of type `RPCMessageType.WHITELIST`") - def _consume_analyzed_df_message(self, producer_name: str, message_data: Any): - # We expect a Dict[str, Any] - if not isinstance(message_data, dict): + def _consume_analyzed_df_message(self, producer_name: str, message: Any): + try: + message = WSAnalyzedDFMessage.parse_obj(message) + except ValidationError: return - key, value = message_data.get('key'), message_data.get('value') + key = message.data.key + df = message.data.df + la = message.data.la - if key and value: - pair, timeframe, candle_type = key - dataframe, last_analyzed = value + pair, timeframe, candle_type = key - # If set, remove the Entry and Exit signals from the Producer - if self._emc_config.get('remove_entry_exit_signals', False): - dataframe = remove_entry_exit_signals(dataframe) + # If set, remove the Entry and Exit signals from the Producer + if self._emc_config.get('remove_entry_exit_signals', False): + df = remove_entry_exit_signals(df) - # Add the dataframe to the dataprovider - self._dp._add_external_df(pair, dataframe, - last_analyzed=last_analyzed, - timeframe=timeframe, - candle_type=candle_type, - producer_name=producer_name) + # Add the dataframe to the dataprovider + self._dp._add_external_df(pair, df, + last_analyzed=la, + timeframe=timeframe, + candle_type=candle_type, + producer_name=producer_name) - logger.debug( - f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") + logger.debug( + f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index df90b982e..9821bc001 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1068,8 +1068,12 @@ class RPC: for pair in pairlist: dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) - _data[pair] = {"key": (pair, timeframe, candle_type), - "value": (dataframe, last_analyzed)} + + _data[pair] = { + "key": (pair, timeframe, candle_type), + "df": dataframe, + "la": last_analyzed + } return _data From 1ef1fc269e2b682a2d8053340e8349436a132269 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 15:26:38 -0600 Subject: [PATCH 216/592] docstring and tests --- freqtrade/strategy/strategy_helper.py | 4 +++- tests/strategy/test_strategy_helpers.py | 23 +++++++++++++++++++++++ 2 files changed, 26 insertions(+), 1 deletion(-) diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py index 55afbf7a8..53f625001 100644 --- a/freqtrade/strategy/strategy_helper.py +++ b/freqtrade/strategy/strategy_helper.py @@ -31,6 +31,8 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, :param ffill: Forwardfill missing values - optional but usually required :param append_timeframe: Rename columns by appending timeframe. :param date_column: A custom date column name. + :param suffix: A string suffix to add at the end of the informative columns. If specified, + append_timeframe must be false. :return: Merged dataframe :raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe """ @@ -57,7 +59,7 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, date_merge = f'date_merge_{timeframe_inf}' informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns] - elif suffix: + elif suffix and not append_timeframe: date_merge = f'date_merge_{suffix}' informative.columns = [f"{col}_{suffix}" for col in informative.columns] diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py index a7c2da26a..8cb990e87 100644 --- a/tests/strategy/test_strategy_helpers.py +++ b/tests/strategy/test_strategy_helpers.py @@ -117,6 +117,29 @@ def test_merge_informative_pair_lower(): merge_informative_pair(data, informative, '1h', '15m', ffill=True) +def test_merge_informative_pair_suffix(): + data = generate_test_data('15m', 20) + informative = generate_test_data('1h', 20) + + result = merge_informative_pair(data, informative, '15m', '1h', + append_timeframe=False, suffix="suf") + + assert 'date' in result.columns + assert result['date'].equals(data['date']) + assert 'date_suf' in result.columns + + assert 'open_suf' in result.columns + assert 'open_1h' not in result.columns + + +def test_merge_informative_pair_suffix_append_timeframe(): + data = generate_test_data('15m', 20) + informative = generate_test_data('1h', 20) + + with pytest.raises(ValueError, match=r"You can not specify `append_timeframe` .*"): + merge_informative_pair(data, informative, '15m', '1h', suffix="suf") + + def test_stoploss_from_open(): open_price_ranges = [ [0.01, 1.00, 30], From f4f2884a66c97c05e6871b1ecf2f12b1bc0ec460 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 7 Sep 2022 18:52:58 -0300 Subject: [PATCH 217/592] Fix freqai backtesting time range issue --- freqtrade/freqai/data_kitchen.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7670cfd45..01b2f1f3b 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -461,6 +461,20 @@ class FreqaiDataKitchen: return df + def remove_training_from_backtesting( + self + ) -> DataFrame: + """ + Function which takes the backtesting time range and + remove training data from dataframe + """ + tr = self.config["timerange"] + backtesting_timerange = TimeRange.parse_timerange(tr) + start = datetime.fromtimestamp(backtesting_timerange.startts, tz=timezone.utc) + df = self.return_dataframe + df = df.loc[df["date"] >= start, :] + return df + def principal_component_analysis(self) -> None: """ Performs Principal Component Analysis on the data for dimensionality reduction @@ -954,6 +968,7 @@ class FreqaiDataKitchen: to_keep = [col for col in dataframe.columns if not col.startswith("&")] self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1) + self.return_dataframe = self.remove_training_from_backtesting() self.full_df = DataFrame() return From a50923f7963a58bddd76284cf470979eb7db0695 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Wed, 7 Sep 2022 17:14:26 -0600 Subject: [PATCH 218/592] add producers attribute to dataprovider --- freqtrade/data/dataprovider.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 4b5494e97..8ca638046 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -54,10 +54,8 @@ class DataProvider: self.__msg_cache = PeriodicCache( maxsize=1000, ttl=timeframe_to_seconds(self._default_timeframe)) - self._num_sources = len( - self._config.get('external_message_consumer', {}).get('producers', []) - ) - self.external_data_enabled = self._num_sources > 0 + self.producers = self._config.get('external_message_consumer', {}).get('producers', []) + self.external_data_enabled = len(self.producers) > 0 def _set_dataframe_max_index(self, limit_index: int): """ From f3417a869069bdb01da844017b00ebf30ee6f208 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 06:59:14 +0200 Subject: [PATCH 219/592] Revert condition sequence to simplify conditions --- freqtrade/strategy/strategy_helper.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py index 53f625001..aa753a829 100644 --- a/freqtrade/strategy/strategy_helper.py +++ b/freqtrade/strategy/strategy_helper.py @@ -55,17 +55,16 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, # Rename columns to be unique date_merge = 'date_merge' - if append_timeframe and not suffix: + if suffix and append_timeframe: + raise ValueError("You can not specify `append_timeframe` as True and a `suffix`.") + elif append_timeframe: date_merge = f'date_merge_{timeframe_inf}' informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns] - elif suffix and not append_timeframe: + elif suffix: date_merge = f'date_merge_{suffix}' informative.columns = [f"{col}_{suffix}" for col in informative.columns] - elif suffix and append_timeframe: - raise ValueError("You can not specify `append_timeframe` as True and a `suffix`.") - # Combine the 2 dataframes # all indicators on the informative sample MUST be calculated before this point if ffill: From 045c3f0f3ae7f27fc8702ec12680060d9c896d09 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:01:37 +0200 Subject: [PATCH 220/592] Reduce diff by avoiding unnecessary changes --- freqtrade/misc.py | 2 +- freqtrade/strategy/interface.py | 34 ++++++++------------------------- tests/rpc/test_rpc_apiserver.py | 1 - 3 files changed, 9 insertions(+), 28 deletions(-) diff --git a/freqtrade/misc.py b/freqtrade/misc.py index 6a93b6f26..b2aca5fd6 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -14,7 +14,7 @@ import pandas import rapidjson from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN -from freqtrade.enums.signaltype import SignalTagType, SignalType +from freqtrade.enums import SignalTagType, SignalType logger = logging.getLogger(__name__) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 93a582e80..0a9a155ea 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -698,11 +698,7 @@ class IStrategy(ABC, HyperStrategyMixin): lock_time = timeframe_to_next_date(self.timeframe, candle_date) return PairLocks.is_pair_locked(pair, lock_time, side=side) - def analyze_ticker( - self, - dataframe: DataFrame, - metadata: dict - ) -> DataFrame: + def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame add several TA indicators and entry order signal to it @@ -716,11 +712,7 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = self.advise_exit(dataframe, metadata) return dataframe - def _analyze_ticker_internal( - self, - dataframe: DataFrame, - metadata: dict - ) -> DataFrame: + def _analyze_ticker_internal(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Parses the given candle (OHLCV) data and returns a populated DataFrame add several TA indicators and buy signal to it @@ -753,20 +745,16 @@ class IStrategy(ABC, HyperStrategyMixin): return dataframe - def analyze_pair( - self, - pair: str - ) -> None: + def analyze_pair(self, pair: str) -> None: """ Fetch data for this pair from dataprovider and analyze. Stores the dataframe into the dataprovider. The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`. :param pair: Pair to analyze. """ - candle_type = self.config.get('candle_type_def', CandleType.SPOT) - - dataframe = self.dp.ohlcv(pair, self.timeframe, candle_type) - + dataframe = self.dp.ohlcv( + pair, self.timeframe, candle_type=self.config.get('candle_type_def', CandleType.SPOT) + ) if not isinstance(dataframe, DataFrame) or dataframe.empty: logger.warning('Empty candle (OHLCV) data for pair %s', pair) return @@ -787,10 +775,7 @@ class IStrategy(ABC, HyperStrategyMixin): logger.warning('Empty dataframe for pair %s', pair) return - def analyze( - self, - pairs: List[str] - ) -> None: + def analyze(self, pairs: List[str]) -> None: """ Analyze all pairs using analyze_pair(). :param pairs: List of pairs to analyze @@ -798,7 +783,7 @@ class IStrategy(ABC, HyperStrategyMixin): for pair in pairs: self.analyze_pair(pair) - @ staticmethod + @staticmethod def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]: """ keep some data for dataframes """ return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1] @@ -1219,9 +1204,6 @@ class IStrategy(ABC, HyperStrategyMixin): dataframe = _create_and_merge_informative_pair( self, dataframe, metadata, inf_data, populate_fn) - # If in follower mode, get analyzed dataframe from leader df's in dp - # otherise run populate_indicators - return self.populate_indicators(dataframe, metadata) def advise_entry(self, dataframe: DataFrame, metadata: dict) -> DataFrame: diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 146303701..5dfa77d8b 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -406,7 +406,6 @@ def test_api_cleanup(default_conf, mocker, caplog): apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) - apiserver.start_api() apiserver.cleanup() assert apiserver._server.cleanup.call_count == 1 From 4e15611b055a7afb5dfc00fd687967fa52bca1bf Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:18:38 +0200 Subject: [PATCH 221/592] Don't crash in case of funding fee fetch error --- freqtrade/exchange/exchange.py | 11 +++++-- freqtrade/freqtradebot.py | 57 ++++++++++++++++++++-------------- 2 files changed, 42 insertions(+), 26 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 569dcad9b..be5af91db 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2509,8 +2509,13 @@ class Exchange: cache=False, drop_incomplete=False, ) - funding_rates = candle_histories[funding_comb] - mark_rates = candle_histories[mark_comb] + try: + # we can't assume we always get histories - for example during exchange downtimes + funding_rates = candle_histories[funding_comb] + mark_rates = candle_histories[mark_comb] + except KeyError: + raise ExchangeError("Could not find funding rates") from None + funding_mark_rates = self.combine_funding_and_mark( funding_rates=funding_rates, mark_rates=mark_rates) @@ -2590,6 +2595,8 @@ class Exchange: :param is_short: trade direction :param amount: Trade amount :param open_date: Open date of the trade + :return: funding fee since open_date + :raies: ExchangeError if something goes wrong. """ if self.trading_mode == TradingMode.FUTURES: if self._config['dry_run']: diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index ec32cae0e..61c323ed3 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -281,14 +281,17 @@ class FreqtradeBot(LoggingMixin): def update_funding_fees(self): if self.trading_mode == TradingMode.FUTURES: trades = Trade.get_open_trades() - for trade in trades: - funding_fees = self.exchange.get_funding_fees( - pair=trade.pair, - amount=trade.amount, - is_short=trade.is_short, - open_date=trade.date_last_filled_utc - ) - trade.funding_fees = funding_fees + try: + for trade in trades: + funding_fees = self.exchange.get_funding_fees( + pair=trade.pair, + amount=trade.amount, + is_short=trade.is_short, + open_date=trade.date_last_filled_utc + ) + trade.funding_fees = funding_fees + except ExchangeError: + logger.warning("Could not update funding fees for open trades.") else: return 0.0 @@ -671,14 +674,12 @@ class FreqtradeBot(LoggingMixin): if not stake_amount: return False - if pos_adjust: - logger.info(f"Position adjust: about to create a new order for {pair} with stake: " - f"{stake_amount} for {trade}") - else: - logger.info( - f"{name} signal found: about create a new trade for {pair} with stake_amount: " - f"{stake_amount} ...") - + msg = (f"Position adjust: about to create a new order for {pair} with stake: " + f"{stake_amount} for {trade}" if pos_adjust + else + f"{name} signal found: about create a new trade for {pair} with stake_amount: " + f"{stake_amount} ...") + logger.info(msg) amount = (stake_amount / enter_limit_requested) * leverage order_type = ordertype or self.strategy.order_types['entry'] @@ -741,8 +742,12 @@ class FreqtradeBot(LoggingMixin): # This is a new trade if trade is None: - funding_fees = self.exchange.get_funding_fees( - pair=pair, amount=amount, is_short=is_short, open_date=open_date) + try: + funding_fees = self.exchange.get_funding_fees( + pair=pair, amount=amount, is_short=is_short, open_date=open_date) + except ExchangeError: + logger.warning("Could not update funding fee.") + trade = Trade( pair=pair, base_currency=base_currency, @@ -1493,12 +1498,16 @@ class FreqtradeBot(LoggingMixin): :param exit_check: CheckTuple with signal and reason :return: True if it succeeds False """ - trade.funding_fees = self.exchange.get_funding_fees( - pair=trade.pair, - amount=trade.amount, - is_short=trade.is_short, - open_date=trade.date_last_filled_utc, - ) + try: + trade.funding_fees = self.exchange.get_funding_fees( + pair=trade.pair, + amount=trade.amount, + is_short=trade.is_short, + open_date=trade.date_last_filled_utc, + ) + except ExchangeError: + logger.warning("Could not update funding fee.") + exit_type = 'exit' exit_reason = exit_tag or exit_check.exit_reason if exit_check.exit_type in ( From 39b6cadd14e8253541c2836daed435059d20670d Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:24:57 +0200 Subject: [PATCH 222/592] Test keyerror case for funding_Fee calculation --- freqtrade/exchange/exchange.py | 2 +- tests/exchange/test_exchange.py | 18 +++++++++++++----- 2 files changed, 14 insertions(+), 6 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index be5af91db..33a56c530 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2514,7 +2514,7 @@ class Exchange: funding_rates = candle_histories[funding_comb] mark_rates = candle_histories[mark_comb] except KeyError: - raise ExchangeError("Could not find funding rates") from None + raise ExchangeError("Could not find funding rates.") from None funding_mark_rates = self.combine_funding_and_mark( funding_rates=funding_rates, mark_rates=mark_rates) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 3b903f8ee..71690ecdf 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -11,8 +11,9 @@ import pytest from pandas import DataFrame from freqtrade.enums import CandleType, MarginMode, TradingMode -from freqtrade.exceptions import (DDosProtection, DependencyException, InvalidOrderException, - OperationalException, PricingError, TemporaryError) +from freqtrade.exceptions import (DDosProtection, DependencyException, ExchangeError, + InvalidOrderException, OperationalException, PricingError, + TemporaryError) from freqtrade.exchange import (Binance, Bittrex, Exchange, Kraken, amount_to_precision, date_minus_candles, market_is_active, price_to_precision, timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date, @@ -4179,17 +4180,24 @@ def test__fetch_and_calculate_funding_fees( type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True}) type(api_mock).has = PropertyMock(return_value={'fetchFundingRateHistory': True}) - exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange) + ex = get_patched_exchange(mocker, default_conf, api_mock, id=exchange) mocker.patch('freqtrade.exchange.Exchange.timeframes', PropertyMock( return_value=['1h', '4h', '8h'])) - funding_fees = exchange._fetch_and_calculate_funding_fees( + funding_fees = ex._fetch_and_calculate_funding_fees( pair='ADA/USDT', amount=amount, is_short=True, open_date=d1, close_date=d2) assert pytest.approx(funding_fees) == expected_fees # Fees for Longs are inverted - funding_fees = exchange._fetch_and_calculate_funding_fees( + funding_fees = ex._fetch_and_calculate_funding_fees( pair='ADA/USDT', amount=amount, is_short=False, open_date=d1, close_date=d2) assert pytest.approx(funding_fees) == -expected_fees + # Return empty "refresh_latest" + mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", return_value={}) + ex = get_patched_exchange(mocker, default_conf, api_mock, id=exchange) + with pytest.raises(ExchangeError, match="Could not find funding rates."): + ex._fetch_and_calculate_funding_fees( + pair='ADA/USDT', amount=amount, is_short=False, open_date=d1, close_date=d2) + @pytest.mark.parametrize('exchange,expected_fees', [ ('binance', -0.0009140999999999999), From 791f61c0899647f3c04ac072305e73187e266268 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:13:15 +0000 Subject: [PATCH 223/592] Add test case for funding fee update failure --- freqtrade/freqtradebot.py | 2 -- tests/test_freqtradebot.py | 10 ++++++++++ 2 files changed, 10 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 61c323ed3..269c562d7 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -292,8 +292,6 @@ class FreqtradeBot(LoggingMixin): trade.funding_fees = funding_fees except ExchangeError: logger.warning("Could not update funding fees for open trades.") - else: - return 0.0 def startup_backpopulate_precision(self): diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 30b0b75b6..5f943504c 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -5430,6 +5430,16 @@ def test_update_funding_fees( )) +def test_update_funding_fees_error(mocker, default_conf, caplog): + mocker.patch('freqtrade.exchange.Exchange.get_funding_fees', side_effect=ExchangeError()) + default_conf['trading_mode'] = 'futures' + default_conf['margin_mode'] = 'isolated' + freqtrade = get_patched_freqtradebot(mocker, default_conf) + freqtrade.update_funding_fees() + + log_has("Could not update funding fees for open trades.", caplog) + + def test_position_adjust(mocker, default_conf_usdt, fee) -> None: patch_RPCManager(mocker) patch_exchange(mocker) From 9ef0ffe277e40159c207bb19782504d4bff492ff Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:19:17 +0000 Subject: [PATCH 224/592] Update tests for funding-Fee exceptions --- freqtrade/freqtradebot.py | 3 ++- tests/test_freqtradebot.py | 8 ++++++-- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 269c562d7..6c001a8d6 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -740,11 +740,12 @@ class FreqtradeBot(LoggingMixin): # This is a new trade if trade is None: + funding_fees = 0.0 try: funding_fees = self.exchange.get_funding_fees( pair=pair, amount=amount, is_short=is_short, open_date=open_date) except ExchangeError: - logger.warning("Could not update funding fee.") + logger.warning("Could not find funding fee.") trade = Trade( pair=pair, diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 5f943504c..565797d81 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -506,7 +506,7 @@ def test_create_trades_multiple_trades( def test_create_trades_preopen(default_conf_usdt, ticker_usdt, fee, mocker, - limit_buy_order_usdt_open) -> None: + limit_buy_order_usdt_open, caplog) -> None: patch_RPCManager(mocker) patch_exchange(mocker) default_conf_usdt['max_open_trades'] = 4 @@ -515,6 +515,7 @@ def test_create_trades_preopen(default_conf_usdt, ticker_usdt, fee, mocker, fetch_ticker=ticker_usdt, create_order=MagicMock(return_value=limit_buy_order_usdt_open), get_fee=fee, + get_funding_fees=MagicMock(side_effect=ExchangeError()), ) freqtrade = FreqtradeBot(default_conf_usdt) patch_get_signal(freqtrade) @@ -522,6 +523,7 @@ def test_create_trades_preopen(default_conf_usdt, ticker_usdt, fee, mocker, # Create 2 existing trades freqtrade.execute_entry('ETH/USDT', default_conf_usdt['stake_amount']) freqtrade.execute_entry('NEO/BTC', default_conf_usdt['stake_amount']) + assert log_has("Could not find funding fee.", caplog) assert len(Trade.get_open_trades()) == 2 # Change order_id for new orders @@ -3666,7 +3668,7 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit( (True, 29.70297029, 2.2, 2.3, -8.63762376, -0.1443212, 'loss'), ]) def test_execute_trade_exit_market_order( - default_conf_usdt, ticker_usdt, fee, is_short, current_rate, amount, + default_conf_usdt, ticker_usdt, fee, is_short, current_rate, amount, caplog, limit, profit_amount, profit_ratio, profit_or_loss, ticker_usdt_sell_up, mocker ) -> None: """ @@ -3694,6 +3696,7 @@ def test_execute_trade_exit_market_order( fetch_ticker=ticker_usdt, get_fee=fee, _is_dry_limit_order_filled=MagicMock(return_value=True), + get_funding_fees=MagicMock(side_effect=ExchangeError()), ) patch_whitelist(mocker, default_conf_usdt) freqtrade = FreqtradeBot(default_conf_usdt) @@ -3719,6 +3722,7 @@ def test_execute_trade_exit_market_order( limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'], exit_check=ExitCheckTuple(exit_type=ExitType.ROI) ) + assert log_has("Could not update funding fee.", caplog) assert not trade.is_open assert pytest.approx(trade.close_profit) == profit_ratio From 5e42defafc005de4d475776ae86ce6e242e8c8ed Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:36:17 +0000 Subject: [PATCH 225/592] Update telegram docs to disable partial exit notifications --- docs/telegram-usage.md | 91 +++++++++++++++++++++--------------------- 1 file changed, 46 insertions(+), 45 deletions(-) diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md index ece8700de..b9324def4 100644 --- a/docs/telegram-usage.md +++ b/docs/telegram-usage.md @@ -90,7 +90,8 @@ Example configuration showing the different settings: "trailing_stop_loss": "on", "stop_loss": "on", "stoploss_on_exchange": "on", - "custom_exit": "silent" + "custom_exit": "silent", + "partial_exit": "on" }, "entry_cancel": "silent", "exit_cancel": "on", @@ -138,7 +139,7 @@ You can create your own keyboard in `config.json`: "enabled": true, "token": "your_telegram_token", "chat_id": "your_telegram_chat_id", - "keyboard": [ + "keyboard": [ ["/daily", "/stats", "/balance", "/profit"], ["/status table", "/performance"], ["/reload_config", "/count", "/logs"] @@ -225,16 +226,16 @@ Once all positions are sold, run `/stop` to completely stop the bot. For each open trade, the bot will send you the following message. Enter Tag is configurable via Strategy. -> **Trade ID:** `123` `(since 1 days ago)` -> **Current Pair:** CVC/BTC +> **Trade ID:** `123` `(since 1 days ago)` +> **Current Pair:** CVC/BTC > **Direction:** Long > **Leverage:** 1.0 -> **Amount:** `26.64180098` +> **Amount:** `26.64180098` > **Enter Tag:** Awesome Long Signal -> **Open Rate:** `0.00007489` -> **Current Rate:** `0.00007489` -> **Current Profit:** `12.95%` -> **Stoploss:** `0.00007389 (-0.02%)` +> **Open Rate:** `0.00007489` +> **Current Rate:** `0.00007489` +> **Current Profit:** `12.95%` +> **Stoploss:** `0.00007389 (-0.02%)` ### /status table @@ -261,26 +262,26 @@ current max Return a summary of your profit/loss and performance. -> **ROI:** Close trades -> ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)` -> ∙ `62.968 USD` -> **ROI:** All trades -> ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)` -> ∙ `33.095 EUR` -> -> **Total Trade Count:** `138` -> **First Trade opened:** `3 days ago` -> **Latest Trade opened:** `2 minutes ago` -> **Avg. Duration:** `2:33:45` -> **Best Performing:** `PAY/BTC: 50.23%` -> **Trading volume:** `0.5 BTC` -> **Profit factor:** `1.04` -> **Max Drawdown:** `9.23% (0.01255 BTC)` +> **ROI:** Close trades +> ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)` +> ∙ `62.968 USD` +> **ROI:** All trades +> ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)` +> ∙ `33.095 EUR` +> +> **Total Trade Count:** `138` +> **First Trade opened:** `3 days ago` +> **Latest Trade opened:** `2 minutes ago` +> **Avg. Duration:** `2:33:45` +> **Best Performing:** `PAY/BTC: 50.23%` +> **Trading volume:** `0.5 BTC` +> **Profit factor:** `1.04` +> **Max Drawdown:** `9.23% (0.01255 BTC)` -The relative profit of `1.2%` is the average profit per trade. -The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`. -Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits. -Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy. +The relative profit of `1.2%` is the average profit per trade. +The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`. +Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits. +Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy. Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`. ### /forceexit @@ -309,27 +310,27 @@ Note that for this to work, `force_entry_enable` needs to be set to true. ### /performance Return the performance of each crypto-currency the bot has sold. -> Performance: -> 1. `RCN/BTC 0.003 BTC (57.77%) (1)` -> 2. `PAY/BTC 0.0012 BTC (56.91%) (1)` -> 3. `VIB/BTC 0.0011 BTC (47.07%) (1)` -> 4. `SALT/BTC 0.0010 BTC (30.24%) (1)` -> 5. `STORJ/BTC 0.0009 BTC (27.24%) (1)` -> ... +> Performance: +> 1. `RCN/BTC 0.003 BTC (57.77%) (1)` +> 2. `PAY/BTC 0.0012 BTC (56.91%) (1)` +> 3. `VIB/BTC 0.0011 BTC (47.07%) (1)` +> 4. `SALT/BTC 0.0010 BTC (30.24%) (1)` +> 5. `STORJ/BTC 0.0009 BTC (27.24%) (1)` +> ... ### /balance Return the balance of all crypto-currency your have on the exchange. -> **Currency:** BTC -> **Available:** 3.05890234 -> **Balance:** 3.05890234 -> **Pending:** 0.0 +> **Currency:** BTC +> **Available:** 3.05890234 +> **Balance:** 3.05890234 +> **Pending:** 0.0 -> **Currency:** CVC -> **Available:** 86.64180098 -> **Balance:** 86.64180098 -> **Pending:** 0.0 +> **Currency:** CVC +> **Available:** 86.64180098 +> **Balance:** 86.64180098 +> **Pending:** 0.0 ### /daily @@ -376,7 +377,7 @@ Month (count) Profit BTC Profit USD Profit % Shows the current whitelist -> Using whitelist `StaticPairList` with 22 pairs +> Using whitelist `StaticPairList` with 22 pairs > `IOTA/BTC, NEO/BTC, TRX/BTC, VET/BTC, ADA/BTC, ETC/BTC, NCASH/BTC, DASH/BTC, XRP/BTC, XVG/BTC, EOS/BTC, LTC/BTC, OMG/BTC, BTG/BTC, LSK/BTC, ZEC/BTC, HOT/BTC, IOTX/BTC, XMR/BTC, AST/BTC, XLM/BTC, NANO/BTC` ### /blacklist [pair] @@ -386,7 +387,7 @@ If Pair is set, then this pair will be added to the pairlist. Also supports multiple pairs, separated by a space. Use `/reload_config` to reset the blacklist. -> Using blacklist `StaticPairList` with 2 pairs +> Using blacklist `StaticPairList` with 2 pairs >`DODGE/BTC`, `HOT/BTC`. ### /edge From 08726a264be3abdb69569170915c23cd1459c0b2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 8 Sep 2022 07:48:36 +0000 Subject: [PATCH 226/592] Update FAQ to point out multiple parallel positions per trade --- docs/faq.md | 27 +++++++++++++++++---------- 1 file changed, 17 insertions(+), 10 deletions(-) diff --git a/docs/faq.md b/docs/faq.md index 381bbceb5..a72268ef9 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -4,7 +4,7 @@ Freqtrade supports spot trading only. -### Can I open short positions? +### Can my bot open short positions? Freqtrade can open short positions in futures markets. This requires the strategy to be made for this - and `"trading_mode": "futures"` in the configuration. @@ -12,9 +12,9 @@ Please make sure to read the [relevant documentation page](leverage.md) first. In spot markets, you can in some cases use leveraged spot tokens, which reflect an inverted pair (eg. BTCUP/USD, BTCDOWN/USD, ETHBULL/USD, ETHBEAR/USD,...) which can be traded with Freqtrade. -### Can I trade options or futures? +### Can my bot trade options or futures? -Futures trading is supported for selected exchanges. +Futures trading is supported for selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an uptodate list of supported exchanges. ## Beginner Tips & Tricks @@ -22,6 +22,13 @@ Futures trading is supported for selected exchanges. ## Freqtrade common issues +### Can freqtrade open multiple positions on the same pair in parallel? + +No. Freqtrade will only open one position per pair at a time. +You can however use the [`adjust_trade_position()` callback](strategy-callbacks.md#adjust-trade-position) to adjust an open position. + +Backtesting provides an option for this in `--eps` - however this is only there to highlight "hidden" signals, and will not work in live. + ### The bot does not start Running the bot with `freqtrade trade --config config.json` shows the output `freqtrade: command not found`. @@ -30,7 +37,7 @@ This could be caused by the following reasons: * The virtual environment is not active. * Run `source .env/bin/activate` to activate the virtual environment. -* The installation did not work correctly. +* The installation did not complete successfully. * Please check the [Installation documentation](installation.md). ### I have waited 5 minutes, why hasn't the bot made any trades yet? @@ -67,7 +74,7 @@ This is not a bot-problem, but will also happen while manual trading. While freqtrade can handle this (it'll sell 99 COIN), fees are often below the minimum tradable lot-size (you can only trade full COIN, not 0.9 COIN). Leaving the dust (0.9 COIN) on the exchange makes usually sense, as the next time freqtrade buys COIN, it'll eat into the remaining small balance, this time selling everything it bought, and therefore slowly declining the dust balance (although it most likely will never reach exactly 0). -Where possible (e.g. on binance), the use of the exchange's dedicated fee currency will fix this. +Where possible (e.g. on binance), the use of the exchange's dedicated fee currency will fix this. On binance, it's sufficient to have BNB in your account, and have "Pay fees in BNB" enabled in your profile. Your BNB balance will slowly decline (as it's used to pay fees) - but you'll no longer encounter dust (Freqtrade will include the fees in the profit calculations). Other exchanges don't offer such possibilities, where it's simply something you'll have to accept or move to a different exchange. @@ -109,7 +116,7 @@ This warning can point to one of the below problems: ### I'm getting the "RESTRICTED_MARKET" message in the log -Currently known to happen for US Bittrex users. +Currently known to happen for US Bittrex users. Read [the Bittrex section about restricted markets](exchanges.md#restricted-markets) for more information. @@ -177,8 +184,8 @@ The GPU improvements would only apply to pandas-native calculations - or ones wr For hyperopt, freqtrade is using scikit-optimize, which is built on top of scikit-learn. Their statement about GPU support is [pretty clear](https://scikit-learn.org/stable/faq.html#will-you-add-gpu-support). -GPU's also are only good at crunching numbers (floating point operations). -For hyperopt, we need both number-crunching (find next parameters) and running python code (running backtesting). +GPU's also are only good at crunching numbers (floating point operations). +For hyperopt, we need both number-crunching (find next parameters) and running python code (running backtesting). As such, GPU's are not too well suited for most parts of hyperopt. The benefit of using GPU would therefore be pretty slim - and will not justify the complexity introduced by trying to add GPU support. @@ -219,9 +226,9 @@ already 8\*10^9\*10 evaluations. A roughly total of 80 billion evaluations. Did you run 100 000 evaluations? Congrats, you've done roughly 1 / 100 000 th of the search space, assuming that the bot never tests the same parameters more than once. -* The time it takes to run 1000 hyperopt epochs depends on things like: The available cpu, hard-disk, ram, timeframe, timerange, indicator settings, indicator count, amount of coins that hyperopt test strategies on and the resulting trade count - which can be 650 trades in a year or 100000 trades depending if the strategy aims for big profits by trading rarely or for many low profit trades. +* The time it takes to run 1000 hyperopt epochs depends on things like: The available cpu, hard-disk, ram, timeframe, timerange, indicator settings, indicator count, amount of coins that hyperopt test strategies on and the resulting trade count - which can be 650 trades in a year or 100000 trades depending if the strategy aims for big profits by trading rarely or for many low profit trades. -Example: 4% profit 650 times vs 0,3% profit a trade 10000 times in a year. If we assume you set the --timerange to 365 days. +Example: 4% profit 650 times vs 0,3% profit a trade 10000 times in a year. If we assume you set the --timerange to 365 days. Example: `freqtrade --config config.json --strategy SampleStrategy --hyperopt SampleHyperopt -e 1000 --timerange 20190601-20200601` From 83770d20fac8d2acd8cf5d8567cc9d85a2b75ad1 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:10:32 -0600 Subject: [PATCH 227/592] fix existing freqtradebot tests --- tests/test_freqtradebot.py | 42 +++++++++++++++++++------------------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index aff0504b3..837a4315f 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -1317,9 +1317,9 @@ def test_create_stoploss_order_invalid_order( assert create_order_mock.call_args[1]['amount'] == trade.amount # Rpc is sending first buy, then sell - assert rpc_mock.call_count == 2 - assert rpc_mock.call_args_list[1][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value - assert rpc_mock.call_args_list[1][0][0]['order_type'] == 'market' + assert rpc_mock.call_count == 3 + assert rpc_mock.call_args_list[2][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value + assert rpc_mock.call_args_list[2][0][0]['order_type'] == 'market' @pytest.mark.parametrize("is_short", [False, True]) @@ -2434,7 +2434,7 @@ def test_manage_open_orders_entry_usercustom( # Trade should be closed since the function returns true freqtrade.manage_open_orders() assert cancel_order_wr_mock.call_count == 1 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() nb_trades = len(trades) assert nb_trades == 0 @@ -2473,7 +2473,7 @@ def test_manage_open_orders_entry( # check it does cancel buy orders over the time limit freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() nb_trades = len(trades) assert nb_trades == 0 @@ -2603,7 +2603,7 @@ def test_check_handle_cancelled_buy( # check it does cancel buy orders over the time limit freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 0 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() assert len(trades) == 0 assert log_has_re( @@ -2634,7 +2634,7 @@ def test_manage_open_orders_buy_exception( # check it does cancel buy orders over the time limit freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 0 - assert rpc_mock.call_count == 0 + assert rpc_mock.call_count == 1 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() nb_trades = len(trades) assert nb_trades == 1 @@ -2681,7 +2681,7 @@ def test_manage_open_orders_exit_usercustom( # Return false - No impact freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 0 - assert rpc_mock.call_count == 0 + assert rpc_mock.call_count == 1 assert open_trade_usdt.is_open is False assert freqtrade.strategy.check_exit_timeout.call_count == 1 assert freqtrade.strategy.check_entry_timeout.call_count == 0 @@ -2691,7 +2691,7 @@ def test_manage_open_orders_exit_usercustom( # Return Error - No impact freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 0 - assert rpc_mock.call_count == 0 + assert rpc_mock.call_count == 1 assert open_trade_usdt.is_open is False assert freqtrade.strategy.check_exit_timeout.call_count == 1 assert freqtrade.strategy.check_entry_timeout.call_count == 0 @@ -2701,7 +2701,7 @@ def test_manage_open_orders_exit_usercustom( freqtrade.strategy.check_entry_timeout = MagicMock(return_value=True) freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 assert open_trade_usdt.is_open is True assert freqtrade.strategy.check_exit_timeout.call_count == 1 assert freqtrade.strategy.check_entry_timeout.call_count == 0 @@ -2761,7 +2761,7 @@ def test_manage_open_orders_exit( # check it does cancel sell orders over the time limit freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 assert open_trade_usdt.is_open is True # Custom user sell-timeout is never called assert freqtrade.strategy.check_exit_timeout.call_count == 0 @@ -2800,7 +2800,7 @@ def test_check_handle_cancelled_exit( # check it does cancel sell orders over the time limit freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 0 - assert rpc_mock.call_count == 1 + assert rpc_mock.call_count == 2 assert open_trade_usdt.is_open is True exit_name = 'Buy' if is_short else 'Sell' assert log_has_re(f"{exit_name} order cancelled on exchange for Trade.*", caplog) @@ -2838,7 +2838,7 @@ def test_manage_open_orders_partial( # note this is for a partially-complete buy order freqtrade.manage_open_orders() assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 2 + assert rpc_mock.call_count == 3 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() assert len(trades) == 1 assert trades[0].amount == 23.0 @@ -2885,7 +2885,7 @@ def test_manage_open_orders_partial_fee( assert log_has_re(r"Applying fee on amount for Trade.*", caplog) assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 2 + assert rpc_mock.call_count == 3 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() assert len(trades) == 1 # Verify that trade has been updated @@ -2935,7 +2935,7 @@ def test_manage_open_orders_partial_except( assert log_has_re(r"Could not update trade amount: .*", caplog) assert cancel_order_mock.call_count == 1 - assert rpc_mock.call_count == 2 + assert rpc_mock.call_count == 3 trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all() assert len(trades) == 1 # Verify that trade has been updated @@ -3150,7 +3150,7 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: reason = CANCEL_REASON['TIMEOUT'] assert freqtrade.handle_cancel_exit(trade, order, reason) assert cancel_order_mock.call_count == 1 - assert send_msg_mock.call_count == 1 + assert send_msg_mock.call_count == 2 assert trade.close_rate is None assert trade.exit_reason is None @@ -3583,7 +3583,7 @@ def test_execute_trade_exit_with_stoploss_on_exchange( trade.is_short = is_short assert trade assert cancel_order.call_count == 1 - assert rpc_mock.call_count == 3 + assert rpc_mock.call_count == 4 @pytest.mark.parametrize("is_short", [False, True]) @@ -3653,10 +3653,10 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit( assert trade.stoploss_order_id is None assert trade.is_open is False assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value - assert rpc_mock.call_count == 3 - assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.ENTRY - assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY_FILL - assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.EXIT_FILL + assert rpc_mock.call_count == 4 + assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY + assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.ENTRY_FILL + assert rpc_mock.call_args_list[3][0][0]['type'] == RPCMessageType.EXIT_FILL @pytest.mark.parametrize( From 4fac12544385caee6a9a64858bbb445b72ea6989 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:14:30 -0600 Subject: [PATCH 228/592] fix apiserver cleanup issues in tests --- tests/rpc/test_rpc_apiserver.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 5dfa77d8b..0efcc00c1 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -54,6 +54,7 @@ def botclient(default_conf, mocker): apiserver.add_rpc_handler(rpc) yield ftbot, TestClient(apiserver.app) # Cleanup ... ? + apiserver.cleanup() finally: ApiServer.shutdown() @@ -261,6 +262,7 @@ def test_api__init__(default_conf, mocker): with pytest.raises(OperationalException, match="RPC Handler already attached."): apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) + apiserver.cleanup() ApiServer.shutdown() @@ -388,6 +390,7 @@ def test_api_run(default_conf, mocker, caplog): MagicMock(side_effect=Exception)) apiserver.start_api() assert log_has("Api server failed to start.", caplog) + apiserver.cleanup() ApiServer.shutdown() From 9b752475dbf0c1d6de6e245781ffdb789c54d3b8 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:20:03 -0600 Subject: [PATCH 229/592] re-add fix to freqtradebot test --- tests/test_freqtradebot.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 6f9ed407c..8b95792e5 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3655,11 +3655,11 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit( assert trade.stoploss_order_id is None assert trade.is_open is False assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value - assert rpc_mock.call_count == 3 - assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.ENTRY - assert rpc_mock.call_args_list[0][0][0]['amount'] > 20 - assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY_FILL - assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.EXIT_FILL + assert rpc_mock.call_count == 4 + assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY + assert rpc_mock.call_args_list[1][0][0]['amount'] > 20 + assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.ENTRY_FILL + assert rpc_mock.call_args_list[3][0][0]['type'] == RPCMessageType.EXIT_FILL @pytest.mark.parametrize( From df3c1261464f8f72063f019ea865759c74b5a18b Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:34:37 -0600 Subject: [PATCH 230/592] fix mypy error --- freqtrade/rpc/api_server/api_ws.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 64c1cebb5..8a3fcfba2 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -9,7 +9,8 @@ from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, - WSRequestSchema, WSWhitelistMessage) + WSMessageSchema, WSRequestSchema, + WSWhitelistMessage) from freqtrade.rpc.rpc import RPC @@ -47,6 +48,7 @@ async def _process_consumer_request( return type, data = websocket_request.type, websocket_request.data + response: WSMessageSchema logger.debug(f"Request of type {type} from {channel}") @@ -61,6 +63,7 @@ async def _process_consumer_request( channel.set_subscriptions(data) # We don't send a response for subscriptions + return elif type == RPCRequestType.WHITELIST: # Get whitelist @@ -70,6 +73,7 @@ async def _process_consumer_request( response = WSWhitelistMessage(data=whitelist) # Send it back await channel.send(response.dict(exclude_none=True)) + return elif type == RPCRequestType.ANALYZED_DF: limit = None @@ -86,6 +90,8 @@ async def _process_consumer_request( response = WSAnalyzedDFMessage(data=message) await channel.send(response.dict(exclude_none=True)) + return + @router.websocket("/message/ws") async def message_endpoint( From 379b1cbc9001f38189afc1bd963bcc6f55601ed3 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:37:41 -0600 Subject: [PATCH 231/592] remove unnecessary returns --- freqtrade/rpc/api_server/api_ws.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 8a3fcfba2..45cc20e4d 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -73,7 +73,6 @@ async def _process_consumer_request( response = WSWhitelistMessage(data=whitelist) # Send it back await channel.send(response.dict(exclude_none=True)) - return elif type == RPCRequestType.ANALYZED_DF: limit = None @@ -90,8 +89,6 @@ async def _process_consumer_request( response = WSAnalyzedDFMessage(data=message) await channel.send(response.dict(exclude_none=True)) - return - @router.websocket("/message/ws") async def message_endpoint( From b3b0c918d98326df8361e5f03302c7ecbd54be65 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:44:03 -0600 Subject: [PATCH 232/592] cleanup old code --- freqtrade/rpc/api_server/ws/schema.py | 12 ------------ freqtrade/rpc/api_server/ws/serializer.py | 10 ---------- freqtrade/rpc/api_server/ws/utils.py | 12 ------------ 3 files changed, 34 deletions(-) delete mode 100644 freqtrade/rpc/api_server/ws/utils.py diff --git a/freqtrade/rpc/api_server/ws/schema.py b/freqtrade/rpc/api_server/ws/schema.py index 3221911de..0baa8d233 100644 --- a/freqtrade/rpc/api_server/ws/schema.py +++ b/freqtrade/rpc/api_server/ws/schema.py @@ -64,15 +64,3 @@ class WSAnalyzedDFMessage(WSMessageSchema): data: AnalyzedDFData # -------------------------------------------------------------------------- - - -if __name__ == "__main__": - message = WSAnalyzedDFMessage( - data={ - "key": ("1", "5m", "spot"), - "df": DataFrame(), - "la": datetime.now() - } - ) - - print(message) diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index c0c24bb28..d1ddd84f0 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -46,16 +46,6 @@ class JSONWebSocketSerializer(WebSocketSerializer): return json.loads(data, object_hook=_json_object_hook) -# ORJSON does not support .loads(object_hook=x) parameter, so we must use RapidJSON - -class RapidJSONWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data): - return rapidjson.dumps(data, default=_json_default) - - def _deserialize(self, data): - return rapidjson.loads(data, object_hook=_json_object_hook) - - class HybridJSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data) -> str: return str(orjson.dumps(data, default=_json_default), "utf-8") diff --git a/freqtrade/rpc/api_server/ws/utils.py b/freqtrade/rpc/api_server/ws/utils.py deleted file mode 100644 index 1ceecab88..000000000 --- a/freqtrade/rpc/api_server/ws/utils.py +++ /dev/null @@ -1,12 +0,0 @@ -from fastapi import WebSocket -# fastapi does not make this available through it, so import directly from starlette -from starlette.websockets import WebSocketState - - -async def is_websocket_alive(ws: WebSocket) -> bool: - if ( - ws.application_state == WebSocketState.CONNECTED and - ws.client_state == WebSocketState.CONNECTED - ): - return True - return False From fac6626459ed8faa8da1f790cd89421f8c026ba4 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 10:54:31 -0600 Subject: [PATCH 233/592] update default timeouts --- config_examples/config_full.example.json | 4 ++-- freqtrade/rpc/external_message_consumer.py | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 9788a0fa9..37c604c72 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -187,9 +187,9 @@ "ws_token": "a_secret_ws_token" } ], - "reply_timeout": 10, + "reply_timeout": 30, "ping_timeout": 5, - "sleep_time": 5, + "sleep_time": 10, "remove_entry_exit_signals": false }, "bot_name": "freqtrade", diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index d1e970826..525f4282c 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -58,9 +58,9 @@ class ExternalMessageConsumer: if self.enabled and len(self.producers) < 1: raise ValueError("You must specify at least 1 Producer to connect to.") - self.reply_timeout = self._emc_config.get('reply_timeout', 10) - self.ping_timeout = self._emc_config.get('ping_timeout', 2) - self.sleep_time = self._emc_config.get('sleep_time', 5) + self.reply_timeout = self._emc_config.get('reply_timeout', 30) + self.ping_timeout = self._emc_config.get('ping_timeout', 5) + self.sleep_time = self._emc_config.get('sleep_time', 10) # The amount of candles per dataframe on the initial request self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 1500) From b9e7af1ce235cae8be27309da01df8ae70144100 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 11:25:30 -0600 Subject: [PATCH 234/592] fix ws token auth --- freqtrade/rpc/api_server/api_auth.py | 2 +- freqtrade/rpc/api_server/api_ws.py | 5 +++++ freqtrade/rpc/api_server/webserver.py | 7 ++----- tests/rpc/test_rpc_apiserver.py | 21 ++++++++++++++++++++- 4 files changed, 28 insertions(+), 7 deletions(-) diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index 6655dbf86..0d1378b6d 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -62,7 +62,7 @@ async def get_ws_token( # Just return the token if it matches return token else: - logger.debug("Denying websocket request") + logger.info("Denying websocket request") # If it doesn't match, close the websocket connection await ws.close(code=status.WS_1008_POLICY_VIOLATION) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 45cc20e4d..384bd4115 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -6,6 +6,7 @@ from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect from starlette.websockets import WebSocketState from freqtrade.enums import RPCMessageType, RPCRequestType +from freqtrade.rpc.api_server.api_auth import get_ws_token from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, @@ -95,6 +96,7 @@ async def message_endpoint( ws: WebSocket, rpc: RPC = Depends(get_rpc), channel_manager=Depends(get_channel_manager), + token: str = Depends(get_ws_token) ): """ Message WebSocket endpoint, facilitates sending RPC messages @@ -105,6 +107,9 @@ async def message_endpoint( # Return a channel ID, pass that instead of ws to the rest of the methods channel = await channel_manager.on_connect(ws) + if not channel: + return + logger.info(f"Consumer connected - {channel}") # Keep connection open until explicitly closed, and process requests diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 6ad3f143e..73e80dd48 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -139,8 +139,7 @@ class ApiServer(RPCHandler): ) def configure_app(self, app: FastAPI, config): - from freqtrade.rpc.api_server.api_auth import (get_ws_token, http_basic_or_jwt_token, - router_login) + from freqtrade.rpc.api_server.api_auth import http_basic_or_jwt_token, router_login from freqtrade.rpc.api_server.api_backtest import router as api_backtest from freqtrade.rpc.api_server.api_v1 import router as api_v1 from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public @@ -155,9 +154,7 @@ class ApiServer(RPCHandler): app.include_router(api_backtest, prefix="/api/v1", dependencies=[Depends(http_basic_or_jwt_token)], ) - app.include_router(ws_router, prefix="/api/v1", - dependencies=[Depends(get_ws_token)] - ) + app.include_router(ws_router, prefix="/api/v1") app.include_router(router_login, prefix="/api/v1", tags=["auth"]) # UI Router MUST be last! app.include_router(router_ui, prefix='') diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 0efcc00c1..ccfe31424 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -10,7 +10,7 @@ from unittest.mock import ANY, MagicMock, PropertyMock import pandas as pd import pytest import uvicorn -from fastapi import FastAPI +from fastapi import FastAPI, WebSocketDisconnect from fastapi.exceptions import HTTPException from fastapi.testclient import TestClient from requests.auth import _basic_auth_str @@ -31,6 +31,7 @@ from tests.conftest import (CURRENT_TEST_STRATEGY, create_mock_trades, get_mock_ BASE_URI = "/api/v1" _TEST_USER = "FreqTrader" _TEST_PASS = "SuperSecurePassword1!" +_TEST_WS_TOKEN = "secret_Ws_t0ken" @pytest.fixture @@ -44,6 +45,7 @@ def botclient(default_conf, mocker): "CORS_origins": ['http://example.com'], "username": _TEST_USER, "password": _TEST_PASS, + "ws_token": _TEST_WS_TOKEN }}) ftbot = get_patched_freqtradebot(mocker, default_conf) @@ -155,6 +157,23 @@ def test_api_auth(): get_user_from_token(b'not_a_token', 'secret1234') +def test_api_ws_auth(botclient): + ftbot, client = botclient + + bad_token = "bad-ws_token" + url = f"/api/v1/message/ws?token={bad_token}" + + with pytest.raises(WebSocketDisconnect): + with client.websocket_connect(url) as websocket: + websocket.receive() + + good_token = _TEST_WS_TOKEN + url = f"/api/v1/message/ws?token={good_token}" + + with client.websocket_connect(url) as websocket: + websocket.send(1) + + def test_api_unauthorized(botclient): ftbot, client = botclient rc = client.get(f"{BASE_URI}/ping") From 2b9c8550b0e6bddc85187958a2cb2816e95c4c2e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 13:58:28 -0600 Subject: [PATCH 235/592] moved ws_schemas, first ws tests --- freqtrade/rpc/api_server/api_ws.py | 19 ++++++++------- .../{ws/schema.py => ws_schemas.py} | 5 +--- freqtrade/rpc/external_message_consumer.py | 9 +++---- tests/rpc/test_rpc_apiserver.py | 24 +++++++++++++++++-- 4 files changed, 38 insertions(+), 19 deletions(-) rename freqtrade/rpc/api_server/{ws/schema.py => ws_schemas.py} (92%) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 384bd4115..f6eb59f87 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -2,6 +2,7 @@ import logging from typing import Any, Dict from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect +from pydantic import ValidationError # fastapi does not make this available through it, so import directly from starlette from starlette.websockets import WebSocketState @@ -9,9 +10,8 @@ from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.api_auth import get_ws_token from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel -from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, - WSMessageSchema, WSRequestSchema, - WSWhitelistMessage) +from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSMessageSchema, + WSRequestSchema, WSWhitelistMessage) from freqtrade.rpc.rpc import RPC @@ -102,13 +102,11 @@ async def message_endpoint( Message WebSocket endpoint, facilitates sending RPC messages """ try: - if is_websocket_alive(ws): - # TODO: - # Return a channel ID, pass that instead of ws to the rest of the methods - channel = await channel_manager.on_connect(ws) + # TODO: + # Return a channel ID, pass that instead of ws to the rest of the methods + channel = await channel_manager.on_connect(ws) - if not channel: - return + if await is_websocket_alive(ws): logger.info(f"Consumer connected - {channel}") @@ -131,6 +129,9 @@ async def message_endpoint( # RuntimeError('Cannot call "send" once a closed message has been sent') await channel_manager.on_disconnect(ws) + else: + ws.close() + except Exception as e: logger.error(f"Failed to serve - {ws.client}") # Log tracebacks to keep track of what errors are happening diff --git a/freqtrade/rpc/api_server/ws/schema.py b/freqtrade/rpc/api_server/ws_schemas.py similarity index 92% rename from freqtrade/rpc/api_server/ws/schema.py rename to freqtrade/rpc/api_server/ws_schemas.py index 0baa8d233..255226d84 100644 --- a/freqtrade/rpc/api_server/ws/schema.py +++ b/freqtrade/rpc/api_server/ws_schemas.py @@ -2,15 +2,12 @@ from datetime import datetime from typing import Any, Dict, List, Optional from pandas import DataFrame -from pydantic import BaseModel, ValidationError +from pydantic import BaseModel from freqtrade.constants import PairWithTimeframe from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType -__all__ = ('WSRequestSchema', 'WSMessageSchema', 'ValidationError') - - class BaseArbitraryModel(BaseModel): class Config: arbitrary_types_allowed = True diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 525f4282c..abeedb0a4 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -11,15 +11,16 @@ from threading import Thread from typing import TYPE_CHECKING, Any, Dict, List import websockets +from pydantic import ValidationError from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RPCMessageType from freqtrade.misc import remove_entry_exit_signals from freqtrade.rpc.api_server.ws.channel import WebSocketChannel -from freqtrade.rpc.api_server.ws.schema import (ValidationError, WSAnalyzedDFMessage, - WSAnalyzedDFRequest, WSMessageSchema, - WSRequestSchema, WSSubscribeRequest, - WSWhitelistMessage, WSWhitelistRequest) +from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSAnalyzedDFRequest, + WSMessageSchema, WSRequestSchema, + WSSubscribeRequest, WSWhitelistMessage, + WSWhitelistRequest) if TYPE_CHECKING: diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index ccfe31424..de093b66f 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -56,8 +56,8 @@ def botclient(default_conf, mocker): apiserver.add_rpc_handler(rpc) yield ftbot, TestClient(apiserver.app) # Cleanup ... ? - apiserver.cleanup() finally: + apiserver.cleanup() ApiServer.shutdown() @@ -171,7 +171,7 @@ def test_api_ws_auth(botclient): url = f"/api/v1/message/ws?token={good_token}" with client.websocket_connect(url) as websocket: - websocket.send(1) + pass def test_api_unauthorized(botclient): @@ -1685,3 +1685,23 @@ def test_health(botclient): ret = rc.json() assert ret['last_process_ts'] == 0 assert ret['last_process'] == '1970-01-01T00:00:00+00:00' + + +def test_api_ws_subscribe(botclient, mocker): + ftbot, client = botclient + ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}" + + sub_mock = mocker.patch( + 'freqtrade.rpc.api_server.ws.channel.WebSocketChannel.set_subscriptions', MagicMock()) + + with client.websocket_connect(ws_url) as ws: + ws.send_json({'type': 'subscribe', 'data': ['whitelist']}) + + # Check call count is now 1 as we sent a valid subscribe request + assert sub_mock.call_count == 1 + + with client.websocket_connect(ws_url) as ws: + ws.send_json({'type': 'subscribe', 'data': 'whitelist'}) + + # Call count hasn't changed as the subscribe request was invalid + assert sub_mock.call_count == 1 From c9d4f666c5fa95e4671ea0a4258abf9ff69b7386 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 14:00:22 -0600 Subject: [PATCH 236/592] minor apiserver test change --- tests/rpc/test_rpc_apiserver.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index de093b66f..6a37e7cdd 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -51,13 +51,15 @@ def botclient(default_conf, mocker): ftbot = get_patched_freqtradebot(mocker, default_conf) rpc = RPC(ftbot) mocker.patch('freqtrade.rpc.api_server.ApiServer.start_api', MagicMock()) + apiserver = None try: apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(rpc) yield ftbot, TestClient(apiserver.app) # Cleanup ... ? finally: - apiserver.cleanup() + if apiserver: + apiserver.cleanup() ApiServer.shutdown() From bc7295579ff89387a402a6255ff5acfa9c583231 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Thu, 8 Sep 2022 22:22:50 +0200 Subject: [PATCH 237/592] improve docs, make example strat hyperoptable --- docs/freqai.md | 22 ++++++++++++-- freqtrade/templates/FreqaiExampleStrategy.py | 31 +++++++++++++------- 2 files changed, 39 insertions(+), 14 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 006fe1393..92e019dfe 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -538,12 +538,28 @@ for each pair, for each backtesting window within the expanded `--timerange`. ### Hyperopt -The [Hyperopt](hyperopt.md) module can be executed with some restrictions: +Users can hyperopt using the same command as typical [hyperopt](hyperopt.md): + +```bash +freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 +``` + +Users need to have the data pre-downloaded in the same fashion as if they were doing a FreqAI [backtest](#backtesting). In addition, users must consider some restrictions when trying to [Hyperopt](hyperopt.md) FreqAI strategies: - The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. - It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md#running-hyperopt-with-smaller-search-space). -- The [Backtesting](#backtesting) instructions also apply apply to Hyperopt. - +- The [Backtesting](#backtesting) instructions also apply to Hyperopt. + +The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. Users need to focus on hyperopting parameters that are not used in their FreqAI features. For example, users should not try to hyperopt rolling window lengths in their feature creation, or any of their FreqAI config which changes predictions. In order to efficiently hyperopt the FreqAI strategy, FreqAI stores predictions as dataframes and reuses them. Hence the requirement to hyperopt entry/exit thresholds/criteria only. + +A good example of a hyperoptable parameter in FreqAI is a value for `DI_values` beyond which we consider outliers and below which we consider inliers: + +```python +di_max = IntParameter(low=1, high=20, default=10, space='buy', optimize=True, load=True) +dataframe['outlier'] = np.where(dataframe['DI_values'] > self.di_max.value/10, 1, 0) +``` + +Which would help the user understand the appropriate Dissimilarity Index values for their particular parameter space. ### Deciding the size of the sliding training window and backtesting duration diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index 78132b06d..8b8e03af7 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -6,7 +6,7 @@ import talib.abstract as ta from pandas import DataFrame from technical import qtpylib -from freqtrade.strategy import IStrategy, merge_informative_pair +from freqtrade.strategy import IStrategy, merge_informative_pair, CategoricalParameter logger = logging.getLogger(__name__) @@ -29,9 +29,6 @@ class FreqaiExampleStrategy(IStrategy): "main_plot": {}, "subplots": { "prediction": {"prediction": {"color": "blue"}}, - "target_roi": { - "target_roi": {"color": "brown"}, - }, "do_predict": { "do_predict": {"color": "brown"}, }, @@ -45,6 +42,11 @@ class FreqaiExampleStrategy(IStrategy): startup_candle_count: int = 40 can_short = False + std_dev_multiplier_buy = CategoricalParameter( + [0.75, 1, 1.25, 1.5, 1.75], default=1.25, space="buy", optimize=True) + std_dev_multiplier_sell = CategoricalParameter( + [0.1, 0.25, 0.4], space="sell", default=0.2, optimize=True) + def informative_pairs(self): whitelist_pairs = self.dp.current_whitelist() corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] @@ -182,21 +184,26 @@ class FreqaiExampleStrategy(IStrategy): # `populate_any_indicators()` for each training period. dataframe = self.freqai.start(dataframe, metadata, self) - - dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25 - dataframe["sell_roi"] = dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * 1.25 + for val in self.std_dev_multiplier_buy.range: + dataframe[f'target_roi_{val}'] = dataframe["&-s_close_mean"] + \ + dataframe["&-s_close_std"] * val + for val in self.std_dev_multiplier_sell.range: + dataframe[f'sell_roi_{val}'] = dataframe["&-s_close_mean"] - \ + dataframe["&-s_close_std"] * val return dataframe def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame: - enter_long_conditions = [df["do_predict"] == 1, df["&-s_close"] > df["target_roi"]] + enter_long_conditions = [df["do_predict"] == 1, df["&-s_close"] + > df[f"target_roi_{self.std_dev_multiplier_buy.value}"]] if enter_long_conditions: df.loc[ reduce(lambda x, y: x & y, enter_long_conditions), ["enter_long", "enter_tag"] ] = (1, "long") - enter_short_conditions = [df["do_predict"] == 1, df["&-s_close"] < df["sell_roi"]] + enter_short_conditions = [df["do_predict"] == 1, df["&-s_close"] + < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"]] if enter_short_conditions: df.loc[ @@ -206,11 +213,13 @@ class FreqaiExampleStrategy(IStrategy): return df def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame: - exit_long_conditions = [df["do_predict"] == 1, df["&-s_close"] < df["sell_roi"] * 0.25] + exit_long_conditions = [df["do_predict"] == 1, df["&-s_close"] < + df[f"sell_roi_{self.std_dev_multiplier_sell.value}"] * 0.25] if exit_long_conditions: df.loc[reduce(lambda x, y: x & y, exit_long_conditions), "exit_long"] = 1 - exit_short_conditions = [df["do_predict"] == 1, df["&-s_close"] > df["target_roi"] * 0.25] + exit_short_conditions = [df["do_predict"] == 1, df["&-s_close"] > + df[f"target_roi_{self.std_dev_multiplier_buy.value}"] * 0.25] if exit_short_conditions: df.loc[reduce(lambda x, y: x & y, exit_short_conditions), "exit_short"] = 1 From c5d918075881f62277f21854fdbd85fd94335024 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Thu, 8 Sep 2022 22:35:52 +0200 Subject: [PATCH 238/592] isort --- freqtrade/templates/FreqaiExampleStrategy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py index 8b8e03af7..991792eb9 100644 --- a/freqtrade/templates/FreqaiExampleStrategy.py +++ b/freqtrade/templates/FreqaiExampleStrategy.py @@ -6,7 +6,7 @@ import talib.abstract as ta from pandas import DataFrame from technical import qtpylib -from freqtrade.strategy import IStrategy, merge_informative_pair, CategoricalParameter +from freqtrade.strategy import CategoricalParameter, IStrategy, merge_informative_pair logger = logging.getLogger(__name__) From 75cf8dbfe428eb2e3874638cf8ae262bda2768bf Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 15:11:36 -0600 Subject: [PATCH 239/592] missed await --- freqtrade/rpc/api_server/api_ws.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index f6eb59f87..16d5ef9a7 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -130,7 +130,7 @@ async def message_endpoint( await channel_manager.on_disconnect(ws) else: - ws.close() + await ws.close() except Exception as e: logger.error(f"Failed to serve - {ws.client}") From 1466d2d26f5cb90fdc1e6343c8fb604f2a0ca657 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 16:27:09 -0600 Subject: [PATCH 240/592] initial message ws docs --- docs/rest-api.md | 71 ++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 68 insertions(+), 3 deletions(-) diff --git a/docs/rest-api.md b/docs/rest-api.md index cc82aadda..5dc7637e5 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -31,7 +31,8 @@ Sample configuration: "jwt_secret_key": "somethingrandom", "CORS_origins": [], "username": "Freqtrader", - "password": "SuperSecret1!" + "password": "SuperSecret1!", + "ws_token": "sercet_Ws_t0ken" }, ``` @@ -66,7 +67,7 @@ secrets.token_hex() !!! Danger "Password selection" Please make sure to select a very strong, unique password to protect your bot from unauthorized access. - Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!). + Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!). ### Configuration with docker @@ -274,7 +275,7 @@ reload_config Reload configuration. show_config - + Returns part of the configuration, relevant for trading operations. start @@ -322,6 +323,70 @@ whitelist ``` +### Message WebSocket + +The API Server makes available a websocket endpoint for subscribing to RPC messages +from the FreqTrade Bot. This can be used to consume real-time data from your bot, such as entry/exit fill messages, whitelist changes, populated indicators for pairs, and more. + +Assuming your rest API is set to `127.0.0.1` on port `8080`, the endpoint is available at `http://localhost:8080/api/v1/message/ws`. + +To access the websocket endpoint, the `ws_token` is required as a query parameter in the endpoint URL. This is set in your rest API config section. To generate a safe `ws_token` you can run the following code: + +``` python +>>> import secrets +>>> secrets.token_urlsafe(16) +'zs9XYCbTPKvux46UJckflw' +``` + +You could then connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=zs9XYCbTPKvux46UJckflw`. + +!!! warning "Warning" + + Please do not use the above example token. To make sure you are secure, generate a completely new token. + + +#### Using the WebSocket + +Once connected to the WebSocket, the bot will broadcast RPC messages to anyone who is subscribed to them. To subscribe to a message, you must first subscribe to the message types. This can be done by sending a JSON request through the WebSocket: + +``` json +{ + "type": "subscribe", + "data": ["whitelist", "analyzed_df"] // A list of string message types +} +``` + +#### Message types + +| Message Type | Description | +|--------------|-------------| +| whitelist | The list of pairs in the bot's whitelist. +| analyzed_df | The dataframe and last_analyzed datetime for a pair. +| entry | Trade has signaled an entry +| entry_fill | Trade enter has filled +| entry_cancel | Trade enter has been canceled +| exit | Trade has signaled an exit +| exit_fill | Trade exit has filled +| exit_cancel | Trade exit has been canceled +| protection_trigger | A protection has triggered for a pair +| protection_trigger_global | A protection has triggered for a pair +| status | A bot's status change +| startup | Startup messages +| warning | Any warnings + +Now anytime those types of RPC messages are sent in the bot, you will receive them through the WebSocket as long as the connection is active. They typically take the same form as the request: + +``` json +{ + "type": "analyzed_df", + "data": { + "key": ["NEO/BTC", "5m", "spot"], + "df": {}, // The dataframe + "la": "2022-09-08 22:14:41.457786+00:00" + } +} +``` + ### OpenAPI interface To enable the builtin openAPI interface (Swagger UI), specify `"enable_openapi": true` in the api_server configuration. From 46cd0ce9948e6d753a4a19b26ff8797d86bcca2c Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 8 Sep 2022 16:30:31 -0600 Subject: [PATCH 241/592] fix sentence in docs --- docs/rest-api.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/rest-api.md b/docs/rest-api.md index 5dc7637e5..f4ac2c350 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -347,7 +347,7 @@ You could then connect to the endpoint at `http://localhost:8080/api/v1/message/ #### Using the WebSocket -Once connected to the WebSocket, the bot will broadcast RPC messages to anyone who is subscribed to them. To subscribe to a message, you must first subscribe to the message types. This can be done by sending a JSON request through the WebSocket: +Once connected to the WebSocket, the bot will broadcast RPC messages to anyone who is subscribed to them. To subscribe to a list of messages, you must send a JSON request through the WebSocket like the one below. The `data` key must be a list of message type strings. ``` json { From 92d71ebdb730c16bcab4eb61e3516ea7a58e4825 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 9 Sep 2022 03:03:30 +0000 Subject: [PATCH 242/592] Bump python from 3.10.6-slim-bullseye to 3.10.7-slim-bullseye Bumps python from 3.10.6-slim-bullseye to 3.10.7-slim-bullseye. --- updated-dependencies: - dependency-name: python dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfile b/Dockerfile index e84a4d095..b3e5d5e88 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM python:3.10.6-slim-bullseye as base +FROM python:3.10.7-slim-bullseye as base # Setup env ENV LANG C.UTF-8 From e256ebd7271bf138a381108cb237ab574947d025 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 9 Sep 2022 07:13:05 +0200 Subject: [PATCH 243/592] Add ws_token to auto-generated config --- freqtrade/commands/build_config_commands.py | 1 + freqtrade/enums/rpcmessagetype.py | 1 - freqtrade/rpc/rpc.py | 4 ++-- freqtrade/templates/base_config.json.j2 | 1 + 4 files changed, 4 insertions(+), 3 deletions(-) diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py index 01cfa800a..1abd26328 100644 --- a/freqtrade/commands/build_config_commands.py +++ b/freqtrade/commands/build_config_commands.py @@ -211,6 +211,7 @@ def ask_user_config() -> Dict[str, Any]: ) # Force JWT token to be a random string answers['api_server_jwt_key'] = secrets.token_hex() + answers['api_server_ws_token'] = secrets.token_urlsafe(25) return answers diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py index 929f6d083..fae121a09 100644 --- a/freqtrade/enums/rpcmessagetype.py +++ b/freqtrade/enums/rpcmessagetype.py @@ -1,7 +1,6 @@ from enum import Enum -# We need to inherit from str so we can use as a str class RPCMessageType(str, Enum): STATUS = 'status' WARNING = 'warning' diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 9821bc001..943c1c667 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -1086,7 +1086,7 @@ class RPC: """ Whitelist data for WebSocket """ return self._freqtrade.active_pair_whitelist - @ staticmethod + @staticmethod def _rpc_analysed_history_full(config, pair: str, timeframe: str, timerange: str, exchange) -> Dict[str, Any]: timerange_parsed = TimeRange.parse_timerange(timerange) @@ -1117,7 +1117,7 @@ class RPC: self._freqtrade.strategy.plot_config['subplots'] = {} return self._freqtrade.strategy.plot_config - @ staticmethod + @staticmethod def _rpc_sysinfo() -> Dict[str, Any]: return { "cpu_pct": psutil.cpu_percent(interval=1, percpu=True), diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2 index 681af84c6..299734a50 100644 --- a/freqtrade/templates/base_config.json.j2 +++ b/freqtrade/templates/base_config.json.j2 @@ -67,6 +67,7 @@ "verbosity": "error", "enable_openapi": false, "jwt_secret_key": "{{ api_server_jwt_key }}", + "ws_token": "{{ api_server_ws_token }}", "CORS_origins": [], "username": "{{ api_server_username }}", "password": "{{ api_server_password }}" From 426f8f37e9f45a8dc7df3bce11b1a0b3ace6c5b3 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 10:45:49 -0600 Subject: [PATCH 244/592] change var names --- freqtrade/constants.py | 2 +- freqtrade/rpc/api_server/webserver.py | 52 +++++++++++----------- freqtrade/rpc/external_message_consumer.py | 8 ++-- 3 files changed, 31 insertions(+), 31 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 2279acc13..e77940b3c 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -502,7 +502,7 @@ CONF_SCHEMA = { 'required': ['name', 'url', 'ws_token'] } }, - 'reply_timeout': {'type': 'integer'}, + 'wait_timeout': {'type': 'integer'}, 'sleep_time': {'type': 'integer'}, 'ping_timeout': {'type': 'integer'}, 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False}, diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 73e80dd48..557857ecc 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -49,9 +49,9 @@ class ApiServer(RPCHandler): # Exchange - only available in webserver mode. _exchange = None # websocket message queue stuff - _channel_manager = None - _thread = None - _loop = None + _ws_channel_manager = None + _ws_thread = None + _ws_loop = None def __new__(cls, *args, **kwargs): """ @@ -69,14 +69,14 @@ class ApiServer(RPCHandler): return self._standalone: bool = standalone self._server = None - self._queue = None - self._background_task = None + self._ws_queue = None + self._ws_background_task = None ApiServer.__initialized = True api_config = self._config['api_server'] - ApiServer._channel_manager = ChannelManager() + ApiServer._ws_channel_manager = ChannelManager() self.app = FastAPI(title="Freqtrade API", docs_url='/docs' if api_config.get('enable_openapi', False) else None, @@ -105,18 +105,18 @@ class ApiServer(RPCHandler): logger.info("Stopping API Server") self._server.cleanup() - if self._thread and self._loop: + if self._ws_thread and self._ws_loop: logger.info("Stopping API Server background tasks") - if self._background_task: + if self._ws_background_task: # Cancel the queue task - self._background_task.cancel() + self._ws_background_task.cancel() - self._thread.join() + self._ws_thread.join() - self._thread = None - self._loop = None - self._background_task = None + self._ws_thread = None + self._ws_loop = None + self._ws_background_task = None @classmethod def shutdown(cls): @@ -127,8 +127,8 @@ class ApiServer(RPCHandler): cls._rpc = None def send_msg(self, msg: Dict[str, str]) -> None: - if self._queue: - sync_q = self._queue.sync_q + if self._ws_queue: + sync_q = self._ws_queue.sync_q sync_q.put(msg) def handle_rpc_exception(self, request, exc): @@ -170,24 +170,24 @@ class ApiServer(RPCHandler): app.add_exception_handler(RPCException, self.handle_rpc_exception) def start_message_queue(self): - if self._thread: + if self._ws_thread: return # Create a new loop, as it'll be just for the background thread - self._loop = asyncio.new_event_loop() + self._ws_loop = asyncio.new_event_loop() # Start the thread - self._thread = Thread(target=self._loop.run_forever) - self._thread.start() + self._ws_thread = Thread(target=self._ws_loop.run_forever) + self._ws_thread.start() # Finally, submit the coro to the thread - self._background_task = asyncio.run_coroutine_threadsafe( - self._broadcast_queue_data(), loop=self._loop) + self._ws_background_task = asyncio.run_coroutine_threadsafe( + self._broadcast_queue_data(), loop=self._ws_loop) async def _broadcast_queue_data(self): # Instantiate the queue in this coroutine so it's attached to our loop - self._queue = ThreadedQueue() - async_queue = self._queue.async_q + self._ws_queue = ThreadedQueue() + async_queue = self._ws_queue.async_q try: while True: @@ -196,13 +196,13 @@ class ApiServer(RPCHandler): message = await async_queue.get() logger.debug(f"Found message of type: {message.get('type')}") # Broadcast it - await self._channel_manager.broadcast(message) + await self._ws_channel_manager.broadcast(message) # Sleep, make this configurable? await asyncio.sleep(0.1) except asyncio.CancelledError: # Disconnect channels and stop the loop on cancel - await self._channel_manager.disconnect_all() - self._loop.stop() + await self._ws_channel_manager.disconnect_all() + self._ws_loop.stop() # For testing, shouldn't happen when stable except Exception as e: diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index abeedb0a4..1c2a27617 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -59,9 +59,9 @@ class ExternalMessageConsumer: if self.enabled and len(self.producers) < 1: raise ValueError("You must specify at least 1 Producer to connect to.") - self.reply_timeout = self._emc_config.get('reply_timeout', 30) - self.ping_timeout = self._emc_config.get('ping_timeout', 5) - self.sleep_time = self._emc_config.get('sleep_time', 10) + self.wait_timeout = self._emc_config.get('wait_timeout', 300) # in seconds + self.ping_timeout = self._emc_config.get('ping_timeout', 10) # in seconds + self.sleep_time = self._emc_config.get('sleep_time', 10) # in seconds # The amount of candles per dataframe on the initial request self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 1500) @@ -220,7 +220,7 @@ class ExternalMessageConsumer: try: message = await asyncio.wait_for( channel.recv(), - timeout=self.reply_timeout + timeout=self.wait_timeout ) try: From 445ab1beeed411531dbe2ba27cba7c026c83949a Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 10:56:54 -0600 Subject: [PATCH 245/592] update docs --- docs/rest-api.md | 48 ++++++++++++++++++++++++++---------------------- 1 file changed, 26 insertions(+), 22 deletions(-) diff --git a/docs/rest-api.md b/docs/rest-api.md index f4ac2c350..485fca6b5 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -330,15 +330,36 @@ from the FreqTrade Bot. This can be used to consume real-time data from your bot Assuming your rest API is set to `127.0.0.1` on port `8080`, the endpoint is available at `http://localhost:8080/api/v1/message/ws`. -To access the websocket endpoint, the `ws_token` is required as a query parameter in the endpoint URL. This is set in your rest API config section. To generate a safe `ws_token` you can run the following code: +To access the websocket endpoint, the `ws_token` is required as a query parameter in the endpoint URL. + + + To generate a safe `ws_token` you can run the following code: ``` python >>> import secrets ->>> secrets.token_urlsafe(16) -'zs9XYCbTPKvux46UJckflw' +>>> secrets.token_urlsafe(25) +'hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q' ``` -You could then connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=zs9XYCbTPKvux46UJckflw`. + +You would then add that token under `ws_token` in your `api_server` config. Like so: + +``` json +"api_server": { + "enabled": true, + "listen_ip_address": "127.0.0.1", + "listen_port": 8080, + "verbosity": "error", + "enable_openapi": false, + "jwt_secret_key": "somethingrandom", + "CORS_origins": [], + "username": "Freqtrader", + "password": "SuperSecret1!", + "ws_token": "hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q" // <----- +}, +``` + +You could then connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q`. !!! warning "Warning" @@ -355,24 +376,7 @@ Once connected to the WebSocket, the bot will broadcast RPC messages to anyone w "data": ["whitelist", "analyzed_df"] // A list of string message types } ``` - -#### Message types - -| Message Type | Description | -|--------------|-------------| -| whitelist | The list of pairs in the bot's whitelist. -| analyzed_df | The dataframe and last_analyzed datetime for a pair. -| entry | Trade has signaled an entry -| entry_fill | Trade enter has filled -| entry_cancel | Trade enter has been canceled -| exit | Trade has signaled an exit -| exit_fill | Trade exit has filled -| exit_cancel | Trade exit has been canceled -| protection_trigger | A protection has triggered for a pair -| protection_trigger_global | A protection has triggered for a pair -| status | A bot's status change -| startup | Startup messages -| warning | Any warnings +For a list of message types, please refer to the RPCMessageType enum in `freqtrade/enums/rpcmessagetype.py` Now anytime those types of RPC messages are sent in the bot, you will receive them through the WebSocket as long as the connection is active. They typically take the same form as the request: From ad9659769331c718098f2ee8acc17c0fbf3ebca0 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 10:59:38 -0600 Subject: [PATCH 246/592] wording --- docs/rest-api.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/rest-api.md b/docs/rest-api.md index 485fca6b5..704f38f00 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -359,7 +359,7 @@ You would then add that token under `ws_token` in your `api_server` config. Like }, ``` -You could then connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q`. +You can now connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q`. !!! warning "Warning" From d38cc061396d615832833fcbc880be5bdced8459 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Wed, 7 Sep 2022 18:52:58 -0300 Subject: [PATCH 247/592] Fix freqai backtesting time range issue --- freqtrade/freqai/data_kitchen.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7670cfd45..01b2f1f3b 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -461,6 +461,20 @@ class FreqaiDataKitchen: return df + def remove_training_from_backtesting( + self + ) -> DataFrame: + """ + Function which takes the backtesting time range and + remove training data from dataframe + """ + tr = self.config["timerange"] + backtesting_timerange = TimeRange.parse_timerange(tr) + start = datetime.fromtimestamp(backtesting_timerange.startts, tz=timezone.utc) + df = self.return_dataframe + df = df.loc[df["date"] >= start, :] + return df + def principal_component_analysis(self) -> None: """ Performs Principal Component Analysis on the data for dimensionality reduction @@ -954,6 +968,7 @@ class FreqaiDataKitchen: to_keep = [col for col in dataframe.columns if not col.startswith("&")] self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1) + self.return_dataframe = self.remove_training_from_backtesting() self.full_df = DataFrame() return From 09679cc79814d7921280846f1291d169ffe23b97 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 11:27:20 -0600 Subject: [PATCH 248/592] fix dependency --- freqtrade/rpc/api_server/deps.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/rpc/api_server/deps.py b/freqtrade/rpc/api_server/deps.py index 360771d77..abd3db036 100644 --- a/freqtrade/rpc/api_server/deps.py +++ b/freqtrade/rpc/api_server/deps.py @@ -42,7 +42,7 @@ def get_exchange(config=Depends(get_config)): def get_channel_manager(): - return ApiServer._channel_manager + return ApiServer._ws_channel_manager def is_webserver_mode(config=Depends(get_config)): From 1b6410d7d1e20d4ede790ac46d4232d8cddaa181 Mon Sep 17 00:00:00 2001 From: Emre Date: Thu, 8 Sep 2022 14:12:19 +0300 Subject: [PATCH 249/592] Add XGBoostRegressor for freqAI, fix mypy errors --- .../prediction_models/BaseClassifierModel.py | 8 ++-- .../prediction_models/BaseRegressionModel.py | 8 ++-- .../prediction_models/BaseTensorFlowModel.py | 2 +- .../prediction_models/XGBoostRegressor.py | 46 +++++++++++++++++++ requirements-freqai.txt | 1 + tests/freqai/test_freqai_interface.py | 31 +++++++++++++ 6 files changed, 87 insertions(+), 9 deletions(-) create mode 100644 freqtrade/freqai/prediction_models/XGBoostRegressor.py diff --git a/freqtrade/freqai/prediction_models/BaseClassifierModel.py b/freqtrade/freqai/prediction_models/BaseClassifierModel.py index e51e26e0f..291bacc82 100644 --- a/freqtrade/freqai/prediction_models/BaseClassifierModel.py +++ b/freqtrade/freqai/prediction_models/BaseClassifierModel.py @@ -21,7 +21,7 @@ class BaseClassifierModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen + self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen @@ -68,7 +68,7 @@ class BaseClassifierModel(IFreqaiModel): return model def predict( - self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False + self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False, **kwargs ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: """ Filter the prediction features data and predict with it. @@ -79,9 +79,9 @@ class BaseClassifierModel(IFreqaiModel): data (NaNs) or felt uncertain about data (PCA and DI index) """ - dk.find_features(unfiltered_dataframe) + dk.find_features(dataframe) filtered_dataframe, _ = dk.filter_features( - unfiltered_dataframe, dk.training_features_list, training_filter=False + dataframe, dk.training_features_list, training_filter=False ) filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe) dk.data_dictionary["prediction_features"] = filtered_dataframe diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py index 45f0c2937..da6fba571 100644 --- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py +++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py @@ -20,7 +20,7 @@ class BaseRegressionModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen + self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen @@ -67,7 +67,7 @@ class BaseRegressionModel(IFreqaiModel): return model def predict( - self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False + self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False, **kwargs ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: """ Filter the prediction features data and predict with it. @@ -78,9 +78,9 @@ class BaseRegressionModel(IFreqaiModel): data (NaNs) or felt uncertain about data (PCA and DI index) """ - dk.find_features(unfiltered_dataframe) + dk.find_features(dataframe) filtered_dataframe, _ = dk.filter_features( - unfiltered_dataframe, dk.training_features_list, training_filter=False + dataframe, dk.training_features_list, training_filter=False ) filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe) dk.data_dictionary["prediction_features"] = filtered_dataframe diff --git a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py index 66e6ec1fc..6fb49239b 100644 --- a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py +++ b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py @@ -17,7 +17,7 @@ class BaseTensorFlowModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen + self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressor.py b/freqtrade/freqai/prediction_models/XGBoostRegressor.py new file mode 100644 index 000000000..a8f250d16 --- /dev/null +++ b/freqtrade/freqai/prediction_models/XGBoostRegressor.py @@ -0,0 +1,46 @@ +import logging +from typing import Any, Dict + +import xgboost as xgb + +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel + + +logger = logging.getLogger(__name__) + + +class XGBoostRegressor(BaseRegressionModel): + """ + User created prediction model. The class needs to override three necessary + functions, predict(), train(), fit(). The class inherits ModelHandler which + has its own DataHandler where data is held, saved, loaded, and managed. + """ + + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: + """ + User sets up the training and test data to fit their desired model here + :param data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. + """ + + xgb.set_config(verbosity=2) + xgb.config_context(verbosity=2) + + X = data_dictionary["train_features"] + y = data_dictionary["train_labels"] + + if self.freqai_info.get("data_split_parameters", {}).get("test_size", 0.1) == 0: + eval_set = None + else: + eval_set = [(data_dictionary["test_features"], data_dictionary["test_labels"])] + + sample_weight = data_dictionary["train_weights"] + + xgb_model = self.get_init_model(dk.pair) + + model = xgb.XGBRegressor(**self.model_training_parameters) + + model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set, xgb_model=xgb_model) + + return model diff --git a/requirements-freqai.txt b/requirements-freqai.txt index 26e4617af..e8d950382 100644 --- a/requirements-freqai.txt +++ b/requirements-freqai.txt @@ -6,3 +6,4 @@ scikit-learn==1.1.2 joblib==1.1.0 catboost==1.0.6; platform_machine != 'aarch64' lightgbm==3.3.2 +xgboost==1.6.2 diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 5441b3c24..7783c00e7 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -172,6 +172,37 @@ def test_train_model_in_series_LightGBMClassifier(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) +def test_train_model_in_series_XGBoostRegressor(mocker, freqai_conf): + freqai_conf.update({"timerange": "20180110-20180130"}) + freqai_conf.update({"freqaimodel": "XGBoostRegressor"}) + freqai_conf.update({"strategy": "freqai_test_strat"}) + + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange) + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = True + freqai.dk = FreqaiDataKitchen(freqai_conf) + timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(timerange, freqai.dk) + + freqai.dd.pair_dict = MagicMock() + + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") + + freqai.train_model_in_series(new_timerange, "ADA/BTC", + strategy, freqai.dk, data_load_timerange) + + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").is_file() + + shutil.rmtree(Path(freqai.dk.full_path)) + + def test_start_backtesting(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180130"}) freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) From df6e43d2c599badef3247f8878cacec2a81f5f79 Mon Sep 17 00:00:00 2001 From: Emre Date: Fri, 9 Sep 2022 00:11:09 +0300 Subject: [PATCH 250/592] Add XGBoostRegressorMultiTarget class --- .../XGBoostRegressorMultiTarget.py | 43 +++++++++++++++++++ tests/freqai/test_freqai_interface.py | 31 +++++++++++++ 2 files changed, 74 insertions(+) create mode 100644 freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py new file mode 100644 index 000000000..5283501d1 --- /dev/null +++ b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py @@ -0,0 +1,43 @@ +import logging +from typing import Any, Dict + +from sklearn.multioutput import MultiOutputRegressor +from xgboost import XGBRegressor + +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel + + +logger = logging.getLogger(__name__) + + +class XGBoostRegressorMultiTarget(BaseRegressionModel): + """ + User created prediction model. The class needs to override three necessary + functions, predict(), train(), fit(). The class inherits ModelHandler which + has its own DataHandler where data is held, saved, loaded, and managed. + """ + + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: + """ + User sets up the training and test data to fit their desired model here + :param data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. + """ + + xgb = XGBRegressor(**self.model_training_parameters) + + X = data_dictionary["train_features"] + y = data_dictionary["train_labels"] + eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) + sample_weight = data_dictionary["train_weights"] + + if self.continual_learning: + logger.warning('Continual learning not supported for MultiTarget models') + + model = MultiOutputRegressor(estimator=xgb) + model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) + train_score = model.score(X, y) + test_score = model.score(*eval_set) + logger.info(f"Train score {train_score}, Test score {test_score}") + return model diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 7783c00e7..ff0eb24a9 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -203,6 +203,37 @@ def test_train_model_in_series_XGBoostRegressor(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) +def test_train_model_in_series_XGBoostRegressorMultiModel(mocker, freqai_conf): + freqai_conf.update({"timerange": "20180110-20180130"}) + freqai_conf.update({"freqaimodel": "XGBoostRegressorMultiTarget"}) + freqai_conf.update({"strategy": "freqai_test_multimodel_strat"}) + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange) + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = True + freqai.dk = FreqaiDataKitchen(freqai_conf) + timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(timerange, freqai.dk) + + freqai.dd.pair_dict = MagicMock() + + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") + + freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + + assert len(freqai.dk.label_list) == 2 + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").is_file() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").is_file() + assert len(freqai.dk.data['training_features_list']) == 26 + + shutil.rmtree(Path(freqai.dk.full_path)) + + def test_start_backtesting(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180130"}) freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) From acb410a0defb4626b52879b56e3d4ab8824c1085 Mon Sep 17 00:00:00 2001 From: Emre Date: Fri, 9 Sep 2022 00:11:43 +0300 Subject: [PATCH 251/592] Remove verbosity params --- freqtrade/freqai/prediction_models/XGBoostRegressor.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressor.py b/freqtrade/freqai/prediction_models/XGBoostRegressor.py index a8f250d16..acc4386f5 100644 --- a/freqtrade/freqai/prediction_models/XGBoostRegressor.py +++ b/freqtrade/freqai/prediction_models/XGBoostRegressor.py @@ -1,7 +1,7 @@ import logging from typing import Any, Dict -import xgboost as xgb +from xgboost import XGBRegressor from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel @@ -24,9 +24,6 @@ class XGBoostRegressor(BaseRegressionModel): all the training and test data/labels. """ - xgb.set_config(verbosity=2) - xgb.config_context(verbosity=2) - X = data_dictionary["train_features"] y = data_dictionary["train_labels"] @@ -39,7 +36,7 @@ class XGBoostRegressor(BaseRegressionModel): xgb_model = self.get_init_model(dk.pair) - model = xgb.XGBRegressor(**self.model_training_parameters) + model = XGBRegressor(**self.model_training_parameters) model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set, xgb_model=xgb_model) From a826c0eb837af2f4f4b68660481e5c9f436caac7 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 9 Sep 2022 19:17:15 +0200 Subject: [PATCH 252/592] ensure signatures match, reduce verbosity --- freqtrade/freqai/freqai_interface.py | 8 +++--- .../prediction_models/BaseClassifierModel.py | 26 +++++++++---------- .../prediction_models/BaseRegressionModel.py | 26 +++++++++---------- .../prediction_models/BaseTensorFlowModel.py | 10 +++---- 4 files changed, 35 insertions(+), 35 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 101df88ec..e4f77a9cf 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -673,12 +673,12 @@ class IFreqaiModel(ABC): # See freqai/prediction_models/CatboostPredictionModel.py for an example. @abstractmethod - def train(self, unfiltered_dataframe: DataFrame, pair: str, + def train(self, unfiltered_df: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datahandler for storing, saving, loading, and analyzing the data. - :param unfiltered_dataframe: Full dataframe for the current training period + :param unfiltered_df: Full dataframe for the current training period :param metadata: pair metadata from strategy. :return: Trained model which can be used to inference (self.predict) """ @@ -697,11 +697,11 @@ class IFreqaiModel(ABC): @abstractmethod def predict( - self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = True, **kwargs + self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs ) -> Tuple[DataFrame, NDArray[np.int_]]: """ Filter the prediction features data and predict with it. - :param unfiltered_dataframe: Full dataframe for the current backtest period. + :param unfiltered_df: Full dataframe for the current backtest period. :param dk: FreqaiDataKitchen = Data management/analysis tool associated to present pair only :param first: boolean = whether this is the first prediction or not. :return: diff --git a/freqtrade/freqai/prediction_models/BaseClassifierModel.py b/freqtrade/freqai/prediction_models/BaseClassifierModel.py index 291bacc82..5142ffb0d 100644 --- a/freqtrade/freqai/prediction_models/BaseClassifierModel.py +++ b/freqtrade/freqai/prediction_models/BaseClassifierModel.py @@ -21,12 +21,12 @@ class BaseClassifierModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs + self, unfiltered_df: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen for storing, saving, loading, and analyzing the data. - :param unfiltered_dataframe: Full dataframe for the current training period + :param unfiltered_df: Full dataframe for the current training period :param metadata: pair metadata from strategy. :return: :model: Trained model which can be used to inference (self.predict) @@ -36,14 +36,14 @@ class BaseClassifierModel(IFreqaiModel): # filter the features requested by user in the configuration file and elegantly handle NaNs features_filtered, labels_filtered = dk.filter_features( - unfiltered_dataframe, + unfiltered_df, dk.training_features_list, dk.label_list, training_filter=True, ) - start_date = unfiltered_dataframe["date"].iloc[0].strftime("%Y-%m-%d") - end_date = unfiltered_dataframe["date"].iloc[-1].strftime("%Y-%m-%d") + start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d") + end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d") logger.info(f"-------------------- Training on data from {start_date} to " f"{end_date}--------------------") # split data into train/test data. @@ -68,25 +68,25 @@ class BaseClassifierModel(IFreqaiModel): return model def predict( - self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False, **kwargs + self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: """ Filter the prediction features data and predict with it. - :param: unfiltered_dataframe: Full dataframe for the current backtest period. + :param: unfiltered_df: Full dataframe for the current backtest period. :return: :pred_df: dataframe containing the predictions :do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove data (NaNs) or felt uncertain about data (PCA and DI index) """ - dk.find_features(dataframe) - filtered_dataframe, _ = dk.filter_features( - dataframe, dk.training_features_list, training_filter=False + dk.find_features(unfiltered_df) + filtered_df, _ = dk.filter_features( + unfiltered_df, dk.training_features_list, training_filter=False ) - filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe) - dk.data_dictionary["prediction_features"] = filtered_dataframe + filtered_df = dk.normalize_data_from_metadata(filtered_df) + dk.data_dictionary["prediction_features"] = filtered_df - self.data_cleaning_predict(dk, filtered_dataframe) + self.data_cleaning_predict(dk, filtered_df) predictions = self.model.predict(dk.data_dictionary["prediction_features"]) pred_df = DataFrame(predictions, columns=dk.label_list) diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py index da6fba571..1d87e42c0 100644 --- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py +++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py @@ -20,12 +20,12 @@ class BaseRegressionModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs + self, unfiltered_df: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen for storing, saving, loading, and analyzing the data. - :param unfiltered_dataframe: Full dataframe for the current training period + :param unfiltered_df: Full dataframe for the current training period :param metadata: pair metadata from strategy. :return: :model: Trained model which can be used to inference (self.predict) @@ -35,14 +35,14 @@ class BaseRegressionModel(IFreqaiModel): # filter the features requested by user in the configuration file and elegantly handle NaNs features_filtered, labels_filtered = dk.filter_features( - unfiltered_dataframe, + unfiltered_df, dk.training_features_list, dk.label_list, training_filter=True, ) - start_date = unfiltered_dataframe["date"].iloc[0].strftime("%Y-%m-%d") - end_date = unfiltered_dataframe["date"].iloc[-1].strftime("%Y-%m-%d") + start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d") + end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d") logger.info(f"-------------------- Training on data from {start_date} to " f"{end_date}--------------------") # split data into train/test data. @@ -67,26 +67,26 @@ class BaseRegressionModel(IFreqaiModel): return model def predict( - self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False, **kwargs + self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: """ Filter the prediction features data and predict with it. - :param: unfiltered_dataframe: Full dataframe for the current backtest period. + :param: unfiltered_df: Full dataframe for the current backtest period. :return: :pred_df: dataframe containing the predictions :do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove data (NaNs) or felt uncertain about data (PCA and DI index) """ - dk.find_features(dataframe) - filtered_dataframe, _ = dk.filter_features( - dataframe, dk.training_features_list, training_filter=False + dk.find_features(unfiltered_df) + filtered_df, _ = dk.filter_features( + unfiltered_df, dk.training_features_list, training_filter=False ) - filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe) - dk.data_dictionary["prediction_features"] = filtered_dataframe + filtered_df = dk.normalize_data_from_metadata(filtered_df) + dk.data_dictionary["prediction_features"] = filtered_df # optional additional data cleaning/analysis - self.data_cleaning_predict(dk, filtered_dataframe) + self.data_cleaning_predict(dk, filtered_df) predictions = self.model.predict(dk.data_dictionary["prediction_features"]) pred_df = DataFrame(predictions, columns=dk.label_list) diff --git a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py index 6fb49239b..eea80f3a2 100644 --- a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py +++ b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py @@ -17,12 +17,12 @@ class BaseTensorFlowModel(IFreqaiModel): """ def train( - self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs + self, unfiltered_df: DataFrame, pair: str, dk: FreqaiDataKitchen, **kwargs ) -> Any: """ Filter the training data and train a model to it. Train makes heavy use of the datakitchen for storing, saving, loading, and analyzing the data. - :param unfiltered_dataframe: Full dataframe for the current training period + :param unfiltered_df: Full dataframe for the current training period :param metadata: pair metadata from strategy. :return: :model: Trained model which can be used to inference (self.predict) @@ -32,14 +32,14 @@ class BaseTensorFlowModel(IFreqaiModel): # filter the features requested by user in the configuration file and elegantly handle NaNs features_filtered, labels_filtered = dk.filter_features( - unfiltered_dataframe, + unfiltered_df, dk.training_features_list, dk.label_list, training_filter=True, ) - start_date = unfiltered_dataframe["date"].iloc[0].strftime("%Y-%m-%d") - end_date = unfiltered_dataframe["date"].iloc[-1].strftime("%Y-%m-%d") + start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d") + end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d") logger.info(f"-------------------- Training on data from {start_date} to " f"{end_date}--------------------") # split data into train/test data. From 6cbc03a96a6ca4234ec1ef06153927894ae38f35 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 11:38:42 -0600 Subject: [PATCH 253/592] support jwt token in place of ws token --- freqtrade/rpc/api_server/api_auth.py | 32 ++++++++++++++++++++-------- freqtrade/rpc/api_server/api_ws.py | 4 ++++ tests/rpc/test_rpc_apiserver.py | 12 ++++++----- 3 files changed, 34 insertions(+), 14 deletions(-) diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index 0d1378b6d..a2b722f0a 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -4,7 +4,7 @@ from datetime import datetime, timedelta from typing import Any, Dict, Union import jwt -from fastapi import APIRouter, Depends, HTTPException, WebSocket, status +from fastapi import APIRouter, Depends, HTTPException, Query, WebSocket, status from fastapi.security import OAuth2PasswordBearer from fastapi.security.http import HTTPBasic, HTTPBasicCredentials @@ -29,7 +29,8 @@ httpbasic = HTTPBasic(auto_error=False) oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token", auto_error=False) -def get_user_from_token(token, secret_key: str, token_type: str = "access"): +def get_user_from_token(token, secret_key: str, token_type: str = "access", + raise_on_error: bool = True) -> Union[bool, str]: credentials_exception = HTTPException( status_code=status.HTTP_401_UNAUTHORIZED, detail="Could not validate credentials", @@ -39,12 +40,21 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access"): payload = jwt.decode(token, secret_key, algorithms=[ALGORITHM]) username: str = payload.get("identity", {}).get('u') if username is None: - raise credentials_exception + if raise_on_error: + raise credentials_exception + else: + return False if payload.get("type") != token_type: - raise credentials_exception + if raise_on_error: + raise credentials_exception + else: + return False except jwt.PyJWTError: - raise credentials_exception + if raise_on_error: + raise credentials_exception + else: + return False return username @@ -53,14 +63,18 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access"): # https://github.com/tiangolo/fastapi/blob/master/fastapi/security/api_key.py async def get_ws_token( ws: WebSocket, - token: Union[str, None] = None, + ws_token: Union[str, None] = Query(..., alias="token"), api_config: Dict[str, Any] = Depends(get_api_config) ): - secret_ws_token = api_config['ws_token'] + secret_ws_token = api_config.get('ws_token', 'secret_ws_t0ken.') + secret_jwt_key = api_config.get('jwt_secret_key', 'super-secret') - if token == secret_ws_token: + if secrets.compare_digest(secret_ws_token, ws_token): # Just return the token if it matches - return token + return ws_token + elif user := get_user_from_token(ws_token, secret_jwt_key, raise_on_error=False): + # If the token is a jwt, and it's valid return the user + return user else: logger.info("Denying websocket request") # If it doesn't match, close the websocket connection diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 16d5ef9a7..25d29a7ce 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -132,6 +132,10 @@ async def message_endpoint( else: await ws.close() + except RuntimeError: + # WebSocket was closed + await channel_manager.on_disconnect(ws) + except Exception as e: logger.error(f"Failed to serve - {ws.client}") # Log tracebacks to keep track of what errors are happening diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 6a37e7cdd..f1aa465f0 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -161,18 +161,20 @@ def test_api_auth(): def test_api_ws_auth(botclient): ftbot, client = botclient + def url(token): return f"/api/v1/message/ws?token={token}" bad_token = "bad-ws_token" - url = f"/api/v1/message/ws?token={bad_token}" - with pytest.raises(WebSocketDisconnect): - with client.websocket_connect(url) as websocket: + with client.websocket_connect(url(bad_token)) as websocket: websocket.receive() good_token = _TEST_WS_TOKEN - url = f"/api/v1/message/ws?token={good_token}" + with client.websocket_connect(url(good_token)) as websocket: + pass - with client.websocket_connect(url) as websocket: + jwt_secret = ftbot.config['api_server'].get('jwt_secret_key', 'super-secret') + jwt_token = create_token({'identity': {'u': 'Freqtrade'}}, jwt_secret) + with client.websocket_connect(url(jwt_token)) as websocket: pass From c13bec26d1b01a6173396dcf1f4daed9236eaad8 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 9 Sep 2022 19:41:28 +0200 Subject: [PATCH 254/592] add freqaimodel to hyperopt command --- docs/freqai.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/freqai.md b/docs/freqai.md index 92e019dfe..09a51c713 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -541,7 +541,7 @@ for each pair, for each backtesting window within the expanded `--timerange`. Users can hyperopt using the same command as typical [hyperopt](hyperopt.md): ```bash -freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 +freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 ``` Users need to have the data pre-downloaded in the same fashion as if they were doing a FreqAI [backtest](#backtesting). In addition, users must consider some restrictions when trying to [Hyperopt](hyperopt.md) FreqAI strategies: From 826eb8525470e8fa638f61247ed80e2f369493c5 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 11:58:30 -0600 Subject: [PATCH 255/592] update confige example --- config_examples/config_full.example.json | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 37c604c72..d8d552814 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -173,7 +173,7 @@ "CORS_origins": [], "username": "freqtrader", "password": "SuperSecurePassword", - "ws_token": "a_secret_ws_token" + "ws_token": "secret_ws_t0ken." }, // The ExternalMessageConsumer config should only be enabled on an instance // that listens to outside data from another instance. This should not be enabled @@ -184,11 +184,11 @@ { "name": "default", "url": "ws://localhost:8081/api/v1/message/ws", - "ws_token": "a_secret_ws_token" + "ws_token": "secret_ws_t0ken." } ], - "reply_timeout": 30, - "ping_timeout": 5, + "poll_timeout": 300, + "ping_timeout": 10, "sleep_time": 10, "remove_entry_exit_signals": false }, From 37fcbeba580143179c9344021ba2b5ceea516902 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 9 Sep 2022 19:58:55 +0200 Subject: [PATCH 256/592] Update backtesting output wording to Entries --- docs/backtesting.md | 74 ++++++++++++------------- freqtrade/optimize/optimize_reports.py | 5 +- tests/optimize/test_optimize_reports.py | 24 ++++---- 3 files changed, 52 insertions(+), 51 deletions(-) diff --git a/docs/backtesting.md b/docs/backtesting.md index 8b2fdc345..f20a53d22 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -107,7 +107,7 @@ Strategy arguments: ## Test your strategy with Backtesting -Now you have good Buy and Sell strategies and some historic data, you want to test it against +Now you have good Entry and exit strategies and some historic data, you want to test it against real data. This is what we call [backtesting](https://en.wikipedia.org/wiki/Backtesting). Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHLCV) data from `user_data/data/` by default. @@ -215,7 +215,7 @@ Sometimes your account has certain fee rebates (fee reductions starting with a c To account for this in backtesting, you can use the `--fee` command line option to supply this value to backtesting. This fee must be a ratio, and will be applied twice (once for trade entry, and once for trade exit). -For example, if the buying and selling commission fee is 0.1% (i.e., 0.001 written as ratio), then you would run backtesting as the following: +For example, if the commission fee per order is 0.1% (i.e., 0.001 written as ratio), then you would run backtesting as the following: ```bash freqtrade backtesting --fee 0.001 @@ -252,41 +252,41 @@ The most important in the backtesting is to understand the result. A backtesting result will look like that: ``` -========================================================= BACKTESTING REPORT ========================================================== -| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins Draws Loss Win% | -|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:-------------|-------------------------:| -| ADA/BTC | 35 | -0.11 | -3.88 | -0.00019428 | -1.94 | 4:35:00 | 14 0 21 40.0 | -| ARK/BTC | 11 | -0.41 | -4.52 | -0.00022647 | -2.26 | 2:03:00 | 3 0 8 27.3 | -| BTS/BTC | 32 | 0.31 | 9.78 | 0.00048938 | 4.89 | 5:05:00 | 18 0 14 56.2 | -| DASH/BTC | 13 | -0.08 | -1.07 | -0.00005343 | -0.53 | 4:39:00 | 6 0 7 46.2 | -| ENG/BTC | 18 | 1.36 | 24.54 | 0.00122807 | 12.27 | 2:50:00 | 8 0 10 44.4 | -| EOS/BTC | 36 | 0.08 | 3.06 | 0.00015304 | 1.53 | 3:34:00 | 16 0 20 44.4 | -| ETC/BTC | 26 | 0.37 | 9.51 | 0.00047576 | 4.75 | 6:14:00 | 11 0 15 42.3 | -| ETH/BTC | 33 | 0.30 | 9.96 | 0.00049856 | 4.98 | 7:31:00 | 16 0 17 48.5 | -| IOTA/BTC | 32 | 0.03 | 1.09 | 0.00005444 | 0.54 | 3:12:00 | 14 0 18 43.8 | -| LSK/BTC | 15 | 1.75 | 26.26 | 0.00131413 | 13.13 | 2:58:00 | 6 0 9 40.0 | -| LTC/BTC | 32 | -0.04 | -1.38 | -0.00006886 | -0.69 | 4:49:00 | 11 0 21 34.4 | -| NANO/BTC | 17 | 1.26 | 21.39 | 0.00107058 | 10.70 | 1:55:00 | 10 0 7 58.5 | -| NEO/BTC | 23 | 0.82 | 18.97 | 0.00094936 | 9.48 | 2:59:00 | 10 0 13 43.5 | -| REQ/BTC | 9 | 1.17 | 10.54 | 0.00052734 | 5.27 | 3:47:00 | 4 0 5 44.4 | -| XLM/BTC | 16 | 1.22 | 19.54 | 0.00097800 | 9.77 | 3:15:00 | 7 0 9 43.8 | -| XMR/BTC | 23 | -0.18 | -4.13 | -0.00020696 | -2.07 | 5:30:00 | 12 0 11 52.2 | -| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 0 23 34.3 | -| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 0 15 31.8 | -| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 | +========================================================= BACKTESTING REPORT ========================================================= +| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins Draws Loss Win% | +|:---------|--------:|---------------:|---------------:|-----------------:|---------------:|:-------------|-------------------------:| +| ADA/BTC | 35 | -0.11 | -3.88 | -0.00019428 | -1.94 | 4:35:00 | 14 0 21 40.0 | +| ARK/BTC | 11 | -0.41 | -4.52 | -0.00022647 | -2.26 | 2:03:00 | 3 0 8 27.3 | +| BTS/BTC | 32 | 0.31 | 9.78 | 0.00048938 | 4.89 | 5:05:00 | 18 0 14 56.2 | +| DASH/BTC | 13 | -0.08 | -1.07 | -0.00005343 | -0.53 | 4:39:00 | 6 0 7 46.2 | +| ENG/BTC | 18 | 1.36 | 24.54 | 0.00122807 | 12.27 | 2:50:00 | 8 0 10 44.4 | +| EOS/BTC | 36 | 0.08 | 3.06 | 0.00015304 | 1.53 | 3:34:00 | 16 0 20 44.4 | +| ETC/BTC | 26 | 0.37 | 9.51 | 0.00047576 | 4.75 | 6:14:00 | 11 0 15 42.3 | +| ETH/BTC | 33 | 0.30 | 9.96 | 0.00049856 | 4.98 | 7:31:00 | 16 0 17 48.5 | +| IOTA/BTC | 32 | 0.03 | 1.09 | 0.00005444 | 0.54 | 3:12:00 | 14 0 18 43.8 | +| LSK/BTC | 15 | 1.75 | 26.26 | 0.00131413 | 13.13 | 2:58:00 | 6 0 9 40.0 | +| LTC/BTC | 32 | -0.04 | -1.38 | -0.00006886 | -0.69 | 4:49:00 | 11 0 21 34.4 | +| NANO/BTC | 17 | 1.26 | 21.39 | 0.00107058 | 10.70 | 1:55:00 | 10 0 7 58.5 | +| NEO/BTC | 23 | 0.82 | 18.97 | 0.00094936 | 9.48 | 2:59:00 | 10 0 13 43.5 | +| REQ/BTC | 9 | 1.17 | 10.54 | 0.00052734 | 5.27 | 3:47:00 | 4 0 5 44.4 | +| XLM/BTC | 16 | 1.22 | 19.54 | 0.00097800 | 9.77 | 3:15:00 | 7 0 9 43.8 | +| XMR/BTC | 23 | -0.18 | -4.13 | -0.00020696 | -2.07 | 5:30:00 | 12 0 11 52.2 | +| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 0 23 34.3 | +| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 0 15 31.8 | +| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 | ========================================================= EXIT REASON STATS ========================================================== -| Exit Reason | Sells | Wins | Draws | Losses | +| Exit Reason | Exits | Wins | Draws | Losses | |:-------------------|--------:|------:|-------:|--------:| | trailing_stop_loss | 205 | 150 | 0 | 55 | | stop_loss | 166 | 0 | 0 | 166 | | exit_signal | 56 | 36 | 0 | 20 | | force_exit | 2 | 0 | 0 | 2 | ====================================================== LEFT OPEN TRADES REPORT ====================================================== -| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Win Draw Loss Win% | -|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:| -| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 0 0 100 | -| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 0 0 100 | -| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 0 0 100 | +| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Win Draw Loss Win% | +|:---------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:| +| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 0 0 100 | +| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 0 0 100 | +| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 0 0 100 | ================== SUMMARY METRICS ================== | Metric | Value | |-----------------------------+---------------------| @@ -356,7 +356,7 @@ The column `Avg Profit %` shows the average profit for all trades made while the The column `Tot Profit %` shows instead the total profit % in relation to the starting balance. In the above results, we have a starting balance of 0.01 BTC and an absolute profit of 0.00762792 BTC - so the `Tot Profit %` will be `(0.00762792 / 0.01) * 100 ~= 76.2%`. -Your strategy performance is influenced by your buy strategy, your exit strategy, and also by the `minimal_roi` and `stop_loss` you have set. +Your strategy performance is influenced by your entry strategy, your exit strategy, and also by the `minimal_roi` and `stop_loss` you have set. For example, if your `minimal_roi` is only `"0": 0.01` you cannot expect the bot to make more profit than 1% (because it will exit every time a trade reaches 1%). @@ -515,7 +515,7 @@ You can then load the trades to perform further analysis as shown in the [data a Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions: - Exchange [trading limits](#trading-limits-in-backtesting) are respected -- Buys happen at open-price +- Entries happen at open-price - All orders are filled at the requested price (no slippage, no unfilled orders) - Exit-signal exits happen at open-price of the consecutive candle - Exit-signal is favored over Stoploss, because exit-signals are assumed to trigger on candle's open @@ -612,11 +612,11 @@ There will be an additional table comparing win/losses of the different strategi Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy. ``` -=========================================================== STRATEGY SUMMARY ========================================================================= -| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | Drawdown % | -|:------------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:| -| Strategy1 | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 | 45.2 | -| Strategy2 | 1487 | -0.13 | -197.58 | -0.00988917 | -98.79 | 4:43:00 | 662 | 0 | 825 | 241.68 | +=========================================================== STRATEGY SUMMARY =========================================================================== +| Strategy | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | Drawdown % | +|:------------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:| +| Strategy1 | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 | 45.2 | +| Strategy2 | 1487 | -0.13 | -197.58 | -0.00988917 | -98.79 | 4:43:00 | 662 | 0 | 825 | 241.68 | ``` ## Next step diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 519022db2..fa6c3f161 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -75,7 +75,8 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]: '.2f', 'd', 's', 's'] -def _get_line_header(first_column: str, stake_currency: str, direction: str = 'Buys') -> List[str]: +def _get_line_header(first_column: str, stake_currency: str, + direction: str = 'Entries') -> List[str]: """ Generate header lines (goes in line with _generate_result_line()) """ @@ -642,7 +643,7 @@ def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_curr if (tag_type == "enter_tag"): headers = _get_line_header("TAG", stake_currency) else: - headers = _get_line_header("TAG", stake_currency, 'Sells') + headers = _get_line_header("TAG", stake_currency, 'Exits') floatfmt = _get_line_floatfmt(stake_currency) output = [ [ diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index 562e12820..5095f2fde 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -40,14 +40,14 @@ def test_text_table_bt_results(): ) result_str = ( - '| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |' - ' Avg Duration | Win Draw Loss Win% |\n' - '|---------+--------+----------------+----------------+------------------+----------------+' - '----------------+-------------------------|\n' - '| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |' - ' 0:20:00 | 2 0 1 66.7 |\n' - '| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |' - ' 0:20:00 | 2 0 1 66.7 |' + '| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | ' + 'Tot Profit % | Avg Duration | Win Draw Loss Win% |\n' + '|---------+-----------+----------------+----------------+------------------+' + '----------------+----------------+-------------------------|\n' + '| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | ' + '12.50 | 0:20:00 | 2 0 1 66.7 |\n' + '| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | ' + '12.50 | 0:20:00 | 2 0 1 66.7 |' ) pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC', @@ -402,13 +402,13 @@ def test_text_table_strategy(testdatadir): bt_res_data_comparison = bt_res_data.pop('strategy_comparison') result_str = ( - '| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |' + '| Strategy | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC |' ' Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |\n' - '|----------------+--------+----------------+----------------+------------------+' + '|----------------+-----------+----------------+----------------+------------------+' '----------------+----------------+-------------------------+-----------------------|\n' - '| StrategyTestV2 | 179 | 0.08 | 14.39 | 0.02608550 |' + '| StrategyTestV2 | 179 | 0.08 | 14.39 | 0.02608550 |' ' 260.85 | 3:40:00 | 170 0 9 95.0 | 0.00308222 BTC 8.67% |\n' - '| TestStrategy | 179 | 0.08 | 14.39 | 0.02608550 |' + '| TestStrategy | 179 | 0.08 | 14.39 | 0.02608550 |' ' 260.85 | 3:40:00 | 170 0 9 95.0 | 0.00308222 BTC 8.67% |' ) From 97be3318f447445dfaab52f8b4d08ba2f8e59112 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 9 Sep 2022 20:17:34 +0200 Subject: [PATCH 257/592] Use Datetime_format from constants --- freqtrade/data/history/history_utils.py | 8 ++++---- freqtrade/freqai/freqai_interface.py | 5 +++-- tests/data/test_history.py | 6 +++--- tests/test_persistence.py | 10 +++++----- 4 files changed, 15 insertions(+), 14 deletions(-) diff --git a/freqtrade/data/history/history_utils.py b/freqtrade/data/history/history_utils.py index 7a3fa4e0c..6a6e29429 100644 --- a/freqtrade/data/history/history_utils.py +++ b/freqtrade/data/history/history_utils.py @@ -228,9 +228,9 @@ def _download_pair_history(pair: str, *, ) logger.debug("Current Start: %s", - f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None') + f"{data.iloc[0]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None') logger.debug("Current End: %s", - f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None') + f"{data.iloc[-1]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None') # Default since_ms to 30 days if nothing is given new_data = exchange.get_historic_ohlcv(pair=pair, @@ -254,9 +254,9 @@ def _download_pair_history(pair: str, *, fill_missing=False, drop_incomplete=False) logger.debug("New Start: %s", - f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None') + f"{data.iloc[0]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None') logger.debug("New End: %s", - f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None') + f"{data.iloc[-1]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None') data_handler.ohlcv_store(pair, timeframe, data=data, candle_type=candle_type) return True diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index c5ac17a3a..7a48f6e15 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -14,6 +14,7 @@ from numpy.typing import NDArray from pandas import DataFrame from freqtrade.configuration import TimeRange +from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.enums import RunMode from freqtrade.exceptions import OperationalException from freqtrade.exchange import timeframe_to_seconds @@ -232,10 +233,10 @@ class IFreqaiModel(ABC): trained_timestamp = tr_train tr_train_startts_str = datetime.fromtimestamp( tr_train.startts, - tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S") + tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT) tr_train_stopts_str = datetime.fromtimestamp( tr_train.stopts, - tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S") + tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT) logger.info( f"Training {metadata['pair']}, {self.pair_it}/{self.total_pairs} pairs" f" from {tr_train_startts_str} to {tr_train_stopts_str}, {train_it}/{total_trains} " diff --git a/tests/data/test_history.py b/tests/data/test_history.py index 9709e7ad0..8081e984f 100644 --- a/tests/data/test_history.py +++ b/tests/data/test_history.py @@ -13,7 +13,7 @@ from pandas import DataFrame from pandas.testing import assert_frame_equal from freqtrade.configuration import TimeRange -from freqtrade.constants import AVAILABLE_DATAHANDLERS +from freqtrade.constants import AVAILABLE_DATAHANDLERS, DATETIME_PRINT_FORMAT from freqtrade.data.converter import ohlcv_to_dataframe from freqtrade.data.history.hdf5datahandler import HDF5DataHandler from freqtrade.data.history.history_utils import (_download_pair_history, _download_trades_history, @@ -386,7 +386,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None: assert td != len(data['UNITTEST/BTC']) start_real = data['UNITTEST/BTC'].iloc[0, 0] assert log_has(f'UNITTEST/BTC, spot, 5m, ' - f'data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}', + f'data starts at {start_real.strftime(DATETIME_PRINT_FORMAT)}', caplog) # Make sure we start fresh - test missing data at end caplog.clear() @@ -401,7 +401,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None: # Shift endtime with +5 - as last candle is dropped (partial candle) end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5) assert log_has(f'UNITTEST/BTC, spot, 5m, ' - f'data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}', + f'data ends at {end_real.strftime(DATETIME_PRINT_FORMAT)}', caplog) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index cdca3bc4d..e7f218c02 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -9,7 +9,7 @@ import arrow import pytest from sqlalchemy import create_engine, text -from freqtrade import constants +from freqtrade.constants import DATETIME_PRINT_FORMAT, DEFAULT_DB_PROD_URL from freqtrade.enums import TradingMode from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.persistence import LocalTrade, Order, Trade, init_db @@ -52,7 +52,7 @@ def test_init_invalid_db_url(): def test_init_prod_db(default_conf, mocker): default_conf.update({'dry_run': False}) - default_conf.update({'db_url': constants.DEFAULT_DB_PROD_URL}) + default_conf.update({'db_url': DEFAULT_DB_PROD_URL}) create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock()) @@ -1739,7 +1739,7 @@ def test_to_json(fee): 'base_currency': 'ADA', 'quote_currency': 'USDT', 'is_open': None, - 'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"), + 'open_date': trade.open_date.strftime(DATETIME_PRINT_FORMAT), 'open_timestamp': int(trade.open_date.timestamp() * 1000), 'open_order_id': 'dry_run_buy_12345', 'close_date': None, @@ -1817,9 +1817,9 @@ def test_to_json(fee): 'pair': 'XRP/BTC', 'base_currency': 'XRP', 'quote_currency': 'BTC', - 'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"), + 'open_date': trade.open_date.strftime(DATETIME_PRINT_FORMAT), 'open_timestamp': int(trade.open_date.timestamp() * 1000), - 'close_date': trade.close_date.strftime("%Y-%m-%d %H:%M:%S"), + 'close_date': trade.close_date.strftime(DATETIME_PRINT_FORMAT), 'close_timestamp': int(trade.close_date.timestamp() * 1000), 'open_rate': 0.123, 'close_rate': 0.125, From 939fb7acb338202dfa2bf945ee51d95e37e14e97 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 9 Sep 2022 20:31:30 +0200 Subject: [PATCH 258/592] Fix enum imports --- freqtrade/commands/db_commands.py | 2 +- freqtrade/exchange/okx.py | 3 +-- freqtrade/rpc/discord.py | 2 +- freqtrade/strategy/interface.py | 5 ++--- freqtrade/strategy/parameters.py | 2 +- tests/exchange/test_okx.py | 3 +-- tests/strategy/test_interface.py | 3 +-- 7 files changed, 8 insertions(+), 12 deletions(-) diff --git a/freqtrade/commands/db_commands.py b/freqtrade/commands/db_commands.py index 618b5cb6e..c424016b1 100644 --- a/freqtrade/commands/db_commands.py +++ b/freqtrade/commands/db_commands.py @@ -4,7 +4,7 @@ from typing import Any, Dict from sqlalchemy import func from freqtrade.configuration.config_setup import setup_utils_configuration -from freqtrade.enums.runmode import RunMode +from freqtrade.enums import RunMode logger = logging.getLogger(__name__) diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py index 9340dd0e4..49f8ea107 100644 --- a/freqtrade/exchange/okx.py +++ b/freqtrade/exchange/okx.py @@ -4,8 +4,7 @@ from typing import Dict, List, Optional, Tuple import ccxt from freqtrade.constants import BuySell -from freqtrade.enums import MarginMode, TradingMode -from freqtrade.enums.candletype import CandleType +from freqtrade.enums import CandleType, MarginMode, TradingMode from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError from freqtrade.exchange import Exchange, date_minus_candles from freqtrade.exchange.common import retrier diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py index 5991f7126..85acfae4e 100644 --- a/freqtrade/rpc/discord.py +++ b/freqtrade/rpc/discord.py @@ -1,7 +1,7 @@ import logging from typing import Any, Dict -from freqtrade.enums.rpcmessagetype import RPCMessageType +from freqtrade.enums import RPCMessageType from freqtrade.rpc import RPC from freqtrade.rpc.webhook import Webhook diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 70cc7fdb3..9401ebebe 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -12,9 +12,8 @@ from pandas import DataFrame from freqtrade.constants import ListPairsWithTimeframes from freqtrade.data.dataprovider import DataProvider -from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, SignalTagType, - SignalType, TradingMode) -from freqtrade.enums.runmode import RunMode +from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RunMode, SignalDirection, + SignalTagType, SignalType, TradingMode) from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds from freqtrade.persistence import Order, PairLocks, Trade diff --git a/freqtrade/strategy/parameters.py b/freqtrade/strategy/parameters.py index c6037ae0b..796fb9514 100644 --- a/freqtrade/strategy/parameters.py +++ b/freqtrade/strategy/parameters.py @@ -7,7 +7,7 @@ from abc import ABC, abstractmethod from contextlib import suppress from typing import Any, Optional, Sequence, Union -from freqtrade.enums.hyperoptstate import HyperoptState +from freqtrade.enums import HyperoptState from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer diff --git a/tests/exchange/test_okx.py b/tests/exchange/test_okx.py index b475b84ff..12322acae 100644 --- a/tests/exchange/test_okx.py +++ b/tests/exchange/test_okx.py @@ -4,8 +4,7 @@ from unittest.mock import MagicMock, PropertyMock import pytest -from freqtrade.enums import MarginMode, TradingMode -from freqtrade.enums.candletype import CandleType +from freqtrade.enums import CandleType, MarginMode, TradingMode from freqtrade.exchange.exchange import timeframe_to_minutes from tests.conftest import get_mock_coro, get_patched_exchange, log_has from tests.exchange.test_exchange import ccxt_exceptionhandlers diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py index 65ee05d71..070e78b1d 100644 --- a/tests/strategy/test_interface.py +++ b/tests/strategy/test_interface.py @@ -11,8 +11,7 @@ from pandas import DataFrame from freqtrade.configuration import TimeRange from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history import load_data -from freqtrade.enums import ExitCheckTuple, ExitType, SignalDirection -from freqtrade.enums.hyperoptstate import HyperoptState +from freqtrade.enums import ExitCheckTuple, ExitType, HyperoptState, SignalDirection from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer from freqtrade.optimize.space import SKDecimal From 05581db4e387ae8c1b2ae7d097e3b20f349e4b16 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 9 Sep 2022 20:37:21 +0200 Subject: [PATCH 259/592] ensure columns are only dropped in training --- freqtrade/freqai/data_kitchen.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 790b3c078..1af01cb6b 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -209,14 +209,13 @@ class FreqaiDataKitchen: filtered_df = unfiltered_df.filter(training_feature_list, axis=1) filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan) - const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index) - if const_cols: - filtered_df = filtered_df.filter(filtered_df.columns.difference(const_cols)) - logger.warning(f"Removed features {const_cols} with constant values.") - drop_index = pd.isnull(filtered_df).any(1) # get the rows that have NaNs, drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement. if (training_filter): + const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index) + if const_cols: + filtered_df = filtered_df.filter(filtered_df.columns.difference(const_cols)) + logger.warning(f"Removed features {const_cols} with constant values.") # we don't care about total row number (total no. datapoints) in training, we only care # about removing any row with NaNs # if labels has multiple columns (user wants to train multiple modelEs), we detect here From 2f6a61521f2bed67a40ed43d08ef53232b7e2ac5 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 9 Sep 2022 17:14:40 -0600 Subject: [PATCH 260/592] add more tests --- tests/data/test_dataprovider.py | 70 +++++++++++++++++++++++++++++++++ tests/rpc/test_rpc_apiserver.py | 6 +++ tests/test_misc.py | 20 ++++++++-- 3 files changed, 92 insertions(+), 4 deletions(-) diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py index 49603feac..812688cb1 100644 --- a/tests/data/test_dataprovider.py +++ b/tests/data/test_dataprovider.py @@ -144,6 +144,76 @@ def test_available_pairs(mocker, default_conf, ohlcv_history): assert dp.available_pairs == [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe), ] +def test_producer_pairs(mocker, default_conf, ohlcv_history): + dataprovider = DataProvider(default_conf, None) + + producer = "default" + whitelist = ["XRP/BTC", "ETH/BTC"] + assert len(dataprovider.get_producer_pairs(producer)) == 0 + + dataprovider._set_producer_pairs(whitelist, producer) + assert len(dataprovider.get_producer_pairs(producer)) == 2 + + new_whitelist = ["BTC/USDT"] + dataprovider._set_producer_pairs(new_whitelist, producer) + assert dataprovider.get_producer_pairs(producer) == new_whitelist + + assert dataprovider.get_producer_pairs("bad") == [] + + +def test_external_df(mocker, default_conf, ohlcv_history): + dataprovider = DataProvider(default_conf, None) + + pair = 'BTC/USDT' + timeframe = default_conf['timeframe'] + candle_type = CandleType.SPOT + + empty_la = datetime.fromtimestamp(0, tz=timezone.utc) + + # no data has been added, any request should return an empty dataframe + dataframe, la = dataprovider.get_external_df(pair, timeframe, candle_type) + assert dataframe.empty + assert la == empty_la + + # the data is added, should return that added dataframe + dataprovider._add_external_df(pair, ohlcv_history, timeframe=timeframe, candle_type=candle_type) + dataframe, la = dataprovider.get_external_df(pair, timeframe, candle_type) + assert len(dataframe) > 0 + assert la > empty_la + + # no data on this producer, should return empty dataframe + dataframe, la = dataprovider.get_external_df(pair, producer_name='bad') + assert dataframe.empty + assert la == empty_la + + # non existent timeframe, empty dataframe + datframe, la = dataprovider.get_external_df(pair, timeframe='1h') + assert dataframe.empty + assert la == empty_la + + +def test_emit_df(mocker, default_conf, ohlcv_history): + mocker.patch('freqtrade.rpc.rpc_manager.RPCManager.__init__', MagicMock()) + rpc_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager', MagicMock()) + send_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager.send_msg', MagicMock()) + + dataprovider = DataProvider(default_conf, exchange=None, rpc=rpc_mock) + dataprovider_no_rpc = DataProvider(default_conf, exchange=None) + + pair = "BTC/USDT" + + # No emit yet + assert send_mock.call_count == 0 + + # Rpc is added, we call emit, should call send_msg + dataprovider._emit_df(pair, ohlcv_history) + assert send_mock.call_count == 1 + + # No rpc added, emit called, should not call send_msg + dataprovider_no_rpc._emit_df(pair, ohlcv_history) + assert send_mock.call_count == 1 + + def test_refresh(mocker, default_conf, ohlcv_history): refresh_mock = MagicMock() mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index f1aa465f0..17705e62e 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -158,6 +158,12 @@ def test_api_auth(): with pytest.raises(HTTPException): get_user_from_token(b'not_a_token', 'secret1234') + # Check returning false instead of error on bad token + assert not get_user_from_token(b'not_a_token', 'secret1234', raise_on_error=False) + + # Check returning false instead of error on bad token type + assert not get_user_from_token(token, 'secret1234', token_type='refresh', raise_on_error=False) + def test_api_ws_auth(botclient): ftbot, client = botclient diff --git a/tests/test_misc.py b/tests/test_misc.py index 107932be4..514fec54a 100644 --- a/tests/test_misc.py +++ b/tests/test_misc.py @@ -7,10 +7,11 @@ from unittest.mock import MagicMock import pytest -from freqtrade.misc import (decimals_per_coin, deep_merge_dicts, file_dump_json, file_load_json, - format_ms_time, pair_to_filename, parse_db_uri_for_logging, plural, - render_template, render_template_with_fallback, round_coin_value, - safe_value_fallback, safe_value_fallback2, shorten_date) +from freqtrade.misc import (dataframe_to_json, decimals_per_coin, deep_merge_dicts, file_dump_json, + file_load_json, format_ms_time, json_to_dataframe, pair_to_filename, + parse_db_uri_for_logging, plural, render_template, + render_template_with_fallback, round_coin_value, safe_value_fallback, + safe_value_fallback2, shorten_date) def test_decimals_per_coin(): @@ -219,3 +220,14 @@ def test_deep_merge_dicts(): res2['first']['rows']['test'] = 'asdf' assert deep_merge_dicts(a, deepcopy(b), allow_null_overrides=False) == res2 + + +def test_dataframe_json(ohlcv_history): + from pandas.testing import assert_frame_equal + json = dataframe_to_json(ohlcv_history) + dataframe = json_to_dataframe(json) + + assert list(ohlcv_history.columns) == list(dataframe.columns) + assert len(ohlcv_history) == len(dataframe) + + assert_frame_equal(ohlcv_history, dataframe) From 170bec0438e10955052fe7782ede7a42a2310cc8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 08:24:23 +0200 Subject: [PATCH 261/592] Fix failing XGBoost tests --- tests/freqai/test_freqai_interface.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index d95ead90c..5f8eeb086 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -174,7 +174,7 @@ def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_train_model_in_series_XGBoostRegressor(mocker, freqai_conf): +def test_extract_data_and_train_model_XGBoostRegressor(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "XGBoostRegressor"}) freqai_conf.update({"strategy": "freqai_test_strat"}) @@ -194,8 +194,8 @@ def test_train_model_in_series_XGBoostRegressor(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() @@ -205,7 +205,7 @@ def test_train_model_in_series_XGBoostRegressor(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_train_model_in_series_XGBoostRegressorMultiModel(mocker, freqai_conf): +def test_extract_data_and_train_model_XGBoostRegressorMultiModel(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "XGBoostRegressorMultiTarget"}) freqai_conf.update({"strategy": "freqai_test_multimodel_strat"}) @@ -224,7 +224,8 @@ def test_train_model_in_series_XGBoostRegressorMultiModel(mocker, freqai_conf): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") - freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.extract_data_and_train_model( + new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) assert len(freqai.dk.label_list) == 2 assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() From b344f78d007c20b75acefa181c2a2129f4787ecd Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 14:19:11 +0200 Subject: [PATCH 262/592] Improve logic for token validation --- freqtrade/rpc/api_server/api_auth.py | 35 +++++++++++----------------- freqtrade/rpc/api_server/api_ws.py | 4 ++-- tests/rpc/test_rpc_apiserver.py | 6 ----- 3 files changed, 16 insertions(+), 29 deletions(-) diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index a2b722f0a..767a2d5b9 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -29,8 +29,7 @@ httpbasic = HTTPBasic(auto_error=False) oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token", auto_error=False) -def get_user_from_token(token, secret_key: str, token_type: str = "access", - raise_on_error: bool = True) -> Union[bool, str]: +def get_user_from_token(token, secret_key: str, token_type: str = "access") -> str: credentials_exception = HTTPException( status_code=status.HTTP_401_UNAUTHORIZED, detail="Could not validate credentials", @@ -40,28 +39,19 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access", payload = jwt.decode(token, secret_key, algorithms=[ALGORITHM]) username: str = payload.get("identity", {}).get('u') if username is None: - if raise_on_error: - raise credentials_exception - else: - return False + raise credentials_exception if payload.get("type") != token_type: - if raise_on_error: - raise credentials_exception - else: - return False + raise credentials_exception except jwt.PyJWTError: - if raise_on_error: - raise credentials_exception - else: - return False + raise credentials_exception return username # This should be reimplemented to better realign with the existing tools provided # by FastAPI regarding API Tokens # https://github.com/tiangolo/fastapi/blob/master/fastapi/security/api_key.py -async def get_ws_token( +async def validate_ws_token( ws: WebSocket, ws_token: Union[str, None] = Query(..., alias="token"), api_config: Dict[str, Any] = Depends(get_api_config) @@ -72,13 +62,16 @@ async def get_ws_token( if secrets.compare_digest(secret_ws_token, ws_token): # Just return the token if it matches return ws_token - elif user := get_user_from_token(ws_token, secret_jwt_key, raise_on_error=False): - # If the token is a jwt, and it's valid return the user - return user else: - logger.info("Denying websocket request") - # If it doesn't match, close the websocket connection - await ws.close(code=status.WS_1008_POLICY_VIOLATION) + try: + user = get_user_from_token(ws_token, secret_jwt_key) + return user + # If the token is a jwt, and it's valid return the user + except HTTPException: + pass + logger.info("Denying websocket request") + # If it doesn't match, close the websocket connection + await ws.close(code=status.WS_1008_POLICY_VIOLATION) def create_token(data: dict, secret_key: str, token_type: str = "access") -> str: diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 25d29a7ce..34b780956 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -7,7 +7,7 @@ from pydantic import ValidationError from starlette.websockets import WebSocketState from freqtrade.enums import RPCMessageType, RPCRequestType -from freqtrade.rpc.api_server.api_auth import get_ws_token +from freqtrade.rpc.api_server.api_auth import validate_ws_token from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSMessageSchema, @@ -96,7 +96,7 @@ async def message_endpoint( ws: WebSocket, rpc: RPC = Depends(get_rpc), channel_manager=Depends(get_channel_manager), - token: str = Depends(get_ws_token) + token: str = Depends(validate_ws_token) ): """ Message WebSocket endpoint, facilitates sending RPC messages diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 17705e62e..f1aa465f0 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -158,12 +158,6 @@ def test_api_auth(): with pytest.raises(HTTPException): get_user_from_token(b'not_a_token', 'secret1234') - # Check returning false instead of error on bad token - assert not get_user_from_token(b'not_a_token', 'secret1234', raise_on_error=False) - - # Check returning false instead of error on bad token type - assert not get_user_from_token(token, 'secret1234', token_type='refresh', raise_on_error=False) - def test_api_ws_auth(botclient): ftbot, client = botclient From 4250174de94b4b27acd5007b009034002212d86e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 14:29:58 +0200 Subject: [PATCH 263/592] Fix ws exception when no token is provided --- freqtrade/rpc/api_server/api_auth.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index 767a2d5b9..93be251ab 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -53,13 +53,13 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access") -> s # https://github.com/tiangolo/fastapi/blob/master/fastapi/security/api_key.py async def validate_ws_token( ws: WebSocket, - ws_token: Union[str, None] = Query(..., alias="token"), + ws_token: Union[str, None] = Query(default=None, alias="token"), api_config: Dict[str, Any] = Depends(get_api_config) ): secret_ws_token = api_config.get('ws_token', 'secret_ws_t0ken.') secret_jwt_key = api_config.get('jwt_secret_key', 'super-secret') - if secrets.compare_digest(secret_ws_token, ws_token): + if ws_token and secrets.compare_digest(secret_ws_token, ws_token): # Just return the token if it matches return ws_token else: From 79985fda015c0f060d0b0aca7d83962c43c75e8e Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Sat, 10 Sep 2022 10:27:17 -0300 Subject: [PATCH 264/592] fix backtesting freqai startup candles bug --- freqtrade/freqai/data_kitchen.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 01b2f1f3b..88d841b9e 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -468,8 +468,14 @@ class FreqaiDataKitchen: Function which takes the backtesting time range and remove training data from dataframe """ + startup_candle_count = self.config.get('startup_candle_count', 0) + tf = self.config['timeframe'] tr = self.config["timerange"] + backtesting_timerange = TimeRange.parse_timerange(tr) + if startup_candle_count > 0 and backtesting_timerange: + backtesting_timerange.subtract_start(timeframe_to_seconds(tf) * startup_candle_count) + start = datetime.fromtimestamp(backtesting_timerange.startts, tz=timezone.utc) df = self.return_dataframe df = df.loc[df["date"] >= start, :] From daf352e6a5dd660e247a38a1a209ff34561ba7a3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 16:01:06 +0200 Subject: [PATCH 265/592] Test online candle fetching in futures, too disable gateio checking on spot markets --- tests/exchange/test_ccxt_compat.py | 27 ++++++++++++++++++++------- 1 file changed, 20 insertions(+), 7 deletions(-) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 49b7684f8..f57b0b366 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -267,13 +267,8 @@ class TestCCXTExchange(): now = datetime.now(timezone.utc) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2)) assert exchange.klines(pair_tf).iloc[-1]['date'] >= timeframe_to_prev_date(timeframe, now) - def test_ccxt__async_get_candle_history(self, exchange): - exchange, exchangename = exchange - # For some weired reason, this test returns random lengths for bittrex. - if not exchange._ft_has['ohlcv_has_history'] or exchangename == 'bittrex': - return - pair = EXCHANGES[exchangename]['pair'] - timeframe = EXCHANGES[exchangename]['timeframe'] + def ccxt__async_get_candle_history(self, exchange, exchangename, pair, timeframe): + candle_type = CandleType.SPOT timeframe_ms = timeframe_to_msecs(timeframe) now = timeframe_to_prev_date( @@ -299,6 +294,24 @@ class TestCCXTExchange(): assert len(candles) >= min(candle_count, candle_count1) assert candles[0][0] == since_ms or (since_ms + timeframe_ms) + def test_ccxt__async_get_candle_history(self, exchange): + exchange, exchangename = exchange + # For some weired reason, this test returns random lengths for bittrex. + if not exchange._ft_has['ohlcv_has_history'] or exchangename in ('bittrex', 'gateio'): + return + pair = EXCHANGES[exchangename]['pair'] + timeframe = EXCHANGES[exchangename]['timeframe'] + self.ccxt__async_get_candle_history(exchange, exchangename, pair, timeframe) + + def test_ccxt__async_get_candle_history_futures(self, exchange_futures): + exchange, exchangename = exchange_futures + if not exchange: + # exchange_futures only returns values for supported exchanges + return + pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) + timeframe = EXCHANGES[exchangename]['timeframe'] + self.ccxt__async_get_candle_history(exchange, exchangename, pair, timeframe) + def test_ccxt_fetch_funding_rate_history(self, exchange_futures): exchange, exchangename = exchange_futures if not exchange: From 10b6aebc5f5ada8b1e6aef733f7c8ccf4e29e8ba Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 10 Sep 2022 16:54:13 +0200 Subject: [PATCH 266/592] enable continual learning and evaluation sets on multioutput models. --- .../BaseClassifierModel.py | 0 .../BaseRegressionModel.py | 0 .../BaseTensorFlowModel.py | 0 .../base_models/FreqaiMultiOutputRegressor.py | 75 +++++++++++++++++++ .../prediction_models/CatboostClassifier.py | 2 +- .../prediction_models/CatboostRegressor.py | 2 +- .../CatboostRegressorMultiTarget.py | 41 +++++++--- .../prediction_models/LightGBMClassifier.py | 2 +- .../prediction_models/LightGBMRegressor.py | 2 +- .../LightGBMRegressorMultiTarget.py | 41 +++++++--- .../prediction_models/XGBoostRegressor.py | 6 +- .../XGBoostRegressorMultiTarget.py | 37 ++++++--- 12 files changed, 170 insertions(+), 38 deletions(-) rename freqtrade/freqai/{prediction_models => base_models}/BaseClassifierModel.py (100%) rename freqtrade/freqai/{prediction_models => base_models}/BaseRegressionModel.py (100%) rename freqtrade/freqai/{prediction_models => base_models}/BaseTensorFlowModel.py (100%) create mode 100644 freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py diff --git a/freqtrade/freqai/prediction_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py similarity index 100% rename from freqtrade/freqai/prediction_models/BaseClassifierModel.py rename to freqtrade/freqai/base_models/BaseClassifierModel.py diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py similarity index 100% rename from freqtrade/freqai/prediction_models/BaseRegressionModel.py rename to freqtrade/freqai/base_models/BaseRegressionModel.py diff --git a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py b/freqtrade/freqai/base_models/BaseTensorFlowModel.py similarity index 100% rename from freqtrade/freqai/prediction_models/BaseTensorFlowModel.py rename to freqtrade/freqai/base_models/BaseTensorFlowModel.py diff --git a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py new file mode 100644 index 000000000..aa5dbe629 --- /dev/null +++ b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py @@ -0,0 +1,75 @@ + +from joblib import Parallel +from sklearn.multioutput import MultiOutputRegressor, _fit_estimator +from sklearn.utils.fixes import delayed +from sklearn.utils.validation import has_fit_parameter + + +class FreqaiMultiOutputRegressor(MultiOutputRegressor): + + def fit(self, X, y, sample_weight=None, fit_params=None): + """Fit the model to data, separately for each output variable. + Parameters + ---------- + X : {array-like, sparse matrix} of shape (n_samples, n_features) + The input data. + y : {array-like, sparse matrix} of shape (n_samples, n_outputs) + Multi-output targets. An indicator matrix turns on multilabel + estimation. + sample_weight : array-like of shape (n_samples,), default=None + Sample weights. If `None`, then samples are equally weighted. + Only supported if the underlying regressor supports sample + weights. + fit_params : A list of dicts for the fit_params + Parameters passed to the ``estimator.fit`` method of each step. + Each dict may contain same or different values (e.g. different + eval_sets or init_models) + .. versionadded:: 0.23 + Returns + ------- + self : object + Returns a fitted instance. + """ + + if not hasattr(self.estimator, "fit"): + raise ValueError("The base estimator should implement a fit method") + + y = self._validate_data(X="no_validation", y=y, multi_output=True) + + # if is_classifier(self): + # check_classification_targets(y) + + if y.ndim == 1: + raise ValueError( + "y must have at least two dimensions for " + "multi-output regression but has only one." + ) + + if sample_weight is not None and not has_fit_parameter( + self.estimator, "sample_weight" + ): + raise ValueError("Underlying estimator does not support sample weights.") + + # fit_params_validated = _check_fit_params(X, fit_params) + + if not fit_params: + fit_params = [None] * y.shape[1] + + # if not init_models: + # init_models = [None] * y.shape[1] + + self.estimators_ = Parallel(n_jobs=self.n_jobs)( + delayed(_fit_estimator)( + self.estimator, X, y[:, i], sample_weight, **fit_params[i] + # init_model=init_models[i], eval_set=eval_sets[i], + # **fit_params_validated + ) + for i in range(y.shape[1]) + ) + + if hasattr(self.estimators_[0], "n_features_in_"): + self.n_features_in_ = self.estimators_[0].n_features_in_ + if hasattr(self.estimators_[0], "feature_names_in_"): + self.feature_names_in_ = self.estimators_[0].feature_names_in_ + + return diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index cd7afd392..60536e6de 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -3,8 +3,8 @@ from typing import Any, Dict from catboost import CatBoostClassifier, Pool +from freqtrade.freqai.base_models.BaseClassifierModel import BaseClassifierModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel logger = logging.getLogger(__name__) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index 1ce31b628..73cf6c88a 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -3,8 +3,8 @@ from typing import Any, Dict from catboost import CatBoostRegressor, Pool +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index bc52bfdd9..a376b2c33 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -1,11 +1,11 @@ import logging from typing import Any, Dict -from catboost import CatBoostRegressor # , Pool -from sklearn.multioutput import MultiOutputRegressor +from catboost import CatBoostRegressor, Pool +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel +from freqtrade.freqai.base_models.FreqaiMultiOutputRegressor import FreqaiMultiOutputRegressor from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) @@ -32,17 +32,34 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): X = data_dictionary["train_features"] y = data_dictionary["train_labels"] - eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) + sample_weight = data_dictionary["train_weights"] - if self.continual_learning: - logger.warning('Continual learning not supported for MultiTarget models') - - model = MultiOutputRegressor(estimator=cbr) - model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) + eval_sets = [None] * y.shape[1] if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: - train_score = model.score(X, y) - test_score = model.score(*eval_set) - logger.info(f"Train score {train_score}, Test score {test_score}") + eval_sets = [None] * data_dictionary['test_labels'].shape[1] + + for i in range(data_dictionary['test_labels'].shape[1]): + eval_sets[i] = Pool( + data=data_dictionary["test_features"], + label=data_dictionary["test_labels"].iloc[:, i], + weight=data_dictionary["test_weights"], + ) + + init_model = self.get_init_model(dk.pair) + + if init_model: + init_models = init_model.estimators_ + else: + init_models = [None] * y.shape[1] + + fit_params = [] + for i in range(len(eval_sets)): + fit_params.append( + {'eval_set': eval_sets[i], 'init_model': init_models[i]}) + + model = FreqaiMultiOutputRegressor(estimator=cbr) + model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) + return model diff --git a/freqtrade/freqai/prediction_models/LightGBMClassifier.py b/freqtrade/freqai/prediction_models/LightGBMClassifier.py index 69867eae3..3eec516ba 100644 --- a/freqtrade/freqai/prediction_models/LightGBMClassifier.py +++ b/freqtrade/freqai/prediction_models/LightGBMClassifier.py @@ -3,8 +3,8 @@ from typing import Any, Dict from lightgbm import LGBMClassifier +from freqtrade.freqai.base_models.BaseClassifierModel import BaseClassifierModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel logger = logging.getLogger(__name__) diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressor.py b/freqtrade/freqai/prediction_models/LightGBMRegressor.py index 99e9ff887..85c9b691c 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressor.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressor.py @@ -3,8 +3,8 @@ from typing import Any, Dict from lightgbm import LGBMRegressor +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py index c34680dbe..7a9b5c36a 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py @@ -2,10 +2,10 @@ import logging from typing import Any, Dict from lightgbm import LGBMRegressor -from sklearn.multioutput import MultiOutputRegressor +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel +from freqtrade.freqai.base_models.FreqaiMultiOutputRegressor import FreqaiMultiOutputRegressor from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) @@ -29,15 +29,36 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel): X = data_dictionary["train_features"] y = data_dictionary["train_labels"] - eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) sample_weight = data_dictionary["train_weights"] - if self.continual_learning: - logger.warning('Continual learning not supported for MultiTarget models') + eval_weights = None + eval_sets = [None] * y.shape[1] - model = MultiOutputRegressor(estimator=lgb) - model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) - train_score = model.score(X, y) - test_score = model.score(*eval_set) - logger.info(f"Train score {train_score}, Test score {test_score}") + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + eval_weights = [data_dictionary["test_weights"]] + eval_sets = [(None, None)] * data_dictionary['test_labels'].shape[1] # type: ignore + for i in range(data_dictionary['test_labels'].shape[1]): + eval_sets[i] = ( # type: ignore + data_dictionary["test_features"], + data_dictionary["test_labels"].iloc[:, i] + ) + + init_model = self.get_init_model(dk.pair) + if init_model: + init_models = init_model.estimators_ + else: + init_models = [None] * y.shape[1] + + fit_params = [] + for i in range(len(eval_sets)): + fit_params.append( + {'eval_set': eval_sets[i], 'eval_sample_weight': eval_weights, + 'init_model': init_models[i]}) + + model = FreqaiMultiOutputRegressor(estimator=lgb) + model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) + + # model = FreqaiMultiOutputRegressor(estimator=lgb) + # model.fit(X=X, y=y, sample_weight=sample_weight, init_models=init_models, + # eval_sets=eval_sets, eval_sample_weight=eval_weights) return model diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressor.py b/freqtrade/freqai/prediction_models/XGBoostRegressor.py index acc4386f5..c9be9ce74 100644 --- a/freqtrade/freqai/prediction_models/XGBoostRegressor.py +++ b/freqtrade/freqai/prediction_models/XGBoostRegressor.py @@ -3,8 +3,8 @@ from typing import Any, Dict from xgboost import XGBRegressor +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) @@ -31,6 +31,7 @@ class XGBoostRegressor(BaseRegressionModel): eval_set = None else: eval_set = [(data_dictionary["test_features"], data_dictionary["test_labels"])] + eval_weights = [data_dictionary['test_weights']] sample_weight = data_dictionary["train_weights"] @@ -38,6 +39,7 @@ class XGBoostRegressor(BaseRegressionModel): model = XGBRegressor(**self.model_training_parameters) - model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set, xgb_model=xgb_model) + model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set, + sample_weight_eval_set=eval_weights, xgb_model=xgb_model) return model diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py index 5283501d1..38c478c0b 100644 --- a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py @@ -1,11 +1,11 @@ import logging from typing import Any, Dict -from sklearn.multioutput import MultiOutputRegressor from xgboost import XGBRegressor +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel +from freqtrade.freqai.base_models.FreqaiMultiOutputRegressor import FreqaiMultiOutputRegressor from freqtrade.freqai.data_kitchen import FreqaiDataKitchen -from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel logger = logging.getLogger(__name__) @@ -29,15 +29,32 @@ class XGBoostRegressorMultiTarget(BaseRegressionModel): X = data_dictionary["train_features"] y = data_dictionary["train_labels"] - eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"]) sample_weight = data_dictionary["train_weights"] - if self.continual_learning: - logger.warning('Continual learning not supported for MultiTarget models') + eval_weights = None + eval_sets = [None] * y.shape[1] + + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + eval_weights = [data_dictionary["test_weights"]] + for i in range(data_dictionary['test_labels'].shape[1]): + eval_sets[i] = [( # type: ignore + data_dictionary["test_features"], + data_dictionary["test_labels"].iloc[:, i] + )] + + init_model = self.get_init_model(dk.pair) + if init_model: + init_models = init_model.estimators_ + else: + init_models = [None] * y.shape[1] + + fit_params = [] + for i in range(len(eval_sets)): + fit_params.append( + {'eval_set': eval_sets[i], 'sample_weight_eval_set': eval_weights, + 'xgb_model': init_models[i]}) + + model = FreqaiMultiOutputRegressor(estimator=xgb) + model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) - model = MultiOutputRegressor(estimator=xgb) - model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set) - train_score = model.score(X, y) - test_score = model.score(*eval_set) - logger.info(f"Train score {train_score}, Test score {test_score}") return model From 60eb02bb62f5952695a69d9eef531d33d91727bf Mon Sep 17 00:00:00 2001 From: Emre Date: Sat, 10 Sep 2022 20:13:16 +0300 Subject: [PATCH 267/592] Add XGBoostClassifier --- .../prediction_models/XGBoostClassifier.py | 85 +++++++++++++++++++ tests/freqai/test_freqai_interface.py | 30 +++++++ 2 files changed, 115 insertions(+) create mode 100644 freqtrade/freqai/prediction_models/XGBoostClassifier.py diff --git a/freqtrade/freqai/prediction_models/XGBoostClassifier.py b/freqtrade/freqai/prediction_models/XGBoostClassifier.py new file mode 100644 index 000000000..8bf5d6281 --- /dev/null +++ b/freqtrade/freqai/prediction_models/XGBoostClassifier.py @@ -0,0 +1,85 @@ +import logging +from typing import Any, Dict, Tuple + +import numpy as np +import numpy.typing as npt +import pandas as pd +from pandas import DataFrame +from pandas.api.types import is_integer_dtype +from sklearn.preprocessing import LabelEncoder +from xgboost import XGBClassifier + +from freqtrade.freqai.base_models.BaseClassifierModel import BaseClassifierModel +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen + + +logger = logging.getLogger(__name__) + + +class XGBoostClassifier(BaseClassifierModel): + """ + User created prediction model. The class needs to override three necessary + functions, predict(), train(), fit(). The class inherits ModelHandler which + has its own DataHandler where data is held, saved, loaded, and managed. + """ + + def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any: + """ + User sets up the training and test data to fit their desired model here + :params: + :data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. + """ + + X = data_dictionary["train_features"].to_numpy() + y = data_dictionary["train_labels"].to_numpy()[:, 0] + + le = LabelEncoder() + if not is_integer_dtype(y): + y = pd.Series(le.fit_transform(y), dtype="int64") + + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0: + eval_set = None + else: + test_features = data_dictionary["test_features"].to_numpy() + test_labels = data_dictionary["test_labels"].to_numpy()[:, 0] + + if not is_integer_dtype(test_labels): + test_labels = pd.Series(le.transform(test_labels), dtype="int64") + + eval_set = [(test_features, test_labels)] + + train_weights = data_dictionary["train_weights"] + + init_model = self.get_init_model(dk.pair) + + model = XGBClassifier(**self.model_training_parameters) + + model.fit(X=X, y=y, eval_set=eval_set, sample_weight=train_weights, + xgb_model=init_model) + + return model + + def predict( + self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs + ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: + """ + Filter the prediction features data and predict with it. + :param: unfiltered_df: Full dataframe for the current backtest period. + :return: + :pred_df: dataframe containing the predictions + :do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove + data (NaNs) or felt uncertain about data (PCA and DI index) + """ + + (pred_df, dk.do_predict) = super().predict(unfiltered_df, dk, **kwargs) + + le = LabelEncoder() + label = dk.label_list[0] + labels_before = list(dk.data['labels_std'].keys()) + labels_after = le.fit_transform(labels_before).tolist() + pred_df[label] = le.inverse_transform(pred_df[label]) + pred_df = pred_df.rename( + columns={labels_after[i]: labels_before[i] for i in range(len(labels_before))}) + + return (pred_df, dk.do_predict) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 5f8eeb086..afcc4fd37 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -174,6 +174,36 @@ def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) +def test_extract_data_and_train_model_XGBoostClassifier(mocker, freqai_conf): + freqai_conf.update({"timerange": "20180110-20180130"}) + freqai_conf.update({"freqaimodel": "XGBoostClassifier"}) + freqai_conf.update({"strategy": "freqai_test_classifier"}) + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange) + + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = True + freqai.dk = FreqaiDataKitchen(freqai_conf) + + timerange = TimeRange.parse_timerange("20180110-20180130") + freqai.dd.load_all_pair_histories(timerange, freqai.dk) + + freqai.dd.pair_dict = MagicMock() + + data_load_timerange = TimeRange.parse_timerange("20180110-20180130") + new_timerange = TimeRange.parse_timerange("20180120-20180130") + + freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", + strategy, freqai.dk, data_load_timerange) + + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists() + assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists() + + def test_extract_data_and_train_model_XGBoostRegressor(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"freqaimodel": "XGBoostRegressor"}) From 311ae8bf1f14e4cc80d6e5ec036c942d9af716bf Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Sat, 10 Sep 2022 14:45:42 -0300 Subject: [PATCH 268/592] freqai backtesting - add startup_candle_count at function description --- freqtrade/freqai/data_kitchen.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 88d841b9e..9168db2aa 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -466,7 +466,8 @@ class FreqaiDataKitchen: ) -> DataFrame: """ Function which takes the backtesting time range and - remove training data from dataframe + remove training data from dataframe, keeping only the + startup_candle_count candles """ startup_candle_count = self.config.get('startup_candle_count', 0) tf = self.config['timeframe'] From d8cdd92140fc908fba0de5d55314ab2181fbc5c8 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 11:47:21 -0600 Subject: [PATCH 269/592] wrap background cleanup in finally, add tests --- freqtrade/rpc/api_server/webserver.py | 9 ++++--- tests/rpc/test_rpc_apiserver.py | 36 +++++++++++++++++++++++++++ 2 files changed, 42 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 557857ecc..3fb8159e1 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -200,14 +200,17 @@ class ApiServer(RPCHandler): # Sleep, make this configurable? await asyncio.sleep(0.1) except asyncio.CancelledError: - # Disconnect channels and stop the loop on cancel - await self._ws_channel_manager.disconnect_all() - self._ws_loop.stop() + pass # For testing, shouldn't happen when stable except Exception as e: logger.exception(f"Exception happened in background task: {e}") + finally: + # Disconnect channels and stop the loop on cancel + await self._ws_channel_manager.disconnect_all() + self._ws_loop.stop() + def start_api(self): """ Start API ... should be run in thread. diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index f1aa465f0..a7774c204 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -3,6 +3,8 @@ Unit test file for rpc/api_server.py """ import json +import logging +import time from datetime import datetime, timedelta, timezone from pathlib import Path from unittest.mock import ANY, MagicMock, PropertyMock @@ -436,6 +438,7 @@ def test_api_cleanup(default_conf, mocker, caplog): apiserver.cleanup() assert apiserver._server.cleanup.call_count == 1 assert log_has("Stopping API Server", caplog) + assert log_has("Stopping API Server background tasks", caplog) ApiServer.shutdown() @@ -1709,3 +1712,36 @@ def test_api_ws_subscribe(botclient, mocker): # Call count hasn't changed as the subscribe request was invalid assert sub_mock.call_count == 1 + + +def test_api_ws_send_msg(default_conf, mocker, caplog): + try: + caplog.set_level(logging.DEBUG) + + default_conf.update({"api_server": {"enabled": True, + "listen_ip_address": "127.0.0.1", + "listen_port": 8080, + "username": "TestUser", + "password": "testPass", + }}) + mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock()) + apiserver = ApiServer(default_conf) + apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) + + # Test message_queue coro receives the message + test_message = {"type": "status", "data": "test"} + apiserver.send_msg(test_message) + time.sleep(1) # Not sure how else to wait for the coro to receive the data + assert log_has("Found message of type: status", caplog) + + # Test if exception logged when error occurs in sending + mocker.patch('freqtrade.rpc.api_server.ws.channel.ChannelManager.broadcast', + side_effect=Exception) + + apiserver.send_msg(test_message) + time.sleep(2) # Not sure how else to wait for the coro to receive the data + assert log_has_re(r"Exception happened in background task.*", caplog) + + finally: + apiserver.cleanup() + ApiServer.shutdown() From f97f1dc5c38bd7e3c0b731404040a2a8e56a20e5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 19:57:21 +0200 Subject: [PATCH 270/592] Test CatboostRegressorMultiTarget, simplify test setup via parametrization --- tests/freqai/test_freqai_interface.py | 44 ++++++--------------------- 1 file changed, 10 insertions(+), 34 deletions(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 5f8eeb086..115ad0ea8 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -46,10 +46,18 @@ def test_extract_data_and_train_model_LightGBM(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_extract_data_and_train_model_LightGBMMultiModel(mocker, freqai_conf): +@pytest.mark.parametrize('model', [ + 'LightGBMRegressorMultiTarget', + 'XGBoostRegressorMultiTarget', + 'CatboostRegressorMultiTarget', + ]) +def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): + if is_arm() and model == 'CatboostRegressorMultiTarget': + pytest.skip("CatBoost is not supported on ARM") + freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"strategy": "freqai_test_multimodel_strat"}) - freqai_conf.update({"freqaimodel": "LightGBMRegressorMultiTarget"}) + freqai_conf.update({"freqaimodel": model}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) @@ -205,38 +213,6 @@ def test_extract_data_and_train_model_XGBoostRegressor(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_extract_data_and_train_model_XGBoostRegressorMultiModel(mocker, freqai_conf): - freqai_conf.update({"timerange": "20180110-20180130"}) - freqai_conf.update({"freqaimodel": "XGBoostRegressorMultiTarget"}) - freqai_conf.update({"strategy": "freqai_test_multimodel_strat"}) - strategy = get_patched_freqai_strategy(mocker, freqai_conf) - exchange = get_patched_exchange(mocker, freqai_conf) - strategy.dp = DataProvider(freqai_conf, exchange) - strategy.freqai_info = freqai_conf.get("freqai", {}) - freqai = strategy.freqai - freqai.live = True - freqai.dk = FreqaiDataKitchen(freqai_conf) - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) - - freqai.dd.pair_dict = MagicMock() - - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") - new_timerange = TimeRange.parse_timerange("20180120-20180130") - - freqai.extract_data_and_train_model( - new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) - - assert len(freqai.dk.label_list) == 2 - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").is_file() - assert len(freqai.dk.data['training_features_list']) == 26 - - shutil.rmtree(Path(freqai.dk.full_path)) - - def test_start_backtesting(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180130"}) freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) From 88892ba663ea8805e06ecd2d101c8982f595ad5f Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 20:06:52 +0200 Subject: [PATCH 271/592] Parametrize regressor tests --- tests/freqai/test_freqai_interface.py | 76 ++++----------------------- 1 file changed, 11 insertions(+), 65 deletions(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 115ad0ea8..bd921c16b 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -17,8 +17,18 @@ def is_arm() -> bool: return "arm" in machine or "aarch64" in machine -def test_extract_data_and_train_model_LightGBM(mocker, freqai_conf): +@pytest.mark.parametrize('model', [ + 'LightGBMRegressor', + 'XGBoostRegressor', + 'CatboostRegressor', + ]) +def test_extract_data_and_train_model_Regressors(mocker, freqai_conf, model): + if is_arm() and model == 'CatboostRegressor': + pytest.skip("CatBoost is not supported on ARM") + + freqai_conf.update({"freqaimodel": model}) freqai_conf.update({"timerange": "20180110-20180130"}) + freqai_conf.update({"strategy": "freqai_test_strat"}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) @@ -86,39 +96,6 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): shutil.rmtree(Path(freqai.dk.full_path)) -@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") -def test_extract_data_and_train_model_Catboost(mocker, freqai_conf): - freqai_conf.update({"timerange": "20180110-20180130"}) - freqai_conf.update({"freqaimodel": "CatboostRegressor"}) - # freqai_conf.get('freqai', {}).update( - # {'model_training_parameters': {"n_estimators": 100, "verbose": 0}}) - strategy = get_patched_freqai_strategy(mocker, freqai_conf) - exchange = get_patched_exchange(mocker, freqai_conf) - strategy.dp = DataProvider(freqai_conf, exchange) - - strategy.freqai_info = freqai_conf.get("freqai", {}) - freqai = strategy.freqai - freqai.live = True - freqai.dk = FreqaiDataKitchen(freqai_conf) - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) - - freqai.dd.pair_dict = MagicMock() - - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") - new_timerange = TimeRange.parse_timerange("20180120-20180130") - - freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) - - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists() - - shutil.rmtree(Path(freqai.dk.full_path)) - - @pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") def test_extract_data_and_train_model_CatboostClassifier(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) @@ -182,37 +159,6 @@ def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf): shutil.rmtree(Path(freqai.dk.full_path)) -def test_extract_data_and_train_model_XGBoostRegressor(mocker, freqai_conf): - freqai_conf.update({"timerange": "20180110-20180130"}) - freqai_conf.update({"freqaimodel": "XGBoostRegressor"}) - freqai_conf.update({"strategy": "freqai_test_strat"}) - - strategy = get_patched_freqai_strategy(mocker, freqai_conf) - exchange = get_patched_exchange(mocker, freqai_conf) - strategy.dp = DataProvider(freqai_conf, exchange) - strategy.freqai_info = freqai_conf.get("freqai", {}) - freqai = strategy.freqai - freqai.live = True - freqai.dk = FreqaiDataKitchen(freqai_conf) - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) - - freqai.dd.pair_dict = MagicMock() - - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") - new_timerange = TimeRange.parse_timerange("20180120-20180130") - - freqai.extract_data_and_train_model( - new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) - - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").is_file() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").is_file() - - shutil.rmtree(Path(freqai.dk.full_path)) - - def test_start_backtesting(mocker, freqai_conf): freqai_conf.update({"timerange": "20180120-20180130"}) freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) From b3fc1cfde94b9b8e67e79d1f35f4ce3f36a4e5e0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 10 Sep 2022 20:17:57 +0200 Subject: [PATCH 272/592] Parametrize classifier tests --- tests/freqai/test_freqai_interface.py | 43 ++++++--------------------- 1 file changed, 9 insertions(+), 34 deletions(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index bd921c16b..2a7cfeb73 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -96,42 +96,17 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): shutil.rmtree(Path(freqai.dk.full_path)) -@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...") -def test_extract_data_and_train_model_CatboostClassifier(mocker, freqai_conf): - freqai_conf.update({"timerange": "20180110-20180130"}) - freqai_conf.update({"freqaimodel": "CatboostClassifier"}) +@pytest.mark.parametrize('model', [ + 'LightGBMClassifier', + 'CatboostClassifier', + ]) +def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): + if is_arm() and model == 'CatboostClassifier': + pytest.skip("CatBoost is not supported on ARM") + + freqai_conf.update({"freqaimodel": model}) freqai_conf.update({"strategy": "freqai_test_classifier"}) - strategy = get_patched_freqai_strategy(mocker, freqai_conf) - exchange = get_patched_exchange(mocker, freqai_conf) - strategy.dp = DataProvider(freqai_conf, exchange) - - strategy.freqai_info = freqai_conf.get("freqai", {}) - freqai = strategy.freqai - freqai.live = True - freqai.dk = FreqaiDataKitchen(freqai_conf) - timerange = TimeRange.parse_timerange("20180110-20180130") - freqai.dd.load_all_pair_histories(timerange, freqai.dk) - - freqai.dd.pair_dict = MagicMock() - - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") - new_timerange = TimeRange.parse_timerange("20180120-20180130") - - freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", - strategy, freqai.dk, data_load_timerange) - - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists() - assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists() - - shutil.rmtree(Path(freqai.dk.full_path)) - - -def test_extract_data_and_train_model_LightGBMClassifier(mocker, freqai_conf): freqai_conf.update({"timerange": "20180110-20180130"}) - freqai_conf.update({"freqaimodel": "LightGBMClassifier"}) - freqai_conf.update({"strategy": "freqai_test_classifier"}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) From 866a5649588c77ec686ba65e581d1306d8ea3751 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 12:51:29 -0600 Subject: [PATCH 273/592] update emc start/shutdown, initial emc tests --- freqtrade/rpc/external_message_consumer.py | 21 +++--- tests/conftest.py | 5 ++ tests/rpc/test_rpc_emc.py | 79 ++++++++++++++++++++++ 3 files changed, 97 insertions(+), 8 deletions(-) create mode 100644 tests/rpc/test_rpc_emc.py diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 1c2a27617..ae7c1f765 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -90,16 +90,16 @@ class ExternalMessageConsumer: """ Start the main internal loop in another thread to run coroutines """ + if self._thread and self._loop: + return + + logger.info("Starting ExternalMessageConsumer") + self._loop = asyncio.new_event_loop() + self._thread = Thread(target=self._loop.run_forever) + self._thread.start() - if not self._thread: - logger.info("Starting ExternalMessageConsumer") - - self._thread = Thread(target=self._loop.run_forever) - self._thread.start() - self._running = True - else: - raise RuntimeError("A loop is already running") + self._running = True self._main_task = asyncio.run_coroutine_threadsafe(self._main(), loop=self._loop) @@ -121,6 +121,11 @@ class ExternalMessageConsumer: self._thread.join() + self._thread = None + self._loop = None + self._sub_tasks = None + self._main_task = None + async def _main(self): """ The main task coroutine diff --git a/tests/conftest.py b/tests/conftest.py index fffac8e0a..6ce767918 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -58,6 +58,11 @@ def log_has(line, logs): return any(line == message for message in logs.messages) +def log_has_when(line, logs, when): + """Check if line is found in caplog's messages during a specified stage""" + return any(line == message.message for message in logs.get_records(when)) + + def log_has_re(line, logs): """Check if line matches some caplog's message.""" return any(re.match(line, message) for message in logs.messages) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py new file mode 100644 index 000000000..6512ff2be --- /dev/null +++ b/tests/rpc/test_rpc_emc.py @@ -0,0 +1,79 @@ +""" +Unit test file for rpc/external_message_consumer.py +""" +import pytest + +from freqtrade.data.dataprovider import DataProvider +from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer +from tests.conftest import log_has, log_has_when + + +@pytest.fixture(autouse=True) +def patched_emc(default_conf, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": "ws://127.0.0.1:8080/api/v1/message/ws", + "ws_token": "secret_Ws_t0ken" + } + ] + } + }) + dataprovider = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dataprovider) + + try: + yield emc + finally: + emc.shutdown() + + +def test_emc_start(patched_emc, caplog): + # Test if the message was printed + assert log_has_when("Starting ExternalMessageConsumer", caplog, "setup") + # Test if the thread and loop objects were created + assert patched_emc._thread and patched_emc._loop + + # Test we call start again nothing happens + prev_thread = patched_emc._thread + patched_emc.start() + assert prev_thread == patched_emc._thread + + +def test_emc_shutdown(patched_emc, caplog): + patched_emc.shutdown() + + assert log_has("Stopping ExternalMessageConsumer", caplog) + # Test the loop has stopped + assert patched_emc._loop is None + # Test if the thread has stopped + assert patched_emc._thread is None + + caplog.clear() + patched_emc.shutdown() + + # Test func didn't run again as it was called once already + assert not log_has("Stopping ExternalMessageConsumer", caplog) + + +def test_emc_init(patched_emc, default_conf, mocker, caplog): + # Test the settings were set correctly + assert patched_emc.initial_candle_limit <= 1500 + assert patched_emc.wait_timeout > 0 + assert patched_emc.sleep_time > 0 + + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [] + } + }) + dataprovider = DataProvider(default_conf, None, None, None) + with pytest.raises(ValueError) as exc: + ExternalMessageConsumer(default_conf, dataprovider) + + # Make sure we failed because of no producers + assert str(exc.value) == "You must specify at least 1 Producer to connect to." From a7baccdb7df6d620b1d23a846d268611cac3ed79 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 13:44:27 -0600 Subject: [PATCH 274/592] update log messages in emc, more tests --- freqtrade/rpc/external_message_consumer.py | 10 ++-- tests/rpc/test_rpc_emc.py | 58 +++++++++++++++++++++- 2 files changed, 62 insertions(+), 6 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index ae7c1f765..c571ac510 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -261,19 +261,19 @@ class ExternalMessageConsumer: try: producer_message = WSMessageSchema.parse_obj(message) except ValidationError as e: - logger.error(f"Invalid message from {producer_name}: {e}") + logger.error(f"Invalid message from `{producer_name}`: {e}") return # We shouldn't get empty messages if producer_message.data is None: return - logger.info(f"Received message of type {producer_message.type} from `{producer_name}`") + logger.info(f"Received message of type `{producer_message.type}` from `{producer_name}`") message_handler = self._message_handlers.get(producer_message.type) if not message_handler: - logger.info(f"Received unhandled message: {producer_message.data}, ignoring...") + logger.info(f"Received unhandled message: `{producer_message.data}`, ignoring...") return message_handler(producer_name, producer_message) @@ -288,7 +288,7 @@ class ExternalMessageConsumer: # Add the pairlist data to the DataProvider self._dp._set_producer_pairs(message.data, producer_name=producer_name) - logger.debug(f"Consumed message from {producer_name} of type `RPCMessageType.WHITELIST`") + logger.debug(f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`") def _consume_analyzed_df_message(self, producer_name: str, message: Any): try: @@ -314,4 +314,4 @@ class ExternalMessageConsumer: producer_name=producer_name) logger.debug( - f"Consumed message from {producer_name} of type RPCMessageType.ANALYZED_DF") + f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`") diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 6512ff2be..f33e80018 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -1,11 +1,14 @@ """ Unit test file for rpc/external_message_consumer.py """ +import logging +from datetime import datetime, timezone + import pytest from freqtrade.data.dataprovider import DataProvider from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer -from tests.conftest import log_has, log_has_when +from tests.conftest import log_has, log_has_re, log_has_when @pytest.fixture(autouse=True) @@ -77,3 +80,56 @@ def test_emc_init(patched_emc, default_conf, mocker, caplog): # Make sure we failed because of no producers assert str(exc.value) == "You must specify at least 1 Producer to connect to." + + +def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): + test_producer = {"name": "test", "url": "ws://test", "ws_token": "test"} + caplog.set_level(logging.DEBUG) + + # Test handle whitelist message + whitelist_message = {"type": "whitelist", "data": ["BTC/USDT"]} + patched_emc.handle_producer_message(test_producer, whitelist_message) + + assert log_has("Received message of type `whitelist` from `test`", caplog) + assert log_has("Consumed message from `test` of type `RPCMessageType.WHITELIST`", caplog) + + # Test handle analyzed_df message + df_message = { + "type": "analyzed_df", + "data": { + "key": ("BTC/USDT", "5m", "spot"), + "df": ohlcv_history, + "la": datetime.now(timezone.utc) + } + } + patched_emc.handle_producer_message(test_producer, df_message) + + assert log_has("Received message of type `analyzed_df` from `test`", caplog) + assert log_has("Consumed message from `test` of type `RPCMessageType.ANALYZED_DF`", caplog) + + # Test unhandled message + unhandled_message = {"type": "status", "data": "RUNNING"} + patched_emc.handle_producer_message(test_producer, unhandled_message) + + assert log_has_re(r"Received unhandled message\: .*", caplog) + + # Test malformed message + caplog.clear() + malformed_message = {"type": "whitelist", "data": {"pair": "BTC/USDT"}} + patched_emc.handle_producer_message(test_producer, malformed_message) + + assert log_has("Received message of type `whitelist` from `test`", caplog) + assert not log_has("Consumed message from `test` of type `RPCMessageType.WHITELIST`", caplog) + + malformed_message = { + "type": "analyzed_df", + "data": { + "key": "BTC/USDT", + "df": ohlcv_history, + "la": datetime.now(timezone.utc) + } + } + patched_emc.handle_producer_message(test_producer, malformed_message) + + assert log_has("Received message of type `analyzed_df` from `test`", caplog) + assert not log_has("Consumed message from `test` of type `RPCMessageType.ANALYZED_DF`", caplog) From c5d031733b271e51edbc54a5f2880f724ace7924 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 13:50:36 -0600 Subject: [PATCH 275/592] remove old param in test fixture --- tests/rpc/test_rpc_emc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index f33e80018..d134a9eb1 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -11,7 +11,7 @@ from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer from tests.conftest import log_has, log_has_re, log_has_when -@pytest.fixture(autouse=True) +@pytest.fixture def patched_emc(default_conf, mocker): default_conf.update({ "external_message_consumer": { From 5a0cfee27e8de330d00168b6de86a2ac84e0ed7f Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 10 Sep 2022 22:16:49 +0200 Subject: [PATCH 276/592] allow user to multithread jobs (advanced users only) --- .../freqai/base_models/FreqaiMultiOutputRegressor.py | 10 ---------- .../prediction_models/CatboostRegressorMultiTarget.py | 3 +++ .../prediction_models/LightGBMRegressorMultiTarget.py | 6 +++--- .../prediction_models/XGBoostRegressorMultiTarget.py | 3 +++ 4 files changed, 9 insertions(+), 13 deletions(-) diff --git a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py index aa5dbe629..a9db81e31 100644 --- a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py +++ b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py @@ -36,9 +36,6 @@ class FreqaiMultiOutputRegressor(MultiOutputRegressor): y = self._validate_data(X="no_validation", y=y, multi_output=True) - # if is_classifier(self): - # check_classification_targets(y) - if y.ndim == 1: raise ValueError( "y must have at least two dimensions for " @@ -50,19 +47,12 @@ class FreqaiMultiOutputRegressor(MultiOutputRegressor): ): raise ValueError("Underlying estimator does not support sample weights.") - # fit_params_validated = _check_fit_params(X, fit_params) - if not fit_params: fit_params = [None] * y.shape[1] - # if not init_models: - # init_models = [None] * y.shape[1] - self.estimators_ = Parallel(n_jobs=self.n_jobs)( delayed(_fit_estimator)( self.estimator, X, y[:, i], sample_weight, **fit_params[i] - # init_model=init_models[i], eval_set=eval_sets[i], - # **fit_params_validated ) for i in range(y.shape[1]) ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index a376b2c33..7fa4e293e 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -60,6 +60,9 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): {'eval_set': eval_sets[i], 'init_model': init_models[i]}) model = FreqaiMultiOutputRegressor(estimator=cbr) + thread_training = self.freqai_info.get('multitarget_parallel_training', False) + if thread_training: + model.n_jobs = y.shape[1] model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) return model diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py index 7a9b5c36a..37c6bb186 100644 --- a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py @@ -56,9 +56,9 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel): 'init_model': init_models[i]}) model = FreqaiMultiOutputRegressor(estimator=lgb) + thread_training = self.freqai_info.get('multitarget_parallel_training', False) + if thread_training: + model.n_jobs = y.shape[1] model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) - # model = FreqaiMultiOutputRegressor(estimator=lgb) - # model.fit(X=X, y=y, sample_weight=sample_weight, init_models=init_models, - # eval_sets=eval_sets, eval_sample_weight=eval_weights) return model diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py index 38c478c0b..920745ec9 100644 --- a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py @@ -55,6 +55,9 @@ class XGBoostRegressorMultiTarget(BaseRegressionModel): 'xgb_model': init_models[i]}) model = FreqaiMultiOutputRegressor(estimator=xgb) + thread_training = self.freqai_info.get('multitarget_parallel_training', False) + if thread_training: + model.n_jobs = y.shape[1] model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params) return model From 2afd5c202c1f906dcd5c04187caa5a67b0337dde Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 14:29:15 -0600 Subject: [PATCH 277/592] update message parsing, tests --- freqtrade/rpc/external_message_consumer.py | 10 +++---- tests/rpc/test_rpc_emc.py | 34 ++++++++++++++++------ 2 files changed, 29 insertions(+), 15 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index c571ac510..1d917577a 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -264,10 +264,6 @@ class ExternalMessageConsumer: logger.error(f"Invalid message from `{producer_name}`: {e}") return - # We shouldn't get empty messages - if producer_message.data is None: - return - logger.info(f"Received message of type `{producer_message.type}` from `{producer_name}`") message_handler = self._message_handlers.get(producer_message.type) @@ -282,7 +278,8 @@ class ExternalMessageConsumer: try: # Validate the message message = WSWhitelistMessage.parse_obj(message) - except ValidationError: + except ValidationError as e: + logger.error(f"Invalid message from `{producer_name}`: {e}") return # Add the pairlist data to the DataProvider @@ -293,7 +290,8 @@ class ExternalMessageConsumer: def _consume_analyzed_df_message(self, producer_name: str, message: Any): try: message = WSAnalyzedDFMessage.parse_obj(message) - except ValidationError: + except ValidationError as e: + logger.error(f"Invalid message from `{producer_name}`: {e}") return key = message.data.key diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index d134a9eb1..9b14c2039 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -82,16 +82,20 @@ def test_emc_init(patched_emc, default_conf, mocker, caplog): assert str(exc.value) == "You must specify at least 1 Producer to connect to." +# Parametrize this? def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): test_producer = {"name": "test", "url": "ws://test", "ws_token": "test"} + producer_name = test_producer['name'] + caplog.set_level(logging.DEBUG) # Test handle whitelist message whitelist_message = {"type": "whitelist", "data": ["BTC/USDT"]} patched_emc.handle_producer_message(test_producer, whitelist_message) - assert log_has("Received message of type `whitelist` from `test`", caplog) - assert log_has("Consumed message from `test` of type `RPCMessageType.WHITELIST`", caplog) + assert log_has(f"Received message of type `whitelist` from `{producer_name}`", caplog) + assert log_has( + f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`", caplog) # Test handle analyzed_df message df_message = { @@ -104,8 +108,9 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): } patched_emc.handle_producer_message(test_producer, df_message) - assert log_has("Received message of type `analyzed_df` from `test`", caplog) - assert log_has("Consumed message from `test` of type `RPCMessageType.ANALYZED_DF`", caplog) + assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog) + assert log_has( + f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`", caplog) # Test unhandled message unhandled_message = {"type": "status", "data": "RUNNING"} @@ -113,13 +118,12 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): assert log_has_re(r"Received unhandled message\: .*", caplog) - # Test malformed message + # Test malformed messages caplog.clear() malformed_message = {"type": "whitelist", "data": {"pair": "BTC/USDT"}} patched_emc.handle_producer_message(test_producer, malformed_message) - assert log_has("Received message of type `whitelist` from `test`", caplog) - assert not log_has("Consumed message from `test` of type `RPCMessageType.WHITELIST`", caplog) + assert log_has_re(r"Invalid message .+", caplog) malformed_message = { "type": "analyzed_df", @@ -131,5 +135,17 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): } patched_emc.handle_producer_message(test_producer, malformed_message) - assert log_has("Received message of type `analyzed_df` from `test`", caplog) - assert not log_has("Consumed message from `test` of type `RPCMessageType.ANALYZED_DF`", caplog) + assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog) + assert log_has_re(r"Invalid message .+", caplog) + + caplog.clear() + malformed_message = {"some": "stuff"} + patched_emc.handle_producer_message(test_producer, malformed_message) + + assert log_has_re(r"Invalid message .+", caplog) + + caplog.clear() + malformed_message = {"type": "whitelist", "data": None} + patched_emc.handle_producer_message(test_producer, malformed_message) + + assert log_has_re(r"Invalid message .+", caplog) From 0bc18ea33c4004939acb62997a8e253b5ba2c08e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 15:12:18 -0600 Subject: [PATCH 278/592] call websocket close in channel close --- freqtrade/rpc/api_server/ws/channel.py | 1 + freqtrade/rpc/api_server/ws/proxy.py | 7 ++++--- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index cffe3092d..f4a0da47b 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -71,6 +71,7 @@ class WebSocketChannel: Close the WebSocketChannel """ + await self._websocket.close() self._closed = True def is_closed(self) -> bool: diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py index da3e04887..2e5a59f05 100644 --- a/freqtrade/rpc/api_server/ws/proxy.py +++ b/freqtrade/rpc/api_server/ws/proxy.py @@ -56,8 +56,10 @@ class WebSocketProxy: Close the websocket connection, only supported by FastAPI WebSockets """ if hasattr(self._websocket, "close"): - return await self._websocket.close(code) - pass + try: + return await self._websocket.close(code) + except RuntimeError: + pass async def accept(self): """ @@ -65,4 +67,3 @@ class WebSocketProxy: """ if hasattr(self._websocket, "accept"): return await self._websocket.accept() - pass From 9a1a4dfb5b82677db48bbab6dd1861ed3a238172 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 16:08:05 -0600 Subject: [PATCH 279/592] more ws endpoint tests --- tests/rpc/test_rpc_apiserver.py | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index a7774c204..2f25f442b 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1714,6 +1714,38 @@ def test_api_ws_subscribe(botclient, mocker): assert sub_mock.call_count == 1 +def test_api_ws_requests(botclient, mocker, caplog): + caplog.set_level(logging.DEBUG) + + ftbot, client = botclient + ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}" + + # Test whitelist request + with client.websocket_connect(ws_url) as ws: + ws.send_json({"type": "whitelist", "data": None}) + response = ws.receive_json() + + assert log_has_re(r"Request of type whitelist from.+", caplog) + assert response['type'] == "whitelist" + + # Test analyzed_df request + with client.websocket_connect(ws_url) as ws: + ws.send_json({"type": "analyzed_df", "data": {}}) + response = ws.receive_json() + + assert log_has_re(r"Request of type analyzed_df from.+", caplog) + assert response['type'] == "analyzed_df" + + caplog.clear() + # Test analyzed_df request with data + with client.websocket_connect(ws_url) as ws: + ws.send_json({"type": "analyzed_df", "data": {"limit": 100}}) + response = ws.receive_json() + + assert log_has_re(r"Request of type analyzed_df from.+", caplog) + assert response['type'] == "analyzed_df" + + def test_api_ws_send_msg(default_conf, mocker, caplog): try: caplog.set_level(logging.DEBUG) From ed4ba8801f039401231bb3e6a6cc3f018de41f33 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sat, 10 Sep 2022 23:57:17 -0600 Subject: [PATCH 280/592] more emc tests --- freqtrade/rpc/external_message_consumer.py | 5 + tests/rpc/test_rpc_emc.py | 177 ++++++++++++++++++++- 2 files changed, 181 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 1d917577a..89fa90c8e 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -203,8 +203,13 @@ class ExternalMessageConsumer: continue + except websockets.exceptions.ConnectionClosedOK: + # Successfully closed, just end + return + except Exception as e: # An unforseen error has occurred, log and stop + logger.error("Unexpected error has occurred:") logger.exception(e) break diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 9b14c2039..a074334c5 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -1,16 +1,26 @@ """ Unit test file for rpc/external_message_consumer.py """ +import asyncio +import functools +import json import logging from datetime import datetime, timezone +from unittest.mock import MagicMock import pytest +import websockets from freqtrade.data.dataprovider import DataProvider from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer from tests.conftest import log_has, log_has_re, log_has_when +_TEST_WS_TOKEN = "secret_Ws_t0ken" +_TEST_WS_HOST = "localhost" +_TEST_WS_PORT = 9989 + + @pytest.fixture def patched_emc(default_conf, mocker): default_conf.update({ @@ -20,7 +30,7 @@ def patched_emc(default_conf, mocker): { "name": "default", "url": "ws://127.0.0.1:8080/api/v1/message/ws", - "ws_token": "secret_Ws_t0ken" + "ws_token": _TEST_WS_TOKEN } ] } @@ -149,3 +159,168 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): patched_emc.handle_producer_message(test_producer, malformed_message) assert log_has_re(r"Invalid message .+", caplog) + + +async def test_emc_create_connection_success(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": f"ws://{_TEST_WS_HOST}:{_TEST_WS_PORT}/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 60, + "ping_timeout": 60, + "sleep_timeout": 60 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + test_producer = default_conf['external_message_consumer']['producers'][0] + lock = asyncio.Lock() + + async def eat(websocket): + pass + + try: + async with websockets.serve(eat, _TEST_WS_HOST, _TEST_WS_PORT): + emc._running = True + await emc._create_connection(test_producer, lock) + emc._running = False + + assert log_has_re(r"Producer connection success.+", caplog) + finally: + emc.shutdown() + + +async def test_emc_create_connection_invalid(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": "ws://localhost:8080/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 60, + "ping_timeout": 60, + "sleep_timeout": 60 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + + lock = asyncio.Lock() + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + test_producer = default_conf['external_message_consumer']['producers'][0] + + try: + # Test invalid URL + test_producer['url'] = "tcp://localhost:8080/api/v1/message/ws" + emc._running = True + await emc._create_connection(test_producer, lock) + emc._running = False + + assert log_has_re(r".+is an invalid WebSocket URL.+", caplog) + finally: + emc.shutdown() + + +async def test_emc_create_connection_error(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": "ws://localhost:8080/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 60, + "ping_timeout": 60, + "sleep_timeout": 60 + } + }) + + # Test unexpected error + mocker.patch('websockets.connect', side_effect=RuntimeError) + + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + try: + await asyncio.sleep(1) + assert log_has("Unexpected error has occurred:", caplog) + finally: + emc.shutdown() + + +async def test_emc_receive_messages(default_conf, caplog, mocker): + """ + Test ExternalMessageConsumer._receive_messages + + Instantiates a patched ExternalMessageConsumer, creates a dummy websocket server, + and listens to the generated messages from the server for 1 second, then checks logs + """ + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": f"ws://{_TEST_WS_HOST}:{_TEST_WS_PORT}/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 60, + "ping_timeout": 60, + "sleep_timeout": 60 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + + lock = asyncio.Lock() + test_producer = default_conf['external_message_consumer']['producers'][0] + + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + # Dummy generator + async def generate_messages(websocket): + try: + for i in range(3): + message = json.dumps({"type": "whitelist", "data": ["BTC/USDT"]}) + await websocket.send(message) + await asyncio.sleep(1) + except websockets.exceptions.ConnectionClosedOK: + return + + loop = asyncio.get_event_loop() + def change_running(emc): emc._running = not emc._running + + try: + # Start the dummy websocket server + async with websockets.serve(generate_messages, _TEST_WS_HOST, _TEST_WS_PORT): + # Change running to True, and call change_running in 1 second + emc._running = True + loop.call_later(1, functools.partial(change_running, emc=emc)) + # Create the connection that receives messages + await emc._create_connection(test_producer, lock) + + assert log_has_re(r"Received message of type `whitelist`.+", caplog) + finally: + emc.shutdown() From 0a8b7686d68c6eae10768eff8f1e035deb080630 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 11 Sep 2022 00:50:18 -0600 Subject: [PATCH 281/592] reworked emc tests --- tests/rpc/test_rpc_emc.py | 183 ++++++++++++++++++++++++++++++++------ 1 file changed, 155 insertions(+), 28 deletions(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index a074334c5..e29419102 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -3,7 +3,6 @@ Unit test file for rpc/external_message_consumer.py """ import asyncio import functools -import json import logging from datetime import datetime, timezone from unittest.mock import MagicMock @@ -220,10 +219,11 @@ async def test_emc_create_connection_invalid(default_conf, caplog, mocker): mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', MagicMock()) + test_producer = default_conf['external_message_consumer']['producers'][0] lock = asyncio.Lock() + dp = DataProvider(default_conf, None, None, None) emc = ExternalMessageConsumer(default_conf, dp) - test_producer = default_conf['external_message_consumer']['producers'][0] try: # Test invalid URL @@ -267,13 +267,7 @@ async def test_emc_create_connection_error(default_conf, caplog, mocker): emc.shutdown() -async def test_emc_receive_messages(default_conf, caplog, mocker): - """ - Test ExternalMessageConsumer._receive_messages - - Instantiates a patched ExternalMessageConsumer, creates a dummy websocket server, - and listens to the generated messages from the server for 1 second, then checks logs - """ +async def test_emc_receive_messages_valid(default_conf, caplog, mocker): default_conf.update({ "external_message_consumer": { "enabled": True, @@ -284,9 +278,9 @@ async def test_emc_receive_messages(default_conf, caplog, mocker): "ws_token": _TEST_WS_TOKEN } ], - "wait_timeout": 60, + "wait_timeout": 1, "ping_timeout": 60, - "sleep_timeout": 60 + "sleep_time": 60 } }) @@ -299,28 +293,161 @@ async def test_emc_receive_messages(default_conf, caplog, mocker): dp = DataProvider(default_conf, None, None, None) emc = ExternalMessageConsumer(default_conf, dp) - # Dummy generator - async def generate_messages(websocket): - try: - for i in range(3): - message = json.dumps({"type": "whitelist", "data": ["BTC/USDT"]}) - await websocket.send(message) - await asyncio.sleep(1) - except websockets.exceptions.ConnectionClosedOK: - return - loop = asyncio.get_event_loop() def change_running(emc): emc._running = not emc._running + class TestChannel: + async def recv(self, *args, **kwargs): + return {"type": "whitelist", "data": ["BTC/USDT"]} + + async def ping(self, *args, **kwargs): + return asyncio.Future() + try: - # Start the dummy websocket server - async with websockets.serve(generate_messages, _TEST_WS_HOST, _TEST_WS_PORT): - # Change running to True, and call change_running in 1 second - emc._running = True - loop.call_later(1, functools.partial(change_running, emc=emc)) - # Create the connection that receives messages - await emc._create_connection(test_producer, lock) + change_running(emc) + loop.call_soon(functools.partial(change_running, emc=emc)) + await emc._receive_messages(TestChannel(), test_producer, lock) assert log_has_re(r"Received message of type `whitelist`.+", caplog) finally: emc.shutdown() + + +async def test_emc_receive_messages_invalid(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": f"ws://{_TEST_WS_HOST}:{_TEST_WS_PORT}/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 1, + "ping_timeout": 60, + "sleep_time": 60 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + + lock = asyncio.Lock() + test_producer = default_conf['external_message_consumer']['producers'][0] + + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + loop = asyncio.get_event_loop() + def change_running(emc): emc._running = not emc._running + + class TestChannel: + async def recv(self, *args, **kwargs): + return {"type": ["BTC/USDT"]} + + async def ping(self, *args, **kwargs): + return asyncio.Future() + + try: + change_running(emc) + loop.call_soon(functools.partial(change_running, emc=emc)) + await emc._receive_messages(TestChannel(), test_producer, lock) + + assert log_has_re(r"Invalid message from.+", caplog) + finally: + emc.shutdown() + + +async def test_emc_receive_messages_timeout(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": f"ws://{_TEST_WS_HOST}:{_TEST_WS_PORT}/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 1, + "ping_timeout": 1, + "sleep_time": 1 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + + lock = asyncio.Lock() + test_producer = default_conf['external_message_consumer']['producers'][0] + + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + loop = asyncio.get_event_loop() + def change_running(emc): emc._running = not emc._running + + class TestChannel: + async def recv(self, *args, **kwargs): + await asyncio.sleep(10) + + async def ping(self, *args, **kwargs): + return asyncio.Future() + + try: + change_running(emc) + loop.call_soon(functools.partial(change_running, emc=emc)) + await emc._receive_messages(TestChannel(), test_producer, lock) + + assert log_has_re(r"Ping error.+", caplog) + finally: + emc.shutdown() + + +async def test_emc_receive_messages_handle_error(default_conf, caplog, mocker): + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "default", + "url": f"ws://{_TEST_WS_HOST}:{_TEST_WS_PORT}/api/v1/message/ws", + "ws_token": _TEST_WS_TOKEN + } + ], + "wait_timeout": 1, + "ping_timeout": 1, + "sleep_time": 1 + } + }) + + mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start', + MagicMock()) + + lock = asyncio.Lock() + test_producer = default_conf['external_message_consumer']['producers'][0] + + dp = DataProvider(default_conf, None, None, None) + emc = ExternalMessageConsumer(default_conf, dp) + + emc.handle_producer_message = MagicMock(side_effect=Exception) + + loop = asyncio.get_event_loop() + def change_running(emc): emc._running = not emc._running + + class TestChannel: + async def recv(self, *args, **kwargs): + return {"type": "whitelist", "data": ["BTC/USDT"]} + + async def ping(self, *args, **kwargs): + return asyncio.Future() + + try: + change_running(emc) + loop.call_soon(functools.partial(change_running, emc=emc)) + await emc._receive_messages(TestChannel(), test_producer, lock) + + assert log_has_re(r"Error handling producer message.+", caplog) + finally: + emc.shutdown() From d598f4334efb965605f7af0918d358b9d89ec008 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 11 Sep 2022 13:28:14 +0200 Subject: [PATCH 282/592] add search share button to website --- mkdocs.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/mkdocs.yml b/mkdocs.yml index 2e5e0c8c9..257db7867 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -49,6 +49,8 @@ theme: logo: "images/logo.png" favicon: "images/logo.png" custom_dir: "docs/overrides" + features: + - search.share palette: - scheme: default primary: "blue grey" From 4476b5a7f4ab0183197a8f0479b9e3ef0d0e7937 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 08:58:40 +0200 Subject: [PATCH 283/592] add user_data arg to test-pairlist --- docs/utils.md | 4 +++- freqtrade/commands/arguments.py | 4 ++-- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/docs/utils.md b/docs/utils.md index 5646365e4..174fa0527 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -525,12 +525,14 @@ Requires a configuration with specified `pairlists` attribute. Can be used to generate static pairlists to be used during backtesting / hyperopt. ``` -usage: freqtrade test-pairlist [-h] [-v] [-c PATH] +usage: freqtrade test-pairlist [-h] [--userdir PATH] [-v] [-c PATH] [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]] [-1] [--print-json] [--exchange EXCHANGE] optional arguments: -h, --help show this help message and exit + --userdir PATH, --user-data-dir PATH + Path to userdata directory. -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). -c PATH, --config PATH Specify configuration file (default: diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index 37ce17f21..2835f8582 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -53,8 +53,8 @@ ARGS_LIST_PAIRS = ["exchange", "print_list", "list_pairs_print_json", "print_one "print_csv", "base_currencies", "quote_currencies", "list_pairs_all", "trading_mode"] -ARGS_TEST_PAIRLIST = ["verbosity", "config", "quote_currencies", "print_one_column", - "list_pairs_print_json", "exchange"] +ARGS_TEST_PAIRLIST = ["user_data_dir", "verbosity", "config", "quote_currencies", + "print_one_column", "list_pairs_print_json", "exchange"] ARGS_CREATE_USERDIR = ["user_data_dir", "reset"] From ccc70a21f274a55b1f68b15a6e9ffbfb39844a5e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 09:02:06 +0200 Subject: [PATCH 284/592] Update pairs_file cli argument description --- docs/data-download.md | 10 +++++----- freqtrade/commands/cli_options.py | 3 ++- 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/docs/data-download.md b/docs/data-download.md index b72e7f337..2b76d4f74 100644 --- a/docs/data-download.md +++ b/docs/data-download.md @@ -25,8 +25,7 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [--include-inactive-pairs] [--timerange TIMERANGE] [--dl-trades] [--exchange EXCHANGE] - [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]] - [--erase] + [-t TIMEFRAMES [TIMEFRAMES ...]] [--erase] [--data-format-ohlcv {json,jsongz,hdf5}] [--data-format-trades {json,jsongz,hdf5}] [--trading-mode {spot,margin,futures}] @@ -37,7 +36,8 @@ optional arguments: -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] Limit command to these pairs. Pairs are space- separated. - --pairs-file FILE File containing a list of pairs to download. + --pairs-file FILE File containing a list of pairs. Takes precedence over + --pairs or pairs configured in the configuration. --days INT Download data for given number of days. --new-pairs-days INT Download data of new pairs for given number of days. Default: `None`. @@ -50,7 +50,7 @@ optional arguments: as --timeframes/-t. --exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no config is provided. - -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...] + -t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...] Specify which tickers to download. Space-separated list. Default: `1m 5m`. --erase Clean all existing data for the selected @@ -61,7 +61,7 @@ optional arguments: --data-format-trades {json,jsongz,hdf5} Storage format for downloaded trades data. (default: `jsongz`). - --trading-mode {spot,margin,futures} + --trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures} Select Trading mode --prepend Allow data prepending. (Data-appending is disabled) diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index 4240a8014..9aacbcc97 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -393,7 +393,8 @@ AVAILABLE_CLI_OPTIONS = { # Download data "pairs_file": Arg( '--pairs-file', - help='File containing a list of pairs to download.', + help='File containing a list of pairs. ' + 'Takes precedence over --pairs or pairs configured in the configuration.', metavar='FILE', ), "days": Arg( From 9c8c7a03a160cdaad21b85d472879e5d5649d269 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 11:24:01 +0200 Subject: [PATCH 285/592] Improve typehint --- freqtrade/data/dataprovider.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 4151b7419..e639b3ae7 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -86,7 +86,7 @@ class DataProvider: """ _candle_type = CandleType.from_string( candle_type) if candle_type != '' else self._config['candle_type_def'] - saved_pair = (pair, str(timeframe), _candle_type) + saved_pair: PairWithTimeframe = (pair, str(timeframe), _candle_type) if saved_pair not in self.__cached_pairs_backtesting: timerange = TimeRange.parse_timerange(None if self._config.get( 'timerange') is None else str(self._config.get('timerange'))) From a48923c0e43eda833aced9afc8a13e98caa29c8f Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 11:38:36 +0200 Subject: [PATCH 286/592] Extract widget colorization to separate function --- freqtrade/optimize/hyperopt.py | 46 ++++++++++++++++++---------------- 1 file changed, 25 insertions(+), 21 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 3becf857f..749e608d3 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -410,7 +410,7 @@ class Hyperopt: model_queue_size=SKOPT_MODEL_QUEUE_SIZE, ) - def run_optimizer_parallel(self, parallel, asked, i) -> List: + def run_optimizer_parallel(self, parallel: Parallel, asked: List[List], i: int) -> List: return parallel(delayed( wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked) @@ -491,6 +491,29 @@ class Hyperopt: else: return self.opt.ask(n_points=n_points), [False for _ in range(n_points)] + def get_progressbar_widgets(self): + if self.print_colorized: + widgets = [ + ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs), + ' (', progressbar.Percentage(), ')] ', + progressbar.Bar(marker=progressbar.AnimatedMarker( + fill='\N{FULL BLOCK}', + fill_wrap=Fore.GREEN + '{}' + Fore.RESET, + marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL, + )), + ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']', + ] + else: + widgets = [ + ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs), + ' (', progressbar.Percentage(), ')] ', + progressbar.Bar(marker=progressbar.AnimatedMarker( + fill='\N{FULL BLOCK}', + )), + ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']', + ] + return widgets + def start(self) -> None: self.random_state = self._set_random_state(self.config.get('hyperopt_random_state')) logger.info(f"Using optimizer random state: {self.random_state}") @@ -526,26 +549,7 @@ class Hyperopt: logger.info(f'Effective number of parallel workers used: {jobs}') # Define progressbar - if self.print_colorized: - widgets = [ - ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs), - ' (', progressbar.Percentage(), ')] ', - progressbar.Bar(marker=progressbar.AnimatedMarker( - fill='\N{FULL BLOCK}', - fill_wrap=Fore.GREEN + '{}' + Fore.RESET, - marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL, - )), - ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']', - ] - else: - widgets = [ - ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs), - ' (', progressbar.Percentage(), ')] ', - progressbar.Bar(marker=progressbar.AnimatedMarker( - fill='\N{FULL BLOCK}', - )), - ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']', - ] + widgets = self.get_progressbar_widgets() with progressbar.ProgressBar( max_value=self.total_epochs, redirect_stdout=False, redirect_stderr=False, widgets=widgets From 32e13d65c3bbba091eac4ae16259adaaf483a02a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 11:54:31 +0200 Subject: [PATCH 287/592] Refactor hyperopt to extract evaluate_result --- freqtrade/optimize/hyperopt.py | 49 ++++++++++++++++++++-------------- 1 file changed, 29 insertions(+), 20 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 749e608d3..3a117f356 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -290,7 +290,7 @@ class Hyperopt: # noinspection PyProtectedMember attr.value = params_dict[attr_name] - def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict: + def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict[str, Any]: """ Used Optimize function. Called once per epoch to optimize whatever is configured. @@ -410,7 +410,9 @@ class Hyperopt: model_queue_size=SKOPT_MODEL_QUEUE_SIZE, ) - def run_optimizer_parallel(self, parallel: Parallel, asked: List[List], i: int) -> List: + def run_optimizer_parallel( + self, parallel: Parallel, asked: List[List], i: int) -> List[Dict[str, Any]]: + """ Start optimizer in a parallel way """ return parallel(delayed( wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked) @@ -514,6 +516,30 @@ class Hyperopt: ] return widgets + def evaluate_result(self, val: Dict[str, Any], current: int, is_random: bool): + """ + Evaluate results returned from generate_optimizer + """ + val['current_epoch'] = current + val['is_initial_point'] = current <= INITIAL_POINTS + + logger.debug("Optimizer epoch evaluated: %s", val) + + is_best = HyperoptTools.is_best_loss(val, self.current_best_loss) + # This value is assigned here and not in the optimization method + # to keep proper order in the list of results. That's because + # evaluations can take different time. Here they are aligned in the + # order they will be shown to the user. + val['is_best'] = is_best + val['is_random'] = is_random + self.print_results(val) + + if is_best: + self.current_best_loss = val['loss'] + self.current_best_epoch = val + + self._save_result(val) + def start(self) -> None: self.random_state = self._set_random_state(self.config.get('hyperopt_random_state')) logger.info(f"Using optimizer random state: {self.random_state}") @@ -569,25 +595,8 @@ class Hyperopt: for j, val in enumerate(f_val): # Use human-friendly indexes here (starting from 1) current = i * jobs + j + 1 - val['current_epoch'] = current - val['is_initial_point'] = current <= INITIAL_POINTS - logger.debug(f"Optimizer epoch evaluated: {val}") - - is_best = HyperoptTools.is_best_loss(val, self.current_best_loss) - # This value is assigned here and not in the optimization method - # to keep proper order in the list of results. That's because - # evaluations can take different time. Here they are aligned in the - # order they will be shown to the user. - val['is_best'] = is_best - val['is_random'] = is_random[j] - self.print_results(val) - - if is_best: - self.current_best_loss = val['loss'] - self.current_best_epoch = val - - self._save_result(val) + self.evaluate_result(val, current, is_random[j]) pbar.update(current) From 78cd46ecd55e1042ef5f20f10ebd7e0c269d6ca0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 11:56:17 +0200 Subject: [PATCH 288/592] hyperopt Remove unnecessary arguments --- freqtrade/optimize/hyperopt.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 3a117f356..76fc84609 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -290,7 +290,7 @@ class Hyperopt: # noinspection PyProtectedMember attr.value = params_dict[attr_name] - def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict[str, Any]: + def generate_optimizer(self, raw_params: List[Any]) -> Dict[str, Any]: """ Used Optimize function. Called once per epoch to optimize whatever is configured. @@ -411,10 +411,10 @@ class Hyperopt: ) def run_optimizer_parallel( - self, parallel: Parallel, asked: List[List], i: int) -> List[Dict[str, Any]]: + self, parallel: Parallel, asked: List[List]) -> List[Dict[str, Any]]: """ Start optimizer in a parallel way """ return parallel(delayed( - wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked) + wrap_non_picklable_objects(self.generate_optimizer))(v) for v in asked) def _set_random_state(self, random_state: Optional[int]) -> int: return random_state or random.randint(1, 2**16 - 1) @@ -588,7 +588,7 @@ class Hyperopt: current_jobs = jobs - n_rest if n_rest > 0 else jobs asked, is_random = self.get_asked_points(n_points=current_jobs) - f_val = self.run_optimizer_parallel(parallel, asked, i) + f_val = self.run_optimizer_parallel(parallel, asked) self.opt.tell(asked, [v['loss'] for v in f_val]) # Calculate progressbar outputs From 68a900a9b7325b0a2b0e1c84f0c694fa862104bc Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 11 Sep 2022 17:29:14 +0200 Subject: [PATCH 289/592] reorganize freqai docs for easier reading, add detailed file structure description --- docs/freqai-configuration.md | 283 +++++++++++ docs/freqai-data-handling.md | 129 +++++ docs/freqai-feature-engineering.md | 274 +++++++++++ docs/freqai-running.md | 104 ++++ docs/freqai.md | 760 +---------------------------- mkdocs.yml | 7 +- 6 files changed, 816 insertions(+), 741 deletions(-) create mode 100644 docs/freqai-configuration.md create mode 100644 docs/freqai-data-handling.md create mode 100644 docs/freqai-feature-engineering.md create mode 100644 docs/freqai-running.md diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md new file mode 100644 index 000000000..5190c59c9 --- /dev/null +++ b/docs/freqai-configuration.md @@ -0,0 +1,283 @@ +# Configuration + +## Setting up the configuration file + +The user interface is isolated to the typical Freqtrade config file. Although there are plenty of additional parameters that a user can choose from, as highlighted in the [parameter table](#parameter-table), a FreqAI config must at minimum include the following parameters (the example inputs are not requires): + +```json + "freqai": { + "enabled": true, + "purge_old_models": true, + "train_period_days": 30, + "backtest_period_days": 7, + "identifier" : "unique-id", + "feature_parameters" : { + "include_timeframes": ["5m","15m","4h"], + "include_corr_pairlist": [ + "ETH/USD", + "LINK/USD", + "BNB/USD" + ], + "label_period_candles": 24, + "include_shifted_candles": 2, + "indicator_periods_candles": [10, 20] + }, + "data_split_parameters" : { + "test_size": 0.25 + }, + "model_training_parameters" : { + "n_estimators": 100 + }, + } +``` + +## Building a FreqAI strategy + +The FreqAI strategy requires the user to include the following lines of code in the standard Freqtrade strategy: + +```python + # user should define the maximum startup candle count (the largest number of candles + # passed to any single indicator) + startup_candle_count: int = 20 + + def informative_pairs(self): + whitelist_pairs = self.dp.current_whitelist() + corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] + informative_pairs = [] + for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]: + for pair in whitelist_pairs: + informative_pairs.append((pair, tf)) + for pair in corr_pairs: + if pair in whitelist_pairs: + continue # avoid duplication + informative_pairs.append((pair, tf)) + return informative_pairs + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + # the model will return all labels created by user in `populate_any_indicators` + # (& appended targets), an indication of whether or not the prediction should be accepted, + # the target mean/std values for each of the labels created by user in + # `populate_any_indicators()` for each training period. + + dataframe = self.freqai.start(dataframe, metadata, self) + + return dataframe + + def populate_any_indicators( + self, pair, df, tf, informative=None, set_generalized_indicators=False + ): + """ + Function designed to automatically generate, name and merge features + from user indicated timeframes in the configuration file. User controls the indicators + passed to the training/prediction by prepending indicators with `'%-' + coin ` + (see convention below). I.e. user should not prepend any supporting metrics + (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the + model. + :param pair: pair to be used as informative + :param df: strategy dataframe which will receive merges from informatives + :param tf: timeframe of the dataframe which will modify the feature names + :param informative: the dataframe associated with the informative pair + :param coin: the name of the coin which will modify the feature names. + """ + + coin = pair.split('/')[0] + + if informative is None: + informative = self.dp.get_pair_dataframe(pair, tf) + + # first loop is automatically duplicating indicators for time periods + for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]: + t = int(t) + informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) + informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) + informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) + + indicators = [col for col in informative if col.startswith("%")] + # This loop duplicates and shifts all indicators to add a sense of recency to data + for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): + if n == 0: + continue + informative_shift = informative[indicators].shift(n) + informative_shift = informative_shift.add_suffix("_shift-" + str(n)) + informative = pd.concat((informative, informative_shift), axis=1) + + df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True) + skip_columns = [ + (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"] + ] + df = df.drop(columns=skip_columns) + + # Add generalized indicators here (because in live, it will call this + # function to populate indicators during training). Notice how we ensure not to + # add them multiple times + if set_generalized_indicators: + + # user adds targets here by prepending them with &- (see convention below) + # If user wishes to use multiple targets, a multioutput prediction model + # needs to be used such as templates/CatboostPredictionMultiModel.py + df["&-s_close"] = ( + df["close"] + .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + .mean() + / df["close"] + - 1 + ) + + return df + + +``` + +Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](freqai-feature_engineering.md#feature-engineering)) and labels ([more information](freqai-running.md#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. + +Another structure to consider is the location of the labels at the bottom of the example function (below `if set_generalized_indicators:`). This is where the user will add single features and labels to their feature set to avoid duplication of them from various configuration parameters that multiply the feature set, such as `include_timeframes`. + +!!! Note + Features **must** be defined in `populate_any_indicators()`. Defining FreqAI features in `populate_indicators()` + will cause the algorithm to fail in live/dry mode. If the user wishes to add generalized features that are not associated with + a specific pair or timeframe, they should use the following structure inside `populate_any_indicators()` + (as exemplified in `freqtrade/templates/FreqaiExampleStrategy.py`): + + ```python + def populate_any_indicators(self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False): + + ... + + # Add generalized indicators here (because in live, it will call only this function to populate + # indicators for retraining). Notice how we ensure not to add them multiple times by associating + # these generalized indicators to the basepair/timeframe + if set_generalized_indicators: + df['%-day_of_week'] = (df["date"].dt.dayofweek + 1) / 7 + df['%-hour_of_day'] = (df['date'].dt.hour + 1) / 25 + + # user adds targets here by prepending them with &- (see convention below) + # If user wishes to use multiple targets, a multioutput prediction model + # needs to be used such as templates/CatboostPredictionMultiModel.py + df["&-s_close"] = ( + df["close"] + .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + .mean() + / df["close"] + - 1 + ) + ``` + + (Please see the example script located in `freqtrade/templates/FreqaiExampleStrategy.py` for a full example of `populate_any_indicators()`.) + +*Important*: The `self.freqai.start()` function cannot be called outside the `populate_indicators()`. + +## Setting the `startup_candle_count` +Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). + +!!! Note + Typically it is best for users to be safe and multiply their expected `startup_candle_count` by 2. There are instances where the talib functions actually require more data than just the passed `period`. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Look out for this log message to confirm that your data is clean: + + ``` + 2022-08-31 15:14:04 - freqtrade.freqai.data_kitchen - INFO - dropped 0 training points due to NaNs in populated dataset 4319. + ``` + +## Creating a dynamic target threshold + +The `&*_std/mean` return values describe the statistical fit of the user defined label *during the most recent training*. This value allows the user to know the rarity of a given prediction. For example, `templates/FreqaiExampleStrategy.py`, creates a `target_roi` which is based on filtering out predictions that are below a given z-score of 1.25. + +```python +dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25 +dataframe["sell_roi"] = dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * 1.25 +``` + +If the user wishes to consider the population +of *historical predictions* for creating the dynamic target instead of the trained labels, (as discussed above) the user +can do so by setting `fit_live_prediction_candles` in the config to the number of historical prediction candles +the user wishes to use to generate target statistics. + +```json + "freqai": { + "fit_live_prediction_candles": 300, + } +``` + +If the user sets this value, FreqAI will initially use the predictions from the training data +and subsequently begin introducing real prediction data as it is generated. FreqAI will save +this historical data to be reloaded if the user stops and restarts a model with the same `identifier`. + + +## Parameter table + +The table below will list all configuration parameters available for FreqAI, presented in the same order as `config_examples/config_freqai.example.json`. + +Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways. + +| Parameter | Description | +|------------|-------------| +| | **General configuration parameters** +| `freqai` | **Required.**
    The parent dictionary containing all the parameters for controlling FreqAI.
    **Datatype:** Dictionary. +| `purge_old_models` | Delete obsolete models (otherwise, all historic models will remain on disk).
    **Datatype:** Boolean. Default: `False`. +| `train_period_days` | **Required.**
    Number of days to use for the training data (width of the sliding window).
    **Datatype:** Positive integer. +| `backtest_period_days` | **Required.**
    Number of days to inference from the trained model before sliding the window defined above, and retraining the model. This can be fractional days, but beware that the user-provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
    **Datatype:** Float. +| `save_backtest_models` | Backtesting operates most efficiently by saving the prediction data and reusing them directly for subsequent runs (when users wish to tune entry/exit parameters). If a user wishes to save models to disk when running backtesting, they should activate `save_backtest_models`. A user may wish to do this if they plan to use the same model files for starting a dry/live instance with the same `identifier`.
    **Datatype:** Boolean. Default: `False`. +| `identifier` | **Required.**
    A unique name for the current model. This can be reused to reload pre-trained models/data.
    **Datatype:** String. +| `live_retrain_hours` | Frequency of retraining during dry/live runs.
    Default set to 0, which means the model will retrain as often as possible.
    **Datatype:** Float > 0. +| `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
    Defaults set to 0, which means models never expire.
    **Datatype:** Positive integer. +| `fit_live_predictions_candles` | Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training data set.
    **Datatype:** Positive integer. +| `follow_mode` | If true, this instance of FreqAI will look for models associated with `identifier` and load those for inferencing. A `follower` will **not** train new models.
    **Datatype:** Boolean. Default: `False`. +| `continual_learning` | If true, FreqAI will start training new models from the final state of the most recently trained model.
    **Datatype:** Boolean. Default: `False`. +| | **Feature parameters** +| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](#feature-engineering).
    **Datatype:** Dictionary. +| `include_timeframes` | A list of timeframes that all indicators in `populate_any_indicators` will be created for. The list is added as features to the base asset feature set.
    **Datatype:** List of timeframes (strings). +| `include_corr_pairlist` | A list of correlated coins that FreqAI will add as additional features to all `pair_whitelist` coins. All indicators set in `populate_any_indicators` during feature engineering (see details [here](#feature-engineering)) will be created for each coin in this list, and that set of features is added to the base asset feature set.
    **Datatype:** List of assets (strings). +| `label_period_candles` | Number of candles into the future that the labels are created for. This is used in `populate_any_indicators` (see `templates/FreqaiExampleStrategy.py` for detailed usage). The user can create custom labels, making use of this parameter or not.
    **Datatype:** Positive integer. +| `include_shifted_candles` | Add features from previous candles to subsequent candles to add historical information. FreqAI takes all features from the `include_shifted_candles` previous candles, duplicates and shifts them so that the information is available for the subsequent candle.
    **Datatype:** Positive integer. +| `weight_factor` | Used to set weights for training data points according to their recency. See details about how it works [here](#controlling-the-model-learning-process).
    **Datatype:** Positive float (typically < 1). +| `indicator_max_period_candles` | **No longer used**. User must use the strategy set `startup_candle_count` which defines the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
    **Datatype:** positive integer. +| `indicator_periods_candles` | Calculate indicators for `indicator_periods_candles` time periods and add them to the feature set.
    **Datatype:** List of positive integers. +| `stratify_training_data` | This value is used to indicate the grouping of the data. For example, 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. See details about how it works [here](#stratifying-the-data-for-training-and-testing-the-model)
    **Datatype:** Positive integer. +| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis)
    **Datatype:** Boolean. +| `DI_threshold` | Activates the Dissimilarity Index for outlier detection when > 0. See details about how it works [here](#removing-outliers-with-the-dissimilarity-index).
    **Datatype:** Positive float (typically < 1). +| `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Boolean. +| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Dictionary. +| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. +| `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 +| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5% (i.e. the percent of data falling within the first standard deviation). Good for preventing overfitting.
    **Datatype:** int. Default: 0 +| `outlier_protection_percentage` | If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact. If the outlier protection is triggered, no predictions will be made based on the training data.
    **Datatype:** Float. Default: `30` +| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** Boolean. Default: False +| | **Data split parameters** +| `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. +| `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. +| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
    **Datatype:** Boolean. +| | **Model training parameters** +| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
    **Datatype:** Dictionary. +| `n_estimators` | The number of boosted trees to fit in regression.
    **Datatype:** Integer. +| `learning_rate` | Boosting learning rate during regression.
    **Datatype:** Float. +| `n_jobs`, `thread_count`, `task_type` | Set the number of threads for parallel processing and the `task_type` (`gpu` or `cpu`). Different model libraries use different parameter names.
    **Datatype:** Float. +| | **Extraneous parameters** +| `keras` | If your model makes use of Keras (typical for Tensorflow-based prediction models), activate this flag so that the model save/loading follows Keras standards.
    **Datatype:** Boolean. Default: `False`. +| `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for shifting candles (`include_shifted_candles`) by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction.
    **Datatype:** Integer. Default: 2. + +## Important dataframe key patterns + +Below are the values the user can expect to include/use inside a typical strategy dataframe (`df[]`): + +| DataFrame Key | Description | +|------------|-------------| +| `df['&*']` | Any dataframe column prepended with `&` in `populate_any_indicators()` is treated as a training target (label) inside FreqAI (typically following the naming convention `&-s*`). The names of these dataframe columns are fed back to the user as the predictions. For example, if the user wishes to predict the price change in the next 40 candles (similar to `templates/FreqaiExampleStrategy.py`), they set `df['&-s_close']`. FreqAI makes the predictions and gives them back under the same key (`df['&-s_close']`) to be used in `populate_entry/exit_trend()`.
    **Datatype:** Depends on the output of the model. +| `df['&*_std/mean']` | Standard deviation and mean values of the user-defined labels during training (or live tracking with `fit_live_predictions_candles`). Commonly used to understand the rarity of a prediction (use the z-score as shown in `templates/FreqaiExampleStrategy.py` to evaluate how often a particular prediction was observed during training or historically with `fit_live_predictions_candles`).
    **Datatype:** Float. +| `df['do_predict']` | Indication of an outlier data point. The return value is integer between -1 and 2, which lets the user know if the prediction is trustworthy or not. `do_predict==1` means the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](#removing-outliers-with-the-dissimilarity-index)) of the input data point is above the user-defined threshold, FreqAI will subtract 1 from `do_predict`, resulting in `do_predict==0`. If `use_SVM_to_remove_outliers()` is active, the Support Vector Machine (SVM) may also detect outliers in training and prediction data. In this case, the SVM will also subtract 1 from `do_predict`. If the input data point was considered an outlier by the SVM but not by the DI, the result will be `do_predict==0`. If both the DI and the SVM considers the input data point to be an outlier, the result will be `do_predict==-1`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`.
    **Datatype:** Integer between -1 and 2. +| `df['DI_values']` | Dissimilarity Index values are proxies to the level of confidence FreqAI has in the prediction. A lower DI means the prediction is close to the training data, i.e., higher prediction confidence.
    **Datatype:** Float. +| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, the user can include the RSI in the training feature set (similar to in `templates/FreqaiExampleStrategy.py`) by setting `df['%-rsi']`. See more details on how this is done [here](#feature-engineering).
    **Note**: Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features is easily engineered using the multiplictative functionality described in the `feature_parameters` table shown above), these features are removed from the dataframe upon return from FreqAI. If the user wishes to keep a particular type of feature for plotting purposes, they can prepend it with `%%`.
    **Datatype:** Depends on the output of the model. + +## Building a custom prediction model + +FreqAI has multiple example prediction model libraries, such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`), `LightGBM`, `XGBoost` regression. However, the user can customize and create their own prediction models using the `IFreqaiModel` class. The user is encouraged to inherit `fit()`, `train()` and `predict()` to let them customize various aspects of their training procedures. + +## Setting classifier targets + +`FreqAI` includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If the user elects to use a classifier, they must ensure the classes are set using strings. For example: + +```python +df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') +``` + +Additionally, the example classifier models do not accommodate multiple labels, but they do allow multi-class classification within a single label column. diff --git a/docs/freqai-data-handling.md b/docs/freqai-data-handling.md new file mode 100644 index 000000000..7ed51599d --- /dev/null +++ b/docs/freqai-data-handling.md @@ -0,0 +1,129 @@ +# Data handling + +`FreqAI` aims to organize prediction data, model files, and meta data in a way that automates crash resilient reloading and simplifies post-processing. Data is organized into `user_data_dir/models/` and contains all the data associated with the trainings and backtests. This file structure is heavily controlled and inferenced by the `FreqaiDataKitchen()` and should therefore not be manually modified. + +## File structure + +The file structure is automatically generated based on the user set `identifier` in the configuration file. The following structure shows where the data is stored for post processing: + +* `config_*.json` + * a copy of the user submitted configuration file +* `historic_predictions.pkl` + * all historic predictions generated during the lifetime of the `identifier` live deployment. These are also used to reload the model after a crash or a config change. A backup file is always held incase of corruption on the main file - FreqAI automatically detects corruption and replaces the corrupted file with the backup. +* `pair_dictionary.json` + * contains the training queue as well as the location of the most recently trained model on disk. +* `sub-train-*_TIMESTAMP` + * a folder containing all the files associated with a single model, such as: + * `*_metadata.json` + * metadata for the model, such as normalization max/mins, expected training feature list, etc. + * `*_model.*` + * the model file saved to disk for reloading from crash. Can be `joblib` (typical boosting libs), `zip` (stable_baselines), `hd5` (keras type), etc. + * `*_pca_object.pkl` + * the PCA transform (if the user set `principal_component_analysis: true` in their config) which will be used to transform unseen prediction features. + * `*_svm_model.pkl` + * the Support Vector Machine model which is used to detect outliers in unseen prediction features. + * `*_trained_df.pkl` + * the dataframe containing all the training features used to train the particular model. This is used for computing the Dissimilarity Index and can be used for post-processing. + * `*_trained_dates.df.pkl` + * dates associated with the `trained_df.pkl`, useful for post-processing. + +The example file structure would look like this: + +``` +├── models +│   └── unique-id +│   ├── config_freqai.example.json +│   ├── historic_predictions.backup.pkl +│   ├── historic_predictions.pkl +│   ├── pair_dictionary.json +│   ├── sub-train-1INCH_1662821319 +│   │   ├── cb_1inch_1662821319_metadata.json +│   │   ├── cb_1inch_1662821319_model.joblib +│   │   ├── cb_1inch_1662821319_pca_object.pkl +│   │   ├── cb_1inch_1662821319_svm_model.joblib +│   │   ├── cb_1inch_1662821319_trained_dates_df.pkl +│   │   └── cb_1inch_1662821319_trained_df.pkl +│   ├── sub-train-1INCH_1662821371 +│   │   ├── cb_1inch_1662821371_metadata.json +│   │   ├── cb_1inch_1662821371_model.joblib +│   │   ├── cb_1inch_1662821371_pca_object.pkl +│   │   ├── cb_1inch_1662821371_svm_model.joblib +│   │   ├── cb_1inch_1662821371_trained_dates_df.pkl +│   │   └── cb_1inch_1662821371_trained_df.pkl +│   ├── sub-train-ADA_1662821344 +│   │   ├── cb_ada_1662821344_metadata.json +│   │   ├── cb_ada_1662821344_model.joblib +│   │   ├── cb_ada_1662821344_pca_object.pkl +│   │   ├── cb_ada_1662821344_svm_model.joblib +│   │   ├── cb_ada_1662821344_trained_dates_df.pkl +│   │   └── cb_ada_1662821344_trained_df.pkl +│   └── sub-train-ADA_1662821399 +│   ├── cb_ada_1662821399_metadata.json +│   ├── cb_ada_1662821399_model.joblib +│   ├── cb_ada_1662821399_pca_object.pkl +│   ├── cb_ada_1662821399_svm_model.joblib +│   ├── cb_ada_1662821399_trained_dates_df.pkl +│   └── cb_ada_1662821399_trained_df.pkl +``` + +## Backtesting + +When users run a backtest, `FreqAI` will automatically save the predictions to be reused for future runs under the same `identifier`. This is a performance enhancement geared towards enabling high-level hyperopting of entry/exit criteria. That means the user will see an additional directory created in their `unique-id` folder called `predictions` which contains all the predictions stored in `hdf` format. + +If users wish to change their features, they **must** use a new identifier which will signal to `FreqAI` to train new models. If users wish to save the models generated during a particular backtest so they can start a live deployment without an initial training, they must set `save_backtest_models` to `True` in their configuration file. + +### Downloading data for backtesting +Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](freqai-configuration.md#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. + +As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). + +## Live deployments + +### Auto data download + +`FreqAI` automatically downloads and proper amount of data to ensure it can train a model using the user defined `train_period_days` and the strategy defined `startup_candle_count`. + +### Historical predictions + +The historical predictions are collected for the life-time of a single `identifier` and stored in `historical_predictions.pkl` + +### Defining model expirations + +During dry/live mode, FreqAI trains each coin pair sequentially (on separate threads/GPU from the main Freqtrade bot). This means that there is always an age discrepancy between models. If a user is training on 50 pairs, and each pair requires 5 minutes to train, the oldest model will be over 4 hours old. This may be undesirable if the characteristic time scale (the trade duration target) for a strategy is less than 4 hours. The user can decide to only make trade entries if the model is less than +a certain number of hours old by setting the `expiration_hours` in the config file: + +```json + "freqai": { + "expiration_hours": 0.5, + } +``` + +In the presented example config, the user will only allow predictions on models that are less than 1/2 hours old. + +### Purging old model data + +FreqAI stores new model files each time it retrains. These files become obsolete as new models are trained and FreqAI adapts to new market conditions. Users planning to leave FreqAI running for extended periods of time with high frequency retraining should enable `purge_old_models` in their config: + +```json + "freqai": { + "purge_old_models": true, + } +``` + +This will automatically purge all models older than the two most recently trained ones. + +### Returning additional info from training + +The user may find that there are some important metrics that they'd like to return to the strategy at the end of each model training. +The user can include these metrics by assigning them to `dk.data['extra_returns_per_train']['my_new_value'] = XYZ` inside their custom prediction model class. FreqAI takes the `my_new_value` assigned in this dictionary and expands it to fit the return dataframe to the strategy. +The user can then use the value in the strategy with `dataframe['my_new_value']`. An example of how this is already used in FreqAI is +the `&*_mean` and `&*_std` values, which indicate the mean and standard deviation of the particular target (label) during the most recent training. +An example, where the user wants to use live metrics from the trade database, is shown below: + +```json + "freqai": { + "extra_returns_per_train": {"total_profit": 4} + } +``` + +The user needs to set the standard dictionary in the config so that FreqAI can return proper dataframe shapes. These values will likely be overridden by the prediction model, but in the case where the model has yet to set them, or needs a default initial value, this is the value that will be returned. diff --git a/docs/freqai-feature-engineering.md b/docs/freqai-feature-engineering.md new file mode 100644 index 000000000..ebde5aa81 --- /dev/null +++ b/docs/freqai-feature-engineering.md @@ -0,0 +1,274 @@ +# Feature engineering + +Feature engineering is handled within the `FreqAI` config file and the user strategy. The user adds all their `base features` to their strategy, such as `RSI`, `MFI`, `EMA`, `SMA` etc. These can be custom indicators or they can be imported from any technical-analysis library that the user can find. These features are added by the user inside the `populate_any_indicators()` method of the strategy by prepending indicators with `%`, and labels with `&`. + +Users should start from an existing `populate_any_indicators()` to ensure they are following some of the conventions that help with feature engineering. Here is an example: + +```python + def populate_any_indicators( + self, pair, df, tf, informative=None, set_generalized_indicators=False + ): + """ + Function designed to automatically generate, name, and merge features + from user-indicated timeframes in the configuration file. The user controls the indicators + passed to the training/prediction by prepending indicators with `'%-' + coin ` + (see convention below). I.e., the user should not prepend any supporting metrics + (e.g., bb_lowerband below) with % unless they explicitly want to pass that metric to the + model. + :param pair: pair to be used as informative + :param df: strategy dataframe which will receive merges from informatives + :param tf: timeframe of the dataframe which will modify the feature names + :param informative: the dataframe associated with the informative pair + :param coin: the name of the coin which will modify the feature names. + """ + + coin = pair.split('/')[0] + + if informative is None: + informative = self.dp.get_pair_dataframe(pair, tf) + + # first loop is automatically duplicating indicators for time periods + for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]: + t = int(t) + informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) + informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) + informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) + + bollinger = qtpylib.bollinger_bands( + qtpylib.typical_price(informative), window=t, stds=2.2 + ) + informative[f"{coin}bb_lowerband-period_{t}"] = bollinger["lower"] + informative[f"{coin}bb_middleband-period_{t}"] = bollinger["mid"] + informative[f"{coin}bb_upperband-period_{t}"] = bollinger["upper"] + + informative[f"%-{coin}bb_width-period_{t}"] = ( + informative[f"{coin}bb_upperband-period_{t}"] + - informative[f"{coin}bb_lowerband-period_{t}"] + ) / informative[f"{coin}bb_middleband-period_{t}"] + informative[f"%-{coin}close-bb_lower-period_{t}"] = ( + informative["close"] / informative[f"{coin}bb_lowerband-period_{t}"] + ) + + informative[f"%-{coin}relative_volume-period_{t}"] = ( + informative["volume"] / informative["volume"].rolling(t).mean() + ) + + indicators = [col for col in informative if col.startswith("%")] + # This loop duplicates and shifts all indicators to add a sense of recency to data + for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): + if n == 0: + continue + informative_shift = informative[indicators].shift(n) + informative_shift = informative_shift.add_suffix("_shift-" + str(n)) + informative = pd.concat((informative, informative_shift), axis=1) + + df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True) + skip_columns = [ + (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"] + ] + df = df.drop(columns=skip_columns) + + # Add generalized indicators here (because in live, it will call this + # function to populate indicators during training). Notice how we ensure not to + # add them multiple times + if set_generalized_indicators: + df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7 + df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25 + + # user adds targets here by prepending them with &- (see convention below) + # If user wishes to use multiple targets, a multioutput prediction model + # needs to be used such as templates/CatboostPredictionMultiModel.py + df["&-s_close"] = ( + df["close"] + .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) + .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) + .mean() + / df["close"] + - 1 + ) + + return df +``` + +In the presented example strategy, the user does not wish to pass the `bb_lowerband` as a feature to the model, +and has therefore not prepended it with `%`. The user does, however, wish to pass `bb_width` to the +model for training/prediction and has therefore prepended it with `%`. + +Now that the user has set their `base features`, they will next expand upon their base features using the powerful `feature_parameters` in their configuration file: + +```json + "freqai": { + ... + "feature_parameters" : { + "include_timeframes": ["5m","15m","4h"], + "include_corr_pairlist": [ + "ETH/USD", + "LINK/USD", + "BNB/USD" + ], + "label_period_candles": 24, + "include_shifted_candles": 2, + "indicator_periods_candles": [10, 20] + }, + ... + } +``` + +The `include_timeframes` in the config above are the timeframes (`tf`) of each call to `populate_any_indicators()` in the strategy. In the present case, the user is asking for the `5m`, `15m`, and `4h` timeframes of the `rsi`, `mfi`, `roc`, and `bb_width` to be included in the feature set. + +The user can ask for each of the defined features to be included also from informative pairs using the `include_corr_pairlist`. This means that the feature set will include all the features from `populate_any_indicators` on all the `include_timeframes` for each of the correlated pairs defined in the config (`ETH/USD`, `LINK/USD`, and `BNB/USD`). + +`include_shifted_candles` indicates the number of previous candles to include in the feature set. For example, `include_shifted_candles: 2` tells `FreqAI` to include the past 2 candles for each of the features in the feature set. + +In total, the number of features the user of the presented example strat has created is: length of `include_timeframes` * no. features in `populate_any_indicators()` * length of `include_corr_pairlist` * no. `include_shifted_candles` * length of `indicator_periods_candles` + $= 3 * 3 * 3 * 2 * 2 = 108$. + + +### Feature normalization + +`FreqAI` is strict when it comes to data normalization - all data is always automatically normalized to the training feature space according to industry standards. This includes all test data and unseen prediction data (dry/live/backtest). `FreqAI` stores all the metadata required to ensure that prediction features will be properly normalized and that predictions are properly denormalized. For this reason, it is not recommended to eschew industry standards and modify `FreqAI` internals - however - advanced users can do so by inheriting `train()` in their custom `IFreqaiModel` and using their own normalization functions. + +### Reducing data dimensionality with Principal Component Analysis + +Users can reduce the dimensionality of their features by activating the `principal_component_analysis` in the config: + +```json + "freqai": { + "feature_parameters" : { + "principal_component_analysis": true + } + } +``` + +This will perform PCA on the features and reduce the dimensionality of the data so that the explained variance of the data set is >= 0.999. + +### Stratifying the data for training and testing the model + +The user can stratify (group) the training/testing data using: + +```json + "freqai": { + "feature_parameters" : { + "stratify_training_data": 3 + } + } +``` + +This will split the data chronologically so that every Xth data point is used to test the model after training. In the +example above, the user is asking for every third data point in the dataframe to be used for +testing; the other points are used for training. + +The test data is used to evaluate the performance of the model after training. If the test score is high, the model is able to capture the behavior of the data well. If the test score is low, either the model either does not capture the complexity of the data, the test data is significantly different from the train data, or a different model should be used. + +### Using the `inlier_metric` + +The `inlier_metric` is a metric aimed at quantifying how different a prediction data point is from the most recent historic data points. + +User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points). + +This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. The cumulative distribution function for the weibull distribution is used to produce a quantile for each of the data points. The quantiles for each lookback point are averaged to create the `inlier_metric`. + +FreqAI adds this `inlier_metric` score to the training features! In other words, your model is trained to recognize how this temporal inlier metric is related to the user set labels. + +This function does **not** remove outliers from the data set. + +### Controlling the model learning process + +Model training parameters are unique to the machine learning library selected by the user. FreqAI allows the user to set any parameter for any library using the `model_training_parameters` dictionary in the user configuration file. The example configuration file (found in `config_examples/config_freqai.example.json`) show some of the example parameters associated with `Catboost` and `LightGBM`, but the user can add any parameters available in those libraries. + +Data split parameters are defined in `data_split_parameters` which can be any parameters associated with `Sklearn`'s `train_test_split()` function. + +FreqAI includes some additional parameters such as `weight_factor`, which allows the user to weight more recent data more strongly +than past data via an exponential function: + +$$ W_i = \exp(\frac{-i}{\alpha*n}) $$ + +where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. Below is a figure showing the effect of different weight factors on the data points (candles) in a feature set. + +![weight-factor](assets/freqai_weight-factor.jpg) + +`train_test_split()` has a parameters called `shuffle` that allows the user to keep the data unshuffled. This is particularly useful to avoid biasing training with temporally auto-correlated data. + +Finally, `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented example config, +the user is asking for `labels` that are 24 candles in the future. + +#### Continual learning + +Users can choose to adopt a "continual learning" strategy by setting `"continual_learning": true` in their configuration file. This setting will train an initial model from scratch, and subsequent trainings will start from the final model state of the preceding training. By default, this is set to `false` which trains a new model from scratch upon each subsequent training. + +### Outlier removal + +#### Removing outliers with the Dissimilarity Index + +The user can tell FreqAI to remove outlier data points from the training/test data sets using a Dissimilarity Index by including the following statement in the config: + +```json + "freqai": { + "feature_parameters" : { + "DI_threshold": 1 + } + } +``` + +Equity and crypto markets suffer from a high level of non-patterned noise in the form of outlier data points. The Dissimilarity Index (DI) aims to quantify the uncertainty associated with each prediction made by the model. The DI allows predictions which are outliers (not existent in the model feature space) to be thrown out due to low levels of certainty. + +To do so, FreqAI measures the distance between each training data point (feature vector), $X_{a}$, and all other training data points: + +$$ d_{ab} = \sqrt{\sum_{j=1}^p(X_{a,j}-X_{b,j})^2} $$ + +where $d_{ab}$ is the distance between the normalized points $a$ and $b$. $p$ is the number of features, i.e., the length of the vector $X$. The characteristic distance, $\overline{d}$ for a set of training data points is simply the mean of the average distances: + +$$ \overline{d} = \sum_{a=1}^n(\sum_{b=1}^n(d_{ab}/n)/n) $$ + +$\overline{d}$ quantifies the spread of the training data, which is compared to the distance between a new prediction feature vectors, $X_k$ and all the training data: + +$$ d_k = \arg \min d_{k,i} $$ + +which enables the estimation of the Dissimilarity Index as: + +$$ DI_k = d_k/\overline{d} $$ + +The user can tweak the DI through the `DI_threshold` to increase or decrease the extrapolation of the trained model. + +Below is a figure that describes the DI for a 3D data set. + +![DI](assets/freqai_DI.jpg) + +#### Removing outliers using a Support Vector Machine (SVM) + +The user can tell FreqAI to remove outlier data points from the training/test data sets using a SVM by setting: + +```json + "freqai": { + "feature_parameters" : { + "use_SVM_to_remove_outliers": true + } + } +``` + +FreqAI will train an SVM on the training data (or components of it if the user activated +`principal_component_analysis`) and remove any data point that the SVM deems to be beyond the feature space. + +The parameter `shuffle` is by default set to `False` to ensure consistent results. If it is set to `True`, running the SVM multiple times on the same data set might result in different outcomes due to `max_iter` being to low for the algorithm to reach the demanded `tol`. Increasing `max_iter` solves this issue but causes the procedure to take longer time. + +The parameter `nu`, *very* broadly, is the amount of data points that should be considered outliers. + +#### Removing outliers with DBSCAN + +The user can configure FreqAI to use DBSCAN to cluster and remove outliers from the training/test data set or incoming outliers from predictions, by activating `use_DBSCAN_to_remove_outliers` in the config: + +```json + "freqai": { + "feature_parameters" : { + "use_DBSCAN_to_remove_outliers": true + } + } +``` + +DBSCAN is an unsupervised machine learning algorithm that clusters data without needing to know how many clusters there should be. + +Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters the data set by setting all data points that have $N-1$ other data points within a distance of $\varepsilon$ as *core points*. A data point that is within a distance of $\varepsilon$ from a *core point* but that does not have $N-1$ other data points within a distance of $\varepsilon$ from itself is considered an *edge point*. A cluster is then the collection of *core points* and *edge points*. Data points that have no other data points at a distance $<\varepsilon$ are considered outliers. The figure below shows a cluster with $N = 3$. + +![dbscan](assets/freqai_dbscan.jpg) + +FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as 1/4 of the no. of time points in the feature set, and `eps` ($\varepsilon$) taken as the elbow point in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. diff --git a/docs/freqai-running.md b/docs/freqai-running.md new file mode 100644 index 000000000..90856c841 --- /dev/null +++ b/docs/freqai-running.md @@ -0,0 +1,104 @@ +# Running FreqAI + +There are two ways to train and deploy an adaptive machine learning model. FreqAI enables live deployment as well as backtesting analyses. In both cases, a model is trained periodically, as shown in the following figure. + +![freqai-window](assets/freqai_moving-window.jpg) + +### Running the model live + +FreqAI can be run dry/live using the following command: + +```bash +freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor +``` + +By default, FreqAI will not find any existing models and will start by training a new one +based on the user's configuration settings. Following training, the model will be used to make predictions on incoming candles until a new model is available. New models are typically generated as often as possible, with FreqAI managing an internal queue of the coin pairs to try to keep all models equally up to date. FreqAI will always use the most recently trained model to make predictions on incoming live data. If the user does not want FreqAI to retrain new models as often as possible, they can set `live_retrain_hours` to tell FreqAI to wait at least that number of hours before training a new model. Additionally, the user can set `expired_hours` to tell FreqAI to avoid making predictions on models that are older than that number of hours. + +If the user wishes to start a dry/live run from a saved backtest model (or from a previously crashed dry/live session), the user only needs to reuse +the same `identifier` parameter: + +```json + "freqai": { + "identifier": "example", + "live_retrain_hours": 0.5 + } +``` + +In this case, although FreqAI will initiate with a +pre-trained model, it will still check to see how much time has elapsed since the model was trained, +and if a full `live_retrain_hours` has elapsed since the end of the loaded model, FreqAI will retrain. + +### Backtesting + +The FreqAI backtesting module can be executed with the following command: + +```bash +freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 +``` + +Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). + +If this command has never been executed with the existing config file, it will train a new model +for each pair, for each backtesting window within the expanded `--timerange`. + +!!! Note "Model reuse" + Once the training is completed, the user can execute the backtesting again with the same config file and + FreqAI will find the trained models and load them instead of spending time training. This is useful + if the user wants to tweak (or even hyperopt) buy and sell criteria inside the strategy. If the user + *wants* to retrain a new model with the same config file, then they should simply change the `identifier`. + This way, the user can return to using any model they wish by simply specifying the `identifier`. + +--- + +### Hyperopt + +Users can hyperopt using the same command as typical [hyperopt](hyperopt.md): + +```bash +freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 +``` + +Users need to have the data pre-downloaded in the same fashion as if they were doing a FreqAI [backtest](#backtesting). In addition, users must consider some restrictions when trying to [Hyperopt](hyperopt.md) FreqAI strategies: + +- The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. +- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md#running-hyperopt-with-smaller-search-space). +- The [Backtesting](#backtesting) instructions also apply to Hyperopt. + +The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. Users need to focus on hyperopting parameters that are not used in their FreqAI features. For example, users should not try to hyperopt rolling window lengths in their feature creation, or any of their FreqAI config which changes predictions. In order to efficiently hyperopt the FreqAI strategy, FreqAI stores predictions as dataframes and reuses them. Hence the requirement to hyperopt entry/exit thresholds/criteria only. + +A good example of a hyperoptable parameter in FreqAI is a value for `DI_values` beyond which we consider outliers and below which we consider inliers: + +```python +di_max = IntParameter(low=1, high=20, default=10, space='buy', optimize=True, load=True) +dataframe['outlier'] = np.where(dataframe['DI_values'] > self.di_max.value/10, 1, 0) +``` + +Which would help the user understand the appropriate Dissimilarity Index values for their particular parameter space. + +### Deciding the size of the sliding training window and backtesting duration + +The user defines the backtesting timerange with the typical `--timerange` parameter in the configuration file. The duration of the sliding training window is set by `train_period_days`, whilst `backtest_period_days` is the sliding backtesting window, both in number of days (`backtest_period_days` can be +a float to indicate sub-daily retraining in live/dry mode). In the presented example config, the user is asking FreqAI to use a training period of 30 days and backtest on the subsequent 7 days. This means that if the user sets `--timerange 20210501-20210701`, FreqAI will train have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). After the training of the model, FreqAI will backtest the subsequent 7 days. The "sliding window" then moves one week forward (emulating FreqAI retraining once per week in live mode) and the new model uses the previous 30 days (including the 7 days used for backtesting by the previous model) to train. This is repeated until the end of `--timerange`. + +!!! Note + Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run. + +### Downloading data for backtesting +Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. + +As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). + +### Setting up a follower + +The user can define: + +```json + "freqai": { + "follow_mode": true, + "identifier": "example" + } +``` + +to indicate to the bot that it should not train models, but instead should look for models trained by a leader with the same `identifier`. In this example, the user has a leader bot with the `identifier: "example"`. The leader bot is already running or launching simultaneously as the follower. +The follower will load models created by the leader and inference them to obtain predictions. diff --git a/docs/freqai.md b/docs/freqai.md index 5f523f58a..955e49250 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -6,18 +6,18 @@ FreqAI is a module designed to automate a variety of tasks associated with train Features include: -* **Self-adaptive retraining**: retrain models during [live deployments](#running-the-model-live) to self-adapt to the market in an unsupervised manner. -* **Rapid feature engineering**: create large rich [feature sets](#feature-engineering) (10k+ features) based on simple user-created strategies. +* **Self-adaptive retraining**: retrain models during [live deployments](freqai-running.md#running-the-model-live) to self-adapt to the market in an unsupervised manner. +* **Rapid feature engineering**: create large rich [feature sets](freqai-feature-engineering.md#feature-engineering) (10k+ features) based on simple user-created strategies. * **High performance**: adaptive retraining occurs on a separate thread (or on GPU if available) from inferencing and bot trade operations. Newest models and data are kept in memory for rapid inferencing. -* **Realistic backtesting**: emulate self-adaptive retraining with a [backtesting module](#backtesting) that automates past retraining. -* **Modifiability**: use the generalized and robust architecture for incorporating any [machine learning library/method](#building-a-custom-prediction-model) available in Python. Eight examples are currently available, including classifiers, regressors, and a convolutional neural network. -* **Smart outlier removal**: remove outliers from training and prediction data sets using a variety of [outlier detection techniques](#outlier-removal). -* **Crash resilience**: store model to disk to make reloading from a crash fast and easy, and [purge obsolete files](#purging-old-model-data) for sustained dry/live runs. -* **Automatic data normalization**: [normalize the data](#feature-normalization) in a smart and statistically safe way. +* **Realistic backtesting**: emulate self-adaptive retraining with a [backtesting module](freqai-running.md#backtesting) that automates past retraining. +* **Extensibility**: use the generalized and robust architecture for incorporating any [machine learning library/method](freqai-configuration.md#building-a-custom-prediction-model) available in Python. Eight examples are currently available, including classifiers, regressors, and a convolutional neural network. +* **Smart outlier removal**: remove outliers from training and prediction data sets using a variety of [outlier detection techniques](freqai-feature-engineering.md#outlier-removal). +* **Crash resilience**: store model to disk to make reloading from a crash fast and easy, and [purge obsolete files](freqai-data-handling.md#purging-old-model-data) for sustained dry/live runs. +* **Automatic data normalization**: [normalize the data](freqai-feature-engineering.md#feature-normalization) in a smart and statistically safe way. * **Automatic data download**: compute the data download timerange and update historic data (in live deployments). * **Cleaning of incoming data**: handle NaNs safely before training and prediction. -* **Dimensionality reduction**: reduce the size of the training data via [Principal Component Analysis](#reducing-data-dimensionality-with-principal-component-analysis). -* **Deploying bot fleets**: set one bot to train models while a fleet of [follower bots](#setting-up-a-follower) inference the models and handle trades. +* **Dimensionality reduction**: reduce the size of the training data via [Principal Component Analysis](freqai-feature-engineering.md#reducing-data-dimensionality-with-principal-component-analysis). +* **Deploying bot fleets**: set one bot to train models while a fleet of [follower bots](freqai-running.md#setting-up-a-follower) inference the models and handle trades. ## Quick start @@ -35,8 +35,7 @@ The example strategy, example prediction model, and example config can be found ## General approach -The user provides FreqAI with a set of custom *base* indicators (the same way as in a typical Freqtrade strategy) as well as target values (*labels*). -FreqAI trains a model to predict the target values based on the input of custom indicators, for each pair in the whitelist. These models are consistently retrained to adapt to market conditions. FreqAI offers the ability to both backtest strategies (emulating reality with periodic retraining) and deploy dry/live runs. In dry/live conditions, FreqAI can be set to constant retraining in a background thread in an effort to keep models as up to date as possible. +The user provides FreqAI with a set of custom *base* indicators (the same way as in a typical Freqtrade strategy) as well as target values (*labels*). FreqAI trains a model to predict the target values based on the input of custom indicators, for each pair in the whitelist. These models are consistently retrained to adapt to market conditions. FreqAI offers the ability to both backtest strategies (emulating reality with periodic retraining) and deploy dry/live runs. In dry/live conditions, FreqAI can be set to constant retraining in a background thread in an effort to keep models as up to date as possible. An overview of the algorithm is shown below, explaining the data processing pipeline and the model usage. @@ -44,19 +43,13 @@ An overview of the algorithm is shown below, explaining the data processing pipe ### Important machine learning vocabulary -**Features** - the quantities with which a model is trained. All features for a single candle is stored as a vector. In FreqAI, the user -builds the feature sets from anything they can construct in the strategy. +**Features** - the quantities with which a model is trained. All features for a single candle is stored as a vector. In FreqAI, the user builds the feature sets from anything they can construct in the strategy. -**Labels** - the target values that a model is trained -toward. Each set of features is associated with a single label that is -defined by the user within the strategy. These labels intentionally look into the -future, and are not available to the model during dry/live/backtesting. +**Labels** - the target values that a model is trained toward. Each set of features is associated with a single label that is defined by the user within the strategy. These labels intentionally look into the future, and are not available to the model during dry/live/backtesting. -**Training** - the process of feeding individual feature sets, composed of historic data, with associated labels into the -model with the goal of matching input feature sets to associated labels. +**Training** - the process of feeding individual feature sets, composed of historic data, with associated labels into the model with the goal of matching input feature sets to associated labels. -**Train data** - a subset of the historic data that is fed to the model during -training. This data directly influences weight connections in the model. +**Train data** - a subset of the historic data that is fed to the model during training. This data directly influences weight connections in the model. **Test data** - a subset of the historic data that is used to evaluate the performance of the model after training. This data does not influence nodal weights within the model. @@ -73,723 +66,7 @@ pip install -r requirements-freqai.txt ### Usage with docker -For docker users, a dedicated tag with freqAI dependencies is available as `:freqai`. -As such - you can replace the image line in your docker-compose file with `image: freqtradeorg/freqtrade:develop_freqai`. -This image contains the regular freqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices. - -## Setting up FreqAI - -### Parameter table - -The table below will list all configuration parameters available for FreqAI, presented in the same order as `config_examples/config_freqai.example.json`. - -Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways. - -| Parameter | Description | -|------------|-------------| -| | **General configuration parameters** -| `freqai` | **Required.**
    The parent dictionary containing all the parameters for controlling FreqAI.
    **Datatype:** Dictionary. -| `purge_old_models` | Delete obsolete models (otherwise, all historic models will remain on disk).
    **Datatype:** Boolean. Default: `False`. -| `train_period_days` | **Required.**
    Number of days to use for the training data (width of the sliding window).
    **Datatype:** Positive integer. -| `backtest_period_days` | **Required.**
    Number of days to inference from the trained model before sliding the window defined above, and retraining the model. This can be fractional days, but beware that the user-provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
    **Datatype:** Float. -| `save_backtest_models` | Backtesting operates most efficiently by saving the prediction data and reusing them directly for subsequent runs (when users wish to tune entry/exit parameters). If a user wishes to save models to disk when running backtesting, they should activate `save_backtest_models`. A user may wish to do this if they plan to use the same model files for starting a dry/live instance with the same `identifier`.
    **Datatype:** Boolean. Default: `False`. -| `identifier` | **Required.**
    A unique name for the current model. This can be reused to reload pre-trained models/data.
    **Datatype:** String. -| `live_retrain_hours` | Frequency of retraining during dry/live runs.
    Default set to 0, which means the model will retrain as often as possible.
    **Datatype:** Float > 0. -| `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
    Defaults set to 0, which means models never expire.
    **Datatype:** Positive integer. -| `fit_live_predictions_candles` | Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training data set.
    **Datatype:** Positive integer. -| `follow_mode` | If true, this instance of FreqAI will look for models associated with `identifier` and load those for inferencing. A `follower` will **not** train new models.
    **Datatype:** Boolean. Default: `False`. -| `continual_learning` | If true, FreqAI will start training new models from the final state of the most recently trained model.
    **Datatype:** Boolean. Default: `False`. -| | **Feature parameters** -| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](#feature-engineering).
    **Datatype:** Dictionary. -| `include_timeframes` | A list of timeframes that all indicators in `populate_any_indicators` will be created for. The list is added as features to the base asset feature set.
    **Datatype:** List of timeframes (strings). -| `include_corr_pairlist` | A list of correlated coins that FreqAI will add as additional features to all `pair_whitelist` coins. All indicators set in `populate_any_indicators` during feature engineering (see details [here](#feature-engineering)) will be created for each coin in this list, and that set of features is added to the base asset feature set.
    **Datatype:** List of assets (strings). -| `label_period_candles` | Number of candles into the future that the labels are created for. This is used in `populate_any_indicators` (see `templates/FreqaiExampleStrategy.py` for detailed usage). The user can create custom labels, making use of this parameter or not.
    **Datatype:** Positive integer. -| `include_shifted_candles` | Add features from previous candles to subsequent candles to add historical information. FreqAI takes all features from the `include_shifted_candles` previous candles, duplicates and shifts them so that the information is available for the subsequent candle.
    **Datatype:** Positive integer. -| `weight_factor` | Used to set weights for training data points according to their recency. See details about how it works [here](#controlling-the-model-learning-process).
    **Datatype:** Positive float (typically < 1). -| `indicator_max_period_candles` | **No longer used**. User must use the strategy set `startup_candle_count` which defines the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
    **Datatype:** positive integer. -| `indicator_periods_candles` | Calculate indicators for `indicator_periods_candles` time periods and add them to the feature set.
    **Datatype:** List of positive integers. -| `stratify_training_data` | This value is used to indicate the grouping of the data. For example, 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. See details about how it works [here](#stratifying-the-data-for-training-and-testing-the-model)
    **Datatype:** Positive integer. -| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis)
    **Datatype:** Boolean. -| `DI_threshold` | Activates the Dissimilarity Index for outlier detection when > 0. See details about how it works [here](#removing-outliers-with-the-dissimilarity-index).
    **Datatype:** Positive float (typically < 1). -| `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Boolean. -| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
    **Datatype:** Dictionary. -| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
    **Datatype:** Boolean. -| `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
    **Datatype:** int. Default: 0 -| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5% (i.e. the percent of data falling within the first standard deviation). Good for preventing overfitting.
    **Datatype:** int. Default: 0 -| `outlier_protection_percentage` | If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact. If the outlier protection is triggered, no predictions will be made based on the training data.
    **Datatype:** Float. Default: `30` -| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
    **Datatype:** Boolean. Default: False -| | **Data split parameters** -| `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
    **Datatype:** Dictionary. -| `test_size` | Fraction of data that should be used for testing instead of training.
    **Datatype:** Positive float < 1. -| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
    **Datatype:** Boolean. -| | **Model training parameters** -| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
    **Datatype:** Dictionary. -| `n_estimators` | The number of boosted trees to fit in regression.
    **Datatype:** Integer. -| `learning_rate` | Boosting learning rate during regression.
    **Datatype:** Float. -| `n_jobs`, `thread_count`, `task_type` | Set the number of threads for parallel processing and the `task_type` (`gpu` or `cpu`). Different model libraries use different parameter names.
    **Datatype:** Float. -| | **Extraneous parameters** -| `keras` | If your model makes use of Keras (typical for Tensorflow-based prediction models), activate this flag so that the model save/loading follows Keras standards.
    **Datatype:** Boolean. Default: `False`. -| `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for shifting candles (`include_shifted_candles`) by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction.
    **Datatype:** Integer. Default: 2. - -### Important dataframe key patterns - -Below are the values the user can expect to include/use inside a typical strategy dataframe (`df[]`): - -| DataFrame Key | Description | -|------------|-------------| -| `df['&*']` | Any dataframe column prepended with `&` in `populate_any_indicators()` is treated as a training target (label) inside FreqAI (typically following the naming convention `&-s*`). The names of these dataframe columns are fed back to the user as the predictions. For example, if the user wishes to predict the price change in the next 40 candles (similar to `templates/FreqaiExampleStrategy.py`), they set `df['&-s_close']`. FreqAI makes the predictions and gives them back under the same key (`df['&-s_close']`) to be used in `populate_entry/exit_trend()`.
    **Datatype:** Depends on the output of the model. -| `df['&*_std/mean']` | Standard deviation and mean values of the user-defined labels during training (or live tracking with `fit_live_predictions_candles`). Commonly used to understand the rarity of a prediction (use the z-score as shown in `templates/FreqaiExampleStrategy.py` to evaluate how often a particular prediction was observed during training or historically with `fit_live_predictions_candles`).
    **Datatype:** Float. -| `df['do_predict']` | Indication of an outlier data point. The return value is integer between -1 and 2, which lets the user know if the prediction is trustworthy or not. `do_predict==1` means the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](#removing-outliers-with-the-dissimilarity-index)) of the input data point is above the user-defined threshold, FreqAI will subtract 1 from `do_predict`, resulting in `do_predict==0`. If `use_SVM_to_remove_outliers()` is active, the Support Vector Machine (SVM) may also detect outliers in training and prediction data. In this case, the SVM will also subtract 1 from `do_predict`. If the input data point was considered an outlier by the SVM but not by the DI, the result will be `do_predict==0`. If both the DI and the SVM considers the input data point to be an outlier, the result will be `do_predict==-1`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`.
    **Datatype:** Integer between -1 and 2. -| `df['DI_values']` | Dissimilarity Index values are proxies to the level of confidence FreqAI has in the prediction. A lower DI means the prediction is close to the training data, i.e., higher prediction confidence.
    **Datatype:** Float. -| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, the user can include the RSI in the training feature set (similar to in `templates/FreqaiExampleStrategy.py`) by setting `df['%-rsi']`. See more details on how this is done [here](#feature-engineering).
    **Note**: Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features is easily engineered using the multiplictative functionality described in the `feature_parameters` table shown above), these features are removed from the dataframe upon return from FreqAI. If the user wishes to keep a particular type of feature for plotting purposes, they can prepend it with `%%`.
    **Datatype:** Depends on the output of the model. - -### File structure - -`user_data_dir/models/` contains all the data associated with the trainings and backtests. -This file structure is heavily controlled and inferenced by the `FreqaiDataKitchen()` -and should therefore not be modified. - -### Example config file - -The user interface is isolated to the typical Freqtrade config file. A FreqAI config should include: - -```json - "freqai": { - "enabled": true, - "startup_candles": 10000, - "purge_old_models": true, - "train_period_days": 30, - "backtest_period_days": 7, - "identifier" : "unique-id", - "feature_parameters" : { - "include_timeframes": ["5m","15m","4h"], - "include_corr_pairlist": [ - "ETH/USD", - "LINK/USD", - "BNB/USD" - ], - "label_period_candles": 24, - "include_shifted_candles": 2, - "indicator_periods_candles": [10, 20] - }, - "data_split_parameters" : { - "test_size": 0.25 - }, - "model_training_parameters" : { - "n_estimators": 100 - }, - } -``` - -## Building a FreqAI strategy - -The FreqAI strategy requires the user to include the following lines of code in the standard Freqtrade strategy: - -```python - # user should define the maximum startup candle count (the largest number of candles - # passed to any single indicator) - startup_candle_count: int = 20 - - def informative_pairs(self): - whitelist_pairs = self.dp.current_whitelist() - corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"] - informative_pairs = [] - for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]: - for pair in whitelist_pairs: - informative_pairs.append((pair, tf)) - for pair in corr_pairs: - if pair in whitelist_pairs: - continue # avoid duplication - informative_pairs.append((pair, tf)) - return informative_pairs - - def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - - # the model will return all labels created by user in `populate_any_indicators` - # (& appended targets), an indication of whether or not the prediction should be accepted, - # the target mean/std values for each of the labels created by user in - # `populate_any_indicators()` for each training period. - - dataframe = self.freqai.start(dataframe, metadata, self) - - return dataframe - - def populate_any_indicators( - self, pair, df, tf, informative=None, set_generalized_indicators=False - ): - """ - Function designed to automatically generate, name and merge features - from user indicated timeframes in the configuration file. User controls the indicators - passed to the training/prediction by prepending indicators with `'%-' + coin ` - (see convention below). I.e. user should not prepend any supporting metrics - (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the - model. - :param pair: pair to be used as informative - :param df: strategy dataframe which will receive merges from informatives - :param tf: timeframe of the dataframe which will modify the feature names - :param informative: the dataframe associated with the informative pair - :param coin: the name of the coin which will modify the feature names. - """ - - coin = pair.split('/')[0] - - if informative is None: - informative = self.dp.get_pair_dataframe(pair, tf) - - # first loop is automatically duplicating indicators for time periods - for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]: - t = int(t) - informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) - informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) - - indicators = [col for col in informative if col.startswith("%")] - # This loop duplicates and shifts all indicators to add a sense of recency to data - for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): - if n == 0: - continue - informative_shift = informative[indicators].shift(n) - informative_shift = informative_shift.add_suffix("_shift-" + str(n)) - informative = pd.concat((informative, informative_shift), axis=1) - - df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True) - skip_columns = [ - (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"] - ] - df = df.drop(columns=skip_columns) - - # Add generalized indicators here (because in live, it will call this - # function to populate indicators during training). Notice how we ensure not to - # add them multiple times - if set_generalized_indicators: - - # user adds targets here by prepending them with &- (see convention below) - # If user wishes to use multiple targets, a multioutput prediction model - # needs to be used such as templates/CatboostPredictionMultiModel.py - df["&-s_close"] = ( - df["close"] - .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - .mean() - / df["close"] - - 1 - ) - - return df - - -``` - -Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](#feature-engineering)) and labels ([more information](#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. - -*Important*: The `self.freqai.start()` function cannot be called outside the `populate_indicators()`. - -### Setting the `startup_candle_count` -Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). - -!!! Note - Typically it is best for users to be safe and multiply their expected `startup_candle_count` by 2. There are instances where the talib functions actually require more data than just the passed `period`. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Look out for this log message to confirm that your data is clean: - - ``` - 2022-08-31 15:14:04 - freqtrade.freqai.data_kitchen - INFO - dropped 0 training points due to NaNs in populated dataset 4319. - ``` - - -## Creating a dynamic target - -The `&*_std/mean` return values describe the statistical fit of the user defined label *during the most recent training*. This value allows the user to know the rarity of a given prediction. For example, `templates/FreqaiExampleStrategy.py`, creates a `target_roi` which is based on filtering out predictions that are below a given z-score of 1.25. - -```python -dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25 -dataframe["sell_roi"] = dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * 1.25 -``` - -If the user wishes to consider the population -of *historical predictions* for creating the dynamic target instead of the trained labels, (as discussed above) the user -can do so by setting `fit_live_prediction_candles` in the config to the number of historical prediction candles -the user wishes to use to generate target statistics. - -```json - "freqai": { - "fit_live_prediction_candles": 300, - } -``` - -If the user sets this value, FreqAI will initially use the predictions from the training data -and subsequently begin introducing real prediction data as it is generated. FreqAI will save -this historical data to be reloaded if the user stops and restarts a model with the same `identifier`. - -## Building a custom prediction model - -FreqAI has multiple example prediction model libraries, such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression. -However, the user can customize and create their own prediction models using the `IFreqaiModel` class. -The user is encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures. - -## Feature engineering - -Features are added by the user inside the `populate_any_indicators()` method of the strategy -by prepending indicators with `%`, and labels with `&`. - -There are some important components/structures that the user *must* include when building their feature set; the use of these is shown below: - -```python - def populate_any_indicators( - self, pair, df, tf, informative=None, set_generalized_indicators=False - ): - """ - Function designed to automatically generate, name, and merge features - from user-indicated timeframes in the configuration file. The user controls the indicators - passed to the training/prediction by prepending indicators with `'%-' + coin ` - (see convention below). I.e., the user should not prepend any supporting metrics - (e.g., bb_lowerband below) with % unless they explicitly want to pass that metric to the - model. - :param pair: pair to be used as informative - :param df: strategy dataframe which will receive merges from informatives - :param tf: timeframe of the dataframe which will modify the feature names - :param informative: the dataframe associated with the informative pair - :param coin: the name of the coin which will modify the feature names. - """ - - coin = pair.split('/')[0] - - if informative is None: - informative = self.dp.get_pair_dataframe(pair, tf) - - # first loop is automatically duplicating indicators for time periods - for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]: - t = int(t) - informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t) - informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t) - informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t) - - bollinger = qtpylib.bollinger_bands( - qtpylib.typical_price(informative), window=t, stds=2.2 - ) - informative[f"{coin}bb_lowerband-period_{t}"] = bollinger["lower"] - informative[f"{coin}bb_middleband-period_{t}"] = bollinger["mid"] - informative[f"{coin}bb_upperband-period_{t}"] = bollinger["upper"] - - informative[f"%-{coin}bb_width-period_{t}"] = ( - informative[f"{coin}bb_upperband-period_{t}"] - - informative[f"{coin}bb_lowerband-period_{t}"] - ) / informative[f"{coin}bb_middleband-period_{t}"] - informative[f"%-{coin}close-bb_lower-period_{t}"] = ( - informative["close"] / informative[f"{coin}bb_lowerband-period_{t}"] - ) - - informative[f"%-{coin}relative_volume-period_{t}"] = ( - informative["volume"] / informative["volume"].rolling(t).mean() - ) - - indicators = [col for col in informative if col.startswith("%")] - # This loop duplicates and shifts all indicators to add a sense of recency to data - for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1): - if n == 0: - continue - informative_shift = informative[indicators].shift(n) - informative_shift = informative_shift.add_suffix("_shift-" + str(n)) - informative = pd.concat((informative, informative_shift), axis=1) - - df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True) - skip_columns = [ - (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"] - ] - df = df.drop(columns=skip_columns) - - # Add generalized indicators here (because in live, it will call this - # function to populate indicators during training). Notice how we ensure not to - # add them multiple times - if set_generalized_indicators: - df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7 - df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25 - - # user adds targets here by prepending them with &- (see convention below) - # If user wishes to use multiple targets, a multioutput prediction model - # needs to be used such as templates/CatboostPredictionMultiModel.py - df["&-s_close"] = ( - df["close"] - .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - .mean() - / df["close"] - - 1 - ) - - return df -``` - -In the presented example strategy, the user does not wish to pass the `bb_lowerband` as a feature to the model, -and has therefore not prepended it with `%`. The user does, however, wish to pass `bb_width` to the -model for training/prediction and has therefore prepended it with `%`. - -The `include_timeframes` in the example config above are the timeframes (`tf`) of each call to `populate_any_indicators()` in the strategy. In the present case, the user is asking for the -`5m`, `15m`, and `4h` timeframes of the `rsi`, `mfi`, `roc`, and `bb_width` to be included in the feature set. - -The user can ask for each of the defined features to be included also from -informative pairs using the `include_corr_pairlist`. This means that the feature -set will include all the features from `populate_any_indicators` on all the `include_timeframes` for each of the correlated pairs defined in the config (`ETH/USD`, `LINK/USD`, and `BNB/USD`). - -`include_shifted_candles` indicates the number of previous -candles to include in the feature set. For example, `include_shifted_candles: 2` tells -FreqAI to include the past 2 candles for each of the features in the feature set. - -In total, the number of features the user of the presented example strat has created is: -length of `include_timeframes` * no. features in `populate_any_indicators()` * length of `include_corr_pairlist` * no. `include_shifted_candles` * length of `indicator_periods_candles` - $= 3 * 3 * 3 * 2 * 2 = 108$. - -Another structure to consider is the location of the labels at the bottom of the example function (below `if set_generalized_indicators:`). -This is where the user will add single features and labels to their feature set to avoid duplication of them from -various configuration parameters that multiply the feature set, such as `include_timeframes`. - -!!! Note - Features **must** be defined in `populate_any_indicators()`. Definining FreqAI features in `populate_indicators()` - will cause the algorithm to fail in live/dry mode. If the user wishes to add generalized features that are not associated with - a specific pair or timeframe, they should use the following structure inside `populate_any_indicators()` - (as exemplified in `freqtrade/templates/FreqaiExampleStrategy.py`): - - ```python - def populate_any_indicators(self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False): - - ... - - # Add generalized indicators here (because in live, it will call only this function to populate - # indicators for retraining). Notice how we ensure not to add them multiple times by associating - # these generalized indicators to the basepair/timeframe - if set_generalized_indicators: - df['%-day_of_week'] = (df["date"].dt.dayofweek + 1) / 7 - df['%-hour_of_day'] = (df['date'].dt.hour + 1) / 25 - - # user adds targets here by prepending them with &- (see convention below) - # If user wishes to use multiple targets, a multioutput prediction model - # needs to be used such as templates/CatboostPredictionMultiModel.py - df["&-s_close"] = ( - df["close"] - .shift(-self.freqai_info["feature_parameters"]["label_period_candles"]) - .rolling(self.freqai_info["feature_parameters"]["label_period_candles"]) - .mean() - / df["close"] - - 1 - ) - ``` - - (Please see the example script located in `freqtrade/templates/FreqaiExampleStrategy.py` for a full example of `populate_any_indicators()`.) - -## Setting classifier targets - -FreqAI includes the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. The user should take care to set the classes using strings: - -```python -df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') -``` - -Additionally, the example classifier models do not accommodate multiple labels, but they do allow multi-class classification within a single label column. - -## Running FreqAI - -There are two ways to train and deploy an adaptive machine learning model. FreqAI enables live deployment as well as backtesting analyses. In both cases, a model is trained periodically, as shown in the following figure. - -![freqai-window](assets/freqai_moving-window.jpg) - -### Running the model live - -FreqAI can be run dry/live using the following command: - -```bash -freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor -``` - -By default, FreqAI will not find any existing models and will start by training a new one -based on the user's configuration settings. Following training, the model will be used to make predictions on incoming candles until a new model is available. New models are typically generated as often as possible, with FreqAI managing an internal queue of the coin pairs to try to keep all models equally up to date. FreqAI will always use the most recently trained model to make predictions on incoming live data. If the user does not want FreqAI to retrain new models as often as possible, they can set `live_retrain_hours` to tell FreqAI to wait at least that number of hours before training a new model. Additionally, the user can set `expired_hours` to tell FreqAI to avoid making predictions on models that are older than that number of hours. - -If the user wishes to start a dry/live run from a saved backtest model (or from a previously crashed dry/live session), the user only needs to reuse -the same `identifier` parameter: - -```json - "freqai": { - "identifier": "example", - "live_retrain_hours": 0.5 - } -``` - -In this case, although FreqAI will initiate with a -pre-trained model, it will still check to see how much time has elapsed since the model was trained, -and if a full `live_retrain_hours` has elapsed since the end of the loaded model, FreqAI will retrain. - -### Backtesting - -The FreqAI backtesting module can be executed with the following command: - -```bash -freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 -``` - -Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). - -If this command has never been executed with the existing config file, it will train a new model -for each pair, for each backtesting window within the expanded `--timerange`. - -!!! Note "Model reuse" - Once the training is completed, the user can execute the backtesting again with the same config file and - FreqAI will find the trained models and load them instead of spending time training. This is useful - if the user wants to tweak (or even hyperopt) buy and sell criteria inside the strategy. If the user - *wants* to retrain a new model with the same config file, then they should simply change the `identifier`. - This way, the user can return to using any model they wish by simply specifying the `identifier`. - ---- - -### Hyperopt - -Users can hyperopt using the same command as typical [hyperopt](hyperopt.md): - -```bash -freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 -``` - -Users need to have the data pre-downloaded in the same fashion as if they were doing a FreqAI [backtest](#backtesting). In addition, users must consider some restrictions when trying to [Hyperopt](hyperopt.md) FreqAI strategies: - -- The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. -- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md#running-hyperopt-with-smaller-search-space). -- The [Backtesting](#backtesting) instructions also apply to Hyperopt. - -The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. Users need to focus on hyperopting parameters that are not used in their FreqAI features. For example, users should not try to hyperopt rolling window lengths in their feature creation, or any of their FreqAI config which changes predictions. In order to efficiently hyperopt the FreqAI strategy, FreqAI stores predictions as dataframes and reuses them. Hence the requirement to hyperopt entry/exit thresholds/criteria only. - -A good example of a hyperoptable parameter in FreqAI is a value for `DI_values` beyond which we consider outliers and below which we consider inliers: - -```python -di_max = IntParameter(low=1, high=20, default=10, space='buy', optimize=True, load=True) -dataframe['outlier'] = np.where(dataframe['DI_values'] > self.di_max.value/10, 1, 0) -``` - -Which would help the user understand the appropriate Dissimilarity Index values for their particular parameter space. - -### Deciding the size of the sliding training window and backtesting duration - -The user defines the backtesting timerange with the typical `--timerange` parameter in the -configuration file. The duration of the sliding training window is set by `train_period_days`, whilst -`backtest_period_days` is the sliding backtesting window, both in number of days (`backtest_period_days` can be -a float to indicate sub-daily retraining in live/dry mode). In the presented example config, -the user is asking FreqAI to use a training period of 30 days and backtest on the subsequent 7 days. -This means that if the user sets `--timerange 20210501-20210701`, -FreqAI will train have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). After the training of the model, FreqAI will backtest the subsequent 7 days. The "sliding window" then moves one week forward (emulating FreqAI retraining once per week in live mode) and the new model uses the previous 30 days (including the 7 days used for backtesting by the previous model) to train. This is repeated until the end of `--timerange`. - -!!! Note - Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run. - -### Downloading data for backtesting -Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. - -As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). - -### Defining model expirations - -During dry/live mode, FreqAI trains each coin pair sequentially (on separate threads/GPU from the main Freqtrade bot). This means that there is always an age discrepancy between models. If a user is training on 50 pairs, and each pair requires 5 minutes to train, the oldest model will be over 4 hours old. This may be undesirable if the characteristic time scale (the trade duration target) for a strategy is less than 4 hours. The user can decide to only make trade entries if the model is less than -a certain number of hours old by setting the `expiration_hours` in the config file: - -```json - "freqai": { - "expiration_hours": 0.5, - } -``` - -In the presented example config, the user will only allow predictions on models that are less than 1/2 hours old. - -### Purging old model data - -FreqAI stores new model files each time it retrains. These files become obsolete as new models are trained and FreqAI adapts to new market conditions. Users planning to leave FreqAI running for extended periods of time with high frequency retraining should enable `purge_old_models` in their config: - -```json - "freqai": { - "purge_old_models": true, - } -``` - -This will automatically purge all models older than the two most recently trained ones. - -### Returning additional info from training - -The user may find that there are some important metrics that they'd like to return to the strategy at the end of each model training. -The user can include these metrics by assigning them to `dk.data['extra_returns_per_train']['my_new_value'] = XYZ` inside their custom prediction model class. FreqAI takes the `my_new_value` assigned in this dictionary and expands it to fit the return dataframe to the strategy. -The user can then use the value in the strategy with `dataframe['my_new_value']`. An example of how this is already used in FreqAI is -the `&*_mean` and `&*_std` values, which indicate the mean and standard deviation of the particular target (label) during the most recent training. -An example, where the user wants to use live metrics from the trade database, is shown below: - -```json - "freqai": { - "extra_returns_per_train": {"total_profit": 4} - } -``` - -The user needs to set the standard dictionary in the config so that FreqAI can return proper dataframe shapes. These values will likely be overridden by the prediction model, but in the case where the model has yet to set them, or needs a default initial value, this is the value that will be returned. - -### Setting up a follower - -The user can define: - -```json - "freqai": { - "follow_mode": true, - "identifier": "example" - } -``` - -to indicate to the bot that it should not train models, but instead should look for models trained by a leader with the same `identifier`. In this example, the user has a leader bot with the `identifier: "example"`. The leader bot is already running or launching simultaneously as the follower. -The follower will load models created by the leader and inference them to obtain predictions. - -## Data manipulation techniques - -### Feature normalization - -The feature set created by the user is automatically normalized to the training data. This includes all test data and unseen prediction data (dry/live/backtest). - -### Reducing data dimensionality with Principal Component Analysis - -Users can reduce the dimensionality of their features by activating the `principal_component_analysis` in the config: - -```json - "freqai": { - "feature_parameters" : { - "principal_component_analysis": true - } - } -``` - -This will perform PCA on the features and reduce the dimensionality of the data so that the explained variance of the data set is >= 0.999. - -### Stratifying the data for training and testing the model - -The user can stratify (group) the training/testing data using: - -```json - "freqai": { - "feature_parameters" : { - "stratify_training_data": 3 - } - } -``` - -This will split the data chronologically so that every Xth data point is used to test the model after training. In the -example above, the user is asking for every third data point in the dataframe to be used for -testing; the other points are used for training. - -The test data is used to evaluate the performance of the model after training. If the test score is high, the model is able to capture the behavior of the data well. If the test score is low, either the model either does not capture the complexity of the data, the test data is significantly different from the train data, or a different model should be used. - -### Using the `inlier_metric` - -The `inlier_metric` is a metric aimed at quantifying how different a prediction data point is from the most recent historic data points. - -User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points). - -This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. The cumulative distribution function for the weibull distribution is used to produce a quantile for each of the data points. The quantiles for each lookback point are averaged to create the `inlier_metric`. - -FreqAI adds this `inlier_metric` score to the training features! In other words, your model is trained to recognize how this temporal inlier metric is related to the user set labels. - -This function does **not** remove outliers from the data set. - -### Controlling the model learning process - -Model training parameters are unique to the machine learning library selected by the user. FreqAI allows the user to set any parameter for any library using the `model_training_parameters` dictionary in the user configuration file. The example configuration file (found in `config_examples/config_freqai.example.json`) show some of the example parameters associated with `Catboost` and `LightGBM`, but the user can add any parameters available in those libraries. - -Data split parameters are defined in `data_split_parameters` which can be any parameters associated with `Sklearn`'s `train_test_split()` function. - -FreqAI includes some additional parameters such as `weight_factor`, which allows the user to weight more recent data more strongly -than past data via an exponential function: - -$$ W_i = \exp(\frac{-i}{\alpha*n}) $$ - -where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. Below is a figure showing the effect of different weight factors on the data points (candles) in a feature set. - -![weight-factor](assets/freqai_weight-factor.jpg) - -`train_test_split()` has a parameters called `shuffle` that allows the user to keep the data unshuffled. This is particularly useful to avoid biasing training with temporally auto-correlated data. - -Finally, `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented example config, -the user is asking for `labels` that are 24 candles in the future. - -### Outlier removal - -#### Removing outliers with the Dissimilarity Index - -The user can tell FreqAI to remove outlier data points from the training/test data sets using a Dissimilarity Index by including the following statement in the config: - -```json - "freqai": { - "feature_parameters" : { - "DI_threshold": 1 - } - } -``` - -Equity and crypto markets suffer from a high level of non-patterned noise in the form of outlier data points. The Dissimilarity Index (DI) aims to quantify the uncertainty associated with each prediction made by the model. The DI allows predictions which are outliers (not existent in the model feature space) to be thrown out due to low levels of certainty. - -To do so, FreqAI measures the distance between each training data point (feature vector), $X_{a}$, and all other training data points: - -$$ d_{ab} = \sqrt{\sum_{j=1}^p(X_{a,j}-X_{b,j})^2} $$ - -where $d_{ab}$ is the distance between the normalized points $a$ and $b$. $p$ is the number of features, i.e., the length of the vector $X$. The characteristic distance, $\overline{d}$ for a set of training data points is simply the mean of the average distances: - -$$ \overline{d} = \sum_{a=1}^n(\sum_{b=1}^n(d_{ab}/n)/n) $$ - -$\overline{d}$ quantifies the spread of the training data, which is compared to the distance between a new prediction feature vectors, $X_k$ and all the training data: - -$$ d_k = \arg \min d_{k,i} $$ - -which enables the estimation of the Dissimilarity Index as: - -$$ DI_k = d_k/\overline{d} $$ - -The user can tweak the DI through the `DI_threshold` to increase or decrease the extrapolation of the trained model. - -Below is a figure that describes the DI for a 3D data set. - -![DI](assets/freqai_DI.jpg) - -#### Removing outliers using a Support Vector Machine (SVM) - -The user can tell FreqAI to remove outlier data points from the training/test data sets using a SVM by setting: - -```json - "freqai": { - "feature_parameters" : { - "use_SVM_to_remove_outliers": true - } - } -``` - -FreqAI will train an SVM on the training data (or components of it if the user activated -`principal_component_analysis`) and remove any data point that the SVM deems to be beyond the feature space. - -The parameter `shuffle` is by default set to `False` to ensure consistent results. If it is set to `True`, running the SVM multiple times on the same data set might result in different outcomes due to `max_iter` being to low for the algorithm to reach the demanded `tol`. Increasing `max_iter` solves this issue but causes the procedure to take longer time. - -The parameter `nu`, *very* broadly, is the amount of data points that should be considered outliers. - -#### Removing outliers with DBSCAN - -The user can configure FreqAI to use DBSCAN to cluster and remove outliers from the training/test data set or incoming outliers from predictions, by activating `use_DBSCAN_to_remove_outliers` in the config: - -```json - "freqai": { - "feature_parameters" : { - "use_DBSCAN_to_remove_outliers": true - } - } -``` - -DBSCAN is an unsupervised machine learning algorithm that clusters data without needing to know how many clusters there should be. - -Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters the data set by setting all data points that have $N-1$ other data points within a distance of $\varepsilon$ as *core points*. A data point that is within a distance of $\varepsilon$ from a *core point* but that does not have $N-1$ other data points within a distance of $\varepsilon$ from itself is considered an *edge point*. A cluster is then the collection of *core points* and *edge points*. Data points that have no other data points at a distance $<\varepsilon$ are considered outliers. The figure below shows a cluster with $N = 3$. - -![dbscan](assets/freqai_dbscan.jpg) - -FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as 1/4 of the no. of time points in the feature set, and `eps` ($\varepsilon$) taken as the elbow point in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. - -## Additional information - -### Common pitfalls - -FreqAI cannot be combined with dynamic `VolumePairlists` (or any pairlist filter that adds and removes pairs dynamically). -This is for performance reasons - FreqAI relies on making quick predictions/retrains. To do this effectively, -it needs to download all the training data at the beginning of a dry/live instance. FreqAI stores and appends -new candles automatically for future retrains. This means that if new pairs arrive later in the dry run due to a volume pairlist, it will not have the data ready. However, FreqAI does work with the `ShufflePairlist` or a `VolumePairlist` which keeps the total pairlist constant (but reorders the pairs according to volume). +For docker users, a dedicated tag with freqAI dependencies is available as `:freqai`. As such - you can replace the image line in your docker-compose file with `image: freqtradeorg/freqtrade:develop_freqai`. This image contains the regular freqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices. ## Credits @@ -804,6 +81,9 @@ Elin Törnquist @th0rntwig Code review, software architecture brainstorming: @xmatthias +Development: +Wagner Costa @wagnercosta + Beta testing and bug reporting: -@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm, -Juha Nykänen @suikula, Wagner Costa @wagnercosta +Stefan Gehring @bloodhunter4rc, @longyu, @paranoidandy, @smidelis, Ryan McMullan @smarmau, +Juha Nykänen @suikula, Johan van der Vlugt @jooopiert, Richárd Józsa @richardjosza diff --git a/mkdocs.yml b/mkdocs.yml index 2e5e0c8c9..95106ae1e 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -23,6 +23,12 @@ nav: - Data Downloading: data-download.md - Backtesting: backtesting.md - Hyperopt: hyperopt.md + - FreqAI: + - Introduction: freqai.md + - Setting-up: freqai-configuration.md + - Feature engineering: freqai-feature-engineering.md + - Running: freqai-running.md + - Data handling: freqai-data-handling.md - Short / Leverage: leverage.md - Utility Sub-commands: utils.md - Plotting: plotting.md @@ -35,7 +41,6 @@ nav: - Advanced Post-installation Tasks: advanced-setup.md - Advanced Strategy: strategy-advanced.md - Advanced Hyperopt: advanced-hyperopt.md - - FreqAI: freqai.md - Edge Positioning: edge.md - Sandbox Testing: sandbox-testing.md - FAQ: faq.md From ede282392f1d9b497da91825017439555646119e Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 11 Sep 2022 17:50:50 +0200 Subject: [PATCH 290/592] add a developers guide --- docs/assets/freqai_algorithm-diagram.jpg | Bin 0 -> 491920 bytes docs/freqai-configuration.md | 2 +- docs/freqai-developers.md | 28 +++++++++++++++++++++++ mkdocs.yml | 1 + 4 files changed, 30 insertions(+), 1 deletion(-) create mode 100644 docs/assets/freqai_algorithm-diagram.jpg create mode 100644 docs/freqai-developers.md diff --git a/docs/assets/freqai_algorithm-diagram.jpg b/docs/assets/freqai_algorithm-diagram.jpg new file mode 100644 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ze;j(f?!|%~yC2%|_pt?)u=KyTojmX4`IP6Iif>xJne)xBT7BdR9QZ4EwW5Lf$Klsy z`@J3iB+S*dp9tK3Gqv~p!9OpA_C%2!ILCR}XX?LawAg#6{%ezrMa7SQ?G{U8-_7}U zuR7m$`@GxdbDwYfe7o}P9@+||J}j7bsQ#f0r%6+viAVL}Uos!#`bY6-7*I70EaCbX QKgTZk0C0lpNA>@k0D^-PmjD0& literal 0 HcmV?d00001 diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index 5190c59c9..706524744 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -130,7 +130,7 @@ The FreqAI strategy requires the user to include the following lines of code in ``` -Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](freqai-feature_engineering.md#feature-engineering)) and labels ([more information](freqai-running.md#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. +Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](freqai-feature-engineering.md#feature-engineering)) and labels ([more information](freqai-running.md#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. Another structure to consider is the location of the labels at the bottom of the example function (below `if set_generalized_indicators:`). This is where the user will add single features and labels to their feature set to avoid duplication of them from various configuration parameters that multiply the feature set, such as `include_timeframes`. diff --git a/docs/freqai-developers.md b/docs/freqai-developers.md new file mode 100644 index 000000000..01cdf1e71 --- /dev/null +++ b/docs/freqai-developers.md @@ -0,0 +1,28 @@ +# Development + +The class structure and details algorithmic overview is depicted in the following diagram: + +![image](assets/freqai_algorithm-diagram.jpg) + +As shown, there are three distinct objects comprising `FreqAI`: + +* IFreqaiModel + * Singular persistent object containing all the necessary logic to collect data, store data, process data, engineer features, run training, and inference models. +* FreqaiDataKitchen + * A non-persistent object which is created uniquely for each unique asset/model. Beyond metadata, it also contains a variety of data processing tools. +* FreqaiDataDrawer + * Singular persistent object containing all the historical predictions, models, and save/load methods. + +There are a variety of built-in prediction models which inherit directly from `IFreqaiModel` including: + +* CatboostRegressor +* CatboostRegressorMultiTarget +* CatboostClassifier +* LightGBMRegressor +* LightGBMRegressorMultiTarget +* LightGBMClassifier +* XGBoostRegressor +* XGBoostRegressorMultiTarget +* XGBoostClassifier + +Each of these have full access to all methods in `IFreqaiModel`. And can therefore, override any of those functions at will. However, advanced users will likely stick to overriding `fit()`, `train()`, `predict()`, and `data_cleaning_train/predict()`. \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 95106ae1e..726924b78 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -29,6 +29,7 @@ nav: - Feature engineering: freqai-feature-engineering.md - Running: freqai-running.md - Data handling: freqai-data-handling.md + - Developer guide: freqai-developers.md - Short / Leverage: leverage.md - Utility Sub-commands: utils.md - Plotting: plotting.md From 72d197a99d0570ae9d3607042d7ec5a533907c8e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 15:42:27 +0200 Subject: [PATCH 291/592] Run first epoch in non-parallel mode this allows dataprovider to load it's cache. closes #7384 --- freqtrade/data/dataprovider.py | 4 +++- freqtrade/optimize/hyperopt.py | 21 +++++++++++++++++---- 2 files changed, 20 insertions(+), 5 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index e639b3ae7..c6519d2b8 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -196,7 +196,9 @@ class DataProvider: Clear pair dataframe cache. """ self.__cached_pairs = {} - self.__cached_pairs_backtesting = {} + # Don't reset backtesting pairs - + # otherwise they're reloaded each time during hyperopt due to with analyze_per_epoch + # self.__cached_pairs_backtesting = {} self.__slice_index = 0 # Exchange functions diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 76fc84609..b0119368f 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -580,11 +580,24 @@ class Hyperopt: max_value=self.total_epochs, redirect_stdout=False, redirect_stderr=False, widgets=widgets ) as pbar: - EVALS = ceil(self.total_epochs / jobs) - for i in range(EVALS): + start = 0 + + if self.analyze_per_epoch: + # First analysis not in parallel mode when using --analyze-per-epoch. + # This allows dataprovider to load it's informative cache. + asked, is_random = self.get_asked_points(n_points=1) + # print(asked) + f_val = self.generate_optimizer(asked[0]) + self.opt.tell(asked, [f_val['loss']]) + self.evaluate_result(f_val, 1, is_random[0]) + pbar.update(1) + start += 1 + + evals = ceil((self.total_epochs - start) / jobs) + for i in range(evals): # Correct the number of epochs to be processed for the last # iteration (should not exceed self.total_epochs in total) - n_rest = (i + 1) * jobs - self.total_epochs + n_rest = (i + 1) * jobs - (self.total_epochs - start) current_jobs = jobs - n_rest if n_rest > 0 else jobs asked, is_random = self.get_asked_points(n_points=current_jobs) @@ -594,7 +607,7 @@ class Hyperopt: # Calculate progressbar outputs for j, val in enumerate(f_val): # Use human-friendly indexes here (starting from 1) - current = i * jobs + j + 1 + current = i * jobs + j + 1 + start self.evaluate_result(val, current, is_random[j]) From 816c1f760373f6fc55710cb2e3f09ae39eb14fc5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 17:51:30 +0200 Subject: [PATCH 292/592] add test for per epoch hyperopt --- tests/optimize/test_hyperopt.py | 39 +++++++++++++++++++++++++++++++++ 1 file changed, 39 insertions(+) diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 0f615b7a3..eaea8aee7 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -922,6 +922,45 @@ def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmpdir, hyperopt.start() +def test_in_strategy_auto_hyperopt_per_epoch(mocker, hyperopt_conf, tmpdir, fee) -> None: + patch_exchange(mocker) + mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) + (Path(tmpdir) / 'hyperopt_results').mkdir(parents=True) + + hyperopt_conf.update({ + 'strategy': 'HyperoptableStrategy', + 'user_data_dir': Path(tmpdir), + 'hyperopt_random_state': 42, + 'spaces': ['all'], + 'epochs': 3, + 'analyze_per_epoch': True, + }) + go = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.generate_optimizer', + return_value={ + 'loss': 0.05, + 'results_explanation': 'foo result', 'params': {}, + 'results_metrics': generate_result_metrics(), + }) + hyperopt = Hyperopt(hyperopt_conf) + hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0) + assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto) + assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter) + assert hyperopt.backtesting.strategy.bot_loop_started is True + + assert hyperopt.backtesting.strategy.buy_rsi.in_space is True + assert hyperopt.backtesting.strategy.buy_rsi.value == 35 + assert hyperopt.backtesting.strategy.sell_rsi.value == 74 + assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30 + buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range + assert isinstance(buy_rsi_range, range) + # Range from 0 - 50 (inclusive) + assert len(list(buy_rsi_range)) == 51 + + hyperopt.start() + # backtesting should be called 3 times (once per epoch) + assert go.call_count == 3 + + def test_SKDecimal(): space = SKDecimal(1, 2, decimals=2) assert 1.5 in space From 982c0315fa2ba909362173c2e892aa7bca2c836b Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 11 Sep 2022 19:31:11 +0200 Subject: [PATCH 293/592] Rename variable --- freqtrade/optimize/hyperopt.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index b0119368f..f15e0b7d8 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -586,10 +586,9 @@ class Hyperopt: # First analysis not in parallel mode when using --analyze-per-epoch. # This allows dataprovider to load it's informative cache. asked, is_random = self.get_asked_points(n_points=1) - # print(asked) - f_val = self.generate_optimizer(asked[0]) - self.opt.tell(asked, [f_val['loss']]) - self.evaluate_result(f_val, 1, is_random[0]) + f_val0 = self.generate_optimizer(asked[0]) + self.opt.tell(asked, [f_val0['loss']]) + self.evaluate_result(f_val0, 1, is_random[0]) pbar.update(1) start += 1 From 5483cf21f694a4bc0ec90bb533d587d5428c7da1 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 11 Sep 2022 11:42:13 -0600 Subject: [PATCH 294/592] remove default secret_ws_token, set timeout min to 0 --- freqtrade/constants.py | 7 ++++--- freqtrade/rpc/api_server/api_auth.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index e77940b3c..2cc2fd115 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -502,12 +502,13 @@ CONF_SCHEMA = { 'required': ['name', 'url', 'ws_token'] } }, - 'wait_timeout': {'type': 'integer'}, - 'sleep_time': {'type': 'integer'}, - 'ping_timeout': {'type': 'integer'}, + 'wait_timeout': {'type': 'integer', 'minimum': 0}, + 'sleep_time': {'type': 'integer', 'minimum': 0}, + 'ping_timeout': {'type': 'integer', 'minimum': 0}, 'remove_signals_analyzed_df': {'type': 'boolean', 'default': False}, 'initial_candle_limit': { 'type': 'integer', + 'minimum': 0, 'maximum': 1500, 'default': 1500 } diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index 93be251ab..1ab158ea7 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -56,7 +56,7 @@ async def validate_ws_token( ws_token: Union[str, None] = Query(default=None, alias="token"), api_config: Dict[str, Any] = Depends(get_api_config) ): - secret_ws_token = api_config.get('ws_token', 'secret_ws_t0ken.') + secret_ws_token = api_config.get('ws_token', None) secret_jwt_key = api_config.get('jwt_secret_key', 'super-secret') if ws_token and secrets.compare_digest(secret_ws_token, ws_token): From 6777d43aea7f169db1711999b4a15c3fedf21a5f Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 03:01:27 +0000 Subject: [PATCH 295/592] Bump sqlalchemy from 1.4.40 to 1.4.41 Bumps [sqlalchemy](https://github.com/sqlalchemy/sqlalchemy) from 1.4.40 to 1.4.41. - [Release notes](https://github.com/sqlalchemy/sqlalchemy/releases) - [Changelog](https://github.com/sqlalchemy/sqlalchemy/blob/main/CHANGES.rst) - [Commits](https://github.com/sqlalchemy/sqlalchemy/commits) --- updated-dependencies: - dependency-name: sqlalchemy dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index fdbe6ac28..d063410d4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,7 +6,7 @@ ccxt==1.93.3 # Pin cryptography for now due to rust build errors with piwheels cryptography==37.0.4 aiohttp==3.8.1 -SQLAlchemy==1.4.40 +SQLAlchemy==1.4.41 python-telegram-bot==13.14 arrow==1.2.3 cachetools==4.2.2 From 6bfe99606179ebb1cbb236b8751da180ccd1b3ca Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 03:01:56 +0000 Subject: [PATCH 296/592] Bump mkdocs-material from 8.4.2 to 8.4.3 Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 8.4.2 to 8.4.3. - [Release notes](https://github.com/squidfunk/mkdocs-material/releases) - [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG) - [Commits](https://github.com/squidfunk/mkdocs-material/compare/8.4.2...8.4.3) --- updated-dependencies: - dependency-name: mkdocs-material dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- docs/requirements-docs.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt index 5a6c46471..d63e79004 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,6 +1,6 @@ markdown==3.3.7 mkdocs==1.3.1 -mkdocs-material==8.4.2 +mkdocs-material==8.4.3 mdx_truly_sane_lists==1.3 pymdown-extensions==9.5 jinja2==3.1.2 From 1ef334411ed5c9ba0204acb41172089bfb5c38dc Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 03:02:01 +0000 Subject: [PATCH 297/592] Bump types-requests from 2.28.9 to 2.28.10 Bumps [types-requests](https://github.com/python/typeshed) from 2.28.9 to 2.28.10. - [Release notes](https://github.com/python/typeshed/releases) - [Commits](https://github.com/python/typeshed/commits) --- updated-dependencies: - dependency-name: types-requests dependency-type: direct:development update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements-dev.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-dev.txt b/requirements-dev.txt index 40ca4e154..69749f843 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -25,6 +25,6 @@ nbconvert==7.0.0 # mypy types types-cachetools==5.2.1 types-filelock==3.2.7 -types-requests==2.28.9 +types-requests==2.28.10 types-tabulate==0.8.11 types-python-dateutil==2.8.19 From a4b7e0a714c0f9624d693772467080c43012649e Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 03:02:06 +0000 Subject: [PATCH 298/592] Bump fastapi from 0.82.0 to 0.83.0 Bumps [fastapi](https://github.com/tiangolo/fastapi) from 0.82.0 to 0.83.0. - [Release notes](https://github.com/tiangolo/fastapi/releases) - [Commits](https://github.com/tiangolo/fastapi/compare/0.82.0...0.83.0) --- updated-dependencies: - dependency-name: fastapi dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index fdbe6ac28..ea8cb39ff 100644 --- a/requirements.txt +++ b/requirements.txt @@ -34,7 +34,7 @@ orjson==3.8.0 sdnotify==0.3.2 # API Server -fastapi==0.82.0 +fastapi==0.83.0 uvicorn==0.18.3 pyjwt==2.4.0 aiofiles==0.8.0 From 6968fc333b584355c90cf9235ee743a23a239e9b Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 03:02:10 +0000 Subject: [PATCH 299/592] Bump jsonschema from 4.15.0 to 4.16.0 Bumps [jsonschema](https://github.com/python-jsonschema/jsonschema) from 4.15.0 to 4.16.0. - [Release notes](https://github.com/python-jsonschema/jsonschema/releases) - [Changelog](https://github.com/python-jsonschema/jsonschema/blob/main/CHANGELOG.rst) - [Commits](https://github.com/python-jsonschema/jsonschema/compare/v4.15.0...v4.16.0) --- updated-dependencies: - dependency-name: jsonschema dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index fdbe6ac28..8a3701bb4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,7 +12,7 @@ arrow==1.2.3 cachetools==4.2.2 requests==2.28.1 urllib3==1.26.12 -jsonschema==4.15.0 +jsonschema==4.16.0 TA-Lib==0.4.24 technical==1.3.0 tabulate==0.8.10 From c149c47afbc20b083c3f6077edcb6fdc1c223801 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 05:05:30 +0000 Subject: [PATCH 300/592] Bump ccxt from 1.93.3 to 1.93.35 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.93.3 to 1.93.35. - [Release notes](https://github.com/ccxt/ccxt/releases) - [Changelog](https://github.com/ccxt/ccxt/blob/master/exchanges.cfg) - [Commits](https://github.com/ccxt/ccxt/compare/1.93.3...1.93.35) --- updated-dependencies: - dependency-name: ccxt dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index d063410d4..af9048c87 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ numpy==1.23.2 pandas==1.4.4 pandas-ta==0.3.14b -ccxt==1.93.3 +ccxt==1.93.35 # Pin cryptography for now due to rust build errors with piwheels cryptography==37.0.4 aiohttp==3.8.1 From 715a71465d36a1b613b2884855b006e892b94ff9 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 12 Sep 2022 07:28:31 +0200 Subject: [PATCH 301/592] Fix auth bug when no token is set --- freqtrade/data/dataprovider.py | 5 ++--- freqtrade/rpc/api_server/api_auth.py | 4 ++-- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 8ca638046..fd7997521 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -88,11 +88,10 @@ class DataProvider: def _set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"): """ Set the pairs received to later be used. - This only supports 1 Producer right now. :param pairlist: List of pairs """ - self.__producer_pairs[producer_name] = pairlist.copy() + self.__producer_pairs[producer_name] = pairlist def get_producer_pairs(self, producer_name: str = "default") -> List[str]: """ @@ -100,7 +99,7 @@ class DataProvider: :returns: List of pairs """ - return self.__producer_pairs.get(producer_name, []) + return self.__producer_pairs.get(producer_name, []).copy() def _emit_df( self, diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py index 1ab158ea7..e91e5941b 100644 --- a/freqtrade/rpc/api_server/api_auth.py +++ b/freqtrade/rpc/api_server/api_auth.py @@ -59,7 +59,7 @@ async def validate_ws_token( secret_ws_token = api_config.get('ws_token', None) secret_jwt_key = api_config.get('jwt_secret_key', 'super-secret') - if ws_token and secrets.compare_digest(secret_ws_token, ws_token): + if ws_token and secret_ws_token and secrets.compare_digest(secret_ws_token, ws_token): # Just return the token if it matches return ws_token else: @@ -69,7 +69,7 @@ async def validate_ws_token( # If the token is a jwt, and it's valid return the user except HTTPException: pass - logger.info("Denying websocket request") + logger.debug("Denying websocket request.") # If it doesn't match, close the websocket connection await ws.close(code=status.WS_1008_POLICY_VIOLATION) From 09cdce864e6fab1efecb28c413f74f21af027fea Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 06:02:21 +0000 Subject: [PATCH 302/592] Bump ta-lib from 0.4.24 to 0.4.25 Bumps [ta-lib](https://github.com/mrjbq7/ta-lib) from 0.4.24 to 0.4.25. - [Release notes](https://github.com/mrjbq7/ta-lib/releases) - [Changelog](https://github.com/mrjbq7/ta-lib/blob/master/CHANGELOG) - [Commits](https://github.com/mrjbq7/ta-lib/compare/TA_Lib-0.4.24...TA_Lib-0.4.25) --- updated-dependencies: - dependency-name: ta-lib dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index a4767bf1b..25f44ab29 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,7 +13,7 @@ cachetools==4.2.2 requests==2.28.1 urllib3==1.26.12 jsonschema==4.16.0 -TA-Lib==0.4.24 +TA-Lib==0.4.25 technical==1.3.0 tabulate==0.8.10 pycoingecko==3.0.0 From 4ac804f795227163d93c03438cddbd8d722fdd9e Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 06:05:04 +0000 Subject: [PATCH 303/592] Bump numpy from 1.23.2 to 1.23.3 Bumps [numpy](https://github.com/numpy/numpy) from 1.23.2 to 1.23.3. - [Release notes](https://github.com/numpy/numpy/releases) - [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst) - [Commits](https://github.com/numpy/numpy/compare/v1.23.2...v1.23.3) --- updated-dependencies: - dependency-name: numpy dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 9bb8e6af0..551440cc4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,4 @@ -numpy==1.23.2 +numpy==1.23.3 pandas==1.4.4 pandas-ta==0.3.14b From 00db473f102fb4c6cee1199930e9fe81c3f7792c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 06:05:22 +0000 Subject: [PATCH 304/592] Bump cryptography from 37.0.4 to 38.0.1 Bumps [cryptography](https://github.com/pyca/cryptography) from 37.0.4 to 38.0.1. - [Release notes](https://github.com/pyca/cryptography/releases) - [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pyca/cryptography/compare/37.0.4...38.0.1) --- updated-dependencies: - dependency-name: cryptography dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 9bb8e6af0..59bef6b11 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ pandas-ta==0.3.14b ccxt==1.93.35 # Pin cryptography for now due to rust build errors with piwheels -cryptography==37.0.4 +cryptography==38.0.1 aiohttp==3.8.1 SQLAlchemy==1.4.41 python-telegram-bot==13.14 From 7ee92db7a2c2f25b48917d285f11ab8f6d474418 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 12 Sep 2022 06:07:40 +0000 Subject: [PATCH 305/592] Bump aiofiles from 0.8.0 to 22.1.0 Bumps [aiofiles](https://github.com/Tinche/aiofiles) from 0.8.0 to 22.1.0. - [Release notes](https://github.com/Tinche/aiofiles/releases) - [Commits](https://github.com/Tinche/aiofiles/compare/v0.8.0...v22.1.0) --- updated-dependencies: - dependency-name: aiofiles dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 345c336f5..e263b7914 100644 --- a/requirements.txt +++ b/requirements.txt @@ -37,7 +37,7 @@ sdnotify==0.3.2 fastapi==0.83.0 uvicorn==0.18.3 pyjwt==2.4.0 -aiofiles==0.8.0 +aiofiles==22.1.0 psutil==5.9.2 # Support for colorized terminal output From f45824acf536ccd7f56d78f0ea692a414709962c Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 12 Sep 2022 09:23:02 +0200 Subject: [PATCH 306/592] Bump precommit types/requests --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 86c4ec1ad..6f2b3ba3c 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -15,7 +15,7 @@ repos: additional_dependencies: - types-cachetools==5.2.1 - types-filelock==3.2.7 - - types-requests==2.28.9 + - types-requests==2.28.10 - types-tabulate==0.8.11 - types-python-dateutil==2.8.19 # stages: [push] From d6205e6cfb653947be23afddaf2679ff236a2e30 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 07:36:11 -0600 Subject: [PATCH 307/592] test logging lines --- freqtrade/rpc/external_message_consumer.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 89fa90c8e..59064c90b 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -305,6 +305,9 @@ class ExternalMessageConsumer: pair, timeframe, candle_type = key + logger.debug(message.data.key) + logger.debug(message.data) + # If set, remove the Entry and Exit signals from the Producer if self._emc_config.get('remove_entry_exit_signals', False): df = remove_entry_exit_signals(df) From 457075b82386006e5d543f207f8cd00151a97e49 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 07:47:30 -0600 Subject: [PATCH 308/592] one more line --- freqtrade/data/dataprovider.py | 1 + 1 file changed, 1 insertion(+) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 94e79c8be..f8ea0073b 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -113,6 +113,7 @@ class DataProvider: :param data: Tuple containing the DataFrame and the datetime it was cached """ if self.__rpc: + logger.debug(f"Sending df {dataframe}") self.__rpc.send_msg( { 'type': RPCMessageType.ANALYZED_DF, From 10852555e593fc84b4d56b58616201154eb1ea24 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 09:53:47 -0600 Subject: [PATCH 309/592] change verbosity of testing log --- freqtrade/data/dataprovider.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index f8ea0073b..19d6d6ae1 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -113,7 +113,7 @@ class DataProvider: :param data: Tuple containing the DataFrame and the datetime it was cached """ if self.__rpc: - logger.debug(f"Sending df {dataframe}") + logger.debug(f"Sending df {dataframe.iloc[-1]}") self.__rpc.send_msg( { 'type': RPCMessageType.ANALYZED_DF, From a477b3c244680e0e2e72d12f5a12a1ed557640f0 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 10:45:59 -0600 Subject: [PATCH 310/592] remove log line, fix tests to not connect to actual ip --- freqtrade/data/dataprovider.py | 1 - tests/rpc/test_rpc_emc.py | 2 +- 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 19d6d6ae1..94e79c8be 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -113,7 +113,6 @@ class DataProvider: :param data: Tuple containing the DataFrame and the datetime it was cached """ if self.__rpc: - logger.debug(f"Sending df {dataframe.iloc[-1]}") self.__rpc.send_msg( { 'type': RPCMessageType.ANALYZED_DF, diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index e29419102..b3f6fdc4d 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -28,7 +28,7 @@ def patched_emc(default_conf, mocker): "producers": [ { "name": "default", - "url": "ws://127.0.0.1:8080/api/v1/message/ws", + "url": "ws://something:port/api/v1/message/ws", "ws_token": _TEST_WS_TOKEN } ] From 0052e5891788ffbfdaf20dd0374599924369644e Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 12 Sep 2022 19:50:22 +0200 Subject: [PATCH 311/592] emc: Fix potential startup timing issue --- freqtrade/rpc/external_message_consumer.py | 6 +++--- tests/rpc/test_rpc_emc.py | 9 ++++----- 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 59064c90b..122863987 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -15,6 +15,7 @@ from pydantic import ValidationError from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RPCMessageType +from freqtrade.exceptions import OperationalException from freqtrade.misc import remove_entry_exit_signals from freqtrade.rpc.api_server.ws.channel import WebSocketChannel from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSAnalyzedDFRequest, @@ -57,7 +58,7 @@ class ExternalMessageConsumer: self.producers = self._emc_config.get('producers', []) if self.enabled and len(self.producers) < 1: - raise ValueError("You must specify at least 1 Producer to connect to.") + raise OperationalException("You must specify at least 1 Producer to connect to.") self.wait_timeout = self._emc_config.get('wait_timeout', 300) # in seconds self.ping_timeout = self._emc_config.get('ping_timeout', 10) # in seconds @@ -97,9 +98,8 @@ class ExternalMessageConsumer: self._loop = asyncio.new_event_loop() self._thread = Thread(target=self._loop.run_forever) - self._thread.start() - self._running = True + self._thread.start() self._main_task = asyncio.run_coroutine_threadsafe(self._main(), loop=self._loop) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index b3f6fdc4d..94635810c 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -11,6 +11,7 @@ import pytest import websockets from freqtrade.data.dataprovider import DataProvider +from freqtrade.exceptions import OperationalException from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer from tests.conftest import log_has, log_has_re, log_has_when @@ -71,7 +72,7 @@ def test_emc_shutdown(patched_emc, caplog): assert not log_has("Stopping ExternalMessageConsumer", caplog) -def test_emc_init(patched_emc, default_conf, mocker, caplog): +def test_emc_init(patched_emc, default_conf): # Test the settings were set correctly assert patched_emc.initial_candle_limit <= 1500 assert patched_emc.wait_timeout > 0 @@ -84,12 +85,10 @@ def test_emc_init(patched_emc, default_conf, mocker, caplog): } }) dataprovider = DataProvider(default_conf, None, None, None) - with pytest.raises(ValueError) as exc: + with pytest.raises(OperationalException, + match="You must specify at least 1 Producer to connect to."): ExternalMessageConsumer(default_conf, dataprovider) - # Make sure we failed because of no producers - assert str(exc.value) == "You must specify at least 1 Producer to connect to." - # Parametrize this? def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): From 867d59b930b27e774fd391d3f372272a5ddcd7d3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 12 Sep 2022 20:00:01 +0200 Subject: [PATCH 312/592] Improve type specifitivity --- freqtrade/rpc/external_message_consumer.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 122863987..bd921cf8e 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -8,7 +8,7 @@ import asyncio import logging import socket from threading import Thread -from typing import TYPE_CHECKING, Any, Dict, List +from typing import TYPE_CHECKING, Any, Callable, Dict, List import websockets from pydantic import ValidationError @@ -80,7 +80,7 @@ class ExternalMessageConsumer: ] # Specify which function to use for which RPCMessageType - self._message_handlers = { + self._message_handlers: Dict[str, Callable[[str, WSMessageSchema], None]] = { RPCMessageType.WHITELIST: self._consume_whitelist_message, RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message, } @@ -279,7 +279,7 @@ class ExternalMessageConsumer: message_handler(producer_name, producer_message) - def _consume_whitelist_message(self, producer_name: str, message: Any): + def _consume_whitelist_message(self, producer_name: str, message: WSMessageSchema): try: # Validate the message message = WSWhitelistMessage.parse_obj(message) @@ -292,7 +292,7 @@ class ExternalMessageConsumer: logger.debug(f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`") - def _consume_analyzed_df_message(self, producer_name: str, message: Any): + def _consume_analyzed_df_message(self, producer_name: str, message: WSMessageSchema): try: message = WSAnalyzedDFMessage.parse_obj(message) except ValidationError as e: From b6434040de76f43d66b710da60f1be4f88b80adf Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 12 Sep 2022 20:24:28 +0200 Subject: [PATCH 313/592] Remove plain json serializer implementation --- freqtrade/rpc/api_server/ws/serializer.py | 9 --------- 1 file changed, 9 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py index d1ddd84f0..22d177f85 100644 --- a/freqtrade/rpc/api_server/ws/serializer.py +++ b/freqtrade/rpc/api_server/ws/serializer.py @@ -1,4 +1,3 @@ -import json import logging from abc import ABC, abstractmethod @@ -38,14 +37,6 @@ class WebSocketSerializer(ABC): await self._websocket.close(code) -class JSONWebSocketSerializer(WebSocketSerializer): - def _serialize(self, data): - return json.dumps(data, default=_json_default) - - def _deserialize(self, data): - return json.loads(data, object_hook=_json_object_hook) - - class HybridJSONWebSocketSerializer(WebSocketSerializer): def _serialize(self, data) -> str: return str(orjson.dumps(data, default=_json_default), "utf-8") From c19a5fbe06e35839255ad0b961d20c39299b7e1d Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 13:57:29 -0600 Subject: [PATCH 314/592] copy data being transferred, remove debug messages in emc --- freqtrade/data/dataprovider.py | 3 ++- freqtrade/rpc/external_message_consumer.py | 19 ++++++++++--------- 2 files changed, 12 insertions(+), 10 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index 94e79c8be..e3bee7118 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -184,7 +184,8 @@ class DataProvider: return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) # We have it, return this data - return self.__producer_pairs_df[producer_name][pair_key] + df, la = self.__producer_pairs_df[producer_name][pair_key] + return (df.copy(), la) def add_pairlisthandler(self, pairlists) -> None: """ diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index bd921cf8e..89edc8417 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -269,6 +269,10 @@ class ExternalMessageConsumer: logger.error(f"Invalid message from `{producer_name}`: {e}") return + if not producer_message.data: + logger.error(f"Empty message received from `{producer_name}`") + return + logger.info(f"Received message of type `{producer_message.type}` from `{producer_name}`") message_handler = self._message_handlers.get(producer_message.type) @@ -282,32 +286,29 @@ class ExternalMessageConsumer: def _consume_whitelist_message(self, producer_name: str, message: WSMessageSchema): try: # Validate the message - message = WSWhitelistMessage.parse_obj(message) + whitelist_message = WSWhitelistMessage.parse_obj(message) except ValidationError as e: logger.error(f"Invalid message from `{producer_name}`: {e}") return # Add the pairlist data to the DataProvider - self._dp._set_producer_pairs(message.data, producer_name=producer_name) + self._dp._set_producer_pairs(whitelist_message.data.copy(), producer_name=producer_name) logger.debug(f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`") def _consume_analyzed_df_message(self, producer_name: str, message: WSMessageSchema): try: - message = WSAnalyzedDFMessage.parse_obj(message) + df_message = WSAnalyzedDFMessage.parse_obj(message) except ValidationError as e: logger.error(f"Invalid message from `{producer_name}`: {e}") return - key = message.data.key - df = message.data.df - la = message.data.la + key = df_message.data.key + df = df_message.data.df + la = df_message.data.la pair, timeframe, candle_type = key - logger.debug(message.data.key) - logger.debug(message.data) - # If set, remove the Entry and Exit signals from the Producer if self._emc_config.get('remove_entry_exit_signals', False): df = remove_entry_exit_signals(df) From 0697041f146fa1f4d3aaa74a0af6419d0a57143f Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 14:09:12 -0600 Subject: [PATCH 315/592] remove copy statement where not needed --- freqtrade/rpc/external_message_consumer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 89edc8417..a9fdd62ca 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -292,7 +292,7 @@ class ExternalMessageConsumer: return # Add the pairlist data to the DataProvider - self._dp._set_producer_pairs(whitelist_message.data.copy(), producer_name=producer_name) + self._dp._set_producer_pairs(whitelist_message.data, producer_name=producer_name) logger.debug(f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`") From 12a3e90f7860920af11eb08047023ee782c21786 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 14:12:39 -0600 Subject: [PATCH 316/592] fix tests --- tests/rpc/test_rpc_emc.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 94635810c..1968c5d39 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -29,7 +29,7 @@ def patched_emc(default_conf, mocker): "producers": [ { "name": "default", - "url": "ws://something:port/api/v1/message/ws", + "url": "ws://null:9891/api/v1/message/ws", "ws_token": _TEST_WS_TOKEN } ] @@ -156,7 +156,7 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history): malformed_message = {"type": "whitelist", "data": None} patched_emc.handle_producer_message(test_producer, malformed_message) - assert log_has_re(r"Invalid message .+", caplog) + assert log_has_re(r"Empty message .+", caplog) async def test_emc_create_connection_success(default_conf, caplog, mocker): From bf2e5dee759bd393dcff91570a9364c944d35f5e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 14:21:39 -0600 Subject: [PATCH 317/592] add running false on shutdown, fix dp typing --- freqtrade/data/dataprovider.py | 14 +++++--------- freqtrade/rpc/external_message_consumer.py | 1 + 2 files changed, 6 insertions(+), 9 deletions(-) diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index e3bee7118..dae8ec162 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -128,9 +128,9 @@ class DataProvider: self, pair: str, dataframe: DataFrame, - last_analyzed: Optional[datetime] = None, - timeframe: Optional[str] = None, - candle_type: Optional[CandleType] = None, + last_analyzed: datetime, + timeframe: str, + candle_type: CandleType, producer_name: str = "default" ) -> None: """ @@ -140,10 +140,7 @@ class DataProvider: :param timeframe: Timeframe to get data for :param candle_type: Any of the enum CandleType (must match trading mode!) """ - _timeframe = self._default_timeframe if not timeframe else timeframe - _candle_type = self._default_candle_type if not candle_type else candle_type - - pair_key = (pair, _timeframe, _candle_type) + pair_key = (pair, timeframe, candle_type) if producer_name not in self.__producer_pairs_df: self.__producer_pairs_df[producer_name] = {} @@ -161,8 +158,7 @@ class DataProvider: producer_name: str = "default" ) -> Tuple[DataFrame, datetime]: """ - Get the pair data from the external sources. Will wait if the policy is - set to, and data is not available. + Get the pair data from the external sources. :param pair: pair to get the data for :param timeframe: Timeframe to get data for diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index a9fdd62ca..e167ce24d 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -109,6 +109,7 @@ class ExternalMessageConsumer: """ if self._thread and self._loop: logger.info("Stopping ExternalMessageConsumer") + self._running = False if self._sub_tasks: # Cancel sub tasks From 75ce9067dcfdc32ad39cdddf7c7c89ee25dc1348 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 12 Sep 2022 16:39:16 -0600 Subject: [PATCH 318/592] fix dp test --- tests/data/test_dataprovider.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py index 812688cb1..9915b6316 100644 --- a/tests/data/test_dataprovider.py +++ b/tests/data/test_dataprovider.py @@ -169,6 +169,7 @@ def test_external_df(mocker, default_conf, ohlcv_history): candle_type = CandleType.SPOT empty_la = datetime.fromtimestamp(0, tz=timezone.utc) + now = datetime.now(timezone.utc) # no data has been added, any request should return an empty dataframe dataframe, la = dataprovider.get_external_df(pair, timeframe, candle_type) @@ -176,7 +177,7 @@ def test_external_df(mocker, default_conf, ohlcv_history): assert la == empty_la # the data is added, should return that added dataframe - dataprovider._add_external_df(pair, ohlcv_history, timeframe=timeframe, candle_type=candle_type) + dataprovider._add_external_df(pair, ohlcv_history, now, timeframe, candle_type) dataframe, la = dataprovider.get_external_df(pair, timeframe, candle_type) assert len(dataframe) > 0 assert la > empty_la From 6d0dfd4dc8f122716784759926e21bc1f0c6c00b Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 12:27:41 -0600 Subject: [PATCH 319/592] continue trying connect on ping error --- freqtrade/rpc/external_message_consumer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index e167ce24d..ef2417225 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -252,11 +252,11 @@ class ExternalMessageConsumer: continue except Exception: - logger.info( + logger.error( f"Ping error {channel} - retrying in {self.sleep_time}s") await asyncio.sleep(self.sleep_time) - break + continue def handle_producer_message(self, producer: Dict[str, Any], message: Dict[str, Any]): """ From 07aa206f71995ffc92f744d40ae40973d1c54813 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 12:36:40 -0600 Subject: [PATCH 320/592] real fix for reconnecting --- freqtrade/rpc/external_message_consumer.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index ef2417225..f8e5315f9 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -205,14 +205,14 @@ class ExternalMessageConsumer: continue except websockets.exceptions.ConnectionClosedOK: - # Successfully closed, just end - return + # Successfully closed, just keep trying to connect again indefinitely + continue except Exception as e: # An unforseen error has occurred, log and stop logger.error("Unexpected error has occurred:") logger.exception(e) - break + continue async def _receive_messages( self, @@ -256,7 +256,7 @@ class ExternalMessageConsumer: f"Ping error {channel} - retrying in {self.sleep_time}s") await asyncio.sleep(self.sleep_time) - continue + break def handle_producer_message(self, producer: Dict[str, Any], message: Dict[str, Any]): """ From aeaca78940131ef4d3165d3d53c2082478d3d192 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 12:39:12 -0600 Subject: [PATCH 321/592] change port in send_msg test --- tests/rpc/test_rpc_apiserver.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 2f25f442b..f22499086 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1752,7 +1752,7 @@ def test_api_ws_send_msg(default_conf, mocker, caplog): default_conf.update({"api_server": {"enabled": True, "listen_ip_address": "127.0.0.1", - "listen_port": 8080, + "listen_port": 9913, "username": "TestUser", "password": "testPass", }}) From 79c70bd52dc402a1e75252532b2a744e1ff0c891 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 13 Sep 2022 20:12:02 +0200 Subject: [PATCH 322/592] use WebSocketState from fastapi available since 0.82.0 --- freqtrade/rpc/api_server/api_ws.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 34b780956..174a0a85e 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -1,10 +1,9 @@ import logging from typing import Any, Dict -from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect +from fastapi import APIRouter, Depends, WebSocketDisconnect +from fastapi.websockets import WebSocket, WebSocketState from pydantic import ValidationError -# fastapi does not make this available through it, so import directly from starlette -from starlette.websockets import WebSocketState from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.api_auth import validate_ws_token From d2abc9417f53f9a330e11dde257d7e014d120f96 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 13 Sep 2022 20:42:24 +0200 Subject: [PATCH 323/592] Simplify ws imports --- freqtrade/rpc/api_server/api_ws.py | 2 +- freqtrade/rpc/api_server/webserver.py | 2 +- freqtrade/rpc/api_server/ws/__init__.py | 6 ++++++ freqtrade/rpc/external_message_consumer.py | 5 ++--- 4 files changed, 10 insertions(+), 5 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 174a0a85e..c4a3e9d4a 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -8,7 +8,7 @@ from pydantic import ValidationError from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.api_auth import validate_ws_token from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc -from freqtrade.rpc.api_server.ws.channel import WebSocketChannel +from freqtrade.rpc.api_server.ws import WebSocketChannel from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSMessageSchema, WSRequestSchema, WSWhitelistMessage) from freqtrade.rpc.rpc import RPC diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 3fb8159e1..7a59a7a4c 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -14,7 +14,7 @@ from starlette.responses import JSONResponse from freqtrade.exceptions import OperationalException from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer -from freqtrade.rpc.api_server.ws.channel import ChannelManager +from freqtrade.rpc.api_server.ws import ChannelManager from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler diff --git a/freqtrade/rpc/api_server/ws/__init__.py b/freqtrade/rpc/api_server/ws/__init__.py index e69de29bb..c00d29e22 100644 --- a/freqtrade/rpc/api_server/ws/__init__.py +++ b/freqtrade/rpc/api_server/ws/__init__.py @@ -0,0 +1,6 @@ +# flake8: noqa: F401 +# isort: off +from freqtrade.rpc.api_server.ws.types import WebSocketType +from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy +from freqtrade.rpc.api_server.ws.serializer import HybridJSONWebSocketSerializer, MsgPackWebSocketSerializer +from freqtrade.rpc.api_server.ws.channel import ChannelManager, WebSocketChannel diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index f8e5315f9..2ff261eee 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -17,7 +17,7 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RPCMessageType from freqtrade.exceptions import OperationalException from freqtrade.misc import remove_entry_exit_signals -from freqtrade.rpc.api_server.ws.channel import WebSocketChannel +from freqtrade.rpc.api_server.ws import WebSocketChannel from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSAnalyzedDFRequest, WSMessageSchema, WSRequestSchema, WSSubscribeRequest, WSWhitelistMessage, @@ -252,8 +252,7 @@ class ExternalMessageConsumer: continue except Exception: - logger.error( - f"Ping error {channel} - retrying in {self.sleep_time}s") + logger.warning(f"Ping error {channel} - retrying in {self.sleep_time}s") await asyncio.sleep(self.sleep_time) break From 877d24bcdd1adb0d3378dbc24a7930d24638cba8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 13 Sep 2022 20:42:32 +0200 Subject: [PATCH 324/592] Fix external dependency of test --- tests/rpc/test_rpc_apiserver.py | 21 +++++++++++++-------- 1 file changed, 13 insertions(+), 8 deletions(-) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index f22499086..e007e0a9e 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1698,8 +1698,7 @@ def test_api_ws_subscribe(botclient, mocker): ftbot, client = botclient ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}" - sub_mock = mocker.patch( - 'freqtrade.rpc.api_server.ws.channel.WebSocketChannel.set_subscriptions', MagicMock()) + sub_mock = mocker.patch('freqtrade.rpc.api_server.ws.WebSocketChannel.set_subscriptions') with client.websocket_connect(ws_url) as ws: ws.send_json({'type': 'subscribe', 'data': ['whitelist']}) @@ -1752,18 +1751,24 @@ def test_api_ws_send_msg(default_conf, mocker, caplog): default_conf.update({"api_server": {"enabled": True, "listen_ip_address": "127.0.0.1", - "listen_port": 9913, - "username": "TestUser", - "password": "testPass", + "listen_port": 8080, + "CORS_origins": ['http://example.com'], + "username": _TEST_USER, + "password": _TEST_PASS, + "ws_token": _TEST_WS_TOKEN }}) - mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock()) + mocker.patch('freqtrade.rpc.telegram.Updater') + mocker.patch('freqtrade.rpc.api_server.ApiServer.start_api') apiserver = ApiServer(default_conf) apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf))) + apiserver.start_message_queue() + # Give the queue thread time to start + time.sleep(0.2) # Test message_queue coro receives the message test_message = {"type": "status", "data": "test"} apiserver.send_msg(test_message) - time.sleep(1) # Not sure how else to wait for the coro to receive the data + time.sleep(0.1) # Not sure how else to wait for the coro to receive the data assert log_has("Found message of type: status", caplog) # Test if exception logged when error occurs in sending @@ -1771,7 +1776,7 @@ def test_api_ws_send_msg(default_conf, mocker, caplog): side_effect=Exception) apiserver.send_msg(test_message) - time.sleep(2) # Not sure how else to wait for the coro to receive the data + time.sleep(0.1) # Not sure how else to wait for the coro to receive the data assert log_has_re(r"Exception happened in background task.*", caplog) finally: From 7b6e465d57e392114d8cca2df24c18c5d4c3e4fe Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 13 Sep 2022 21:28:11 +0200 Subject: [PATCH 325/592] Remove gate live test skip --- tests/exchange/test_ccxt_compat.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index f57b0b366..82be6196a 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -297,7 +297,7 @@ class TestCCXTExchange(): def test_ccxt__async_get_candle_history(self, exchange): exchange, exchangename = exchange # For some weired reason, this test returns random lengths for bittrex. - if not exchange._ft_has['ohlcv_has_history'] or exchangename in ('bittrex', 'gateio'): + if not exchange._ft_has['ohlcv_has_history'] or exchangename in ('bittrex'): return pair = EXCHANGES[exchangename]['pair'] timeframe = EXCHANGES[exchangename]['timeframe'] From 46a425d1b640d8b15c2115e3478cd635e0dfdbd8 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 13:36:21 -0600 Subject: [PATCH 326/592] fix OOM on emc test --- tests/rpc/test_rpc_emc.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 1968c5d39..7bb727810 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -184,14 +184,14 @@ async def test_emc_create_connection_success(default_conf, caplog, mocker): test_producer = default_conf['external_message_consumer']['producers'][0] lock = asyncio.Lock() + emc._running = True + async def eat(websocket): - pass + emc._running = False try: async with websockets.serve(eat, _TEST_WS_HOST, _TEST_WS_PORT): - emc._running = True await emc._create_connection(test_producer, lock) - emc._running = False assert log_has_re(r"Producer connection success.+", caplog) finally: From 7a98775f012d9467b951427d56daead30e630e37 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 13 Sep 2022 22:07:59 +0200 Subject: [PATCH 327/592] Version bump apiVersion --- freqtrade/rpc/api_server/api_v1.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index bf21715b7..53f5c16d7 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -38,7 +38,8 @@ logger = logging.getLogger(__name__) # 2.15: Add backtest history endpoints # 2.16: Additional daily metrics # 2.17: Forceentry - leverage, partial force_exit -API_VERSION = 2.17 +# 2.20: Add websocket endpoints +API_VERSION = 2.20 # Public API, requires no auth. router_public = APIRouter() From d75d5a7dadaf60f3e0fc619af73d2964527a8d4a Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 16:06:25 -0600 Subject: [PATCH 328/592] debug ping error message --- freqtrade/rpc/external_message_consumer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 2ff261eee..fd6ccfacd 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -251,8 +251,9 @@ class ExternalMessageConsumer: logger.debug(f"Connection to {channel} still alive...") continue - except Exception: + except Exception as e: logger.warning(f"Ping error {channel} - retrying in {self.sleep_time}s") + logger.debug(e, exc_info=e) await asyncio.sleep(self.sleep_time) break From 06350a13cbad4de1780058dde2b145bca3146171 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 16:39:53 -0600 Subject: [PATCH 329/592] support specifying message size in emc config --- freqtrade/constants.py | 6 ++++++ freqtrade/rpc/external_message_consumer.py | 5 ++++- 2 files changed, 10 insertions(+), 1 deletion(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 2cc2fd115..470ffb2a3 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -511,6 +511,12 @@ CONF_SCHEMA = { 'minimum': 0, 'maximum': 1500, 'default': 1500 + }, + 'max_message_size': { + 'type': 'integer', + 'minimum': 1048576, # 1mb + 'maxmium': 8388608, # 8.3mb, + 'default': 1048576, # 1mb } }, 'required': ['producers'] diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index fd6ccfacd..7dd6c09b0 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -67,6 +67,9 @@ class ExternalMessageConsumer: # The amount of candles per dataframe on the initial request self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 1500) + # Message size limit, default 1mb + self.message_size_limit = self._emc_config.get('message_size_limit', 2**20) + # Setting these explicitly as they probably shouldn't be changed by a user # Unless we somehow integrate this with the strategy to allow creating # callbacks for the messages @@ -175,7 +178,7 @@ class ExternalMessageConsumer: ws_url = f"{url}?token={token}" # This will raise InvalidURI if the url is bad - async with websockets.connect(ws_url) as ws: + async with websockets.connect(ws_url, max_size=self.message_size_limit) as ws: channel = WebSocketChannel(ws, channel_id=name) logger.info(f"Producer connection success - {channel}") From 37dd22c89e2e50bce49ffce17277dc06d2abec8b Mon Sep 17 00:00:00 2001 From: initrv Date: Wed, 14 Sep 2022 03:40:13 +0300 Subject: [PATCH 330/592] Fixed a bug that prevents clearing old models Corrects the error of clearing old models when the model directory contains directories with names that do not match a regular expression --- freqtrade/freqai/data_drawer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 9eeabef8f..1c091f1be 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -355,7 +355,7 @@ class FreqaiDataDrawer: for dir in model_folders: result = pattern.match(str(dir.name)) if result is None: - break + continue coin = result.group(1) timestamp = result.group(2) From aed19ff6cee279f1446338dab54b2bb348145902 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 13 Sep 2022 19:17:12 -0600 Subject: [PATCH 331/592] fix The future belongs to a different loop error --- freqtrade/rpc/api_server/ws/channel.py | 1 - 1 file changed, 1 deletion(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index f4a0da47b..cffe3092d 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -71,7 +71,6 @@ class WebSocketChannel: Close the WebSocketChannel """ - await self._websocket.close() self._closed = True def is_closed(self) -> bool: From 49800e4cc300eb39b412287a05480a98962c354b Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 14 Sep 2022 06:55:05 +0200 Subject: [PATCH 332/592] pin ci python to 3.10.6 for now --- .github/workflows/ci.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index bb5bc209e..91d53044d 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -24,7 +24,7 @@ jobs: strategy: matrix: os: [ ubuntu-18.04, ubuntu-20.04, ubuntu-22.04 ] - python-version: ["3.8", "3.9", "3.10"] + python-version: ["3.8", "3.9", "3.10.6"] steps: - uses: actions/checkout@v3 @@ -121,7 +121,7 @@ jobs: strategy: matrix: os: [ macos-latest ] - python-version: ["3.8", "3.9", "3.10"] + python-version: ["3.8", "3.9", "3.10.6"] steps: - uses: actions/checkout@v3 @@ -205,7 +205,7 @@ jobs: strategy: matrix: os: [ windows-latest ] - python-version: ["3.8", "3.9", "3.10"] + python-version: ["3.8", "3.9", "3.10.6"] steps: - uses: actions/checkout@v3 From 91bc3d11618c3f5bf47a8a71166544cf4e0b7a0f Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 14 Sep 2022 07:04:14 +0200 Subject: [PATCH 333/592] Update docs aroudn use_exit_signal close #7413 --- docs/strategy-customization.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index 2b6e1fb2f..b97bd6d23 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -264,7 +264,8 @@ def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFram ### Exit signal rules Edit the method `populate_exit_trend()` into your strategy file to update your exit strategy. -Please note that the exit-signal is only used if `use_exit_signal` is set to true in the configuration. +The exit-signal is only used for exits if `use_exit_signal` is set to true in the configuration. +`use_exit_signal` will not influence [signal collision rules](#colliding-signals) - which will still apply and can prevent entries. It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected. From 711849abd6fc48c5936d31bc4e8a7afc130c0dfb Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 14 Sep 2022 07:16:57 +0200 Subject: [PATCH 334/592] Use Wheels for win builds --- .../TA_Lib-0.4.24-cp310-cp310-win_amd64.whl | Bin 515758 -> 0 bytes .../TA_Lib-0.4.24-cp38-cp38-win_amd64.whl | Bin 518186 -> 0 bytes .../TA_Lib-0.4.24-cp39-cp39-win_amd64.whl | Bin 515822 -> 0 bytes .../TA_Lib-0.4.25-cp310-cp310-win_amd64.whl | Bin 0 -> 500560 bytes .../TA_Lib-0.4.25-cp38-cp38-win_amd64.whl | Bin 0 -> 506094 bytes .../TA_Lib-0.4.25-cp39-cp39-win_amd64.whl | Bin 0 -> 503429 bytes build_helpers/install_windows.ps1 | 6 +++--- docs/windows_installation.md | 4 ++-- 8 files changed, 5 insertions(+), 5 deletions(-) delete mode 100644 build_helpers/TA_Lib-0.4.24-cp310-cp310-win_amd64.whl delete mode 100644 build_helpers/TA_Lib-0.4.24-cp38-cp38-win_amd64.whl delete mode 100644 build_helpers/TA_Lib-0.4.24-cp39-cp39-win_amd64.whl create mode 100644 build_helpers/TA_Lib-0.4.25-cp310-cp310-win_amd64.whl 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