From 0c810868de467e8a9a5f5f3941992117abadb31a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 18 Sep 2022 14:59:16 +0200 Subject: [PATCH 001/258] Add Dataprovider to pairlist --- freqtrade/freqtradebot.py | 5 ++++- freqtrade/optimize/backtesting.py | 2 +- freqtrade/plugins/pairlistmanager.py | 6 ++++-- tests/plugins/test_pairlist.py | 10 +++++----- 4 files changed, 14 insertions(+), 9 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 72b88a82f..169af2ab6 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -82,7 +82,10 @@ 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.rpc) + self.dataprovider = DataProvider(self.config, self.exchange, rpc=self.rpc) + self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider) + + self.dataprovider.add_pairlisthandler(self.pairlists) # Attach Dataprovider to strategy instance self.strategy.dp = self.dataprovider diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 2a1c44f7f..aa25e049a 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -110,7 +110,7 @@ class Backtesting: self.timeframe = str(self.config.get('timeframe')) self.timeframe_min = timeframe_to_minutes(self.timeframe) self.init_backtest_detail() - self.pairlists = PairListManager(self.exchange, self.config) + self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider) if 'VolumePairList' in self.pairlists.name_list: raise OperationalException("VolumePairList not allowed for backtesting. " "Please use StaticPairlist instead.") diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index e01abb297..763307d3f 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -3,11 +3,12 @@ PairList manager class """ import logging from functools import partial -from typing import Dict, List +from typing import Dict, List, Optional from cachetools import TTLCache, cached from freqtrade.constants import Config, ListPairsWithTimeframes +from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import CandleType from freqtrade.exceptions import OperationalException from freqtrade.mixins import LoggingMixin @@ -21,13 +22,14 @@ logger = logging.getLogger(__name__) class PairListManager(LoggingMixin): - def __init__(self, exchange, config: Config) -> None: + def __init__(self, exchange, config: Config, dataprovider: DataProvider = None) -> None: self._exchange = exchange self._config = config self._whitelist = self._config['exchange'].get('pair_whitelist') self._blacklist = self._config['exchange'].get('pair_blacklist', []) self._pairlist_handlers: List[IPairList] = [] self._tickers_needed = False + self._dataprovider: Optional[DataProvider] = dataprovider for pairlist_handler_config in self._config.get('pairlists', []): pairlist_handler = PairListResolver.load_pairlist( pairlist_handler_config['method'], diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index 538751251..26b7ebbe2 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -126,7 +126,7 @@ def test_log_cached(mocker, static_pl_conf, markets, tickers): def test_load_pairlist_noexist(mocker, markets, default_conf): freqtrade = get_patched_freqtradebot(mocker, default_conf) mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)) - plm = PairListManager(freqtrade.exchange, default_conf) + plm = PairListManager(freqtrade.exchange, default_conf, MagicMock()) with pytest.raises(OperationalException, match=r"Impossible to load Pairlist 'NonexistingPairList'. " r"This class does not exist or contains Python code errors."): @@ -137,7 +137,7 @@ def test_load_pairlist_noexist(mocker, markets, default_conf): def test_load_pairlist_verify_multi(mocker, markets_static, default_conf): freqtrade = get_patched_freqtradebot(mocker, default_conf) mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_static)) - plm = PairListManager(freqtrade.exchange, default_conf) + plm = PairListManager(freqtrade.exchange, default_conf, MagicMock()) # Call different versions one after the other, should always consider what was passed in # and have no side-effects (therefore the same check multiple times) assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', ], print) == ['ETH/BTC', 'XRP/BTC'] @@ -269,7 +269,7 @@ def test_refresh_pairlist_dynamic(mocker, shitcoinmarkets, tickers, whitelist_co with pytest.raises(OperationalException, match=r'`number_assets` not specified. Please check your configuration ' r'for "pairlist.config.number_assets"'): - PairListManager(freqtrade.exchange, whitelist_conf) + PairListManager(freqtrade.exchange, whitelist_conf, MagicMock()) def test_refresh_pairlist_dynamic_2(mocker, shitcoinmarkets, tickers, whitelist_conf_2): @@ -694,7 +694,7 @@ def test_PrecisionFilter_error(mocker, whitelist_conf) -> None: with pytest.raises(OperationalException, match=r"PrecisionFilter can only work with stoploss defined\..*"): - PairListManager(MagicMock, whitelist_conf) + PairListManager(MagicMock, whitelist_conf, MagicMock()) def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None: @@ -703,7 +703,7 @@ def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None: del Trade.query mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) exchange = get_patched_exchange(mocker, whitelist_conf) - pm = PairListManager(exchange, whitelist_conf) + pm = PairListManager(exchange, whitelist_conf, MagicMock()) pm.refresh_pairlist() assert log_has("PerformanceFilter is not available in this mode.", caplog) From 4940fa7be3520e6096ccbd6f7231d0eb6b9b128b Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 18 Sep 2022 15:29:57 +0200 Subject: [PATCH 002/258] Add Producer Pairlist --- freqtrade/constants.py | 2 +- .../plugins/pairlist/ProducerPairList.py | 87 +++++++++++++++++++ 2 files changed, 88 insertions(+), 1 deletion(-) create mode 100644 freqtrade/plugins/pairlist/ProducerPairList.py diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 4c2bd6e18..e0e42c821 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -31,7 +31,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss', 'CalmarHyperOptLoss', 'MaxDrawDownHyperOptLoss', 'MaxDrawDownRelativeHyperOptLoss', 'ProfitDrawDownHyperOptLoss'] -AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', +AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'ProducerPairList', 'AgeFilter', 'OffsetFilter', 'PerformanceFilter', 'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter', 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter'] diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py new file mode 100644 index 000000000..81320f713 --- /dev/null +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -0,0 +1,87 @@ +""" +External Pair List provider + +Provides pair list from Leader data +""" +import logging +from typing import Any, Dict, List, Optional + +from freqtrade.plugins.pairlist.IPairList import IPairList + + +logger = logging.getLogger(__name__) + + +class ProducerPairList(IPairList): + """ + PairList plugin for use with external_message_consumer. + Will use pairs given from leader data. + + Usage: + "pairlists": [ + { + "method": "ProducerPairList", + "number_assets": 5, + "producer_name": "default", + } + ], + """ + + 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('number_assets') + self._producer_name = self._pairlistconfig.get('producer_name', 'default') + if config.get('external_message_consumer').get('enabled') is False: + raise ValueError("ProducerPairList requires external_message_consumer to be enabled.") + + @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} - {self._producer_name}" + + def _filter_pairlist(self, pairlist: Optional[List[str]]): + upstream_pairlist = self._pairlistmanager._dataprovider.get_producer_pairs( + self._producer_name) + + if pairlist is None: + pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(self._producer_name) + + pairs = list(dict.fromkeys(upstream_pairlist + pairlist))[:self._num_assets] + + return pairs + + 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 + """ + pairs = self._filter_pairlist(None) + self.log_once(f"Received pairs: {pairs}", logger.debug) + pairs = self._whitelist_for_active_markets(self.verify_whitelist(pairs, logger.info)) + self.log_once(f"New Pairlist: {pairs}", logger.info) + return pairs + + 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._filter_pairlist(pairlist) From 527fd36134f16995ebf960a42fff1080100e8af7 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 09:38:20 +0200 Subject: [PATCH 003/258] num_assets should be optional --- freqtrade/plugins/pairlist/ProducerPairList.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index 81320f713..0dc90ac0f 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -32,7 +32,7 @@ class ProducerPairList(IPairList): pairlist_pos: int) -> None: super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) - self._num_assets = self._pairlistconfig.get('number_assets') + self._num_assets: int = self._pairlistconfig.get('number_assets', 0) self._producer_name = self._pairlistconfig.get('producer_name', 'default') if config.get('external_message_consumer').get('enabled') is False: raise ValueError("ProducerPairList requires external_message_consumer to be enabled.") @@ -60,7 +60,9 @@ class ProducerPairList(IPairList): if pairlist is None: pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(self._producer_name) - pairs = list(dict.fromkeys(upstream_pairlist + pairlist))[:self._num_assets] + pairs = list(dict.fromkeys(upstream_pairlist + pairlist)) + if self._num_assets: + pairs = pairs[:self._num_assets] return pairs From 1c089dcd51fb192ed41beb98573cd915c2be380e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 09:40:44 +0200 Subject: [PATCH 004/258] Add docs for Producer/consumer pairlist --- docs/includes/pairlists.md | 29 ++++++++++++++++++++++++++++- 1 file changed, 28 insertions(+), 1 deletion(-) diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md index 0f55c1b79..7dff75a02 100644 --- a/docs/includes/pairlists.md +++ b/docs/includes/pairlists.md @@ -22,6 +22,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged * [`StaticPairList`](#static-pair-list) (default, if not configured differently) * [`VolumePairList`](#volume-pair-list) +* [`ProducerPairList`](#producerpairlist) * [`AgeFilter`](#agefilter) * [`OffsetFilter`](#offsetfilter) * [`PerformanceFilter`](#performancefilter) @@ -84,7 +85,7 @@ Filtering instances (not the first position in the list) will not apply any cach You can define a minimum volume with `min_value` - which will filter out pairs with a volume lower than the specified value in the specified timerange. -### VolumePairList Advanced mode +##### VolumePairList Advanced mode `VolumePairList` can also operate in an advanced mode to build volume over a given timerange of specified candle size. It utilizes exchange historical candle data, builds a typical price (calculated by (open+high+low)/3) and multiplies the typical price with every candle's volume. The sum is the `quoteVolume` over the given range. This allows different scenarios, for a more smoothened volume, when using longer ranges with larger candle sizes, or the opposite when using a short range with small candles. @@ -146,6 +147,32 @@ More sophisticated approach can be used, by using `lookback_timeframe` for candl !!! Note `VolumePairList` does not support backtesting mode. +#### ProducerPairList + +With `ProducerPairList`, you can reuse the pairlist from a [Producer](producer-consumer.md) without explicitly defining the pairlist on each consumer. + +[Consumer mode](producer-consumer.md) is required for this pairlist to work. + +The pairlist will perform a check on active pairs against the current exchange configuration to avoid attempting to trade on invalid markets. + +You can limit the length of the pairlist with the optional parameter `number_assets`. Using `"number_assets"=0` or omitting this key will result in the reuse of all producer pairs valid for the current setup. + +```json +"pairlists": [ + { + "method": "ProducerPairList", + "number_assets": 5, + "producer_name": "default", + } +], +``` + + +!!! Tip "Combining pairlists" + This pairlist can be combined with all other pairlists and filters for further pairlist reduction, and can also act as an "additional" pairlist, on top of already defined pairs. + `ProducerPairList` can also be used multiple times in sequence, combining the pairs from multiple producers. + Obviously in complex such configurations, the Producer may not provide data for all pairs, so the strategy must be fit for this. + #### AgeFilter Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity). From 30d51b6939819b541b9582284b93d17bc6927783 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 09:43:39 +0200 Subject: [PATCH 005/258] Move "pairlist" logging to manager --- freqtrade/plugins/pairlist/ProducerPairList.py | 1 - freqtrade/plugins/pairlist/VolumePairList.py | 2 -- freqtrade/plugins/pairlistmanager.py | 2 ++ 3 files changed, 2 insertions(+), 3 deletions(-) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index 0dc90ac0f..d0fb4ada2 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -75,7 +75,6 @@ class ProducerPairList(IPairList): pairs = self._filter_pairlist(None) self.log_once(f"Received pairs: {pairs}", logger.debug) pairs = self._whitelist_for_active_markets(self.verify_whitelist(pairs, logger.info)) - self.log_once(f"New Pairlist: {pairs}", logger.info) return pairs def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py index 9dcada291..b290f76aa 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -232,6 +232,4 @@ class VolumePairList(IPairList): # Limit pairlist to the requested number of pairs pairs = pairs[:self._number_pairs] - self.log_once(f"Searching {self._number_pairs} pairs: {pairs}", logger.info) - return pairs diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index 763307d3f..5ed319e93 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -98,6 +98,8 @@ class PairListManager(LoggingMixin): # to ensure blacklist is respected. pairlist = self.verify_blacklist(pairlist, logger.warning) + self.log_once(f"Whitelist with {len(pairlist)} pairs: {pairlist}", logger.info) + self._whitelist = pairlist def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]: From 1bb45a2650df119a5dad27b37a0390584254655e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 09:47:57 +0200 Subject: [PATCH 006/258] Fix crash due to insufficient check --- freqtrade/plugins/pairlist/ProducerPairList.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index d0fb4ada2..dc575f29b 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -34,7 +34,7 @@ class ProducerPairList(IPairList): self._num_assets: int = self._pairlistconfig.get('number_assets', 0) self._producer_name = self._pairlistconfig.get('producer_name', 'default') - if config.get('external_message_consumer').get('enabled') is False: + if config.get('external_message_consumer', {}).get('enabled') is False: raise ValueError("ProducerPairList requires external_message_consumer to be enabled.") @property From bd106b4b8eaf581b0a77a31e1d1f8133ba067b9a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 10:13:00 +0200 Subject: [PATCH 007/258] Add tests for Producerpairlist --- .../plugins/pairlist/ProducerPairList.py | 6 +- tests/conftest.py | 2 + tests/plugins/test_pairlist.py | 72 +++++++++++++++++++ 3 files changed, 78 insertions(+), 2 deletions(-) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index dc575f29b..fa351c9cc 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -6,6 +6,7 @@ Provides pair list from Leader data import logging from typing import Any, Dict, List, Optional +from freqtrade.exceptions import OperationalException from freqtrade.plugins.pairlist.IPairList import IPairList @@ -34,8 +35,9 @@ class ProducerPairList(IPairList): self._num_assets: int = self._pairlistconfig.get('number_assets', 0) self._producer_name = self._pairlistconfig.get('producer_name', 'default') - if config.get('external_message_consumer', {}).get('enabled') is False: - raise ValueError("ProducerPairList requires external_message_consumer to be enabled.") + if not config.get('external_message_consumer', {}).get('enabled'): + raise OperationalException( + "ProducerPairList requires external_message_consumer to be enabled.") @property def needstickers(self) -> bool: diff --git a/tests/conftest.py b/tests/conftest.py index 51b1b03e3..a9eeb481e 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -200,6 +200,8 @@ def patch_freqtradebot(mocker, config) -> None: mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock()) mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock()) patch_whitelist(mocker, config) + mocker.patch('freqtrade.freqtradebot.ExternalMessageConsumer') + mocker.patch('freqtrade.configuration.config_validation._validate_consumers') def get_patched_freqtradebot(mocker, config) -> FreqtradeBot: diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index 26b7ebbe2..a6b5813da 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -9,6 +9,7 @@ import pytest import time_machine from freqtrade.constants import AVAILABLE_PAIRLISTS +from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import CandleType, RunMode from freqtrade.exceptions import OperationalException from freqtrade.persistence import Trade @@ -40,6 +41,12 @@ def whitelist_conf(default_conf): "sort_key": "quoteVolume", }, ] + default_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [], + } + }) return default_conf @@ -1167,6 +1174,10 @@ def test_spreadfilter_invalid_data(mocker, default_conf, markets, tickers, caplo "[{'OffsetFilter': 'OffsetFilter - Taking 10 Pairs, starting from 5.'}]", None ), + ({"method": "ProducerPairList"}, + "[{'ProducerPairList': 'ProducerPairList - default'}]", + None + ), ]) def test_pricefilter_desc(mocker, whitelist_conf, markets, pairlistconfig, desc_expected, exception_expected): @@ -1341,3 +1352,64 @@ def test_expand_pairlist_keep_invalid(wildcardlist, pairs, expected): expand_pairlist(wildcardlist, pairs, keep_invalid=True) else: assert sorted(expand_pairlist(wildcardlist, pairs, keep_invalid=True)) == sorted(expected) + + +def test_ProducerPairlist_no_emc(mocker, whitelist_conf): + mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) + + whitelist_conf['pairlists'] = [ + { + "method": "ProducerPairList", + "number_assets": 10, + "producer_name": "hello_world", + } + ] + del whitelist_conf['external_message_consumer'] + + with pytest.raises(OperationalException, + match=r"ProducerPairList requires external_message_consumer to be enabled."): + get_patched_freqtradebot(mocker, whitelist_conf) + + +def test_ProducerPairlist(mocker, whitelist_conf, markets): + mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) + mocker.patch.multiple('freqtrade.exchange.Exchange', + markets=PropertyMock(return_value=markets), + exchange_has=MagicMock(return_value=True), + ) + whitelist_conf['pairlists'] = [ + { + "method": "ProducerPairList", + "number_assets": 2, + "producer_name": "hello_world", + } + ] + whitelist_conf.update({ + "external_message_consumer": { + "enabled": True, + "producers": [ + { + "name": "hello_world", + "host": "null", + "port": 9891, + "ws_token": "dummy", + } + ] + } + }) + + exchange = get_patched_exchange(mocker, whitelist_conf) + dp = DataProvider(whitelist_conf, exchange, None) + pairs = ['ETH/BTC', 'LTC/BTC', 'XRP/BTC'] + # different producer + dp._set_producer_pairs(pairs + ['MEEP/USDT'], 'default') + pm = PairListManager(exchange, whitelist_conf, dp) + pm.refresh_pairlist() + assert pm.whitelist == [] + # proper producer + dp._set_producer_pairs(pairs, 'hello_world') + pm.refresh_pairlist() + + # Pairlist reduced to 2 + assert pm.whitelist == pairs[:2] + assert len(pm.whitelist) == 2 From af59572cb9a7abd5286540de3dc3a38fb355cc64 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 25 Sep 2022 19:32:39 +0200 Subject: [PATCH 008/258] prior pairlists should go first --- freqtrade/plugins/pairlist/ProducerPairList.py | 2 +- tests/plugins/test_pairlist.py | 13 +++++++++++++ 2 files changed, 14 insertions(+), 1 deletion(-) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index fa351c9cc..50b674e60 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -62,7 +62,7 @@ class ProducerPairList(IPairList): if pairlist is None: pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(self._producer_name) - pairs = list(dict.fromkeys(upstream_pairlist + pairlist)) + pairs = list(dict.fromkeys(pairlist + upstream_pairlist)) if self._num_assets: pairs = pairs[:self._num_assets] diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index a6b5813da..82fc99d7a 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -1413,3 +1413,16 @@ def test_ProducerPairlist(mocker, whitelist_conf, markets): # Pairlist reduced to 2 assert pm.whitelist == pairs[:2] assert len(pm.whitelist) == 2 + whitelist_conf['exchange']['pair_whitelist'] = ['TKN/BTC'] + + whitelist_conf['pairlists'] = [ + {"method": "StaticPairList"}, + { + "method": "ProducerPairList", + "producer_name": "hello_world", + } + ] + pm = PairListManager(exchange, whitelist_conf, dp) + pm.refresh_pairlist() + assert len(pm.whitelist) == 4 + assert pm.whitelist == ['TKN/BTC'] + pairs From 8eda3a45a3e91a1dc2720ca5d4b5f9a4301836e9 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 27 Sep 2022 19:47:49 +0200 Subject: [PATCH 009/258] Test backest detail with leverage --- .../test_backtesting_adjust_position.py | 21 ++++++++++++------- tests/test_integration.py | 17 +++++++++------ 2 files changed, 25 insertions(+), 13 deletions(-) diff --git a/tests/optimize/test_backtesting_adjust_position.py b/tests/optimize/test_backtesting_adjust_position.py index 71f8cdcea..99c160a40 100644 --- a/tests/optimize/test_backtesting_adjust_position.py +++ b/tests/optimize/test_backtesting_adjust_position.py @@ -93,11 +93,16 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> t["close_rate"], 6) < round(ln.iloc[0]["high"], 6)) -def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> None: +@pytest.mark.parametrize('leverage', [ + 1, 2 +]) +def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, leverage) -> None: default_conf['use_exit_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=10) mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf')) + mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=10) + patch_exchange(mocker) default_conf.update({ "stake_amount": 100.0, @@ -105,6 +110,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non "strategy": "StrategyTestV3" }) backtesting = Backtesting(default_conf) + backtesting._can_short = True backtesting._set_strategy(backtesting.strategylist[0]) pair = 'XRP/USDT' row = [ @@ -120,18 +126,19 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non '', # enter_tag '', # exit_tag ] + backtesting.strategy.leverage = MagicMock(return_value=leverage) trade = backtesting._enter_trade(pair, row=row, direction='long') trade.orders[0].close_bt_order(row[0], trade) assert trade assert pytest.approx(trade.stake_amount) == 100.0 - assert pytest.approx(trade.amount) == 47.61904762 + assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 1 backtesting.strategy.adjust_trade_position = MagicMock(return_value=None) trade = backtesting._get_adjust_trade_entry_for_candle(trade, row) assert trade assert pytest.approx(trade.stake_amount) == 100.0 - assert pytest.approx(trade.amount) == 47.61904762 + assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 1 # Increase position by 100 backtesting.strategy.adjust_trade_position = MagicMock(return_value=100) @@ -140,7 +147,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non assert trade assert pytest.approx(trade.stake_amount) == 200.0 - assert pytest.approx(trade.amount) == 95.23809524 + assert pytest.approx(trade.amount) == 95.23809524 * leverage assert len(trade.orders) == 2 # Reduce by more than amount - no change to trade. @@ -150,7 +157,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non assert trade assert pytest.approx(trade.stake_amount) == 200.0 - assert pytest.approx(trade.amount) == 95.23809524 + assert pytest.approx(trade.amount) == 95.23809524 * leverage assert len(trade.orders) == 2 assert trade.nr_of_successful_entries == 2 @@ -160,7 +167,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non assert trade assert pytest.approx(trade.stake_amount) == 100.0 - assert pytest.approx(trade.amount) == 47.61904762 + assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 3 assert trade.nr_of_successful_entries == 2 assert trade.nr_of_successful_exits == 1 @@ -171,7 +178,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non assert trade assert pytest.approx(trade.stake_amount) == 100.0 - assert pytest.approx(trade.amount) == 47.61904762 + assert pytest.approx(trade.amount) == 47.61904762 * leverage assert len(trade.orders) == 3 assert trade.nr_of_successful_entries == 2 assert trade.nr_of_successful_exits == 1 diff --git a/tests/test_integration.py b/tests/test_integration.py index a7b4fbdd3..a848de5d3 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -2,7 +2,7 @@ from unittest.mock import MagicMock import pytest -from freqtrade.enums import ExitCheckTuple, ExitType +from freqtrade.enums import ExitCheckTuple, ExitType, TradingMode from freqtrade.persistence import Trade from freqtrade.persistence.models import Order from freqtrade.rpc.rpc import RPC @@ -455,10 +455,12 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert pytest.approx(trade.orders[-1].amount) == 61.538461232 -def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> None: +@pytest.mark.parametrize('leverage', [1, 2]) +def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog, leverage) -> None: default_conf_usdt['position_adjustment_enable'] = True freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) + freqtrade.trading_mode = TradingMode.FUTURES mocker.patch.multiple( 'freqtrade.exchange.Exchange', fetch_ticker=ticker_usdt, @@ -467,15 +469,17 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non price_to_precision=lambda s, x, y: y, get_min_pair_stake_amount=MagicMock(return_value=10), ) + mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=10) patch_get_signal(freqtrade) + freqtrade.strategy.leverage = MagicMock(return_value=leverage) freqtrade.enter_positions() assert len(Trade.get_trades().all()) == 1 trade = Trade.get_trades().first() assert len(trade.orders) == 1 assert pytest.approx(trade.stake_amount) == 60 - assert pytest.approx(trade.amount) == 30.0 + assert pytest.approx(trade.amount) == 30.0 * leverage assert trade.open_rate == 2.0 # Too small size @@ -484,8 +488,9 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non trade = Trade.get_trades().first() 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 smaller than the minimum of 10.", caplog) + assert pytest.approx(trade.amount) == 30.0 * leverage + assert log_has_re( + r"Remaining amount of \d\.\d+.* would be smaller than the minimum of 10.", caplog) freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-20) @@ -494,7 +499,7 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non assert len(trade.orders) == 2 assert trade.orders[-1].ft_order_side == 'sell' assert pytest.approx(trade.stake_amount) == 40.198 - assert pytest.approx(trade.amount) == 20.099 + assert pytest.approx(trade.amount) == 20.099 * leverage assert trade.open_rate == 2.0 assert trade.is_open caplog.clear() From 30a5bb08ddcc0708a3a50217243608a294174f20 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 27 Sep 2022 19:53:55 +0200 Subject: [PATCH 010/258] partial exits should account for leverage --- freqtrade/freqtradebot.py | 2 +- freqtrade/optimize/backtesting.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 72b88a82f..b1c95a721 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -597,7 +597,7 @@ class FreqtradeBot(LoggingMixin): # We should decrease our position amount = self.exchange.amount_to_contract_precision( trade.pair, - abs(float(FtPrecise(stake_amount) / FtPrecise(current_exit_rate)))) + abs(float(FtPrecise(stake_amount * trade.leverage) / 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 - diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index e942bdfeb..efe199bdf 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -540,7 +540,7 @@ class Backtesting: if stake_amount is not None and stake_amount < 0.0: amount = amount_to_contract_precision( - abs(stake_amount) / current_rate, trade.amount_precision, + abs(stake_amount * trade.leverage) / current_rate, trade.amount_precision, self.precision_mode, trade.contract_size) if amount == 0.0: return trade From 255c748ca2ac6c4ee58452c8f0e17f077afd2a11 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 27 Sep 2022 19:55:17 +0200 Subject: [PATCH 011/258] Update docs for new trade_position behavior --- docs/strategy-callbacks.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md index 0b8403414..ea10fc472 100644 --- a/docs/strategy-callbacks.md +++ b/docs/strategy-callbacks.md @@ -643,7 +643,7 @@ This callback is **not** called when there is an open order (either buy or sell) Additional Buys are ignored once you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits. -Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade. Modifications to leverage are not possible. +Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade. Modifications to leverage are not possible, and the stake-amount is assumed to be before applying leverage. !!! Note "About stake size" Using fixed stake size means it will be the amount used for the first order, just like without position adjustment. From 683b084323d45e0647327756e71ed4ccd4f1d6dd Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Wed, 28 Sep 2022 18:23:56 +0200 Subject: [PATCH 012/258] Set train-test-split shuffle=False as default and remove stratification --- docs/freqai-parameter-table.md | 3 +-- docs/freqai-running.md | 17 ----------------- freqtrade/freqai/data_kitchen.py | 12 +++--------- 3 files changed, 4 insertions(+), 28 deletions(-) diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md index 5969f43c6..c4d044ba4 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -27,8 +27,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)).
**Datatype:** Positive float (typically < 1). | `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. `FreqAI` uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN
**Datatype:** Positive integer. | `indicator_periods_candles` | Time periods to calculate indicators for. The indicators are added to the base indicator dataset.
**Datatype:** List of positive integers. -| `stratify_training_data` | Split the feature set into training and testing datasets. For example, `stratify_training_data: 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](freqai-running.md#data-stratification-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. defaults to `false`. +| `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. defaults to `False`. | `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features.
**Datatype:** Integer, defaults to `0`. | `DI_threshold` | Activates the use of the Dissimilarity Index for outlier detection when set to > 0. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di).
**Datatype:** Positive float (typically < 1). | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training dataset, as well as from incoming data points. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm).
**Datatype:** Boolean. diff --git a/docs/freqai-running.md b/docs/freqai-running.md index 6c7b56da1..bfefe88c2 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -105,23 +105,6 @@ During dry/live mode, FreqAI trains each coin pair sequentially (on separate thr In the presented example config, the user will only allow predictions on models that are less than 1/2 hours old. -## Data stratification for training and testing the model - -You 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 does not capture the complexity of the data, the test data is significantly different from the train data, or a different type of model should be used. - ## Controlling the model learning process Model training parameters are unique to the selected machine learning library. FreqAI allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement. diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index f4fa4e5fd..9e22667f3 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -134,20 +134,14 @@ class FreqaiDataKitchen: """ feat_dict = self.freqai_config["feature_parameters"] + shuffle = self.freqai_config.get('data_split_parameters', {}).get('shuffle', False) + weights: npt.ArrayLike if feat_dict.get("weight_factor", 0) > 0: weights = self.set_weights_higher_recent(len(filtered_dataframe)) else: weights = np.ones(len(filtered_dataframe)) - if feat_dict.get("stratify_training_data", 0) > 0: - stratification = np.zeros(len(filtered_dataframe)) - for i in range(1, len(stratification)): - if i % feat_dict.get("stratify_training_data", 0) == 0: - stratification[i] = 1 - else: - stratification = None - if self.freqai_config.get('data_split_parameters', {}).get('test_size', 0.1) != 0: ( train_features, @@ -160,7 +154,7 @@ class FreqaiDataKitchen: filtered_dataframe[: filtered_dataframe.shape[0]], labels, weights, - stratify=stratification, + shuffle=shuffle, **self.config["freqai"]["data_split_parameters"], ) else: From 772abfc6f033aec44c414cf3d183485bd5b5979c Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Wed, 28 Sep 2022 19:29:02 +0200 Subject: [PATCH 013/258] Add default value for shuffle in docs --- docs/freqai-parameter-table.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md index c4d044ba4..8e19226ba 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -40,7 +40,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | | **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` | The 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. +| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`.
**Datatype:** Boolean.
Defaut: `False`. | | **Model training parameters** | `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `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 you select 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. From 00965d8c069eaf82c5d42c19d3b4b9901dae2183 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 28 Sep 2022 20:20:22 +0200 Subject: [PATCH 014/258] Default to assume stored data only contains complete candles closes #7468 --- freqtrade/data/converter.py | 3 +-- freqtrade/data/history/history_utils.py | 2 +- freqtrade/data/history/idatahandler.py | 2 +- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py index 67461973f..98ed15489 100644 --- a/freqtrade/data/converter.py +++ b/freqtrade/data/converter.py @@ -47,8 +47,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *, def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *, - fill_missing: bool = True, - drop_incomplete: bool = True) -> DataFrame: + fill_missing: bool, drop_incomplete: bool) -> DataFrame: """ Cleanse a OHLCV dataframe by * Grouping it by date (removes duplicate tics) diff --git a/freqtrade/data/history/history_utils.py b/freqtrade/data/history/history_utils.py index 6a6e29429..93534e919 100644 --- a/freqtrade/data/history/history_utils.py +++ b/freqtrade/data/history/history_utils.py @@ -26,7 +26,7 @@ def load_pair_history(pair: str, datadir: Path, *, timerange: Optional[TimeRange] = None, fill_up_missing: bool = True, - drop_incomplete: bool = True, + drop_incomplete: bool = False, startup_candles: int = 0, data_format: str = None, data_handler: IDataHandler = None, diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py index c2d92fc4f..80e29f4c0 100644 --- a/freqtrade/data/history/idatahandler.py +++ b/freqtrade/data/history/idatahandler.py @@ -275,7 +275,7 @@ class IDataHandler(ABC): candle_type: CandleType, *, timerange: Optional[TimeRange] = None, fill_missing: bool = True, - drop_incomplete: bool = True, + drop_incomplete: bool = False, startup_candles: int = 0, warn_no_data: bool = True, ) -> DataFrame: From b4fb28e4ef992f9ec44f2814f83dc5fbf7eb10de Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 28 Sep 2022 20:23:56 +0200 Subject: [PATCH 015/258] Update tests for new dataload strategy --- tests/data/test_datahandler.py | 4 ++-- tests/data/test_entryexitanalysis.py | 4 ++-- tests/data/test_history.py | 8 +++---- tests/optimize/test_backtesting.py | 32 ++++++++++++++-------------- 4 files changed, 24 insertions(+), 24 deletions(-) diff --git a/tests/data/test_datahandler.py b/tests/data/test_datahandler.py index 8e1b0050a..5d6d60f84 100644 --- a/tests/data/test_datahandler.py +++ b/tests/data/test_datahandler.py @@ -139,10 +139,10 @@ def test_jsondatahandler_ohlcv_purge(mocker, testdatadir): def test_jsondatahandler_ohlcv_load(testdatadir, caplog): dh = JsonDataHandler(testdatadir) df = dh.ohlcv_load('XRP/ETH', '5m', 'spot') - assert len(df) == 711 + assert len(df) == 712 df_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', candle_type="mark") - assert len(df_mark) == 99 + assert len(df_mark) == 100 df_no_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', 'spot') assert len(df_no_mark) == 0 diff --git a/tests/data/test_entryexitanalysis.py b/tests/data/test_entryexitanalysis.py index 09fbe9957..588220465 100755 --- a/tests/data/test_entryexitanalysis.py +++ b/tests/data/test_entryexitanalysis.py @@ -124,8 +124,8 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp assert '0' in captured.out assert '0.01616' in captured.out assert '34.049' in captured.out - assert '0.104104' in captured.out - assert '47.0996' in captured.out + assert '0.104411' in captured.out + assert '52.8292' in captured.out # test group 1 args = get_args(base_args + ['--analysis-groups', "1"]) diff --git a/tests/data/test_history.py b/tests/data/test_history.py index 5642442b2..e7e3d4063 100644 --- a/tests/data/test_history.py +++ b/tests/data/test_history.py @@ -377,8 +377,8 @@ def test_load_partial_missing(testdatadir, caplog) -> None: td = ((end - start).total_seconds() // 60 // 5) + 1 assert td != len(data['UNITTEST/BTC']) - # Shift endtime with +5 - as last candle is dropped (partial candle) - end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5) + # Shift endtime with +5 + end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]) assert log_has(f'UNITTEST/BTC, spot, 5m, ' f'data ends at {end_real.strftime(DATETIME_PRINT_FORMAT)}', caplog) @@ -447,7 +447,7 @@ def test_get_timerange(default_conf, mocker, testdatadir) -> None: ) min_date, max_date = get_timerange(data) assert min_date.isoformat() == '2017-11-04T23:02:00+00:00' - assert max_date.isoformat() == '2017-11-14T22:58:00+00:00' + assert max_date.isoformat() == '2017-11-14T22:59:00+00:00' def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir) -> None: @@ -470,7 +470,7 @@ def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir) min_date, max_date, timeframe_to_minutes('1m')) assert len(caplog.record_tuples) == 1 assert log_has( - "UNITTEST/BTC has missing frames: expected 14396, got 13680, that's 716 missing values", + "UNITTEST/BTC has missing frames: expected 14397, got 13681, that's 716 missing values", caplog) diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index bd87b2b42..907e97fb7 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -80,7 +80,7 @@ def load_data_test(what, testdatadir): data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC', - fill_missing=True)} + fill_missing=True, drop_incomplete=True)} # FIX: fixturize this? @@ -323,7 +323,7 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None: backtesting = Backtesting(default_conf) backtesting._set_strategy(backtesting.strategylist[0]) processed = backtesting.strategy.advise_all_indicators(data) - assert len(processed['UNITTEST/BTC']) == 102 + assert len(processed['UNITTEST/BTC']) == 103 # Load strategy to compare the result between Backtesting function and strategy are the same strategy = StrategyResolver.load_strategy(default_conf) @@ -1165,9 +1165,9 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Parameter --enable-position-stacking detected ...' ] @@ -1244,9 +1244,9 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Parameter --enable-position-stacking detected ...', f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}', 'Running backtesting for Strategy StrategyTestV2', @@ -1355,9 +1355,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Parameter --enable-position-stacking detected ...', f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}', 'Running backtesting for Strategy StrategyTestV2', @@ -1371,7 +1371,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat assert 'EXIT REASON STATS' in captured.out assert 'DAY BREAKDOWN' in captured.out assert 'LEFT OPEN TRADES REPORT' in captured.out - assert '2017-11-14 21:17:00 -> 2017-11-14 22:58:00 | Max open trades : 1' in captured.out + assert '2017-11-14 21:17:00 -> 2017-11-14 22:59:00 | Max open trades : 1' in captured.out assert 'STRATEGY SUMMARY' in captured.out @@ -1503,9 +1503,9 @@ def test_backtest_start_nomock_futures(default_conf_usdt, mocker, 'Parameter -i/--timeframe detected ... Using timeframe: 1h ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2021-11-17 01:00:00 ' - 'up to 2021-11-21 03:00:00 (4 days).', + 'up to 2021-11-21 04:00:00 (4 days).', 'Backtesting with data from 2021-11-17 21:00:00 ' - 'up to 2021-11-21 03:00:00 (3 days).', + 'up to 2021-11-21 04:00:00 (3 days).', 'XRP/USDT, funding_rate, 8h, data starts at 2021-11-18 00:00:00', 'XRP/USDT, mark, 8h, data starts at 2021-11-18 00:00:00', f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}', @@ -1616,9 +1616,9 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker, 'Parameter --timeframe-detail detected, using 1m for intra-candle backtesting ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2019-10-11 00:00:00 ' - 'up to 2019-10-13 11:10:00 (2 days).', + 'up to 2019-10-13 11:15:00 (2 days).', 'Backtesting with data from 2019-10-11 01:40:00 ' - 'up to 2019-10-13 11:10:00 (2 days).', + 'up to 2019-10-13 11:15:00 (2 days).', f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}', ] @@ -1719,7 +1719,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days).', + 'up to 2017-11-14 22:59:00 (0 days).', 'Parameter --enable-position-stacking detected ...', ] @@ -1732,7 +1732,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda 'Running backtesting for Strategy StrategyTestV2', 'Running backtesting for Strategy StrategyTestV3', 'Ignoring max_open_trades (--disable-max-market-positions was used) ...', - 'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).', + 'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:59:00 (0 days).', ] elif run_id == '2' and min_backtest_date < start_time: assert backtestmock.call_count == 0 @@ -1745,7 +1745,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda 'Reusing result of previous backtest for StrategyTestV2', 'Running backtesting for Strategy StrategyTestV3', 'Ignoring max_open_trades (--disable-max-market-positions was used) ...', - 'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).', + 'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:59:00 (0 days).', ] assert backtestmock.call_count == 1 From 38aca8e908fb532f44e889d35257961437866b93 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 30 Sep 2022 00:22:31 +0200 Subject: [PATCH 016/258] fix failing svm test --- tests/freqai/test_freqai_datakitchen.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index f7446420d..b99ac236d 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -86,7 +86,7 @@ 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 8.09%", + "SVM detected 8.66%", caplog, ) From be48131185764d0b707e706de4f0aa6d2a688193 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 30 Sep 2022 00:33:08 +0200 Subject: [PATCH 017/258] make shuffle false in constants --- freqtrade/constants.py | 1 + freqtrade/freqai/data_kitchen.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index e14e81343..acab8489c 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -567,6 +567,7 @@ CONF_SCHEMA = { "properties": { "test_size": {"type": "number"}, "random_state": {"type": "integer"}, + "shuffle": {"type": "boolean", "default": False} }, }, "model_training_parameters": { diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 9e22667f3..5cf9b2f03 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -134,7 +134,8 @@ class FreqaiDataKitchen: """ feat_dict = self.freqai_config["feature_parameters"] - shuffle = self.freqai_config.get('data_split_parameters', {}).get('shuffle', False) + if 'shuffle' not in self.freqai_config['data_split_parameters']: + self.freqai_config["data_split_parameters"].update({'shuffle': False}) weights: npt.ArrayLike if feat_dict.get("weight_factor", 0) > 0: @@ -154,7 +155,6 @@ class FreqaiDataKitchen: filtered_dataframe[: filtered_dataframe.shape[0]], labels, weights, - shuffle=shuffle, **self.config["freqai"]["data_split_parameters"], ) else: From 34951f59d2c54aaf6bcb02d8bf6810f544dca877 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 06:44:19 +0200 Subject: [PATCH 018/258] Update failing tests --- tests/data/test_btanalysis.py | 2 +- tests/strategy/test_interface.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index dab76d0cb..ec7b457ea 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -235,7 +235,7 @@ def test_calculate_market_change(testdatadir): data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m') result = calculate_market_change(data) assert isinstance(result, float) - assert pytest.approx(result) == 0.00955514 + assert pytest.approx(result) == 0.01100002 def test_combine_dataframes_with_mean(testdatadir): diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py index 070e78b1d..294021c83 100644 --- a/tests/strategy/test_interface.py +++ b/tests/strategy/test_interface.py @@ -288,7 +288,7 @@ def test_advise_all_indicators(default_conf, testdatadir) -> None: data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange, fill_up_missing=True) processed = strategy.advise_all_indicators(data) - assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed + assert len(processed['UNITTEST/BTC']) == 103 def test_populate_any_indicators(default_conf, testdatadir) -> None: @@ -300,7 +300,7 @@ def test_populate_any_indicators(default_conf, testdatadir) -> None: processed = strategy.populate_any_indicators('UNITTEST/BTC', data, '5m') assert processed == data assert id(processed) == id(data) - assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed + assert len(processed['UNITTEST/BTC']) == 103 def test_freqai_not_initialized(default_conf) -> None: From 2d2ff2fff6c45c366e58289ea668c71ccc57da53 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 07:02:18 +0200 Subject: [PATCH 019/258] remove unnecessary assignments and comments --- freqtrade/freqtradebot.py | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index e912fa832..175f6f148 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1393,16 +1393,10 @@ class FreqtradeBot(LoggingMixin): trade.open_order_id = None logger.info(f'{side} Order timeout for {trade}.') else: - # if trade is partially complete, edit the stake details for the trade - # and close the order - # cancel_order may not contain the full order dict, so we need to fallback - # to the order dict acquired before cancelling. - # we need to fall back to the values from order if corder does not contain these keys. + # update_trade_state (and subsequently recalc_trade_from_orders) will handle updates + # to the trade object trade.amount = filled_amount - # * Check edge cases, we don't want to make leverage > 1.0 if we don't have to - # * (for leverage modes which aren't isolated futures) - trade.stake_amount = trade.amount * trade.open_rate / trade.leverage self.update_trade_state(trade, trade.open_order_id, corder) trade.open_order_id = None @@ -1442,8 +1436,6 @@ class FreqtradeBot(LoggingMixin): trade.close_rate_requested = None trade.close_profit = None trade.close_profit_abs = None - trade.close_date = None - trade.is_open = True trade.open_order_id = None trade.exit_reason = None cancelled = True From 561600e98ba85da1992bc69dbccda844d77580ca Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 07:05:21 +0200 Subject: [PATCH 020/258] Remove false test statements a trade is ONLY closed on `.close()` - which will only happen once the last order has been filled. --- tests/test_freqtradebot.py | 6 ------ 1 file changed, 6 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 5fe4d4011..02a3b7cf6 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -2673,7 +2673,6 @@ def test_manage_open_orders_exit_usercustom( open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime open_trade_usdt.close_profit_abs = 0.001 - open_trade_usdt.is_open = False Trade.query.session.add(open_trade_usdt) Trade.commit() @@ -2687,7 +2686,6 @@ def test_manage_open_orders_exit_usercustom( freqtrade.manage_open_orders() assert cancel_order_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 @@ -2697,7 +2695,6 @@ def test_manage_open_orders_exit_usercustom( freqtrade.manage_open_orders() assert cancel_order_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 @@ -2707,7 +2704,6 @@ def test_manage_open_orders_exit_usercustom( freqtrade.manage_open_orders() assert cancel_order_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 @@ -2755,7 +2751,6 @@ def test_manage_open_orders_exit( open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime open_trade_usdt.close_profit_abs = 0.001 - open_trade_usdt.is_open = False open_trade_usdt.is_short = is_short Trade.query.session.add(open_trade_usdt) @@ -2796,7 +2791,6 @@ def test_check_handle_cancelled_exit( open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime - open_trade_usdt.is_open = False open_trade_usdt.is_short = is_short Trade.query.session.add(open_trade_usdt) From 7dd984e25e5472f0a2fa069b81bc6f520e3ac1cd Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 07:13:57 +0200 Subject: [PATCH 021/258] Simplify cancel_entry --- freqtrade/freqtradebot.py | 7 ++----- tests/test_freqtradebot.py | 2 ++ 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 175f6f148..83089152a 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1343,11 +1343,12 @@ class FreqtradeBot(LoggingMixin): replacing: Optional[bool] = False ) -> bool: """ - Buy cancel - cancel order + entry cancel - cancel order :param replacing: Replacing order - prevent trade deletion. :return: True if order was fully cancelled """ was_trade_fully_canceled = False + side = trade.entry_side.capitalize() # Cancelled orders may have the status of 'canceled' or 'closed' if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES: @@ -1374,7 +1375,6 @@ class FreqtradeBot(LoggingMixin): corder = order reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] - side = trade.entry_side.capitalize() logger.info('%s order %s for %s.', side, reason, trade) # Using filled to determine the filled amount @@ -1388,15 +1388,12 @@ class FreqtradeBot(LoggingMixin): was_trade_fully_canceled = True reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}" else: - # FIXME TODO: This could possibly reworked to not duplicate the code 15 lines below. self.update_trade_state(trade, trade.open_order_id, corder) trade.open_order_id = None logger.info(f'{side} Order timeout for {trade}.') else: # update_trade_state (and subsequently recalc_trade_from_orders) will handle updates # to the trade object - trade.amount = filled_amount - self.update_trade_state(trade, trade.open_order_id, corder) trade.open_order_id = None diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 02a3b7cf6..7c7132bdd 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -2998,6 +2998,7 @@ def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_ trade.open_rate = 200 trade.is_short = False trade.entry_side = "buy" + trade.amount = 100 l_order['filled'] = 0.0 l_order['status'] = 'open' trade.nr_of_successful_entries = 0 @@ -3086,6 +3087,7 @@ def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order trade.entry_side = "buy" trade.open_order_id = "open_order_noop" trade.nr_of_successful_entries = 0 + trade.amount = 100 l_order['filled'] = 0.0 l_order['status'] = 'open' reason = CANCEL_REASON['TIMEOUT'] From f6a0d677d2050dba3e805c4a69c5cbb65941e695 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 07:23:50 +0200 Subject: [PATCH 022/258] Remove pointless notification assignment --- freqtrade/freqtradebot.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 83089152a..532d5d3d8 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1692,11 +1692,6 @@ class FreqtradeBot(LoggingMixin): 'stake_amount': trade.stake_amount, } - if 'fiat_display_currency' in self.config: - msg.update({ - 'fiat_currency': self.config['fiat_display_currency'], - }) - # Send the message self.rpc.send_msg(msg) From 0d8dfc1a922a8fb6550f94a449f1c56c7e63ef5b Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 13:47:26 +0200 Subject: [PATCH 023/258] Force joblib update via setup.py --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 0581081fa..d3f9ea7c0 100644 --- a/setup.py +++ b/setup.py @@ -72,7 +72,7 @@ setup( 'pandas', 'tables', 'blosc', - 'joblib', + 'joblib>=1.2.0', 'pyarrow; platform_machine != "armv7l"', 'fastapi', 'uvicorn', From cc06c60fd8f8d45cc9b4643d005dcef209351d57 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 15:43:05 +0200 Subject: [PATCH 024/258] Fix pandas deprecation warnings from freqAI --- 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 f4fa4e5fd..400e70fc8 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -210,7 +210,7 @@ class FreqaiDataKitchen: 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_df).any(1) # get the rows that have NaNs, + drop_index = pd.isnull(filtered_df).any(axis=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) @@ -221,7 +221,7 @@ class FreqaiDataKitchen: # about removing any row with NaNs # if labels has multiple columns (user wants to train multiple modelEs), we detect here labels = unfiltered_df.filter(label_list, axis=1) - drop_index_labels = pd.isnull(labels).any(1) + drop_index_labels = pd.isnull(labels).any(axis=1) drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0) dates = unfiltered_df['date'] filtered_df = filtered_df[ @@ -249,7 +249,7 @@ 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_df).any(1) + drop_index = pd.isnull(filtered_df).any(axis=1) self.data["filter_drop_index_prediction"] = drop_index filtered_df.fillna(0, inplace=True) # replacing all NaNs with zeros to avoid issues in 'prediction', but any prediction @@ -808,7 +808,7 @@ class FreqaiDataKitchen: :, :no_prev_pts ] distances = distances.replace([np.inf, -np.inf], np.nan) - drop_index = pd.isnull(distances).any(1) + drop_index = pd.isnull(distances).any(axis=1) distances = distances[drop_index == 0] inliers = pd.DataFrame(index=distances.index) From bd664580fbd3459884d61c6db46cff37e366bfb9 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 15:07:18 +0200 Subject: [PATCH 025/258] Don't unnecessarily reset order_id --- freqtrade/freqtradebot.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 532d5d3d8..387bae534 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1345,7 +1345,7 @@ class FreqtradeBot(LoggingMixin): """ entry cancel - cancel order :param replacing: Replacing order - prevent trade deletion. - :return: True if order was fully cancelled + :return: True if trade was fully cancelled """ was_trade_fully_canceled = False side = trade.entry_side.capitalize() @@ -1389,14 +1389,12 @@ class FreqtradeBot(LoggingMixin): reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}" else: self.update_trade_state(trade, trade.open_order_id, corder) - trade.open_order_id = None logger.info(f'{side} Order timeout for {trade}.') else: # update_trade_state (and subsequently recalc_trade_from_orders) will handle updates # to the trade object self.update_trade_state(trade, trade.open_order_id, corder) - trade.open_order_id = None logger.info(f'Partial {trade.entry_side} order timeout for {trade}.') reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}" From d462f4029998a8ff22d98aa7763851248baecb2d Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 15:26:34 +0200 Subject: [PATCH 026/258] Simple test improvements --- tests/test_freqtradebot.py | 40 +++++++++++++++++++++++++++++--------- 1 file changed, 31 insertions(+), 9 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 7c7132bdd..0f1a05ab4 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -2661,6 +2661,7 @@ def test_manage_open_orders_exit_usercustom( rpc_mock = patch_RPCManager(mocker) cancel_order_mock = MagicMock() patch_exchange(mocker) + mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=0.0) et_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit') mocker.patch.multiple( 'freqtrade.exchange.Exchange', @@ -2744,7 +2745,8 @@ def test_manage_open_orders_exit( 'freqtrade.exchange.Exchange', fetch_ticker=ticker_usdt, fetch_order=MagicMock(return_value=limit_sell_order_old), - cancel_order=cancel_order_mock + cancel_order=cancel_order_mock, + get_min_pair_stake_amount=MagicMock(return_value=0), ) freqtrade = FreqtradeBot(default_conf_usdt) @@ -3117,20 +3119,21 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: amount=2, exchange='binance', open_rate=0.245441, - open_order_id="123456", + open_order_id="sell_123456", open_date=arrow.utcnow().shift(days=-2).datetime, fee_open=fee.return_value, fee_close=fee.return_value, close_rate=0.555, close_date=arrow.utcnow().datetime, exit_reason="sell_reason_whatever", + stake_amount=0.245441 * 2, ) trade.orders = [ - Order( + Order( ft_order_side='buy', ft_pair=trade.pair, - ft_is_open=True, - order_id='123456', + ft_is_open=False, + order_id='buy_123456', status="closed", symbol=trade.pair, order_type="market", @@ -3143,15 +3146,33 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: order_date=trade.open_date, order_filled_date=trade.open_date, ), + Order( + ft_order_side='sell', + ft_pair=trade.pair, + ft_is_open=True, + order_id='sell_123456', + status="open", + symbol=trade.pair, + order_type="limit", + side="sell", + price=trade.open_rate, + average=trade.open_rate, + filled=0.0, + remaining=trade.amount, + cost=trade.open_rate * trade.amount, + order_date=trade.open_date, + order_filled_date=trade.open_date, + ), ] - order = {'id': "123456", + order = {'id': "sell_123456", 'remaining': 1, 'amount': 1, 'status': "open"} reason = CANCEL_REASON['TIMEOUT'] + send_msg_mock.reset_mock() assert freqtrade.handle_cancel_exit(trade, order, reason) assert cancel_order_mock.call_count == 1 - assert send_msg_mock.call_count == 2 + assert send_msg_mock.call_count == 1 assert trade.close_rate is None assert trade.exit_reason is None @@ -3177,8 +3198,9 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None: patch_RPCManager(mocker) patch_exchange(mocker) - mocker.patch( - 'freqtrade.exchange.Exchange.cancel_order_with_result', side_effect=InvalidOrderException()) + mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=0.0) + mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', + side_effect=InvalidOrderException()) freqtrade = FreqtradeBot(default_conf_usdt) From 649879192b6453520ffa550ba7eb509696989c8b Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 15:12:57 +0200 Subject: [PATCH 027/258] Implement partial sell --- freqtrade/freqtradebot.py | 52 +++++++++++++++++++++------------------ 1 file changed, 28 insertions(+), 24 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 387bae534..67d734ce2 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1409,37 +1409,41 @@ class FreqtradeBot(LoggingMixin): :return: True if exit order was cancelled, false otherwise """ cancelled = False - # if trade is not partially completed, just cancel the order - if order['remaining'] == order['amount'] or order.get('filled') == 0.0: - if not self.exchange.check_order_canceled_empty(order): - try: - # if trade is not partially completed, just delete the order - co = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, - trade.amount) - trade.update_order(co) - except InvalidOrderException: - logger.exception( - f"Could not cancel {trade.exit_side} order {trade.open_order_id}") - return False - logger.info('%s order %s for %s.', trade.exit_side.capitalize(), reason, trade) - else: - reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] - logger.info('%s order %s for %s.', trade.exit_side.capitalize(), reason, trade) - trade.update_order(order) + # Cancelled orders may have the status of 'canceled' or 'closed' + if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES: + filled_val: float = order.get('filled', 0.0) or 0.0 + filled_rem_stake = trade.stake_amount - filled_val * trade.open_rate + minstake = self.exchange.get_min_pair_stake_amount( + trade.pair, trade.open_rate, self.strategy.stoploss) + # Double-check remaining amount + if filled_val > 0 and minstake and filled_rem_stake < minstake: + logger.warning( + f"Order {trade.open_order_id} for {trade.pair} not cancelled, " + f"as the filled amount of {filled_val} would result in an unexitable trade.") + return False + try: + co = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, + trade.amount) + except InvalidOrderException: + logger.exception( + f"Could not cancel {trade.exit_side} order {trade.open_order_id}") + return False trade.close_rate = None trade.close_rate_requested = None trade.close_profit = None trade.close_profit_abs = None - trade.open_order_id = None trade.exit_reason = None - cancelled = True - self.wallets.update() - else: - # TODO: figure out how to handle partially complete sell orders - reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'] - cancelled = False + self.update_trade_state(trade, trade.open_order_id, co) + logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') + cancelled = True + else: + reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] + logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') + self.update_trade_state(trade, trade.open_order_id, order) + + self.wallets.update() order_obj = trade.select_order_by_order_id(order['id']) if not order_obj: raise DependencyException( From c946d30596c46c823ad02a738c072594e555f24d Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 16:17:48 +0200 Subject: [PATCH 028/258] Add partial cancel message --- freqtrade/freqtradebot.py | 23 ++++++++++++++++++----- tests/test_freqtradebot.py | 16 +++++++++++++++- 2 files changed, 33 insertions(+), 6 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 67d734ce2..b98135fa5 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1416,11 +1416,24 @@ class FreqtradeBot(LoggingMixin): minstake = self.exchange.get_min_pair_stake_amount( trade.pair, trade.open_rate, self.strategy.stoploss) # Double-check remaining amount - if filled_val > 0 and minstake and filled_rem_stake < minstake: - logger.warning( - f"Order {trade.open_order_id} for {trade.pair} not cancelled, " - f"as the filled amount of {filled_val} would result in an unexitable trade.") - return False + if filled_val > 0: + reason = constants.CANCEL_REASON['PARTIALLY_FILLED'] + if minstake and filled_rem_stake < minstake: + logger.warning( + f"Order {trade.open_order_id} for {trade.pair} not cancelled, " + f"as the filled amount of {filled_val} would result in an unexitable trade.") + reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'] + + order_obj = trade.select_order_by_order_id(order['id']) + if not order_obj: + raise DependencyException( + f"Order_obj not found for {order['id']}. This should not have happened.") + self._notify_exit_cancel( + trade, + order_type=self.strategy.order_types['exit'], + reason=reason, order=order_obj, sub_trade=trade.amount != order['amount'] + ) + return False try: co = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 0f1a05ab4..415abbc10 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3111,6 +3111,9 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: cancel_order=cancel_order_mock, ) mocker.patch('freqtrade.exchange.Exchange.get_rate', return_value=0.245441) + mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=0.2) + + mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_order_fee') freqtrade = FreqtradeBot(default_conf_usdt) @@ -3178,7 +3181,9 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: send_msg_mock.reset_mock() + # Partial exit - below exit threshold order['amount'] = 2 + order['filled'] = 1.9 assert not freqtrade.handle_cancel_exit(trade, order, reason) # Assert cancel_order was not called (callcount remains unchanged) assert cancel_order_mock.call_count == 1 @@ -3188,12 +3193,21 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: assert not freqtrade.handle_cancel_exit(trade, order, reason) - send_msg_mock.call_args_list[0][0][0]['reason'] = CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'] + assert (send_msg_mock.call_args_list[0][0][0]['reason'] + == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']) # Message should not be iterated again assert trade.exit_order_status == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'] assert send_msg_mock.call_count == 1 + send_msg_mock.reset_mock() + + order['filled'] = 1 + assert freqtrade.handle_cancel_exit(trade, order, reason) + assert send_msg_mock.call_count == 1 + assert (send_msg_mock.call_args_list[0][0][0]['reason'] + == CANCEL_REASON['PARTIALLY_FILLED']) + def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None: patch_RPCManager(mocker) From 819488c906a01cc25995d715c3da36656748518e Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 16:59:23 +0200 Subject: [PATCH 029/258] Improve exit message wording --- freqtrade/freqtradebot.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index b98135fa5..37bf032fa 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1446,8 +1446,10 @@ class FreqtradeBot(LoggingMixin): trade.close_rate_requested = None trade.close_profit = None trade.close_profit_abs = None - trade.exit_reason = None + # Set exit_reason for fill message + trade.exit_reason = trade.exit_reason + f", {reason}" if trade.exit_reason else reason self.update_trade_state(trade, trade.open_order_id, co) + trade.exit_reason = None logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') cancelled = True From 47ef99f5886ca1373256b19ccf1878a9abf4f9bc Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 30 Sep 2022 17:18:27 +0200 Subject: [PATCH 030/258] Simplify interface to notify_exit_cancel --- freqtrade/freqtradebot.py | 25 +++++++++++-------------- 1 file changed, 11 insertions(+), 14 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 37bf032fa..2b20e40fd 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1420,18 +1420,15 @@ class FreqtradeBot(LoggingMixin): reason = constants.CANCEL_REASON['PARTIALLY_FILLED'] if minstake and filled_rem_stake < minstake: logger.warning( - f"Order {trade.open_order_id} for {trade.pair} not cancelled, " - f"as the filled amount of {filled_val} would result in an unexitable trade.") + f"Order {trade.open_order_id} for {trade.pair} not cancelled, as " + f"the filled amount of {filled_val} would result in an unexitable trade.") reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'] - order_obj = trade.select_order_by_order_id(order['id']) - if not order_obj: - raise DependencyException( - f"Order_obj not found for {order['id']}. This should not have happened.") self._notify_exit_cancel( trade, order_type=self.strategy.order_types['exit'], - reason=reason, order=order_obj, sub_trade=trade.amount != order['amount'] + reason=reason, order_id=order['id'], + sub_trade=trade.amount != order['amount'] ) return False @@ -1459,16 +1456,11 @@ class FreqtradeBot(LoggingMixin): self.update_trade_state(trade, trade.open_order_id, order) self.wallets.update() - order_obj = trade.select_order_by_order_id(order['id']) - if not order_obj: - raise DependencyException( - f"Order_obj not found for {order['id']}. This should not have happened.") - sub_trade = order_obj.amount != trade.amount self._notify_exit_cancel( trade, order_type=self.strategy.order_types['exit'], - reason=reason, order=order_obj, sub_trade=sub_trade + reason=reason, order_id=order['id'], sub_trade=trade.amount != order['amount'] ) return cancelled @@ -1665,7 +1657,7 @@ class FreqtradeBot(LoggingMixin): self.rpc.send_msg(msg) def _notify_exit_cancel(self, trade: Trade, order_type: str, reason: str, - order: Order, sub_trade: bool = False) -> None: + order_id: str, sub_trade: bool = False) -> None: """ Sends rpc notification when a sell cancel occurred. """ @@ -1674,6 +1666,11 @@ class FreqtradeBot(LoggingMixin): else: trade.exit_order_status = reason + order = trade.select_order_by_order_id(order_id) + if not order: + raise DependencyException( + f"Order_obj not found for {order_id}. This should not have happened.") + profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested profit_trade = trade.calc_profit(rate=profit_rate) current_rate = self.exchange.get_rate( From cdc01a07819f2634ce33c0bf9dc666924673e1ad Mon Sep 17 00:00:00 2001 From: Emre Date: Fri, 30 Sep 2022 15:22:05 -0700 Subject: [PATCH 031/258] Fix feature list match for pca --- freqtrade/freqai/data_kitchen.py | 5 +++++ freqtrade/freqai/freqai_interface.py | 4 ++++ 2 files changed, 9 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 400e70fc8..c05900bad 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1,5 +1,6 @@ import copy import logging +import re import shutil from datetime import datetime, timezone from math import cos, sin @@ -881,6 +882,10 @@ class FreqaiDataKitchen: """ column_names = dataframe.columns features = [c for c in column_names if "%" in c] + pca_features = [c for c in column_names if re.search(r"^PC\d+$", c)] + if not features and pca_features: + features = pca_features + if not features: raise OperationalException("Could not find any features!") diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index d9f917338..bf625b2a7 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -434,6 +434,10 @@ class IFreqaiModel(ABC): feature_list = dk.data["training_features_list_raw"] else: feature_list = dk.data['training_features_list'] + + if self.ft_params.get('principal_component_analysis', False): + feature_list = dk.data['training_features_list'] + if dk.training_features_list != feature_list: raise OperationalException( "Trying to access pretrained model with `identifier` " From fad90269391fb35a92c3fc03fa24d3b51720bc28 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 08:35:51 +0200 Subject: [PATCH 032/258] Update updating docs closes #7507 --- docs/updating.md | 9 +++++++++ docs/windows_installation.md | 2 +- 2 files changed, 10 insertions(+), 1 deletion(-) diff --git a/docs/updating.md b/docs/updating.md index 8dc7279a4..893bc846e 100644 --- a/docs/updating.md +++ b/docs/updating.md @@ -37,3 +37,12 @@ pip install -e . # Ensure freqUI is at the latest version freqtrade install-ui ``` + +### Problems updating + +Update-problems usually come missing dependencies (you didn't follow the above instructions) - or from updated dependencies, which fail to install (for example TA-lib). +Please refer to the corresponding installation sections (common problems linked below) + +Common problems and their solutions: + +* [ta-lib update on windows](windows_installation.md#2-install-ta-lib) diff --git a/docs/windows_installation.md b/docs/windows_installation.md index 9fbbf8250..5cfae8c10 100644 --- a/docs/windows_installation.md +++ b/docs/windows_installation.md @@ -34,7 +34,7 @@ python -m venv .env .env\Scripts\activate.ps1 # optionally install ta-lib from wheel # Eventually adjust the below filename to match the downloaded wheel -pip install --find-links build_helpers\ TA-Lib +pip install --find-links build_helpers\ TA-Lib -U pip install -r requirements.txt pip install -e . freqtrade From 545d65235261563dbc4b482dea82e2d76f0c5440 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 09:02:05 +0200 Subject: [PATCH 033/258] Update okx exception wording --- freqtrade/exchange/okx.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py index 2db5fb6a9..fe1c94017 100644 --- a/freqtrade/exchange/okx.py +++ b/freqtrade/exchange/okx.py @@ -78,7 +78,7 @@ class Okx(Exchange): raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( - f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e + f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e From a96aa568bfa81c7c78ba60cc676483f3903a2d74 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 09:21:40 +0200 Subject: [PATCH 034/258] Add binance futures mode checks closes #7505 --- docs/assets/binance_futures_settings.png | Bin 0 -> 81500 bytes docs/exchanges.md | 19 ++++++++++---- freqtrade/exchange/binance.py | 31 +++++++++++++++++++++++ tests/exchange/test_binance.py | 18 +++++++++++++ tests/exchange/test_ccxt_compat.py | 1 + 5 files changed, 64 insertions(+), 5 deletions(-) create mode 100644 docs/assets/binance_futures_settings.png diff --git a/docs/assets/binance_futures_settings.png b/docs/assets/binance_futures_settings.png new file mode 100644 index 0000000000000000000000000000000000000000..a3f7a2c7032d54c80b2206bad0a38cd5c7729d2a GIT binary patch literal 81500 zcma%iWl&s8xb4O@Ft}^5;KAKp1HnCbaCZw5971ppE`tOQF2UX1-QD$0&aL}?zp9y< 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z(8oN?Kj`QEa)QIi`Ra5@fjm3_`W8%mm;D26-HxvNa9g#t>NRmGhR1%SJrC}9>Fxu~qL zp<5`FXO??d3!nF837NnE{=+E7H{QuQAtSg(pnvhYLgnpLxPq&4rh9uwr$#WqNv)m* z-MtsF{Uh-=Az7Wr^r>&6=_4;Fbi||K2L7TcP@H$9"` 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 sites + +Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized. + +* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`. +* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`. + ### Binance Futures Binance has specific (unfortunately complex) [Futures Trading Quantitative Rules](https://www.binance.com/en/support/faq/4f462ebe6ff445d4a170be7d9e897272) which need to be followed, and which prohibit a too low stake-amount (among others) for too many orders. @@ -87,12 +94,14 @@ When trading on Binance Futures market, orderbook must be used because there is }, ``` -### Binance sites +#### Binance futures settings -Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized. +Users will also have to have the futures-setting "Position Mode" set to "One-way Mode", and "Asset Mode" set to "Single-Asset Mode". +These settings will be checked on startup, and freqtrade will show an error if this setting is wrong. -* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`. -* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`. +![Binance futures settings](assets/binance_futures_settings.png) + +Freqtrade will not attempt to change these settings. ## Kraken diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py index f9fb4a8b1..a0d4b2d82 100644 --- a/freqtrade/exchange/binance.py +++ b/freqtrade/exchange/binance.py @@ -68,6 +68,37 @@ class Binance(Exchange): tickers = deep_merge_dicts(bidsasks, tickers, allow_null_overrides=False) return tickers + @retrier + def additional_exchange_init(self) -> None: + """ + Additional exchange initialization logic. + .api will be available at this point. + Must be overridden in child methods if required. + """ + try: + if self.trading_mode == TradingMode.FUTURES and not self._config['dry_run']: + position_side = self._api.fapiPrivateGetPositionsideDual() + self._log_exchange_response('position_side_setting', position_side) + assets_margin = self._api.fapiPrivateGetMultiAssetsMargin() + self._log_exchange_response('multi_asset_margin', assets_margin) + msg = "" + if position_side.get('dualSidePosition') is True: + msg += ( + "\nHedge Mode is not supported by freqtrade. " + "Please change 'Position Mode' on your binance futures account.") + if assets_margin.get('multiAssetsMargin') is True: + msg += ("\nMulti-Asset Mode is not supported by freqtrade. " + "Please change 'Asset Mode' on your binance futures account.") + if msg: + raise OperationalException(msg) + except ccxt.DDoSProtection as e: + raise DDosProtection(e) from e + except (ccxt.NetworkError, ccxt.ExchangeError) as e: + raise TemporaryError( + f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e + except ccxt.BaseError as e: + raise OperationalException(e) from e + @retrier def _set_leverage( self, diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py index e9f4dfa8a..ef5cb1240 100644 --- a/tests/exchange/test_binance.py +++ b/tests/exchange/test_binance.py @@ -501,6 +501,24 @@ def test_fill_leverage_tiers_binance_dryrun(default_conf, mocker, leverage_tiers assert len(v) == len(value) +def test_additional_exchange_init_binance(default_conf, mocker): + api_mock = MagicMock() + api_mock.fapiPrivateGetPositionsideDual = MagicMock(return_value={"dualSidePosition": True}) + api_mock.fapiPrivateGetMultiAssetsMargin = MagicMock(return_value={"multiAssetsMargin": True}) + default_conf['dry_run'] = False + default_conf['trading_mode'] = TradingMode.FUTURES + default_conf['margin_mode'] = MarginMode.ISOLATED + with pytest.raises(OperationalException, + match=r"Hedge Mode is not supported.*\nMulti-Asset Mode is not supported.*"): + get_patched_exchange(mocker, default_conf, id="binance", api_mock=api_mock) + api_mock.fapiPrivateGetPositionsideDual = MagicMock(return_value={"dualSidePosition": False}) + api_mock.fapiPrivateGetMultiAssetsMargin = MagicMock(return_value={"multiAssetsMargin": False}) + exchange = get_patched_exchange(mocker, default_conf, id="binance", api_mock=api_mock) + assert exchange + ccxt_exceptionhandlers(mocker, default_conf, api_mock, 'binance', + "additional_exchange_init", "fapiPrivateGetPositionsideDual") + + def test__set_leverage_binance(mocker, default_conf): api_mock = MagicMock() diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 82be6196a..6798cd2f7 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -137,6 +137,7 @@ def exchange_futures(request, exchange_conf, class_mocker): 'freqtrade.exchange.binance.Binance.fill_leverage_tiers') class_mocker.patch('freqtrade.exchange.exchange.Exchange.fetch_trading_fees') class_mocker.patch('freqtrade.exchange.okx.Okx.additional_exchange_init') + class_mocker.patch('freqtrade.exchange.binance.Binance.additional_exchange_init') class_mocker.patch('freqtrade.exchange.exchange.Exchange.load_cached_leverage_tiers', return_value=None) class_mocker.patch('freqtrade.exchange.exchange.Exchange.cache_leverage_tiers') From 201bbbcee67d33a70dc81e1a04743345fedacd35 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 09:32:16 +0200 Subject: [PATCH 035/258] Okx formatting --- freqtrade/exchange/okx.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py index fe1c94017..6792c2cba 100644 --- a/freqtrade/exchange/okx.py +++ b/freqtrade/exchange/okx.py @@ -78,7 +78,8 @@ class Okx(Exchange): raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( - f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}') from e + f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}' + ) from e except ccxt.BaseError as e: raise OperationalException(e) from e From 8f8b5cc28ef82ddeed11c216058cd0c1c47ee710 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 09:35:21 +0200 Subject: [PATCH 036/258] Disable log spam from analyze_df in webhook/discord --- freqtrade/rpc/discord.py | 2 +- freqtrade/rpc/webhook.py | 8 ++++++++ 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py index 9efe6f427..c48508300 100644 --- a/freqtrade/rpc/discord.py +++ b/freqtrade/rpc/discord.py @@ -30,9 +30,9 @@ class Discord(Webhook): pass def send_msg(self, msg) -> None: - logger.info(f"Sending discord message: {msg}") if msg['type'].value in self.config['discord']: + logger.info(f"Sending discord message: {msg}") msg['strategy'] = self.strategy msg['timeframe'] = self.timeframe diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py index 6109e80bc..bb3b3922f 100644 --- a/freqtrade/rpc/webhook.py +++ b/freqtrade/rpc/webhook.py @@ -61,6 +61,14 @@ class Webhook(RPCHandler): RPCMessageType.STARTUP, RPCMessageType.WARNING): valuedict = whconfig.get('webhookstatus') + elif msg['type'] in ( + RPCMessageType.PROTECTION_TRIGGER, + RPCMessageType.PROTECTION_TRIGGER_GLOBAL, + RPCMessageType.WHITELIST, + RPCMessageType.ANALYZED_DF, + RPCMessageType.STRATEGY_MSG): + # Don't fail for non-implemented types + return else: raise NotImplementedError('Unknown message type: {}'.format(msg['type'])) if not valuedict: From 6702a1b21905be3a6a8b00222c20e2c5e09bc449 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 09:45:58 +0200 Subject: [PATCH 037/258] Update test to verify webhook won't log-spam on new messagetypes --- tests/rpc/test_rpc_webhook.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py index 4d65b4966..3bbb85d54 100644 --- a/tests/rpc/test_rpc_webhook.py +++ b/tests/rpc/test_rpc_webhook.py @@ -365,6 +365,14 @@ def test_exception_send_msg(default_conf, mocker, caplog): with pytest.raises(NotImplementedError): webhook.send_msg(msg) + # Test no failure for not implemented but known messagetypes + for e in RPCMessageType: + msg = { + 'type': e, + 'status': 'whatever' + } + webhook.send_msg(msg) + def test__send_msg(default_conf, mocker, caplog): default_conf["webhook"] = get_webhook_dict() From f2b875483f671dca812f2298ea1177ca1433b823 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 1 Oct 2022 13:14:59 +0200 Subject: [PATCH 038/258] ensure raw features match when PCA is employed --- freqtrade/freqai/data_kitchen.py | 4 ---- freqtrade/freqai/freqai_interface.py | 13 +++++-------- 2 files changed, 5 insertions(+), 12 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index c05900bad..766eb981f 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -1,6 +1,5 @@ import copy import logging -import re import shutil from datetime import datetime, timezone from math import cos, sin @@ -882,9 +881,6 @@ class FreqaiDataKitchen: """ column_names = dataframe.columns features = [c for c in column_names if "%" in c] - pca_features = [c for c in column_names if re.search(r"^PC\d+$", c)] - if not features and pca_features: - features = pca_features if not features: raise OperationalException("Could not find any features!") diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index bf625b2a7..5cc6d3f69 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -275,7 +275,8 @@ class IFreqaiModel(ABC): if dk.check_if_backtest_prediction_exists(): self.dd.load_metadata(dk) - self.check_if_feature_list_matches_strategy(dataframe_train, dk) + dk.find_features(dataframe_train) + self.check_if_feature_list_matches_strategy(dk) append_df = dk.get_backtesting_prediction() dk.append_predictions(append_df) else: @@ -296,7 +297,6 @@ class IFreqaiModel(ABC): else: self.model = self.dd.load_data(pair, dk) - # self.check_if_feature_list_matches_strategy(dataframe_train, 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) @@ -420,7 +420,7 @@ class IFreqaiModel(ABC): return def check_if_feature_list_matches_strategy( - self, dataframe: DataFrame, dk: FreqaiDataKitchen + self, dk: FreqaiDataKitchen ) -> None: """ Ensure user is passing the proper feature set if they are reusing an `identifier` pointing @@ -429,15 +429,12 @@ class IFreqaiModel(ABC): :param dk: FreqaiDataKitchen = non-persistent data container/analyzer for current coin/bot loop """ - dk.find_features(dataframe) + if "training_features_list_raw" in dk.data: feature_list = dk.data["training_features_list_raw"] else: feature_list = dk.data['training_features_list'] - if self.ft_params.get('principal_component_analysis', False): - feature_list = dk.data['training_features_list'] - if dk.training_features_list != feature_list: raise OperationalException( "Trying to access pretrained model with `identifier` " @@ -510,7 +507,7 @@ class IFreqaiModel(ABC): dk.use_DBSCAN_to_remove_outliers(predict=True) # ensure user is feeding the correct indicators to the model - self.check_if_feature_list_matches_strategy(dk.data_dictionary['prediction_features'], dk) + self.check_if_feature_list_matches_strategy(dk) def model_exists(self, dk: FreqaiDataKitchen) -> bool: """ From cd514cf15d35aa53774070c3bdd40ffd0f67ec00 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 1 Oct 2022 14:18:46 +0200 Subject: [PATCH 039/258] fix inlier metric in backtesting --- freqtrade/freqai/base_models/BaseClassifierModel.py | 2 +- freqtrade/freqai/base_models/BaseRegressionModel.py | 2 +- freqtrade/freqai/data_drawer.py | 2 +- freqtrade/freqai/data_kitchen.py | 2 ++ freqtrade/freqai/freqai_interface.py | 8 ++++---- 5 files changed, 9 insertions(+), 7 deletions(-) diff --git a/freqtrade/freqai/base_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py index 70f212d2a..09f1bf98c 100644 --- a/freqtrade/freqai/base_models/BaseClassifierModel.py +++ b/freqtrade/freqai/base_models/BaseClassifierModel.py @@ -92,7 +92,7 @@ class BaseClassifierModel(IFreqaiModel): filtered_df = dk.normalize_data_from_metadata(filtered_df) dk.data_dictionary["prediction_features"] = filtered_df - self.data_cleaning_predict(dk, filtered_df) + self.data_cleaning_predict(dk) predictions = self.model.predict(dk.data_dictionary["prediction_features"]) pred_df = DataFrame(predictions, columns=dk.label_list) diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py index 2450bf305..5d89dd356 100644 --- a/freqtrade/freqai/base_models/BaseRegressionModel.py +++ b/freqtrade/freqai/base_models/BaseRegressionModel.py @@ -92,7 +92,7 @@ class BaseRegressionModel(IFreqaiModel): dk.data_dictionary["prediction_features"] = filtered_df # optional additional data cleaning/analysis - self.data_cleaning_predict(dk, filtered_df) + self.data_cleaning_predict(dk) predictions = self.model.predict(dk.data_dictionary["prediction_features"]) pred_df = DataFrame(predictions, columns=dk.label_list) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 1839724f8..471f6875c 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -423,7 +423,7 @@ class FreqaiDataDrawer: dk.data["data_path"] = str(dk.data_path) dk.data["model_filename"] = str(dk.model_filename) - dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns) + dk.data["training_features_list"] = dk.training_features_list dk.data["label_list"] = dk.label_list # store the metadata with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp: diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 766eb981f..7efefd127 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -844,10 +844,12 @@ class FreqaiDataKitchen: 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) + # self.find_features(self.data_dictionary[f'{set_}_features']) else: self.data_dictionary['prediction_features'] = pd.concat( [compute_df, inlier_metric], axis=1) self.data_dictionary['prediction_features'].fillna(0, inplace=True) + # self.find_features(self.data_dictionary['prediction_features']) logger.info('Inlier metric computed and added to features.') diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 5cc6d3f69..78539bae5 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -482,13 +482,16 @@ class IFreqaiModel(ABC): 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: + def data_cleaning_predict(self, dk: FreqaiDataKitchen) -> None: """ Base data cleaning method for predict. Functions here are complementary to the functions of data_cleaning_train. """ ft_params = self.freqai_info["feature_parameters"] + # ensure user is feeding the correct indicators to the model + self.check_if_feature_list_matches_strategy(dk) + if ft_params.get('inlier_metric_window', 0): dk.compute_inlier_metric(set_='predict') @@ -506,9 +509,6 @@ class IFreqaiModel(ABC): if ft_params.get("use_DBSCAN_to_remove_outliers", False): dk.use_DBSCAN_to_remove_outliers(predict=True) - # ensure user is feeding the correct indicators to the model - self.check_if_feature_list_matches_strategy(dk) - def model_exists(self, dk: FreqaiDataKitchen) -> bool: """ Given a pair and path, check if a model already exists From f4c6b99d63b6da87da9318cbf599e074fa6a50e0 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 1 Oct 2022 14:23:15 +0200 Subject: [PATCH 040/258] remove commented lines --- freqtrade/freqai/data_kitchen.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7efefd127..766eb981f 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -844,12 +844,10 @@ class FreqaiDataKitchen: 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) - # self.find_features(self.data_dictionary[f'{set_}_features']) else: self.data_dictionary['prediction_features'] = pd.concat( [compute_df, inlier_metric], axis=1) self.data_dictionary['prediction_features'].fillna(0, inplace=True) - # self.find_features(self.data_dictionary['prediction_features']) logger.info('Inlier metric computed and added to features.') From 2c94ed2e59c5ef7eeb6a33c2caea045ad0a3e491 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 1 Oct 2022 21:20:14 +0200 Subject: [PATCH 041/258] Decrease message throughput fixes memory leak by queue raising indefinitely --- freqtrade/rpc/api_server/webserver.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index df4324740..53af91477 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -198,8 +198,10 @@ class ApiServer(RPCHandler): logger.debug(f"Found message of type: {message.get('type')}") # Broadcast it await self._ws_channel_manager.broadcast(message) - # Sleep, make this configurable? - await asyncio.sleep(0.1) + # Limit messages per sec. + # Could cause problems with queue size if too low, and + # problems with network traffik if too high. + await asyncio.sleep(0.001) except asyncio.CancelledError: pass From 564318415eb5d9ed41a3b8c1e85801d65bea7856 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 08:12:03 +0200 Subject: [PATCH 042/258] Improve test resiliance --- tests/rpc/test_rpc_emc.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 28adc66b9..b73a64f06 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -207,12 +207,15 @@ async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker): }) dp = DataProvider(default_conf, None, None, None) + # Handle start explicitly to avoid messing with threading in tests + mocker.patch("freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start",) emc = ExternalMessageConsumer(default_conf, dp) try: - await asyncio.sleep(0.01) + await emc._create_connection(emc.producers[0], asyncio.Lock()) assert log_has_re(r".+ is an invalid WebSocket URL .+", caplog) finally: + emc._running = False emc.shutdown() From 308fa430078bea9719fdb40a24cec6cca4c5c0f5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 08:30:19 +0200 Subject: [PATCH 043/258] Don't use magicmock as trade object --- tests/test_freqtradebot.py | 26 +++++++++++--------------- 1 file changed, 11 insertions(+), 15 deletions(-) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 0f1a05ab4..ca9e63890 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -28,6 +28,7 @@ from tests.conftest import (create_mock_trades, create_mock_trades_usdt, get_pat from tests.conftest_trades import (MOCK_TRADE_COUNT, entry_side, exit_side, mock_order_1, mock_order_2, mock_order_2_sell, mock_order_3, mock_order_3_sell, mock_order_4, mock_order_5_stoploss, mock_order_6_sell) +from tests.conftest_trades_usdt import mock_trade_usdt_4 def patch_RPCManager(mocker) -> MagicMock: @@ -2980,7 +2981,7 @@ def test_manage_open_orders_exception(default_conf_usdt, ticker_usdt, open_trade @pytest.mark.parametrize("is_short", [False, True]) -def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_short) -> None: +def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_short, fee) -> None: patch_RPCManager(mocker) patch_exchange(mocker) l_order = limit_order[entry_side(is_short)] @@ -2994,16 +2995,12 @@ def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_ freqtrade = FreqtradeBot(default_conf_usdt) freqtrade._notify_enter_cancel = MagicMock() - # TODO: Convert to real trade - trade = MagicMock() - trade.pair = 'LTC/USDT' - trade.open_rate = 200 - trade.is_short = False - trade.entry_side = "buy" - trade.amount = 100 + trade = mock_trade_usdt_4(fee, is_short) + Trade.query.session.add(trade) + Trade.commit() + l_order['filled'] = 0.0 l_order['status'] = 'open' - trade.nr_of_successful_entries = 0 reason = CANCEL_REASON['TIMEOUT'] assert freqtrade.handle_cancel_enter(trade, l_order, reason) assert cancel_order_mock.call_count == 1 @@ -3035,7 +3032,7 @@ def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_ @pytest.mark.parametrize("is_short", [False, True]) @pytest.mark.parametrize("limit_buy_order_canceled_empty", ['binance', 'ftx', 'kraken', 'bittrex'], indirect=['limit_buy_order_canceled_empty']) -def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_short, +def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_short, fee, limit_buy_order_canceled_empty) -> None: patch_RPCManager(mocker) patch_exchange(mocker) @@ -3046,11 +3043,10 @@ def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_sho freqtrade = FreqtradeBot(default_conf_usdt) reason = CANCEL_REASON['TIMEOUT'] - # TODO: Convert to real trade - trade = MagicMock() - trade.nr_of_successful_entries = 0 - trade.pair = 'LTC/ETH' - trade.entry_side = "sell" if is_short else "buy" + + trade = mock_trade_usdt_4(fee, is_short) + Trade.query.session.add(trade) + Trade.commit() assert freqtrade.handle_cancel_enter(trade, limit_buy_order_canceled_empty, reason) assert cancel_order_mock.call_count == 0 assert log_has_re( From 9bb061073d541867892d7736cba57a7a46b1b96d Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 08:36:34 +0200 Subject: [PATCH 044/258] Improve tests --- freqtrade/exchange/exchange.py | 2 +- tests/test_freqtradebot.py | 24 +++++++++++++----------- 2 files changed, 14 insertions(+), 12 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index f01e464fa..61a6efb45 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1292,7 +1292,7 @@ class Exchange: order = self.fetch_order(order_id, pair) except InvalidOrderException: logger.warning(f"Could not fetch cancelled order {order_id}.") - order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}} + order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}} return order diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index ca9e63890..e19436a9f 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -1061,6 +1061,7 @@ def test_add_stoploss_on_exchange(mocker, default_conf_usdt, limit_order, is_sho freqtrade = FreqtradeBot(default_conf_usdt) freqtrade.strategy.order_types['stoploss_on_exchange'] = True + # TODO: should not be magicmock trade = MagicMock() trade.is_short = is_short trade.open_order_id = None @@ -1102,6 +1103,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_ # First case: when stoploss is not yet set but the order is open # should get the stoploss order id immediately # and should return false as no trade actually happened + # TODO: should not be magicmock trade = MagicMock() trade.is_short = is_short trade.is_open = True @@ -1880,6 +1882,7 @@ def test_exit_positions(mocker, default_conf_usdt, limit_order, is_short, caplog return_value=limit_order[entry_side(is_short)]) mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[]) + # TODO: should not be magicmock trade = MagicMock() trade.is_short = is_short trade.open_order_id = '123' @@ -1903,6 +1906,7 @@ def test_exit_positions_exception(mocker, default_conf_usdt, limit_order, caplog order = limit_order[entry_side(is_short)] mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order) + # TODO: should not be magicmock trade = MagicMock() trade.is_short = is_short trade.open_order_id = None @@ -2043,6 +2047,7 @@ def test_update_trade_state_exception(mocker, default_conf_usdt, is_short, limit freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order) + # TODO: should not be magicmock trade = MagicMock() trade.open_order_id = '123' trade.amount = 123 @@ -2061,6 +2066,7 @@ def test_update_trade_state_orderexception(mocker, default_conf_usdt, caplog) -> mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=InvalidOrderException)) + # TODO: should not be magicmock trade = MagicMock() trade.open_order_id = '123' @@ -3064,7 +3070,7 @@ def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_sho 'String Return value', 123 ]) -def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order, is_short, +def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order, is_short, fee, cancelorder) -> None: patch_RPCManager(mocker) patch_exchange(mocker) @@ -3072,20 +3078,15 @@ def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order cancel_order_mock = MagicMock(return_value=cancelorder) mocker.patch.multiple( 'freqtrade.exchange.Exchange', - cancel_order=cancel_order_mock + cancel_order=cancel_order_mock, + fetch_order=MagicMock(side_effect=InvalidOrderException) ) freqtrade = FreqtradeBot(default_conf_usdt) freqtrade._notify_enter_cancel = MagicMock() - # TODO: Convert to real trade - trade = MagicMock() - trade.pair = 'LTC/USDT' - trade.entry_side = "buy" - trade.open_rate = 200 - trade.entry_side = "buy" - trade.open_order_id = "open_order_noop" - trade.nr_of_successful_entries = 0 - trade.amount = 100 + trade = mock_trade_usdt_4(fee, is_short) + Trade.query.session.add(trade) + Trade.commit() l_order['filled'] = 0.0 l_order['status'] = 'open' reason = CANCEL_REASON['TIMEOUT'] @@ -3200,6 +3201,7 @@ def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None: freqtrade = FreqtradeBot(default_conf_usdt) + # TODO: should not be magicmock trade = MagicMock() reason = CANCEL_REASON['TIMEOUT'] order = {'remaining': 1, From e686faf1bc8afa77327a9c1ae3774c8eb87716b4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 08:37:37 +0200 Subject: [PATCH 045/258] Remove faulty test cleanup --- 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 b73a64f06..84a2658a0 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -212,10 +212,10 @@ async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker): emc = ExternalMessageConsumer(default_conf, dp) try: + emc._running = True await emc._create_connection(emc.producers[0], asyncio.Lock()) assert log_has_re(r".+ is an invalid WebSocket URL .+", caplog) finally: - emc._running = False emc.shutdown() From d0b8c8b1a0a1c39f062d4e756ac5c128302ae287 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 08:45:41 +0200 Subject: [PATCH 046/258] improve invalid canceled order response handling --- freqtrade/exchange/exchange.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 61a6efb45..5648d8716 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1292,7 +1292,14 @@ class Exchange: order = self.fetch_order(order_id, pair) except InvalidOrderException: logger.warning(f"Could not fetch cancelled order {order_id}.") - order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}} + order = { + 'id': order_id, + 'status': 'canceled', + 'amount': amount, + 'filled': 0.0, + 'fee': {}, + 'info': {} + } return order From 21440eaec2e0a05fb16fbc7856921359418866ce Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Sun, 2 Oct 2022 12:47:58 +0200 Subject: [PATCH 047/258] Fix typos and correct/improve descriptions --- docs/freqai-configuration.md | 6 ++-- docs/freqai-developers.md | 8 ++--- docs/freqai-feature-engineering.md | 6 ++-- docs/freqai-parameter-table.md | 20 ++++++------ docs/freqai-running.md | 50 +++++++++++++++--------------- docs/freqai.md | 13 ++++---- 6 files changed, 51 insertions(+), 52 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index 50e75b658..683fc9b34 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -166,11 +166,11 @@ Below are the values you can expect to include/use inside a typical strategy dat | 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 as the predictions. For example, to predict the price change in the next 40 candles (similar to `templates/FreqaiExampleStrategy.py`), you would 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['&*']` | Any dataframe column prepended with `&` in `populate_any_indicators()` is treated as a training target (label) inside `FreqAI` (typically following the naming convention `&-s*`). For example, to predict the close price 40 candles into the future, you would set `df['&-s_close'] = df['close'].shift(-self.freqai_info["feature_parameters"]["label_period_candles"])` with `"label_period_candles": 40` in the config. `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 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` and explained [here](#creating-a-dynamic-target-threshold) 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 you know if the prediction is trustworthy or not. `do_predict==1` means that the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di)) of the input data point is above the threshold defined in the config, `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, see details [here](freqai-feature-engineering.md#identifying-outliers-using-a-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, or vice versa, 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['do_predict']` | Indication of an outlier data point. The return value is integer between -2 and 2, which lets you know if the prediction is trustworthy or not. `do_predict==1` means that the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di)) of the input data point is above the threshold defined in the config, `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, see details [here](freqai-feature-engineering.md#identifying-outliers-using-a-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, or vice versa, 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`. As with the SVM, if `use_DBSCAN_to_remove_outliers` is active, DBSCAN (see details [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan)) may also detect outliers and subtract 1 from `do_predict`. Hence, if both the SVM and DBSCAN are active and identify a datapoint that was above the DI threshold as an outlier, the result will be `do_predict==-2`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`.
**Datatype:** Integer between -2 and 2. | `df['DI_values']` | Dissimilarity Index (DI) values are proxies for 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. See details about the DI [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di).
**Datatype:** Float. -| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, you 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](freqai-feature-engineering.md).
**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`. To keep a particular type of feature for plotting purposes, you would prepend it with `%%`.
**Datatype:** Depends on the output of the model. +| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, you 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](freqai-feature-engineering.md).
**Note:** Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features are easily engineered using the multiplictative functionality of, e.g., `include_shifted_candles` and `include_timeframes` as described in the [parameter table](freqai-parameter-table.md)), these features are removed from the dataframe that is returned from `FreqAI` to the strategy. To keep a particular type of feature for plotting purposes, you would prepend it with `%%`.
**Datatype:** Depends on the output of the model. ## Setting the `startup_candle_count` diff --git a/docs/freqai-developers.md b/docs/freqai-developers.md index 4bff46f2f..9794e0efa 100644 --- a/docs/freqai-developers.md +++ b/docs/freqai-developers.md @@ -27,13 +27,13 @@ The file structure is automatically generated based on the model `identifier` se | Structure | Description | |-----------|-------------| | `config_*.json` | A copy of the model specific configuration file. | -| `historic_predictions.pkl` | A file containing all historic predictions generated during the lifetime of the `identifier` model during live deployment. `historic_predictions.pkl` is 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**. | +| `historic_predictions.pkl` | A file containing all historic predictions generated during the lifetime of the `identifier` model during live deployment. `historic_predictions.pkl` is used to reload the model after a crash or a config change. A backup file is always held in case of corruption on the main file.`FreqAI`**automatically** detects corruption and replaces the corrupted file with the backup. | | `pair_dictionary.json` | A file containing the training queue as well as the on disk location of the most recently trained model. | | `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.
+|| `*_metadata.json` - Metadata for the model, such as normalization max/min, expected training feature list, etc.
|| `*_model.*` - The model file saved to disk for reloading from a crash. Can be `joblib` (typical boosting libs), `zip` (stable_baselines), `hd5` (keras type), etc.
-|| `*_pca_object.pkl` - The [Principal component analysis (PCA)](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis) transform (if `principal_component_analysis: true` is set in the config) which will be used to transform unseen prediction features.
-|| `*_svm_model.pkl` - The [Support Vector Machine (SVM)](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm) model which is used to detect outliers in unseen prediction features.
+|| `*_pca_object.pkl` - The [Principal component analysis (PCA)](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis) transform (if `principal_component_analysis: True` is set in the config) which will be used to transform unseen prediction features.
+|| `*_svm_model.pkl` - The [Support Vector Machine (SVM)](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm) model (if `use_SVM_to_remove_outliers: True` is set in the config) which is used to detect outliers in unseen prediction features.
|| `*_trained_df.pkl` - The dataframe containing all the training features used to train the `identifier` model. This is used for computing the [Dissimilarity Index (DI)](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di) and can also be used for post-processing.
|| `*_trained_dates.df.pkl` - The dates associated with the `trained_df.pkl`, which is useful for post-processing. | diff --git a/docs/freqai-feature-engineering.md b/docs/freqai-feature-engineering.md index 8f061b9fd..bd700bbf7 100644 --- a/docs/freqai-feature-engineering.md +++ b/docs/freqai-feature-engineering.md @@ -4,7 +4,7 @@ Low level feature engineering is performed in the user strategy within a function called `populate_any_indicators()`. That function sets the `base features` such as, `RSI`, `MFI`, `EMA`, `SMA`, time of day, volume, etc. The `base features` can be custom indicators or they can be imported from any technical-analysis library that you can find. One important syntax rule is that all `base features` string names are prepended with `%`, while labels/targets are prepended with `&`. -Meanwhile, high level feature engineering is handled within `"feature_parameters":{}` in the `FreqAI` config. Within this file, it is possible to decide large scale feature expansions on top of the `base_features` such as "including correlated pairs" or "including informative timeframes" or even "including recent candles." +Meanwhile, high level feature engineering is handled within `"feature_parameters":{}` in the `FreqAI` config. Within this file, it is possible to decide large scale feature expansions on top of the `base_features` such as "including correlated pairs" or "including informative timeframes" or even "including recent candles." It is advisable to start from the template `populate_any_indicators()` in the source provided example strategy (found in `templates/FreqaiExampleStrategy.py`) to ensure that the feature definitions are following the correct conventions. Here is an example of how to set the indicators and labels in the strategy: @@ -141,7 +141,7 @@ Another example, where the user wants to use live metrics from the trade databas } ``` -You need 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, the preset values are what will be returned. +You need 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, the pre-set values are what will be returned. ## Feature normalization @@ -265,4 +265,4 @@ 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) (external website)) with `min_samples` ($N$) taken as 1/4 of the no. of time points in the feature set. `eps` ($\varepsilon$) is computed automatically 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. +`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) (external website)) with `min_samples` ($N$) taken as 1/4 of the no. of time points (candles) in the feature set. `eps` ($\varepsilon$) is computed automatically 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-parameter-table.md b/docs/freqai-parameter-table.md index 8e19226ba..2ec8fac30 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -11,8 +11,8 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `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 `train_period_days` window defined above, and retraining the model during backtesting (more info [here](freqai-running.md#backtesting)). This can be fractional days, but beware that the provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
**Datatype:** Float. | `identifier` | **Required.**
A unique ID for the current model. If models are saved to disk, the `identifier` allows for reloading specific pre-trained models/data.
**Datatype:** String. -| `live_retrain_hours` | Frequency of retraining during dry/live runs.
**Datatype:** Float > 0.
Default: 0 (models retrain as often as possible). -| `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
**Datatype:** Positive integer.
Default: 0 (models never expire). +| `live_retrain_hours` | Frequency of retraining during dry/live runs.
**Datatype:** Float > 0.
Default: `0` (models retrain as often as possible). +| `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
**Datatype:** Positive integer.
Default: `0` (models never expire). | `purge_old_models` | Delete obsolete models.
**Datatype:** Boolean.
Default: `False` (all historic models remain on disk). | `save_backtest_models` | Save models to disk when running backtesting. Backtesting operates most efficiently by saving the prediction data and reusing them directly for subsequent runs (when you wish to tune entry/exit parameters). Saving backtesting models to disk also allows to use the same model files for starting a dry/live instance with the same model `identifier`.
**Datatype:** Boolean.
Default: `False` (no models are saved). | `fit_live_predictions_candles` | Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training dataset (more information can be found [here](freqai-configuration.md#creating-a-dynamic-target-threshold)).
**Datatype:** Positive integer. @@ -25,16 +25,16 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `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). You can create custom labels and choose whether to make use of this parameter or not.
**Datatype:** Positive integer. | `include_shifted_candles` | Add features from previous candles to subsequent candles with the intent of adding historical information. If used, `FreqAI` will duplicate and shift all features from the `include_shifted_candles` previous candles so that the information is available for the subsequent candle.
**Datatype:** Positive integer. | `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)).
**Datatype:** Positive float (typically < 1). -| `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. `FreqAI` uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN
**Datatype:** Positive integer. +| `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. `FreqAI` uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN.
**Datatype:** Positive integer. | `indicator_periods_candles` | Time periods to calculate indicators for. The indicators are added to the base indicator dataset.
**Datatype:** List of positive integers. -| `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. defaults to `False`. -| `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features.
**Datatype:** Integer, defaults to `0`. +| `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.
Default: `False`. +| `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features.
**Datatype:** Integer.
Default: `0`. | `DI_threshold` | Activates the use of the Dissimilarity Index for outlier detection when set to > 0. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di).
**Datatype:** Positive float (typically < 1). | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training dataset, as well as from incoming data points. See details about how it works [here](freqai-feature-engineering.md#identifying-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](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary. | `use_DBSCAN_to_remove_outliers` | Cluster data using the DBSCAN algorithm to identify and remove outliers from training and prediction data. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan).
**Datatype:** Boolean. -| `inlier_metric_window` | If set, `FreqAI` adds an `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`, i.e., the number of previous time points to compare the current candle to. Details of how the `inlier_metric` is computed can be found [here](freqai-feature-engineering.md#inlier-metric).
**Datatype:** Integer.
Default: 0. -| `noise_standard_deviation` | If set, `FreqAI` adds noise to the training features with the aim of preventing overfitting. `FreqAI` generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. `noise_standard_deviation` should be kept relative to the normalized space, i.e., between -1 and 1. In other words, since data in `FreqAI` is always normalized to be between -1 and 1, `noise_standard_deviation: 0.05` would result in 32% of the data being randomly increased/decreased by more than 2.5% (i.e., the percent of data falling within the first standard deviation).
**Datatype:** Integer.
Default: 0. +| `inlier_metric_window` | If set, `FreqAI` adds an `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`, i.e., the number of previous time points to compare the current candle to. Details of how the `inlier_metric` is computed can be found [here](freqai-feature-engineering.md#inlier-metric).
**Datatype:** Integer.
Default: `0`. +| `noise_standard_deviation` | If set, `FreqAI` adds noise to the training features with the aim of preventing overfitting. `FreqAI` generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. `noise_standard_deviation` should be kept relative to the normalized space, i.e., between -1 and 1. In other words, since data in `FreqAI` is always normalized to be between -1 and 1, `noise_standard_deviation: 0.05` would result in 32% of the data being randomly increased/decreased by more than 2.5% (i.e., the percent of data falling within the first standard deviation).
**Datatype:** Integer.
Default: `0`. | `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. 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, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset.
**Datatype:** Float.
Default: `30`. | `reverse_train_test_order` | Split the feature dataset (see below) and use the latest data split for training 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, you should be careful to understand the unorthodox nature of this parameter before employing it.
**Datatype:** Boolean.
Default: `False` (no reversal). | | **Data split parameters** @@ -43,9 +43,9 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`.
**Datatype:** Boolean.
Defaut: `False`. | | **Model training parameters** | `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `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 you select 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_estimators` | The number of boosted trees to fit in the training of the model.
**Datatype:** Integer. +| `learning_rate` | Boosting learning rate during training of the model.
**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 the selected model makes use of Keras (typical for Tensorflow-based prediction models), this flag needs to be activated 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. +| `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`. diff --git a/docs/freqai-running.md b/docs/freqai-running.md index bfefe88c2..6299a80f3 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -1,4 +1,4 @@ -# Running FreqAI +# Running `FreqAI` There are two ways to train and deploy an adaptive machine learning model - live deployment and historical backtesting. In both cases, `FreqAI` runs/simulates periodic retraining of models as shown in the following figure: @@ -6,13 +6,13 @@ There are two ways to train and deploy an adaptive machine learning model - live ## Live deployments -FreqAI can be run dry/live using the following command: +`FreqAI` can be run dry/live using the following command: ```bash freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor ``` -When launched, FreqAI will start training a new model, with a new `identifier`, based on the config 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 you do not want FreqAI to retrain new models as often as possible, you can set `live_retrain_hours` to tell FreqAI to wait at least that number of hours before training a new model. Additionally, you can set `expired_hours` to tell FreqAI to avoid making predictions on models that are older than that number of hours. +When launched, `FreqAI` will start training a new model, with a new `identifier`, based on the config 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 you do not want `FreqAI` to retrain new models as often as possible, you can set `live_retrain_hours` to tell `FreqAI` to wait at least that number of hours before training a new model. Additionally, you can set `expired_hours` to tell `FreqAI` to avoid making predictions on models that are older than that number of hours. Trained models are by default saved to disk to allow for reuse during backtesting or after a crash. You can opt to [purge old models](#purging-old-model-data) to save disk space by setting `"purge_old_models": true` in the config. @@ -25,19 +25,19 @@ To start a dry/live run from a saved backtest model (or from a previously crashe } ``` -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. If a full `live_retrain_hours` has elapsed since the end of the loaded model, FreqAI will start training a new model. +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. If a full `live_retrain_hours` has elapsed since the end of the loaded model, `FreqAI` will start training a new model. ### Automatic data download -FreqAI automatically downloads the proper amount of data needed to ensure training of a model through the defined `train_period_days` and `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters). +`FreqAI` automatically downloads the proper amount of data needed to ensure training of a model through the defined `train_period_days` and `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters). ### Saving prediction data -All predictions made during the lifetime of a specific `identifier` model are stored in `historical_predictions.pkl` to allow for reloading after a crash or changes made to the config. +All predictions made during the lifetime of a specific `identifier` model are stored in `historic_predictions.pkl` to allow for reloading after a crash or changes made to the config. ### Purging old model data -FreqAI stores new model files after each successful training. These files become obsolete as new models are generated to adapt to new market conditions. If you are planning to leave FreqAI running for extended periods of time with high frequency retraining, you should enable `purge_old_models` in the config: +`FreqAI` stores new model files after each successful training. These files become obsolete as new models are generated to adapt to new market conditions. If you are planning to leave `FreqAI` running for extended periods of time with high frequency retraining, you should enable `purge_old_models` in the config: ```json "freqai": { @@ -49,20 +49,20 @@ This will automatically purge all models older than the two most recently traine ## Backtesting -The FreqAI backtesting module can be executed with the following command: +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 ``` -If this command has never been executed with the existing config file, FreqAI will train a new model +If this command has never been executed with the existing config file, `FreqAI` will train a new model for each pair, for each backtesting window within the expanded `--timerange`. -Backtesting mode requires [downloading the necessary data](#downloading-data-to-cover-the-full-backtest-period) before deployment (unlike in dry/live mode where FreqAI handles the data downloading automatically). You 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 set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-size-of-the-sliding-training-window-and-backtesting-duration). +Backtesting mode requires [downloading the necessary data](#downloading-data-to-cover-the-full-backtest-period) before deployment (unlike in dry/live mode where `FreqAI` handles the data downloading automatically). You 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 set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-size-of-the-sliding-training-window-and-backtesting-duration). !!! Note "Model reuse" Once the training is completed, you 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 + `FreqAI` will find the trained models and load them instead of spending time training. This is useful if you want to tweak (or even hyperopt) buy and sell criteria inside the strategy. If you *want* to retrain a new model with the same config file, you should simply change the `identifier`. This way, you can return to using any model you wish by simply specifying the `identifier`. @@ -71,7 +71,7 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to- ### Saving prediction data -To allow for tweaking your strategy (**not** the features!), FreqAI will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria. +To allow for tweaking your strategy (**not** the features!), `FreqAI` will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria. An additional directory called `predictions`, which contains all the predictions stored in `hdf` format, will be created in the `unique-id` folder. @@ -81,21 +81,21 @@ To save the models generated during a particular backtest so that you can start ### Downloading data to cover the full backtest period -For live/dry deployments, FreqAI will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the 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` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting timerange. +For live/dry deployments, `FreqAI` will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range. -As an example, to backtest the `--timerange 20210501-20210701` using the [example config](freqai-configuration.md#setting-up-the-configuration-file) which sets `train_period_days` to 30, together with `startup_candle_count: 40` on a maximum `include_timeframes` of 1h, the start date for the downloaded data needs to be `20210501` - 30 days - 40 * 1h / 24 hours = 20210330 (31.7 days earlier than the start of the desired training timerange). +As an example, to backtest the `--timerange 20210501-20210701` using the [example config](freqai-configuration.md#setting-up-the-configuration-file) which sets `train_period_days` to 30, together with `startup_candle_count: 40` on a maximum `include_timeframes` of 1h, the start date for the downloaded data needs to be `20210501` - 30 days - 40 * 1h / 24 hours = 20210330 (31.7 days earlier than the start of the desired training time range). ### Deciding the size of the sliding training window and backtesting duration -The backtesting timerange is defined 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](freqai-configuration.md#setting-up-the-configuration-file) (found in `config_examples/config_freqai.example.json`), the user is asking FreqAI to use a training period of 30 days and backtest on the subsequent 7 days. 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`. This means that if you set `--timerange 20210501-20210701`, FreqAI will have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). +The backtesting time range is defined 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](freqai-configuration.md#setting-up-the-configuration-file) (found in `config_examples/config_freqai.example.json`), the user is asking `FreqAI` to use a training period of 30 days and backtest on the subsequent 7 days. 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`. This means that if you set `--timerange 20210501-20210701`, `FreqAI` will have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). !!! Note - Although fractional `backtest_period_days` is allowed, you 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, by setting a `--timerange` of 10 days, and 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 train constantly. In this case, backtesting would take the exact same amount of time as a dry run. + Although fractional `backtest_period_days` is allowed, you 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, by setting a `--timerange` of 10 days, and 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 train constantly. In this case, backtesting would take the exact same amount of time as a dry run. ## 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 you are 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. You 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: +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 you are 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. You 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": { @@ -107,15 +107,15 @@ In the presented example config, the user will only allow predictions on models ## Controlling the model learning process -Model training parameters are unique to the selected machine learning library. FreqAI allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement. +Model training parameters are unique to the selected machine learning library. `FreqAI` allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement. Data split parameters are defined in `data_split_parameters` which can be any parameters associated with Scikit-learn's `train_test_split()` function. `train_test_split()` has a parameters called `shuffle` which allows to shuffle the data or keep it unshuffled. This is particularly useful to avoid biasing training with temporally auto-correlated data. More details about these parameters can be found the [Scikit-learn website](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). -The FreqAI specific parameter `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented [example config](freqai-configuration.md#setting-up-the-configuration-file), the user is asking for `labels` that are 24 candles in the future. +The `FreqAI` specific parameter `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented [example config](freqai-configuration.md#setting-up-the-configuration-file), the user is asking for `labels` that are 24 candles in the future. ## Continual learning -You can choose to adopt a continual learning scheme by setting `"continual_learning": true` in the config. By enabling `continual_learning`, after training an initial model from scratch, subsequent trainings will start from the final model state of the preceding training. This gives the new model a "memory" of the previous state. By default, this is set to `false` which means that all new models are trained from scratch, without input from previous models. +You can choose to adopt a continual learning scheme by setting `"continual_learning": true` in the config. By enabling `continual_learning`, after training an initial model from scratch, subsequent trainings will start from the final model state of the preceding training. This gives the new model a "memory" of the previous state. By default, this is set to `False` which means that all new models are trained from scratch, without input from previous models. ## Hyperopt @@ -125,15 +125,15 @@ You can hyperopt using the same command as for [typical Freqtrade hyperopt](hype freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 ``` -`hyperopt` requires you to have the data pre-downloaded in the same fashion as if you were doing [backtesting](#backtesting). In addition, you must consider some restrictions when trying to hyperopt FreqAI strategies: +`hyperopt` requires you to have the data pre-downloaded in the same fashion as if you were doing [backtesting](#backtesting). In addition, you must consider some restrictions when trying to hyperopt `FreqAI` strategies: -- The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. +- The `--analyze-per-epoch` hyperopt parameter is not compatible with `FreqAI`. - It's not possible to hyperopt indicators in the `populate_any_indicators()` function. This means that you 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 instructions also apply to hyperopt. -The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. You need to focus on hyperopting parameters that are not used in your features. For example, you should not try to hyperopt rolling window lengths in the feature creation, or any part of the 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. +The best method for combining hyperopt and `FreqAI` is to focus on hyperopting entry/exit thresholds/criteria. You need to focus on hyperopting parameters that are not used in your features. For example, you should not try to hyperopt rolling window lengths in the feature creation, or any part of the `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 threshold for the [Dissimilarity Index (DI)](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di) `DI_values` beyond which we consider data points as outliers: +A good example of a hyperoptable parameter in `FreqAI` is a threshold for the [Dissimilarity Index (DI)](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di) `DI_values` beyond which we consider data points as outliers: ```python di_max = IntParameter(low=1, high=20, default=10, space='buy', optimize=True, load=True) diff --git a/docs/freqai.md b/docs/freqai.md index 91adbf7ef..5ab019ca7 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -45,17 +45,17 @@ An overview of the algorithm, explaining the data processing pipeline and model ### Important machine learning vocabulary -**Features** - the parameters, based on historic data, on which a model is trained. All features for a single candle is stored as a vector. In `FreqAI`, you build a feature data sets from anything you can construct in the strategy. +**Features** - the parameters, based on historic data, on which a model is trained. All features for a single candle are stored as a vector. In `FreqAI`, you build a feature data set from anything you can construct in the strategy. -**Labels** - the target values that a model is trained toward. Each feature vector is associated with a single label that is defined by you 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 the model is trained toward. Each feature vector is associated with a single label that is defined by you within the strategy. These labels intentionally look into the future and are what you are training the model to be able to predict. -**Training** - the process of "teaching" the model to match the feature sets to the associated labels. Different types of models "learn" in different ways. More information about the different models can be found [here](freqai-configuration.md#using-different-prediction-models). +**Training** - the process of "teaching" the model to match the feature sets to the associated labels. Different types of models "learn" in different ways which means that one might be better than another for a specific application. More information about the different models that are already implemented in `FreqAI` can be found [here](freqai-configuration.md#using-different-prediction-models). -**Train data** - a subset of the feature data set that is fed to the model during training. This data directly influences weight connections in the model. +**Train data** - a subset of the feature data set that is fed to the model during training to "teach" the model how to predict the targets. This data directly influences weight connections in the model. **Test data** - a subset of the feature data set that is used to evaluate the performance of the model after training. This data does not influence nodal weights within the model. -**Inferencing** - the process of feeding a trained model new data on which it will make a prediction. +**Inferencing** - the process of feeding a trained model new unseen data on which it will make a prediction. ## Install prerequisites @@ -96,5 +96,4 @@ Software development: Wagner Costa @wagnercosta Beta testing and bug reporting: -Stefan Gehring @bloodhunter4rc, @longyu, Andrew Robert Lawless @paranoidandy, Pascal Schmidt @smidelis, Ryan McMullan @smarmau, -Juha Nykänen @suikula, Johan van der Vlugt @jooopiert, Richárd Józsa @richardjosza +Stefan Gehring @bloodhunter4rc, @longyu, Andrew Lawless @paranoidandy, Pascal Schmidt @smidelis, Ryan McMullan @smarmau, Juha Nykänen @suikula, Johan van der Vlugt @jooopiert, Richárd Józsa @richardjosza, Timothy Pogue @wizrds From 1727f99b58906420bd656f4ef08162ab98500d58 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 2 Oct 2022 18:11:52 +0200 Subject: [PATCH 048/258] Fix missing mock --- tests/test_freqtradebot.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 462857dd6..cdea772dc 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3095,6 +3095,9 @@ def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order cancel_order_mock.reset_mock() l_order['filled'] = 1.0 + order = deepcopy(l_order) + order['status'] = 'canceled' + mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order) assert not freqtrade.handle_cancel_enter(trade, l_order, reason) assert cancel_order_mock.call_count == 1 From b70f18f4c36c13aa3930fa812148fd452a48e18b Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 2 Oct 2022 18:33:39 +0200 Subject: [PATCH 049/258] add close price and date to historic_predictions --- freqtrade/freqai/data_drawer.py | 6 +++++- freqtrade/freqai/freqai_interface.py | 9 ++++++--- 2 files changed, 11 insertions(+), 4 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 471f6875c..0d3bdea29 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -257,7 +257,7 @@ class FreqaiDataDrawer: def append_model_predictions(self, pair: str, predictions: DataFrame, do_preds: NDArray[np.int_], - dk: FreqaiDataKitchen, len_df: int) -> None: + dk: FreqaiDataKitchen, strat_df: DataFrame) -> None: """ Append model predictions to historic predictions dataframe, then set the strategy return dataframe to the tail of the historic predictions. The length of @@ -266,6 +266,7 @@ class FreqaiDataDrawer: historic predictions. """ + len_df = len(strat_df) index = self.historic_predictions[pair].index[-1:] columns = self.historic_predictions[pair].columns @@ -293,6 +294,9 @@ class FreqaiDataDrawer: for return_str in rets: df[return_str].iloc[-1] = rets[return_str] + df['close_price'].iloc[-1] = strat_df['close'].iloc[-1] + df['date_pred'].iloc[-1] = strat_df['date'].iloc[-1] + self.model_return_values[pair] = df.tail(len_df).reset_index(drop=True) def attach_return_values_to_return_dataframe( diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 78539bae5..5ac7bc32c 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -393,7 +393,7 @@ class IFreqaiModel(ABC): # allows FreqUI to show full return values. pred_df, do_preds = self.predict(dataframe, dk) if pair not in self.dd.historic_predictions: - self.set_initial_historic_predictions(pred_df, dk, pair) + self.set_initial_historic_predictions(pred_df, dk, pair, dataframe) self.dd.set_initial_return_values(pair, pred_df) dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe) @@ -414,7 +414,7 @@ class IFreqaiModel(ABC): if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live: self.fit_live_predictions(dk, pair) - self.dd.append_model_predictions(pair, pred_df, do_preds, dk, len(dataframe)) + self.dd.append_model_predictions(pair, pred_df, do_preds, dk, dataframe) dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe) return @@ -583,7 +583,7 @@ class IFreqaiModel(ABC): self.dd.purge_old_models() def set_initial_historic_predictions( - self, pred_df: DataFrame, dk: FreqaiDataKitchen, pair: str + self, pred_df: DataFrame, dk: FreqaiDataKitchen, pair: str, strat_df: DataFrame ) -> None: """ This function is called only if the datadrawer failed to load an @@ -626,6 +626,9 @@ class IFreqaiModel(ABC): for return_str in dk.data['extra_returns_per_train']: hist_preds_df[return_str] = 0 + hist_preds_df['close_price'] = strat_df['close'] + hist_preds_df['date_pred'] = strat_df['date'] + # # for keras type models, the conv_window needs to be prepended so # # viewing is correct in frequi if self.freqai_info.get('keras', False) or self.ft_params.get('inlier_metric_window', 0): From 6f7b75d4b064b1e6803fdf803520d4cb30acc26f Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 03:01:13 +0000 Subject: [PATCH 050/258] Bump time-machine from 2.8.1 to 2.8.2 Bumps [time-machine](https://github.com/adamchainz/time-machine) from 2.8.1 to 2.8.2. - [Release notes](https://github.com/adamchainz/time-machine/releases) - [Changelog](https://github.com/adamchainz/time-machine/blob/main/HISTORY.rst) - [Commits](https://github.com/adamchainz/time-machine/compare/2.8.1...2.8.2) --- updated-dependencies: - dependency-name: time-machine 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 d50105662..5b76a4701 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -17,7 +17,7 @@ pytest-mock==3.8.2 pytest-random-order==1.0.4 isort==5.10.1 # For datetime mocking -time-machine==2.8.1 +time-machine==2.8.2 # Convert jupyter notebooks to markdown documents nbconvert==7.0.0 From f722104f7e6c314f40a876317662fc2bab77ee87 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 03:01:30 +0000 Subject: [PATCH 051/258] Bump catboost from 1.0.6 to 1.1 Bumps [catboost](https://github.com/catboost/catboost) from 1.0.6 to 1.1. - [Release notes](https://github.com/catboost/catboost/releases) - [Changelog](https://github.com/catboost/catboost/blob/master/RELEASE.md) - [Commits](https://github.com/catboost/catboost/compare/v1.0.6...v1.1) --- updated-dependencies: - dependency-name: catboost dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements-freqai.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-freqai.txt b/requirements-freqai.txt index 9cdd431fe..cf0d2eb07 100644 --- a/requirements-freqai.txt +++ b/requirements-freqai.txt @@ -4,6 +4,6 @@ # Required for freqai scikit-learn==1.1.2 joblib==1.2.0 -catboost==1.0.6; platform_machine != 'aarch64' +catboost==1.1; platform_machine != 'aarch64' lightgbm==3.3.2 xgboost==1.6.2 From 0a7e4d6da5cfca90503c29d082153e243276c746 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 03:01:36 +0000 Subject: [PATCH 052/258] Bump mkdocs from 1.3.1 to 1.4.0 Bumps [mkdocs](https://github.com/mkdocs/mkdocs) from 1.3.1 to 1.4.0. - [Release notes](https://github.com/mkdocs/mkdocs/releases) - [Commits](https://github.com/mkdocs/mkdocs/compare/1.3.1...1.4.0) --- updated-dependencies: - dependency-name: mkdocs dependency-type: direct:production update-type: version-update:semver-minor ... 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 176947438..6e199f8b4 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,5 +1,5 @@ markdown==3.3.7 -mkdocs==1.3.1 +mkdocs==1.4.0 mkdocs-material==8.5.3 mdx_truly_sane_lists==1.3 pymdown-extensions==9.5 From 70d6c27e3efb6499b0870a3f0f05094d3cea04f2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 03:01:38 +0000 Subject: [PATCH 053/258] Bump pytest-mock from 3.8.2 to 3.9.0 Bumps [pytest-mock](https://github.com/pytest-dev/pytest-mock) from 3.8.2 to 3.9.0. - [Release notes](https://github.com/pytest-dev/pytest-mock/releases) - [Changelog](https://github.com/pytest-dev/pytest-mock/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pytest-dev/pytest-mock/compare/v3.8.2...v3.9.0) --- updated-dependencies: - dependency-name: pytest-mock dependency-type: direct:development update-type: version-update:semver-minor ... 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 d50105662..788df662d 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -13,7 +13,7 @@ pre-commit==2.20.0 pytest==7.1.3 pytest-asyncio==0.19.0 pytest-cov==3.0.0 -pytest-mock==3.8.2 +pytest-mock==3.9.0 pytest-random-order==1.0.4 isort==5.10.1 # For datetime mocking From 373132e135adedb4f919e30303f50751fb0d389c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 03:01:50 +0000 Subject: [PATCH 054/258] Bump ccxt from 1.93.98 to 1.95.2 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.93.98 to 1.95.2. - [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/1.93.98...1.95.2) --- 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 366b3c3fa..3cc830290 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ pandas==1.5.0; platform_machine != 'armv7l' pandas==1.4.3; platform_machine == 'armv7l' pandas-ta==0.3.14b -ccxt==1.93.98 +ccxt==1.95.2 # Pin cryptography for now due to rust build errors with piwheels cryptography==38.0.1 aiohttp==3.8.3 From 6defa62297302c7c2dea43363c46633c3cb0fa1d Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 04:35:31 +0000 Subject: [PATCH 055/258] Bump mkdocs-material from 8.5.3 to 8.5.6 Bumps [mkdocs-material](https://github.com/squidfunk/mkdocs-material) from 8.5.3 to 8.5.6. - [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/8.5.3...8.5.6) --- 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 6e199f8b4..b5548aeea 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,6 +1,6 @@ markdown==3.3.7 mkdocs==1.4.0 -mkdocs-material==8.5.3 +mkdocs-material==8.5.6 mdx_truly_sane_lists==1.3 pymdown-extensions==9.5 jinja2==3.1.2 From f3d4c56b3bead774805f57f76cc3c05805a57caf Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 04:35:34 +0000 Subject: [PATCH 056/258] Bump pytest-cov from 3.0.0 to 4.0.0 Bumps [pytest-cov](https://github.com/pytest-dev/pytest-cov) from 3.0.0 to 4.0.0. - [Release notes](https://github.com/pytest-dev/pytest-cov/releases) - [Changelog](https://github.com/pytest-dev/pytest-cov/blob/master/CHANGELOG.rst) - [Commits](https://github.com/pytest-dev/pytest-cov/compare/v3.0.0...v4.0.0) --- updated-dependencies: - dependency-name: pytest-cov 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 788df662d..fcb364930 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -12,7 +12,7 @@ mypy==0.971 pre-commit==2.20.0 pytest==7.1.3 pytest-asyncio==0.19.0 -pytest-cov==3.0.0 +pytest-cov==4.0.0 pytest-mock==3.9.0 pytest-random-order==1.0.4 isort==5.10.1 From 4cf4642a6caa4f06d558cacd48a5cf31337cdfcf Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 3 Oct 2022 06:39:20 +0200 Subject: [PATCH 057/258] Parametrize EMC test --- tests/rpc/test_rpc_emc.py | 38 +++++++------------------------------- 1 file changed, 7 insertions(+), 31 deletions(-) diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py index 84a2658a0..93ae829d5 100644 --- a/tests/rpc/test_rpc_emc.py +++ b/tests/rpc/test_rpc_emc.py @@ -188,15 +188,19 @@ async def test_emc_create_connection_success(default_conf, caplog, mocker): emc.shutdown() -async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker): +@pytest.mark.parametrize('host,port', [ + (_TEST_WS_HOST, -1), + ("10000.1241..2121/", _TEST_WS_PORT), +]) +async def test_emc_create_connection_invalid_url(default_conf, caplog, mocker, host, port): default_conf.update({ "external_message_consumer": { "enabled": True, "producers": [ { "name": "default", - "host": _TEST_WS_HOST, - "port": -1, + "host": host, + "port": port, "ws_token": _TEST_WS_TOKEN } ], @@ -219,34 +223,6 @@ async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker): emc.shutdown() -async def test_emc_create_connection_invalid_host(default_conf, caplog, mocker): - default_conf.update({ - "external_message_consumer": { - "enabled": True, - "producers": [ - { - "name": "default", - "host": "10000.1241..2121/", - "port": _TEST_WS_PORT, - "ws_token": _TEST_WS_TOKEN - } - ], - "wait_timeout": 60, - "ping_timeout": 60, - "sleep_timeout": 60 - } - }) - - dp = DataProvider(default_conf, None, None, None) - emc = ExternalMessageConsumer(default_conf, dp) - - try: - await asyncio.sleep(0.01) - 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": { From 3c789bca63420b35de233a8b4ec0fe7de03d024a Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 05:07:25 +0000 Subject: [PATCH 058/258] Bump pymdown-extensions from 9.5 to 9.6 Bumps [pymdown-extensions](https://github.com/facelessuser/pymdown-extensions) from 9.5 to 9.6. - [Release notes](https://github.com/facelessuser/pymdown-extensions/releases) - [Commits](https://github.com/facelessuser/pymdown-extensions/compare/9.5...9.6) --- updated-dependencies: - dependency-name: pymdown-extensions dependency-type: direct:production update-type: version-update:semver-minor ... 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 b5548aeea..4ff1780cf 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -2,5 +2,5 @@ markdown==3.3.7 mkdocs==1.4.0 mkdocs-material==8.5.6 mdx_truly_sane_lists==1.3 -pymdown-extensions==9.5 +pymdown-extensions==9.6 jinja2==3.1.2 From a78d6a05a6477d16c6a983befc2c3599b7537e61 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 3 Oct 2022 06:10:30 +0000 Subject: [PATCH 059/258] Bump mypy from 0.971 to 0.981 Bumps [mypy](https://github.com/python/mypy) from 0.971 to 0.981. - [Release notes](https://github.com/python/mypy/releases) - [Commits](https://github.com/python/mypy/compare/v0.971...v0.981) --- updated-dependencies: - dependency-name: mypy dependency-type: direct:development update-type: version-update:semver-minor ... 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 fcb364930..922f6980d 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -8,7 +8,7 @@ coveralls==3.3.1 flake8==5.0.4 flake8-tidy-imports==4.8.0 -mypy==0.971 +mypy==0.981 pre-commit==2.20.0 pytest==7.1.3 pytest-asyncio==0.19.0 From 6ecd92de4a8cdcccd364aa56098b3b4ba89f93de Mon Sep 17 00:00:00 2001 From: Robert Caulk Date: Mon, 3 Oct 2022 09:55:57 +0200 Subject: [PATCH 060/258] Allow updating without changing identifier --- freqtrade/freqai/data_drawer.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 0d3bdea29..603c477a0 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -294,6 +294,12 @@ class FreqaiDataDrawer: for return_str in rets: df[return_str].iloc[-1] = rets[return_str] + # this logic carries users between version without needing to + # change their identifier + if 'close_price' not in df.columns: + df['close_price'] = 0 + df['date_pred'] = 0 + df['close_price'].iloc[-1] = strat_df['close'].iloc[-1] df['date_pred'].iloc[-1] = strat_df['date'].iloc[-1] From c2d0eca9d896d70b62dfa436ac62615d02bc9325 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Mon, 3 Oct 2022 11:01:58 +0200 Subject: [PATCH 061/258] Remove backticks around FreqAI --- docs/freqai-configuration.md | 28 +++++++++--------- docs/freqai-developers.md | 8 +++--- docs/freqai-feature-engineering.md | 32 ++++++++++----------- docs/freqai-parameter-table.md | 16 +++++------ docs/freqai-running.md | 46 +++++++++++++++--------------- docs/freqai.md | 26 ++++++++--------- 6 files changed, 78 insertions(+), 78 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index 683fc9b34..d24c60057 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -1,10 +1,10 @@ # Configuration -`FreqAI` is configured through the typical [Freqtrade config file](configuration.md) and the standard [Freqtrade strategy](strategy-customization.md). Examples of `FreqAI` config and strategy files can be found in `config_examples/config_freqai.example.json` and `freqtrade/templates/FreqaiExampleStrategy.py`, respectively. +FreqAI is configured through the typical [Freqtrade config file](configuration.md) and the standard [Freqtrade strategy](strategy-customization.md). Examples of FreqAI config and strategy files can be found in `config_examples/config_freqai.example.json` and `freqtrade/templates/FreqaiExampleStrategy.py`, respectively. ## Setting up the configuration file - Although there are plenty of additional parameters to choose from, as highlighted in the [parameter table](freqai-parameter-table.md#parameter-table), a `FreqAI` config must at minimum include the following parameters (the parameter values are only examples): + Although there are plenty of additional parameters to choose from, as highlighted in the [parameter table](freqai-parameter-table.md#parameter-table), a FreqAI config must at minimum include the following parameters (the parameter values are only examples): ```json "freqai": { @@ -35,9 +35,9 @@ A full example config is available in `config_examples/config_freqai.example.json`. -## Building a `FreqAI` strategy +## Building a FreqAI strategy -The `FreqAI` strategy requires including the following lines of code in the standard [Freqtrade strategy](strategy-customization.md): +The FreqAI strategy requires including the following lines of code in the standard [Freqtrade strategy](strategy-customization.md): ```python # user should define the maximum startup candle count (the largest number of candles @@ -129,7 +129,7 @@ Notice also the location of the labels under `if set_generalized_indicators:` at The `self.freqai.start()` function cannot be called outside the `populate_indicators()`. !!! Note - Features **must** be defined in `populate_any_indicators()`. Defining `FreqAI` features in `populate_indicators()` + Features **must** be defined in `populate_any_indicators()`. Defining FreqAI features in `populate_indicators()` will cause the algorithm to fail in live/dry mode. In order to add generalized features that are not associated with a specific pair or timeframe, the following structure inside `populate_any_indicators()` should be used (as exemplified in `freqtrade/templates/FreqaiExampleStrategy.py`): @@ -166,15 +166,15 @@ Below are the values you can expect to include/use inside a typical strategy dat | 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*`). For example, to predict the close price 40 candles into the future, you would set `df['&-s_close'] = df['close'].shift(-self.freqai_info["feature_parameters"]["label_period_candles"])` with `"label_period_candles": 40` in the config. `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['&*']` | Any dataframe column prepended with `&` in `populate_any_indicators()` is treated as a training target (label) inside FreqAI (typically following the naming convention `&-s*`). For example, to predict the close price 40 candles into the future, you would set `df['&-s_close'] = df['close'].shift(-self.freqai_info["feature_parameters"]["label_period_candles"])` with `"label_period_candles": 40` in the config. 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 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` and explained [here](#creating-a-dynamic-target-threshold) 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 -2 and 2, which lets you know if the prediction is trustworthy or not. `do_predict==1` means that the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di)) of the input data point is above the threshold defined in the config, `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, see details [here](freqai-feature-engineering.md#identifying-outliers-using-a-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, or vice versa, 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`. As with the SVM, if `use_DBSCAN_to_remove_outliers` is active, DBSCAN (see details [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan)) may also detect outliers and subtract 1 from `do_predict`. Hence, if both the SVM and DBSCAN are active and identify a datapoint that was above the DI threshold as an outlier, the result will be `do_predict==-2`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`.
**Datatype:** Integer between -2 and 2. -| `df['DI_values']` | Dissimilarity Index (DI) values are proxies for 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. See details about the DI [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di).
**Datatype:** Float. -| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, you 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](freqai-feature-engineering.md).
**Note:** Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features are easily engineered using the multiplictative functionality of, e.g., `include_shifted_candles` and `include_timeframes` as described in the [parameter table](freqai-parameter-table.md)), these features are removed from the dataframe that is returned from `FreqAI` to the strategy. To keep a particular type of feature for plotting purposes, you would prepend it with `%%`.
**Datatype:** Depends on the output of the model. +| `df['do_predict']` | Indication of an outlier data point. The return value is integer between -2 and 2, which lets you know if the prediction is trustworthy or not. `do_predict==1` means that the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di)) of the input data point is above the threshold defined in the config, 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, see details [here](freqai-feature-engineering.md#identifying-outliers-using-a-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, or vice versa, 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`. As with the SVM, if `use_DBSCAN_to_remove_outliers` is active, DBSCAN (see details [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan)) may also detect outliers and subtract 1 from `do_predict`. Hence, if both the SVM and DBSCAN are active and identify a datapoint that was above the DI threshold as an outlier, the result will be `do_predict==-2`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`.
**Datatype:** Integer between -2 and 2. +| `df['DI_values']` | Dissimilarity Index (DI) values are proxies for 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. See details about the DI [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di).
**Datatype:** Float. +| `df['%*']` | Any dataframe column prepended with `%` in `populate_any_indicators()` is treated as a training feature. For example, you 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](freqai-feature-engineering.md).
**Note:** Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features are easily engineered using the multiplictative functionality of, e.g., `include_shifted_candles` and `include_timeframes` as described in the [parameter table](freqai-parameter-table.md)), these features are removed from the dataframe that is returned from FreqAI to the strategy. To keep a particular type of feature for plotting purposes, you would prepend it with `%%`.
**Datatype:** Depends on the output of the model. ## Setting the `startup_candle_count` -The `startup_candle_count` in the `FreqAI` strategy needs to be set up in the same way as in the standard 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 the `dataprovider`, to avoid any NaNs at the beginning of the first training. You can easily set this value by identifying the longest period (in candle units) which is passed to the indicator creation functions (e.g., Ta-Lib functions). In the presented example, `startup_candle_count` is 20 since this is the maximum value in `indicators_periods_candles`. +The `startup_candle_count` in the FreqAI strategy needs to be set up in the same way as in the standard 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 the `dataprovider`, to avoid any NaNs at the beginning of the first training. You can easily set this value by identifying the longest period (in candle units) which is passed to the indicator creation functions (e.g., Ta-Lib functions). In the presented example, `startup_candle_count` is 20 since this is the maximum value in `indicators_periods_candles`. !!! Note There are instances where the Ta-Lib functions actually require more data than just the passed `period` or else the feature dataset gets populated with NaNs. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Hence, it is typically safest to multiply the expected `startup_candle_count` by 2. Look out for this log message to confirm that the data is clean: @@ -185,7 +185,7 @@ The `startup_candle_count` in the `FreqAI` strategy needs to be set up in the sa ## Creating a dynamic target threshold -Deciding when to enter or exit a trade can be done in a dynamic way to reflect current market conditions. `FreqAI` allows you to return additional information from the training of a model (more info [here](freqai-feature-engineering.md#returning-additional-info-from-training)). For example, the `&*_std/mean` return values describe the statistical distribution of the target/label *during the most recent training*. Comparing a given prediction to these values allows you to know the rarity of the prediction. In `templates/FreqaiExampleStrategy.py`, the `target_roi` and `sell_roi` are defined to be 1.25 z-scores away from the mean which causes predictions that are closer to the mean to be filtered out. +Deciding when to enter or exit a trade can be done in a dynamic way to reflect current market conditions. FreqAI allows you to return additional information from the training of a model (more info [here](freqai-feature-engineering.md#returning-additional-info-from-training)). For example, the `&*_std/mean` return values describe the statistical distribution of the target/label *during the most recent training*. Comparing a given prediction to these values allows you to know the rarity of the prediction. In `templates/FreqaiExampleStrategy.py`, the `target_roi` and `sell_roi` are defined to be 1.25 z-scores away from the mean which causes predictions that are closer to the mean to be filtered out. ```python dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25 @@ -200,15 +200,15 @@ To consider the population of *historical predictions* for creating the dynamic } ``` -If this value is set, `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 you stop and restart a model with the same `identifier`. +If this value is set, 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 you stop and restart a model with the same `identifier`. ## Using different prediction models -`FreqAI` has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `Catboost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. However, it is possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. +FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `Catboost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. However, it is possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. ### Setting classifier targets -`FreqAI` includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example: +FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example: ```python df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') diff --git a/docs/freqai-developers.md b/docs/freqai-developers.md index 9794e0efa..37f4543b7 100644 --- a/docs/freqai-developers.md +++ b/docs/freqai-developers.md @@ -2,13 +2,13 @@ ## Project architecture -The architecture and functions of `FreqAI` are generalized to encourages development of unique features, functions, models, etc. +The architecture and functions of FreqAI are generalized to encourages development of unique features, functions, models, etc. The class structure and a detailed algorithmic overview is depicted in the following diagram: ![image](assets/freqai_algorithm-diagram.jpg) -As shown, there are three distinct objects comprising `FreqAI`: +As shown, there are three distinct objects comprising FreqAI: * **IFreqaiModel** - A singular persistent object containing all the necessary logic to collect, store, and 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. @@ -18,7 +18,7 @@ There are a variety of built-in [prediction models](freqai-configuration.md#usin ## Data handling -`FreqAI` aims to organize model files, prediction data, and meta data in a way that simplifies post-processing and enhances crash resilience by automatic data reloading. The data is saved in a file structure,`user_data_dir/models/`, which contains all the data associated with the trainings and backtests. The `FreqaiDataKitchen()` relies heavily on the file structure for proper training and inferencing and should therefore not be manually modified. +FreqAI aims to organize model files, prediction data, and meta data in a way that simplifies post-processing and enhances crash resilience by automatic data reloading. The data is saved in a file structure,`user_data_dir/models/`, which contains all the data associated with the trainings and backtests. The `FreqaiDataKitchen()` relies heavily on the file structure for proper training and inferencing and should therefore not be manually modified. ### File structure @@ -27,7 +27,7 @@ The file structure is automatically generated based on the model `identifier` se | Structure | Description | |-----------|-------------| | `config_*.json` | A copy of the model specific configuration file. | -| `historic_predictions.pkl` | A file containing all historic predictions generated during the lifetime of the `identifier` model during live deployment. `historic_predictions.pkl` is used to reload the model after a crash or a config change. A backup file is always held in case of corruption on the main file.`FreqAI`**automatically** detects corruption and replaces the corrupted file with the backup. | +| `historic_predictions.pkl` | A file containing all historic predictions generated during the lifetime of the `identifier` model during live deployment. `historic_predictions.pkl` is used to reload the model after a crash or a config change. A backup file is always held in case of corruption on the main file. FreqAI **automatically** detects corruption and replaces the corrupted file with the backup. | | `pair_dictionary.json` | A file containing the training queue as well as the on disk location of the most recently trained model. | | `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/min, expected training feature list, etc.
diff --git a/docs/freqai-feature-engineering.md b/docs/freqai-feature-engineering.md index bd700bbf7..b7c23aa60 100644 --- a/docs/freqai-feature-engineering.md +++ b/docs/freqai-feature-engineering.md @@ -4,7 +4,7 @@ Low level feature engineering is performed in the user strategy within a function called `populate_any_indicators()`. That function sets the `base features` such as, `RSI`, `MFI`, `EMA`, `SMA`, time of day, volume, etc. The `base features` can be custom indicators or they can be imported from any technical-analysis library that you can find. One important syntax rule is that all `base features` string names are prepended with `%`, while labels/targets are prepended with `&`. -Meanwhile, high level feature engineering is handled within `"feature_parameters":{}` in the `FreqAI` config. Within this file, it is possible to decide large scale feature expansions on top of the `base_features` such as "including correlated pairs" or "including informative timeframes" or even "including recent candles." +Meanwhile, high level feature engineering is handled within `"feature_parameters":{}` in the FreqAI config. Within this file, it is possible to decide large scale feature expansions on top of the `base_features` such as "including correlated pairs" or "including informative timeframes" or even "including recent candles." It is advisable to start from the template `populate_any_indicators()` in the source provided example strategy (found in `templates/FreqaiExampleStrategy.py`) to ensure that the feature definitions are following the correct conventions. Here is an example of how to set the indicators and labels in the strategy: @@ -122,7 +122,7 @@ The `include_timeframes` in the config above are the timeframes (`tf`) of each c You can ask for each of the defined features to be included also for 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` in the presented example). -`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. +`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` $= 3 * 3 * 3 * 2 * 2 = 108$. @@ -131,7 +131,7 @@ In total, the number of features the user of the presented example strat has cre Important metrics can be returned to the strategy at the end of each model training by assigning them to `dk.data['extra_returns_per_train']['my_new_value'] = XYZ` inside the custom prediction model class. -`FreqAI` takes the `my_new_value` assigned in this dictionary and expands it to fit the dataframe that is returned to the strategy. You can then use the returned metrics in your strategy through `dataframe['my_new_value']`. An example of how return values can be used in `FreqAI` are the `&*_mean` and `&*_std` values that are used to [created a dynamic target threshold](freqai-configuration.md#creating-a-dynamic-target-threshold). +FreqAI takes the `my_new_value` assigned in this dictionary and expands it to fit the dataframe that is returned to the strategy. You can then use the returned metrics in your strategy through `dataframe['my_new_value']`. An example of how return values can be used in FreqAI are the `&*_mean` and `&*_std` values that are used to [created a dynamic target threshold](freqai-configuration.md#creating-a-dynamic-target-threshold). Another example, where the user wants to use live metrics from the trade database, is shown below: @@ -141,15 +141,15 @@ Another example, where the user wants to use live metrics from the trade databas } ``` -You need 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, the pre-set values are what will be returned. +You need 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, the pre-set values are what will be returned. ## Feature normalization -`FreqAI` is strict when it comes to data normalization. The train features, $X^{train}$, are always normalized to [-1, 1] using a shifted min-max normalization: +FreqAI is strict when it comes to data normalization. The train features, $X^{train}$, are always normalized to [-1, 1] using a shifted min-max normalization: $$X^{train}_{norm} = 2 * \frac{X^{train} - X^{train}.min()}{X^{train}.max() - X^{train}.min()} - 1$$ -All other data (test data and unseen prediction data in dry/live/backtest) is always automatically normalized to the training feature space according to industry standards. `FreqAI` stores all the metadata required to ensure that test and 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. +All other data (test data and unseen prediction data in dry/live/backtest) is always automatically normalized to the training feature space according to industry standards. FreqAI stores all the metadata required to ensure that test and 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. ## Data dimensionality reduction with Principal Component Analysis @@ -169,17 +169,17 @@ This will perform PCA on the features and reduce their dimensionality so that th The `inlier_metric` is a metric aimed at quantifying how similar a the features of a data point are to the most recent historic data points. -You define the lookback window by setting `inlier_metric_window` and `FreqAI` computes the distance between the present time point and each of the previous `inlier_metric_window` lookback points. A Weibull function is fit to each of the lookback distributions and its cumulative distribution function (CDF) is used to produce a quantile for each lookback point. The `inlier_metric` is then computed for each time point as the average of the corresponding lookback quantiles. The figure below explains the concept for an `inlier_metric_window` of 5. +You define the lookback window by setting `inlier_metric_window` and FreqAI computes the distance between the present time point and each of the previous `inlier_metric_window` lookback points. A Weibull function is fit to each of the lookback distributions and its cumulative distribution function (CDF) is used to produce a quantile for each lookback point. The `inlier_metric` is then computed for each time point as the average of the corresponding lookback quantiles. The figure below explains the concept for an `inlier_metric_window` of 5. ![inlier-metric](assets/freqai_inlier-metric.jpg) -`FreqAI` adds the `inlier_metric` to the training features and hence gives the model access to a novel type of temporal information. +FreqAI adds the `inlier_metric` to the training features and hence gives the model access to a novel type of temporal information. This function does **not** remove outliers from the data set. ## Weighting features for temporal importance -`FreqAI` allows you to set a `weight_factor` to weight recent data more strongly than past data via an exponential function: +FreqAI allows you to set a `weight_factor` to weight recent data more strongly than past data via an exponential function: $$ W_i = \exp(\frac{-i}{\alpha*n}) $$ @@ -189,13 +189,13 @@ where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. B ## Outlier detection -Equity and crypto markets suffer from a high level of non-patterned noise in the form of outlier data points. `FreqAI` implements a variety of methods to identify such outliers and hence mitigate risk. +Equity and crypto markets suffer from a high level of non-patterned noise in the form of outlier data points. FreqAI implements a variety of methods to identify such outliers and hence mitigate risk. ### Identifying outliers with the Dissimilarity Index (DI) The Dissimilarity Index (DI) aims to quantify the uncertainty associated with each prediction made by the model. -You can tell `FreqAI` to remove outlier data points from the training/test data sets using the DI by including the following statement in the config: +You can tell FreqAI to remove outlier data points from the training/test data sets using the DI by including the following statement in the config: ```json "freqai": { @@ -205,7 +205,7 @@ You can tell `FreqAI` to remove outlier data points from the training/test data } ``` - 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: + 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: $$ d_{ab} = \sqrt{\sum_{j=1}^p(X_{a,j}-X_{b,j})^2} $$ @@ -229,7 +229,7 @@ Below is a figure that describes the DI for a 3D data set. ### Identifying outliers using a Support Vector Machine (SVM) -You can tell `FreqAI` to remove outlier data points from the training/test data sets using a Support Vector Machine (SVM) by including the following statement in the config: +You can tell FreqAI to remove outlier data points from the training/test data sets using a Support Vector Machine (SVM) by including the following statement in the config: ```json "freqai": { @@ -241,7 +241,7 @@ You can tell `FreqAI` to remove outlier data points from the training/test data The SVM will be trained on the training data and any data point that the SVM deems to be beyond the feature space will be removed. -`FreqAI` uses `sklearn.linear_model.SGDOneClassSVM` (details are available on scikit-learn's webpage [here](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html) (external website)) and you can elect to provide additional parameters for the SVM, such as `shuffle`, and `nu`. +FreqAI uses `sklearn.linear_model.SGDOneClassSVM` (details are available on scikit-learn's webpage [here](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html) (external website)) and you can elect to provide additional parameters for the SVM, such as `shuffle`, and `nu`. 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. @@ -249,7 +249,7 @@ The parameter `nu`, *very* broadly, is the amount of data points that should be ### Identifying outliers with DBSCAN -You 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: +You 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": { @@ -265,4 +265,4 @@ 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) (external website)) with `min_samples` ($N$) taken as 1/4 of the no. of time points (candles) in the feature set. `eps` ($\varepsilon$) is computed automatically 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. +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) (external website)) with `min_samples` ($N$) taken as 1/4 of the no. of time points (candles) in the feature set. `eps` ($\varepsilon$) is computed automatically 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-parameter-table.md b/docs/freqai-parameter-table.md index 2ec8fac30..38d7ece94 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -1,13 +1,13 @@ # Parameter table -The table below will list all configuration parameters available for `FreqAI`. Some of the parameters are exemplified in `config_examples/config_freqai.example.json`. +The table below will list all configuration parameters available for FreqAI. Some of the parameters are exemplified in `config_examples/config_freqai.example.json`. Mandatory parameters are marked as **Required** and have to be set in one of the suggested ways. | Parameter | Description | |------------|-------------| | | **General configuration parameters** -| `freqai` | **Required.**
The parent dictionary containing all the parameters for controlling `FreqAI`.
**Datatype:** Dictionary. +| `freqai` | **Required.**
The parent dictionary containing all the parameters for controlling FreqAI.
**Datatype:** Dictionary. | `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 `train_period_days` window defined above, and retraining the model during backtesting (more info [here](freqai-running.md#backtesting)). This can be fractional days, but beware that the provided `timerange` will be divided by this number to yield the number of trainings necessary to complete the backtest.
**Datatype:** Float. | `identifier` | **Required.**
A unique ID for the current model. If models are saved to disk, the `identifier` allows for reloading specific pre-trained models/data.
**Datatype:** String. @@ -21,11 +21,11 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | | **Feature parameters** | `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](freqai-feature-engineering.md).
**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 indicators dataset.
**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](freqai-feature-engineering.md)) will be created for each correlated coin. The correlated coins features are added to the base indicators dataset.
**Datatype:** List of assets (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](freqai-feature-engineering.md)) will be created for each correlated coin. The correlated coins features are added to the base indicators dataset.
**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). You can create custom labels and choose whether to make use of this parameter or not.
**Datatype:** Positive integer. -| `include_shifted_candles` | Add features from previous candles to subsequent candles with the intent of adding historical information. If used, `FreqAI` will duplicate and shift all features from the `include_shifted_candles` previous candles so that the information is available for the subsequent candle.
**Datatype:** Positive integer. +| `include_shifted_candles` | Add features from previous candles to subsequent candles with the intent of adding historical information. If used, FreqAI will duplicate and shift all features from the `include_shifted_candles` previous candles so that the information is available for the subsequent candle.
**Datatype:** Positive integer. | `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)).
**Datatype:** Positive float (typically < 1). -| `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. `FreqAI` uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN.
**Datatype:** Positive integer. +| `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN.
**Datatype:** Positive integer. | `indicator_periods_candles` | Time periods to calculate indicators for. The indicators are added to the base indicator dataset.
**Datatype:** List of positive integers. | `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.
Default: `False`. | `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features.
**Datatype:** Integer.
Default: `0`. @@ -33,9 +33,9 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training dataset, as well as from incoming data points. See details about how it works [here](freqai-feature-engineering.md#identifying-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](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary. | `use_DBSCAN_to_remove_outliers` | Cluster data using the DBSCAN algorithm to identify and remove outliers from training and prediction data. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan).
**Datatype:** Boolean. -| `inlier_metric_window` | If set, `FreqAI` adds an `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`, i.e., the number of previous time points to compare the current candle to. Details of how the `inlier_metric` is computed can be found [here](freqai-feature-engineering.md#inlier-metric).
**Datatype:** Integer.
Default: `0`. -| `noise_standard_deviation` | If set, `FreqAI` adds noise to the training features with the aim of preventing overfitting. `FreqAI` generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. `noise_standard_deviation` should be kept relative to the normalized space, i.e., between -1 and 1. In other words, since data in `FreqAI` is always normalized to be between -1 and 1, `noise_standard_deviation: 0.05` would result in 32% of the data being randomly increased/decreased by more than 2.5% (i.e., the percent of data falling within the first standard deviation).
**Datatype:** Integer.
Default: `0`. -| `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. 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, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset.
**Datatype:** Float.
Default: `30`. +| `inlier_metric_window` | If set, FreqAI adds an `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`, i.e., the number of previous time points to compare the current candle to. Details of how the `inlier_metric` is computed can be found [here](freqai-feature-engineering.md#inlier-metric).
**Datatype:** Integer.
Default: `0`. +| `noise_standard_deviation` | If set, FreqAI adds noise to the training features with the aim of preventing overfitting. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. `noise_standard_deviation` should be kept relative to the normalized space, i.e., between -1 and 1. In other words, since data in FreqAI is always normalized to be between -1 and 1, `noise_standard_deviation: 0.05` would result in 32% of the data being randomly increased/decreased by more than 2.5% (i.e., the percent of data falling within the first standard deviation).
**Datatype:** Integer.
Default: `0`. +| `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. 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, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset.
**Datatype:** Float.
Default: `30`. | `reverse_train_test_order` | Split the feature dataset (see below) and use the latest data split for training 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, you should be careful to understand the unorthodox nature of this parameter before employing it.
**Datatype:** Boolean.
Default: `False` (no reversal). | | **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. diff --git a/docs/freqai-running.md b/docs/freqai-running.md index 6299a80f3..b8994aed9 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -1,18 +1,18 @@ -# Running `FreqAI` +# Running FreqAI -There are two ways to train and deploy an adaptive machine learning model - live deployment and historical backtesting. In both cases, `FreqAI` runs/simulates periodic retraining of models as shown in the following figure: +There are two ways to train and deploy an adaptive machine learning model - live deployment and historical backtesting. In both cases, FreqAI runs/simulates periodic retraining of models as shown in the following figure: ![freqai-window](assets/freqai_moving-window.jpg) ## Live deployments -`FreqAI` can be run dry/live using the following command: +FreqAI can be run dry/live using the following command: ```bash freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor ``` -When launched, `FreqAI` will start training a new model, with a new `identifier`, based on the config 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 you do not want `FreqAI` to retrain new models as often as possible, you can set `live_retrain_hours` to tell `FreqAI` to wait at least that number of hours before training a new model. Additionally, you can set `expired_hours` to tell `FreqAI` to avoid making predictions on models that are older than that number of hours. +When launched, FreqAI will start training a new model, with a new `identifier`, based on the config 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 you do not want FreqAI to retrain new models as often as possible, you can set `live_retrain_hours` to tell FreqAI to wait at least that number of hours before training a new model. Additionally, you can set `expired_hours` to tell FreqAI to avoid making predictions on models that are older than that number of hours. Trained models are by default saved to disk to allow for reuse during backtesting or after a crash. You can opt to [purge old models](#purging-old-model-data) to save disk space by setting `"purge_old_models": true` in the config. @@ -25,11 +25,11 @@ To start a dry/live run from a saved backtest model (or from a previously crashe } ``` -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. If a full `live_retrain_hours` has elapsed since the end of the loaded model, `FreqAI` will start training a new model. +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. If a full `live_retrain_hours` has elapsed since the end of the loaded model, FreqAI will start training a new model. ### Automatic data download -`FreqAI` automatically downloads the proper amount of data needed to ensure training of a model through the defined `train_period_days` and `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters). +FreqAI automatically downloads the proper amount of data needed to ensure training of a model through the defined `train_period_days` and `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters). ### Saving prediction data @@ -37,7 +37,7 @@ All predictions made during the lifetime of a specific `identifier` model are st ### Purging old model data -`FreqAI` stores new model files after each successful training. These files become obsolete as new models are generated to adapt to new market conditions. If you are planning to leave `FreqAI` running for extended periods of time with high frequency retraining, you should enable `purge_old_models` in the config: +FreqAI stores new model files after each successful training. These files become obsolete as new models are generated to adapt to new market conditions. If you are planning to leave FreqAI running for extended periods of time with high frequency retraining, you should enable `purge_old_models` in the config: ```json "freqai": { @@ -49,20 +49,20 @@ This will automatically purge all models older than the two most recently traine ## Backtesting -The `FreqAI` backtesting module can be executed with the following command: +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 ``` -If this command has never been executed with the existing config file, `FreqAI` will train a new model +If this command has never been executed with the existing config file, FreqAI will train a new model for each pair, for each backtesting window within the expanded `--timerange`. -Backtesting mode requires [downloading the necessary data](#downloading-data-to-cover-the-full-backtest-period) before deployment (unlike in dry/live mode where `FreqAI` handles the data downloading automatically). You 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 set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-size-of-the-sliding-training-window-and-backtesting-duration). +Backtesting mode requires [downloading the necessary data](#downloading-data-to-cover-the-full-backtest-period) before deployment (unlike in dry/live mode where FreqAI handles the data downloading automatically). You 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 set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-size-of-the-sliding-training-window-and-backtesting-duration). !!! Note "Model reuse" Once the training is completed, you 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 + FreqAI will find the trained models and load them instead of spending time training. This is useful if you want to tweak (or even hyperopt) buy and sell criteria inside the strategy. If you *want* to retrain a new model with the same config file, you should simply change the `identifier`. This way, you can return to using any model you wish by simply specifying the `identifier`. @@ -71,31 +71,31 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to- ### Saving prediction data -To allow for tweaking your strategy (**not** the features!), `FreqAI` will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria. +To allow for tweaking your strategy (**not** the features!), FreqAI will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria. An additional directory called `predictions`, which contains all the predictions stored in `hdf` format, will be created in the `unique-id` folder. -To change your **features**, you **must** set a new `identifier` in the config to signal to `FreqAI` to train new models. +To change your **features**, you **must** set a new `identifier` in the config to signal to FreqAI to train new models. To save the models generated during a particular backtest so that you can start a live deployment from one of them instead of training a new model, you must set `save_backtest_models` to `True` in the config. ### Downloading data to cover the full backtest period -For live/dry deployments, `FreqAI` will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range. +For live/dry deployments, FreqAI will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range. As an example, to backtest the `--timerange 20210501-20210701` using the [example config](freqai-configuration.md#setting-up-the-configuration-file) which sets `train_period_days` to 30, together with `startup_candle_count: 40` on a maximum `include_timeframes` of 1h, the start date for the downloaded data needs to be `20210501` - 30 days - 40 * 1h / 24 hours = 20210330 (31.7 days earlier than the start of the desired training time range). ### Deciding the size of the sliding training window and backtesting duration The backtesting time range is defined 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](freqai-configuration.md#setting-up-the-configuration-file) (found in `config_examples/config_freqai.example.json`), the user is asking `FreqAI` to use a training period of 30 days and backtest on the subsequent 7 days. 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`. This means that if you set `--timerange 20210501-20210701`, `FreqAI` will have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). +a float to indicate sub-daily retraining in live/dry mode). In the presented [example config](freqai-configuration.md#setting-up-the-configuration-file) (found in `config_examples/config_freqai.example.json`), the user is asking FreqAI to use a training period of 30 days and backtest on the subsequent 7 days. 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`. This means that if you set `--timerange 20210501-20210701`, FreqAI will have trained 8 separate models at the end of `--timerange` (because the full range comprises 8 weeks). !!! Note - Although fractional `backtest_period_days` is allowed, you 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, by setting a `--timerange` of 10 days, and 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 train constantly. In this case, backtesting would take the exact same amount of time as a dry run. + Although fractional `backtest_period_days` is allowed, you 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, by setting a `--timerange` of 10 days, and 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 train constantly. In this case, backtesting would take the exact same amount of time as a dry run. ## 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 you are 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. You 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: +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 you are 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. You 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": { @@ -107,11 +107,11 @@ In the presented example config, the user will only allow predictions on models ## Controlling the model learning process -Model training parameters are unique to the selected machine learning library. `FreqAI` allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement. +Model training parameters are unique to the selected machine learning library. FreqAI allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement. Data split parameters are defined in `data_split_parameters` which can be any parameters associated with Scikit-learn's `train_test_split()` function. `train_test_split()` has a parameters called `shuffle` which allows to shuffle the data or keep it unshuffled. This is particularly useful to avoid biasing training with temporally auto-correlated data. More details about these parameters can be found the [Scikit-learn website](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). -The `FreqAI` specific parameter `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented [example config](freqai-configuration.md#setting-up-the-configuration-file), the user is asking for `labels` that are 24 candles in the future. +The FreqAI specific parameter `label_period_candles` defines the offset (number of candles into the future) used for the `labels`. In the presented [example config](freqai-configuration.md#setting-up-the-configuration-file), the user is asking for `labels` that are 24 candles in the future. ## Continual learning @@ -125,15 +125,15 @@ You can hyperopt using the same command as for [typical Freqtrade hyperopt](hype freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --timerange 20220428-20220507 ``` -`hyperopt` requires you to have the data pre-downloaded in the same fashion as if you were doing [backtesting](#backtesting). In addition, you must consider some restrictions when trying to hyperopt `FreqAI` strategies: +`hyperopt` requires you to have the data pre-downloaded in the same fashion as if you were doing [backtesting](#backtesting). In addition, you must consider some restrictions when trying to hyperopt FreqAI strategies: -- The `--analyze-per-epoch` hyperopt parameter is not compatible with `FreqAI`. +- The `--analyze-per-epoch` hyperopt parameter is not compatible with FreqAI. - It's not possible to hyperopt indicators in the `populate_any_indicators()` function. This means that you 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 instructions also apply to hyperopt. -The best method for combining hyperopt and `FreqAI` is to focus on hyperopting entry/exit thresholds/criteria. You need to focus on hyperopting parameters that are not used in your features. For example, you should not try to hyperopt rolling window lengths in the feature creation, or any part of the `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. +The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. You need to focus on hyperopting parameters that are not used in your features. For example, you should not try to hyperopt rolling window lengths in the feature creation, or any part of the 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 threshold for the [Dissimilarity Index (DI)](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di) `DI_values` beyond which we consider data points as outliers: +A good example of a hyperoptable parameter in FreqAI is a threshold for the [Dissimilarity Index (DI)](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di) `DI_values` beyond which we consider data points as outliers: ```python di_max = IntParameter(low=1, high=20, default=10, space='buy', optimize=True, load=True) diff --git a/docs/freqai.md b/docs/freqai.md index 5ab019ca7..b7f0fe21a 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -1,10 +1,10 @@ ![freqai-logo](assets/freqai_doc_logo.svg) -# `FreqAI` +# FreqAI ## Introduction -`FreqAI` is a software designed to automate a variety of tasks associated with training a predictive machine learning model to generate market forecasts given a set of input features. +FreqAI is a software designed to automate a variety of tasks associated with training a predictive machine learning model to generate market forecasts given a set of input features. Features include: @@ -23,7 +23,7 @@ Features include: ## Quick start -The easiest way to quickly test `FreqAI` is to run it in dry mode with the following command: +The easiest way to quickly test FreqAI is to run it in dry mode with the following command: ```bash freqtrade trade --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates @@ -37,7 +37,7 @@ An example strategy, prediction model, and config to use as a starting points ca ## General approach -You provide `FreqAI` with a set of custom *base indicators* (the same way as in a [typical Freqtrade strategy](strategy-customization.md)) as well as target values (*labels*). For each pair in the whitelist, `FreqAI` trains a model to predict the target values based on the input of custom indicators. The models are then consistently retrained, with a predetermined frequency, to adapt to market conditions. `FreqAI` offers the ability to both backtest strategies (emulating reality with periodic retraining on historic data) and deploy dry/live runs. In dry/live conditions, `FreqAI` can be set to constant retraining in a background thread to keep models as up to date as possible. +You provide FreqAI with a set of custom *base indicators* (the same way as in a [typical Freqtrade strategy](strategy-customization.md)) as well as target values (*labels*). For each pair in the whitelist, FreqAI trains a model to predict the target values based on the input of custom indicators. The models are then consistently retrained, with a predetermined frequency, to adapt to market conditions. FreqAI offers the ability to both backtest strategies (emulating reality with periodic retraining on historic data) and deploy dry/live runs. In dry/live conditions, FreqAI can be set to constant retraining in a background thread to keep models as up to date as possible. An overview of the algorithm, explaining the data processing pipeline and model usage, is shown below. @@ -45,11 +45,11 @@ An overview of the algorithm, explaining the data processing pipeline and model ### Important machine learning vocabulary -**Features** - the parameters, based on historic data, on which a model is trained. All features for a single candle are stored as a vector. In `FreqAI`, you build a feature data set from anything you can construct in the strategy. +**Features** - the parameters, based on historic data, on which a model is trained. All features for a single candle are stored as a vector. In FreqAI, you build a feature data set from anything you can construct in the strategy. **Labels** - the target values that the model is trained toward. Each feature vector is associated with a single label that is defined by you within the strategy. These labels intentionally look into the future and are what you are training the model to be able to predict. -**Training** - the process of "teaching" the model to match the feature sets to the associated labels. Different types of models "learn" in different ways which means that one might be better than another for a specific application. More information about the different models that are already implemented in `FreqAI` can be found [here](freqai-configuration.md#using-different-prediction-models). +**Training** - the process of "teaching" the model to match the feature sets to the associated labels. Different types of models "learn" in different ways which means that one might be better than another for a specific application. More information about the different models that are already implemented in FreqAI can be found [here](freqai-configuration.md#using-different-prediction-models). **Train data** - a subset of the feature data set that is fed to the model during training to "teach" the model how to predict the targets. This data directly influences weight connections in the model. @@ -59,7 +59,7 @@ An overview of the algorithm, explaining the data processing pipeline and model ## Install prerequisites -The normal Freqtrade install process will ask if you wish to install `FreqAI` dependencies. You should reply "yes" to this question if you wish to use `FreqAI`. If you did not reply yes, you can manually install these dependencies after the install with: +The normal Freqtrade install process will ask if you wish to install FreqAI dependencies. You should reply "yes" to this question if you wish to use FreqAI. If you did not reply yes, you can manually install these dependencies after the install with: ``` bash pip install -r requirements-freqai.txt @@ -70,18 +70,18 @@ pip install -r requirements-freqai.txt ### Usage with docker -If you are using docker, 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. +If you are using docker, 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. ## 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). +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). ## Credits -`FreqAI` is developed by a group of individuals who all contribute specific skillsets to the project. +FreqAI is developed by a group of individuals who all contribute specific skillsets to the project. Conception and software development: Robert Caulk @robcaulk From 265795824b99fd997e5e21e6be2b3862f01fa461 Mon Sep 17 00:00:00 2001 From: Robert Caulk Date: Mon, 3 Oct 2022 11:58:22 +0200 Subject: [PATCH 062/258] make default type for close_price and date_pred np.nan --- freqtrade/freqai/data_drawer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 603c477a0..d6dbe8c6c 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -297,8 +297,8 @@ class FreqaiDataDrawer: # this logic carries users between version without needing to # change their identifier if 'close_price' not in df.columns: - df['close_price'] = 0 - df['date_pred'] = 0 + df['close_price'] = np.nan + df['date_pred'] = np.nan df['close_price'].iloc[-1] = strat_df['close'].iloc[-1] df['date_pred'].iloc[-1] = strat_df['date'].iloc[-1] From 3585742b43db7eddfb3cd05f580a763fa24c6bfd Mon Sep 17 00:00:00 2001 From: Robert Caulk Date: Mon, 3 Oct 2022 17:28:45 +0200 Subject: [PATCH 063/258] remove trailing whitespace --- 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 d6dbe8c6c..cde72bfb5 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -294,7 +294,7 @@ class FreqaiDataDrawer: for return_str in rets: df[return_str].iloc[-1] = rets[return_str] - # this logic carries users between version without needing to + # this logic carries users between version without needing to # change their identifier if 'close_price' not in df.columns: df['close_price'] = np.nan From ca22d857b7369c868214ffea456b322b159e7da2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 3 Oct 2022 18:09:53 +0200 Subject: [PATCH 064/258] Improve handling of trades that fail to cancel as they are closed --- freqtrade/freqtradebot.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 2b20e40fd..4ec9c34ce 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1444,9 +1444,14 @@ class FreqtradeBot(LoggingMixin): trade.close_profit = None trade.close_profit_abs = None # Set exit_reason for fill message + exit_reason_prev = trade.exit_reason trade.exit_reason = trade.exit_reason + f", {reason}" if trade.exit_reason else reason self.update_trade_state(trade, trade.open_order_id, co) - trade.exit_reason = None + # Order might be filled above in odd timing issues. + if co.get('status') in ('canceled', 'cancelled'): + trade.exit_reason = None + else: + trade.exit_reason = exit_reason_prev logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') cancelled = True From 7f475e37d7cf788b1ec822c405b7d367bd8c17e5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 3 Oct 2022 20:00:56 +0200 Subject: [PATCH 065/258] refactor refresh_latest_ohlcv --- freqtrade/exchange/exchange.py | 54 +++++++++++++++++++++------------- 1 file changed, 34 insertions(+), 20 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 5648d8716..aba149496 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1870,6 +1870,38 @@ class Exchange: return self._async_get_candle_history( pair, timeframe, since_ms=since_ms, candle_type=candle_type) + def _build_ohlcv_dl_jobs( + self, pair_list: ListPairsWithTimeframes, since_ms: Optional[int], + cache: bool) -> Tuple[List[Coroutine], List[Tuple[str, str, CandleType]]]: + """ + Build Coroutines to execute as part of refresh_latest_ohlcv + """ + input_coroutines = [] + cached_pairs = [] + for pair, timeframe, candle_type in set(pair_list): + if ( + timeframe not in self.timeframes + and candle_type in (CandleType.SPOT, CandleType.FUTURES) + ): + logger.warning( + f"Cannot download ({pair}, {timeframe}) combination as this timeframe is " + f"not available on {self.name}. Available timeframes are " + f"{', '.join(self.timeframes)}.") + continue + + if ((pair, timeframe, candle_type) not in self._klines or not cache + or self._now_is_time_to_refresh(pair, timeframe, candle_type)): + input_coroutines.append(self._build_coroutine( + pair, timeframe, candle_type=candle_type, since_ms=since_ms)) + + else: + logger.debug( + f"Using cached candle (OHLCV) data for {pair}, {timeframe}, {candle_type} ..." + ) + cached_pairs.append((pair, timeframe, candle_type)) + + return input_coroutines, cached_pairs + def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *, since_ms: Optional[int] = None, cache: bool = True, drop_incomplete: Optional[bool] = None @@ -1887,27 +1919,9 @@ class Exchange: """ logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list)) drop_incomplete = self._ohlcv_partial_candle if drop_incomplete is None else drop_incomplete - input_coroutines = [] - cached_pairs = [] - # Gather coroutines to run - for pair, timeframe, candle_type in set(pair_list): - if (timeframe not in self.timeframes - and candle_type in (CandleType.SPOT, CandleType.FUTURES)): - logger.warning( - f"Cannot download ({pair}, {timeframe}) combination as this timeframe is " - f"not available on {self.name}. Available timeframes are " - f"{', '.join(self.timeframes)}.") - continue - if ((pair, timeframe, candle_type) not in self._klines or not cache - or self._now_is_time_to_refresh(pair, timeframe, candle_type)): - input_coroutines.append(self._build_coroutine( - pair, timeframe, candle_type=candle_type, since_ms=since_ms)) - else: - logger.debug( - f"Using cached candle (OHLCV) data for {pair}, {timeframe}, {candle_type} ..." - ) - cached_pairs.append((pair, timeframe, candle_type)) + # Gather coroutines to run + input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache) results_df = {} # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling From 7f308c5186e76381ec76cbc82a0c568e1725aa87 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 06:42:04 +0200 Subject: [PATCH 066/258] Remove last occurance of timerange index --- tests/data/test_history.py | 2 +- tests/test_plotting.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/data/test_history.py b/tests/data/test_history.py index e7e3d4063..b985666cc 100644 --- a/tests/data/test_history.py +++ b/tests/data/test_history.py @@ -480,7 +480,7 @@ def test_validate_backtest_data(default_conf, mocker, caplog, testdatadir) -> No default_conf.update({'strategy': CURRENT_TEST_STRATEGY}) strategy = StrategyResolver.load_strategy(default_conf) - timerange = TimeRange('index', 'index', 200, 250) + timerange = TimeRange() data = strategy.advise_all_indicators( load_data( datadir=testdatadir, diff --git a/tests/test_plotting.py b/tests/test_plotting.py index 52e96e477..f13bdee13 100644 --- a/tests/test_plotting.py +++ b/tests/test_plotting.py @@ -63,7 +63,7 @@ def test_init_plotscript(default_conf, mocker, testdatadir): def test_add_indicators(default_conf, testdatadir, caplog): pair = "UNITTEST/BTC" - timerange = TimeRange(None, 'line', 0, -1000) + timerange = TimeRange() data = history.load_pair_history(pair=pair, timeframe='1m', datadir=testdatadir, timerange=timerange) From bc6729f724b4d8ef2f39d7b51c224c252a79bc41 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 06:53:35 +0200 Subject: [PATCH 067/258] Improve readability of "now_is_time_to_refresh" --- freqtrade/exchange/exchange.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index aba149496..b071c677b 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1962,10 +1962,8 @@ class Exchange: interval_in_sec = timeframe_to_seconds(timeframe) return not ( - (self._pairs_last_refresh_time.get( - (pair, timeframe, candle_type), - 0 - ) + interval_in_sec) >= arrow.utcnow().int_timestamp + (self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0) + + interval_in_sec) >= arrow.utcnow().int_timestamp ) @retrier_async From 016e438468162af803051964da58cde8051a195c Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 08:37:07 +0000 Subject: [PATCH 068/258] Calculate market-change in hyperopt closes #7532 --- freqtrade/optimize/hyperopt.py | 7 ++++++- tests/optimize/test_hyperopt.py | 7 +++++++ 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 162556705..9b16873bb 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -24,6 +24,7 @@ from pandas import DataFrame from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN, Config from freqtrade.data.converter import trim_dataframes from freqtrade.data.history import get_timerange +from freqtrade.data.metrics import calculate_market_change from freqtrade.enums import HyperoptState from freqtrade.exceptions import OperationalException from freqtrade.misc import deep_merge_dicts, file_dump_json, plural @@ -111,6 +112,7 @@ class Hyperopt: self.clean_hyperopt() + self.market_change = 0 self.num_epochs_saved = 0 self.current_best_epoch: Optional[Dict[str, Any]] = None @@ -357,7 +359,7 @@ class Hyperopt: strat_stats = generate_strategy_stats( self.pairlist, self.backtesting.strategy.get_strategy_name(), - backtesting_results, min_date, max_date, market_change=0 + backtesting_results, min_date, max_date, market_change=self.market_change ) results_explanation = HyperoptTools.format_results_explanation_string( strat_stats, self.config['stake_currency']) @@ -425,6 +427,9 @@ class Hyperopt: # Trim startup period from analyzed dataframe to get correct dates for output. trimmed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) self.min_date, self.max_date = get_timerange(trimmed) + if not self.market_change: + self.market_change = calculate_market_change(trimmed, 'close') + # Real trimming will happen as part of backtesting. return preprocessed diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index eaea8aee7..5666ebabc 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -297,6 +297,7 @@ def test_params_no_optimize_details(hyperopt) -> None: def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', @@ -530,6 +531,7 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -581,6 +583,7 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) mocker.patch( @@ -622,6 +625,7 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None: def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -663,6 +667,7 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -736,6 +741,7 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf, caplog) -> None: def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -778,6 +784,7 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None: dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') + mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5) mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) From eb8eebe49225c10d91566b09e4c987124493b9be Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 10:08:58 +0000 Subject: [PATCH 069/258] Reset open_order_id after trade cancel Part of #7526 --- freqtrade/freqtradebot.py | 6 ++++-- tests/test_freqtradebot.py | 1 + 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 4ec9c34ce..15398ca04 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1389,11 +1389,13 @@ class FreqtradeBot(LoggingMixin): reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}" else: self.update_trade_state(trade, trade.open_order_id, corder) + trade.open_order_id = None logger.info(f'{side} Order timeout for {trade}.') else: # update_trade_state (and subsequently recalc_trade_from_orders) will handle updates # to the trade object self.update_trade_state(trade, trade.open_order_id, corder) + trade.open_order_id = None logger.info(f'Partial {trade.entry_side} order timeout for {trade}.') reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}" @@ -1450,6 +1452,7 @@ class FreqtradeBot(LoggingMixin): # Order might be filled above in odd timing issues. if co.get('status') in ('canceled', 'cancelled'): trade.exit_reason = None + trade.open_order_id = None else: trade.exit_reason = exit_reason_prev @@ -1459,8 +1462,7 @@ class FreqtradeBot(LoggingMixin): reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') self.update_trade_state(trade, trade.open_order_id, order) - - self.wallets.update() + trade.open_order_id = None self._notify_exit_cancel( trade, diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index cdea772dc..c127e3850 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3178,6 +3178,7 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None: assert send_msg_mock.call_count == 1 assert trade.close_rate is None assert trade.exit_reason is None + assert trade.open_order_id is None send_msg_mock.reset_mock() From a6296be2f575c8630de1c5ea3f3cc237676a47c3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 10:27:04 +0000 Subject: [PATCH 070/258] Update market_change datatype --- 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 9b16873bb..d93bbbfc1 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -112,7 +112,7 @@ class Hyperopt: self.clean_hyperopt() - self.market_change = 0 + self.market_change = 0.0 self.num_epochs_saved = 0 self.current_best_epoch: Optional[Dict[str, Any]] = None From 68db0bc647338af421afb603c8345651799759ee Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 18:25:23 +0200 Subject: [PATCH 071/258] move check_exchange to exchange package --- freqtrade/configuration/__init__.py | 1 - freqtrade/configuration/configuration.py | 4 +- .../check_exchange.py | 0 tests/exchange/test_exchange_utils.py | 69 +++++++++++++++++++ tests/test_configuration.py | 63 +---------------- 5 files changed, 73 insertions(+), 64 deletions(-) rename freqtrade/{configuration => exchange}/check_exchange.py (100%) create mode 100644 tests/exchange/test_exchange_utils.py diff --git a/freqtrade/configuration/__init__.py b/freqtrade/configuration/__init__.py index 730a4e47f..dee42d535 100644 --- a/freqtrade/configuration/__init__.py +++ b/freqtrade/configuration/__init__.py @@ -1,6 +1,5 @@ # flake8: noqa: F401 -from freqtrade.configuration.check_exchange import check_exchange from freqtrade.configuration.config_setup import setup_utils_configuration from freqtrade.configuration.config_validation import validate_config_consistency from freqtrade.configuration.configuration import Configuration diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index 76105cc4d..5e6da4178 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -8,7 +8,6 @@ from pathlib import Path from typing import Any, Callable, Dict, List, Optional from freqtrade import constants -from freqtrade.configuration.check_exchange import check_exchange from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir from freqtrade.configuration.environment_vars import enironment_vars_to_dict @@ -100,6 +99,9 @@ class Configuration: self._process_freqai_options(config) + # Import check_exchange here to avoid import cycle problems + from freqtrade.exchange.check_exchange import check_exchange + # Check if the exchange set by the user is supported check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True)) diff --git a/freqtrade/configuration/check_exchange.py b/freqtrade/exchange/check_exchange.py similarity index 100% rename from freqtrade/configuration/check_exchange.py rename to freqtrade/exchange/check_exchange.py diff --git a/tests/exchange/test_exchange_utils.py b/tests/exchange/test_exchange_utils.py new file mode 100644 index 000000000..a454b37d0 --- /dev/null +++ b/tests/exchange/test_exchange_utils.py @@ -0,0 +1,69 @@ +# pragma pylint: disable=missing-docstring, protected-access, invalid-name + +import pytest + +from freqtrade.enums import RunMode +from freqtrade.exceptions import OperationalException +from freqtrade.exchange.check_exchange import check_exchange +from tests.conftest import log_has_re + + +def test_check_exchange(default_conf, caplog) -> None: + # Test an officially supported by Freqtrade team exchange + default_conf['runmode'] = RunMode.DRY_RUN + default_conf.get('exchange').update({'name': 'BITTREX'}) + assert check_exchange(default_conf) + assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.", + caplog) + caplog.clear() + + # Test an officially supported by Freqtrade team exchange + default_conf.get('exchange').update({'name': 'binance'}) + assert check_exchange(default_conf) + assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.", + caplog) + caplog.clear() + + # Test an available exchange, supported by ccxt + default_conf.get('exchange').update({'name': 'huobipro'}) + assert check_exchange(default_conf) + assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, " + r"but not officially supported " + r"by the Freqtrade development team\. .*", caplog) + caplog.clear() + + # Test a 'bad' exchange, which known to have serious problems + default_conf.get('exchange').update({'name': 'bitmex'}) + with pytest.raises(OperationalException, + match=r"Exchange .* will not work with Freqtrade\..*"): + check_exchange(default_conf) + caplog.clear() + + # Test a 'bad' exchange with check_for_bad=False + default_conf.get('exchange').update({'name': 'bitmex'}) + assert check_exchange(default_conf, False) + assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, " + r"but not officially supported " + r"by the Freqtrade development team\. .*", caplog) + caplog.clear() + + # Test an invalid exchange + default_conf.get('exchange').update({'name': 'unknown_exchange'}) + with pytest.raises( + OperationalException, + match=r'Exchange "unknown_exchange" is not known to the ccxt library ' + r'and therefore not available for the bot.*' + ): + check_exchange(default_conf) + + # Test no exchange... + default_conf.get('exchange').update({'name': ''}) + default_conf['runmode'] = RunMode.PLOT + assert check_exchange(default_conf) + + # Test no exchange... + default_conf.get('exchange').update({'name': ''}) + default_conf['runmode'] = RunMode.UTIL_EXCHANGE + with pytest.raises(OperationalException, + match=r'This command requires a configured exchange.*'): + check_exchange(default_conf) diff --git a/tests/test_configuration.py b/tests/test_configuration.py index 99edf0233..2336e3585 100644 --- a/tests/test_configuration.py +++ b/tests/test_configuration.py @@ -11,7 +11,7 @@ import pytest from jsonschema import ValidationError from freqtrade.commands import Arguments -from freqtrade.configuration import Configuration, check_exchange, validate_config_consistency +from freqtrade.configuration import Configuration, validate_config_consistency from freqtrade.configuration.config_validation import validate_config_schema from freqtrade.configuration.deprecated_settings import (check_conflicting_settings, process_deprecated_setting, @@ -584,67 +584,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None: assert config['runmode'] == RunMode.HYPEROPT -def test_check_exchange(default_conf, caplog) -> None: - # Test an officially supported by Freqtrade team exchange - default_conf['runmode'] = RunMode.DRY_RUN - default_conf.get('exchange').update({'name': 'BITTREX'}) - assert check_exchange(default_conf) - assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.", - caplog) - caplog.clear() - - # Test an officially supported by Freqtrade team exchange - default_conf.get('exchange').update({'name': 'binance'}) - assert check_exchange(default_conf) - assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.", - caplog) - caplog.clear() - - # Test an available exchange, supported by ccxt - default_conf.get('exchange').update({'name': 'huobipro'}) - assert check_exchange(default_conf) - assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, " - r"but not officially supported " - r"by the Freqtrade development team\. .*", caplog) - caplog.clear() - - # Test a 'bad' exchange, which known to have serious problems - default_conf.get('exchange').update({'name': 'bitmex'}) - with pytest.raises(OperationalException, - match=r"Exchange .* will not work with Freqtrade\..*"): - check_exchange(default_conf) - caplog.clear() - - # Test a 'bad' exchange with check_for_bad=False - default_conf.get('exchange').update({'name': 'bitmex'}) - assert check_exchange(default_conf, False) - assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, " - r"but not officially supported " - r"by the Freqtrade development team\. .*", caplog) - caplog.clear() - - # Test an invalid exchange - default_conf.get('exchange').update({'name': 'unknown_exchange'}) - with pytest.raises( - OperationalException, - match=r'Exchange "unknown_exchange" is not known to the ccxt library ' - r'and therefore not available for the bot.*' - ): - check_exchange(default_conf) - - # Test no exchange... - default_conf.get('exchange').update({'name': ''}) - default_conf['runmode'] = RunMode.PLOT - assert check_exchange(default_conf) - - # Test no exchange... - default_conf.get('exchange').update({'name': ''}) - default_conf['runmode'] = RunMode.UTIL_EXCHANGE - with pytest.raises(OperationalException, - match=r'This command requires a configured exchange.*'): - check_exchange(default_conf) - - def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None: patched_configuration_load_config_file(mocker, default_conf) From c1d8ade2fa0fce58b49ee7324b27c4875ff5f008 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 19:28:57 +0200 Subject: [PATCH 072/258] Improve supported exchange check by supporting exchange aliases --- freqtrade/exchange/__init__.py | 4 ++-- freqtrade/exchange/check_exchange.py | 6 +++--- freqtrade/exchange/exchange.py | 7 +------ tests/exchange/test_exchange_utils.py | 20 ++++++++++++++++++-- 4 files changed, 24 insertions(+), 13 deletions(-) diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py index ff7ec7e04..1b5ca11ee 100644 --- a/freqtrade/exchange/__init__.py +++ b/freqtrade/exchange/__init__.py @@ -12,8 +12,8 @@ from freqtrade.exchange.coinbasepro import Coinbasepro 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, + is_exchange_known_ccxt, 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/check_exchange.py b/freqtrade/exchange/check_exchange.py index c3d859275..69330bcd0 100644 --- a/freqtrade/exchange/check_exchange.py +++ b/freqtrade/exchange/check_exchange.py @@ -3,8 +3,8 @@ import logging from freqtrade.constants import Config from freqtrade.enums import RunMode from freqtrade.exceptions import OperationalException -from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt, - is_exchange_officially_supported, validate_exchange) +from freqtrade.exchange import available_exchanges, is_exchange_known_ccxt, validate_exchange +from freqtrade.exchange.common import MAP_EXCHANGE_CHILDCLASS, SUPPORTED_EXCHANGES logger = logging.getLogger(__name__) @@ -52,7 +52,7 @@ def check_exchange(config: Config, check_for_bad: bool = True) -> bool: else: logger.warning(f'Exchange "{exchange}" will not work with Freqtrade. Reason: {reason}') - if is_exchange_officially_supported(exchange): + if MAP_EXCHANGE_CHILDCLASS.get(exchange, exchange) in SUPPORTED_EXCHANGES: logger.info(f'Exchange "{exchange}" is officially supported ' f'by the Freqtrade development team.') else: diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index b071c677b..cb9cbebbd 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -30,8 +30,7 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun RetryableOrderError, TemporaryError) from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, - SUPPORTED_EXCHANGES, remove_credentials, retrier, - retrier_async) + remove_credentials, retrier, retrier_async) from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json, safe_value_fallback2) from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -2773,10 +2772,6 @@ def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = Non return exchange_name in ccxt_exchanges(ccxt_module) -def is_exchange_officially_supported(exchange_name: str) -> bool: - return exchange_name in SUPPORTED_EXCHANGES - - def ccxt_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]: """ Return the list of all exchanges known to ccxt diff --git a/tests/exchange/test_exchange_utils.py b/tests/exchange/test_exchange_utils.py index a454b37d0..db206ab98 100644 --- a/tests/exchange/test_exchange_utils.py +++ b/tests/exchange/test_exchange_utils.py @@ -20,10 +20,26 @@ def test_check_exchange(default_conf, caplog) -> None: # Test an officially supported by Freqtrade team exchange default_conf.get('exchange').update({'name': 'binance'}) assert check_exchange(default_conf) - assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.", - caplog) + assert log_has_re( + r"Exchange \"binance\" is officially supported by the Freqtrade development team\.", + caplog) caplog.clear() + # Test an officially supported by Freqtrade team exchange + default_conf.get('exchange').update({'name': 'binanceus'}) + assert check_exchange(default_conf) + assert log_has_re( + r"Exchange \"binanceus\" is officially supported by the Freqtrade development team\.", + caplog) + caplog.clear() + + # Test an officially supported by Freqtrade team exchange - with remapping + default_conf.get('exchange').update({'name': 'okex'}) + assert check_exchange(default_conf) + assert log_has_re( + r"Exchange \"okex\" is officially supported by the Freqtrade development team\.", + caplog) + caplog.clear() # Test an available exchange, supported by ccxt default_conf.get('exchange').update({'name': 'huobipro'}) assert check_exchange(default_conf) From 3264d7b8900c3d9d955248a212009f1dbd5642c4 Mon Sep 17 00:00:00 2001 From: Marek Cieplucha Date: Tue, 4 Oct 2022 20:27:13 +0200 Subject: [PATCH 073/258] Fix for #7534 in backtesting --- freqtrade/optimize/backtesting.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 376c2de7c..83159dfe4 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -1045,7 +1045,7 @@ class Backtesting: if requested_rate: self._enter_trade(pair=trade.pair, row=row, trade=trade, requested_rate=requested_rate, - requested_stake=(order.remaining * order.price), + requested_stake=(order.remaining * order.price / trade.leverage), direction='short' if trade.is_short else 'long') self.replaced_entry_orders += 1 else: From 5019300d5c1752e71bfb360fe5a26e42c8aca26c Mon Sep 17 00:00:00 2001 From: Marek Cieplucha Date: Tue, 4 Oct 2022 20:28:47 +0200 Subject: [PATCH 074/258] Fix for #7534 in bot --- freqtrade/freqtradebot.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 15398ca04..213bc6157 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1311,7 +1311,7 @@ class FreqtradeBot(LoggingMixin): # place new order only if new price is supplied self.execute_entry( pair=trade.pair, - stake_amount=(order_obj.remaining * order_obj.price), + stake_amount=(order_obj.remaining * order_obj.price / trade.leverage) price=adjusted_entry_price, trade=trade, is_short=trade.is_short, From 4df533feb0c806a729390035e1d990febc90996a Mon Sep 17 00:00:00 2001 From: Marek Cieplucha Date: Tue, 4 Oct 2022 21:16:30 +0200 Subject: [PATCH 075/258] Add missing comma --- freqtrade/freqtradebot.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 213bc6157..cd111679c 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1311,7 +1311,7 @@ class FreqtradeBot(LoggingMixin): # place new order only if new price is supplied self.execute_entry( pair=trade.pair, - stake_amount=(order_obj.remaining * order_obj.price / trade.leverage) + stake_amount=(order_obj.remaining * order_obj.price / trade.leverage), price=adjusted_entry_price, trade=trade, is_short=trade.is_short, From ca913fb29d02dc7c8492f926ab1f6268b6812e5f Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 07:28:34 +0200 Subject: [PATCH 076/258] Add leveraged test-case for order-adjustment --- tests/test_integration.py | 33 ++++++++++++++++++++++++--------- 1 file changed, 24 insertions(+), 9 deletions(-) diff --git a/tests/test_integration.py b/tests/test_integration.py index a848de5d3..f2504c23a 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -351,8 +351,13 @@ def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.nr_of_successful_exits == 1 -def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: +@pytest.mark.parametrize('leverage', [ + 1, 2 +]) +def test_dca_order_adjust(default_conf_usdt, ticker_usdt, leverage, fee, mocker) -> None: default_conf_usdt['position_adjustment_enable'] = True + default_conf_usdt['trading_mode'] = 'futures' + default_conf_usdt['margin_mode'] = 'isolated' freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) mocker.patch.multiple( @@ -363,9 +368,14 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: price_to_precision=lambda s, x, y: y, ) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=False) + mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=10) + mocker.patch("freqtrade.exchange.Exchange.get_funding_fees", return_value=0) + mocker.patch("freqtrade.exchange.Exchange.get_maintenance_ratio_and_amt", return_value=(0, 0)) patch_get_signal(freqtrade) freqtrade.strategy.custom_entry_price = lambda **kwargs: ticker_usdt['ask'] * 0.96 + freqtrade.strategy.leverage = MagicMock(return_value=leverage) + freqtrade.strategy.minimal_roi = {0: 0.2} freqtrade.enter_positions() @@ -377,6 +387,8 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.open_rate == 1.96 assert trade.stop_loss_pct is None assert trade.stop_loss == 0.0 + assert trade.leverage == leverage + assert trade.stake_amount == 60 assert trade.initial_stop_loss == 0.0 assert trade.initial_stop_loss_pct is None # No adjustment @@ -396,6 +408,7 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.open_rate == 1.96 assert trade.stop_loss_pct is None assert trade.stop_loss == 0.0 + assert trade.stake_amount == 60 assert trade.initial_stop_loss == 0.0 assert trade.initial_stop_loss_pct is None @@ -407,9 +420,10 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.open_order_id is None # Open rate is not adjusted yet assert trade.open_rate == 1.99 + assert trade.stake_amount == 60 assert trade.stop_loss_pct == -0.1 - assert trade.stop_loss == 1.99 * 0.9 - assert trade.initial_stop_loss == 1.99 * 0.9 + assert pytest.approx(trade.stop_loss) == 1.99 * (1 - 0.1 / leverage) + assert pytest.approx(trade.initial_stop_loss) == 1.99 * (1 - 0.1 / leverage) assert trade.initial_stop_loss_pct == -0.1 # 2nd order - not filling @@ -422,7 +436,7 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.open_order_id is not None assert trade.open_rate == 1.99 assert trade.orders[-1].price == 1.96 - assert trade.orders[-1].cost == 120 + assert trade.orders[-1].cost == 120 * leverage # Replace new order with diff. order at a lower price freqtrade.strategy.adjust_entry_price = MagicMock(return_value=1.95) @@ -432,8 +446,9 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert len(trade.orders) == 4 assert trade.open_order_id is not None assert trade.open_rate == 1.99 + assert trade.stake_amount == 60 assert trade.orders[-1].price == 1.95 - assert pytest.approx(trade.orders[-1].cost) == 120 + assert pytest.approx(trade.orders[-1].cost) == 120 * leverage # Fill DCA order freqtrade.strategy.adjust_trade_position = MagicMock(return_value=None) @@ -446,13 +461,13 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: assert trade.open_order_id is None assert pytest.approx(trade.open_rate) == 1.963153456 assert trade.orders[-1].price == 1.95 - assert pytest.approx(trade.orders[-1].cost) == 120 + assert pytest.approx(trade.orders[-1].cost) == 120 * leverage assert trade.orders[-1].status == 'closed' - assert pytest.approx(trade.amount) == 91.689215 + assert pytest.approx(trade.amount) == 91.689215 * leverage # Check the 2 filled orders equal the above amount - assert pytest.approx(trade.orders[1].amount) == 30.150753768 - assert pytest.approx(trade.orders[-1].amount) == 61.538461232 + assert pytest.approx(trade.orders[1].amount) == 30.150753768 * leverage + assert pytest.approx(trade.orders[-1].amount) == 61.538461232 * leverage @pytest.mark.parametrize('leverage', [1, 2]) From 0e0bda8f130488b7de38e563e483b92b4649a6f1 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 5 Oct 2022 14:08:03 +0200 Subject: [PATCH 077/258] improve freqai tests --- tests/freqai/conftest.py | 7 +- tests/freqai/test_freqai_datadrawer.py | 2 +- tests/freqai/test_freqai_datakitchen.py | 10 +-- tests/freqai/test_freqai_interface.py | 88 +++++++++++++++++++++---- 4 files changed, 87 insertions(+), 20 deletions(-) diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 2c6210a0e..026b45afc 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -29,15 +29,16 @@ def freqai_conf(default_conf, tmpdir): "enabled": True, "startup_candles": 10000, "purge_old_models": True, - "train_period_days": 5, + "train_period_days": 2, "backtest_period_days": 2, "live_retrain_hours": 0, "expiration_hours": 1, "identifier": "uniqe-id100", "live_trained_timestamp": 0, + "data_kitchen_thread_count": 2, "feature_parameters": { "include_timeframes": ["5m"], - "include_corr_pairlist": ["ADA/BTC", "DASH/BTC"], + "include_corr_pairlist": ["ADA/BTC"], "label_period_candles": 20, "include_shifted_candles": 1, "DI_threshold": 0.9, @@ -47,7 +48,7 @@ def freqai_conf(default_conf, tmpdir): "stratify_training_data": 0, "indicator_periods_candles": [10], }, - "data_split_parameters": {"test_size": 0.33, "random_state": 1}, + "data_split_parameters": {"test_size": 0.33, "shuffle": False}, "model_training_parameters": {"n_estimators": 100}, }, "config_files": [Path('config_examples', 'config_freqai.example.json')] diff --git a/tests/freqai/test_freqai_datadrawer.py b/tests/freqai/test_freqai_datadrawer.py index a6df60e61..1d1c44a1e 100644 --- a/tests/freqai/test_freqai_datadrawer.py +++ b/tests/freqai/test_freqai_datadrawer.py @@ -90,5 +90,5 @@ def test_use_strategy_to_populate_indicators(mocker, freqai_conf): df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, 'LTC/BTC') - assert len(df.columns) == 45 + assert len(df.columns) == 33 shutil.rmtree(Path(freqai.dk.full_path)) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index b99ac236d..023193818 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -71,14 +71,14 @@ 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(r"DBSCAN found eps of 2\.3\d\.", caplog) + assert log_has_re(r"DBSCAN found eps of 1.75", 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) == 2.54 + assert round(avg_mean_dist, 2) == 1.99 def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf, caplog): @@ -86,7 +86,7 @@ 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 8.66%", + "SVM detected 7.36%", caplog, ) @@ -125,7 +125,7 @@ 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 + assert len(freqai.dk.data) == 32 def test_filter_features(mocker, freqai_conf): @@ -139,7 +139,7 @@ def test_filter_features(mocker, freqai_conf): training_filter=True, ) - assert len(filtered_df.columns) == 26 + assert len(filtered_df.columns) == 14 def test_make_train_test_datasets(mocker, freqai_conf): diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 4512a43f0..7921659bc 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -7,10 +7,14 @@ import pytest from freqtrade.configuration import TimeRange from freqtrade.data.dataprovider import DataProvider +from freqtrade.enums import RunMode from freqtrade.freqai.data_kitchen import FreqaiDataKitchen +from freqtrade.freqai.utils import download_all_data_for_training, get_required_data_timerange +from freqtrade.persistence import Trade from freqtrade.plugins.pairlistmanager import PairListManager from tests.conftest import get_patched_exchange, log_has_re from tests.freqai.conftest import get_patched_freqai_strategy +from freqtrade.optimize.backtesting import Backtesting def is_arm() -> bool: @@ -18,15 +22,21 @@ def is_arm() -> bool: return "arm" in machine or "aarch64" in machine +def is_mac() -> bool: + machine = platform.system() + return "Darwin" in machine + + @pytest.mark.parametrize('model', [ 'LightGBMRegressor', 'XGBoostRegressor', 'CatboostRegressor', ]) -def test_extract_data_and_train_model_Regressors(mocker, freqai_conf, model): +def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model): if is_arm() and model == 'CatboostRegressor': pytest.skip("CatBoost is not supported on ARM") + model_save_ext = 'joblib' freqai_conf.update({"freqaimodel": model}) freqai_conf.update({"timerange": "20180110-20180130"}) freqai_conf.update({"strategy": "freqai_test_strat"}) @@ -43,16 +53,16 @@ def test_extract_data_and_train_model_Regressors(mocker, freqai_conf, model): freqai.dd.pair_dict = MagicMock() - data_load_timerange = TimeRange.parse_timerange("20180110-20180130") - new_timerange = TimeRange.parse_timerange("20180120-20180130") + data_load_timerange = TimeRange.parse_timerange("20180125-20180130") + new_timerange = TimeRange.parse_timerange("20180127-20180130") 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}_model.{model_save_ext}").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)) @@ -92,7 +102,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): 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 + assert len(freqai.dk.data['training_features_list']) == 14 shutil.rmtree(Path(freqai.dk.full_path)) @@ -136,9 +146,28 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): shutil.rmtree(Path(freqai.dk.full_path)) -def test_start_backtesting(mocker, freqai_conf): - freqai_conf.update({"timerange": "20180120-20180130"}) +@pytest.mark.parametrize( + "model, num_files, strat", + [ + ("LightGBMRegressor", 6, "freqai_test_strat"), + ("XGBoostRegressor", 6, "freqai_test_strat"), + ("CatboostRegressor", 6, "freqai_test_strat"), + ("XGBoostClassifier", 6, "freqai_test_classifier"), + ("LightGBMClassifier", 6, "freqai_test_classifier"), + ("CatboostClassifier", 6, "freqai_test_classifier") + ], + ) +def test_start_backtesting(mocker, freqai_conf, model, num_files, strat): freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) + freqai_conf['runmode'] = RunMode.BACKTEST + Trade.use_db = False + if is_arm() and "Catboost" in model: + pytest.skip("CatBoost is not supported on ARM") + + freqai_conf.update({"freqaimodel": model}) + freqai_conf.update({"timerange": "20180120-20180130"}) + freqai_conf.update({"strategy": strat}) + strategy = get_patched_freqai_strategy(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf) strategy.dp = DataProvider(freqai_conf, exchange) @@ -157,8 +186,8 @@ 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) == 6 - + assert len(model_folders) == num_files + Backtesting.cleanup() shutil.rmtree(Path(freqai.dk.full_path)) @@ -211,7 +240,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): assert len(model_folders) == 6 - # without deleting the exiting folder structure, re-run + # without deleting the existing folder structure, re-run freqai_conf.update({"timerange": "20180120-20180130"}) strategy = get_patched_freqai_strategy(mocker, freqai_conf) @@ -375,3 +404,40 @@ def test_freqai_informative_pairs(mocker, freqai_conf, timeframes, corr_pairs): pairs_b = strategy.gather_informative_pairs() # we expect unique pairs * timeframes assert len(pairs_b) == len(set(pairlist + corr_pairs)) * len(timeframes) + + +def test_start_set_train_queue(mocker, freqai_conf, caplog): + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + pairlist = PairListManager(exchange, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange, pairlist) + strategy.freqai_info = freqai_conf.get("freqai", {}) + freqai = strategy.freqai + freqai.live = False + + freqai.train_queue = freqai._set_train_queue() + + assert log_has_re( + "Set fresh train queue from whitelist.", + caplog, + ) + + +def test_get_required_data_timerange(mocker, freqai_conf): + time_range = get_required_data_timerange(freqai_conf) + assert (time_range.stopts - time_range.startts) == 177300 + + +def test_download_all_data_for_training(mocker, freqai_conf, caplog, tmpdir): + strategy = get_patched_freqai_strategy(mocker, freqai_conf) + exchange = get_patched_exchange(mocker, freqai_conf) + pairlist = PairListManager(exchange, freqai_conf) + strategy.dp = DataProvider(freqai_conf, exchange, pairlist) + freqai_conf['pairs'] = freqai_conf['exchange']['pair_whitelist'] + freqai_conf['datadir'] = Path(tmpdir) + download_all_data_for_training(strategy.dp, freqai_conf) + + assert log_has_re( + "Downloading", + caplog, + ) From 4edb30bfa82bbfeed89eefedb222afd18aec0819 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 5 Oct 2022 14:11:19 +0200 Subject: [PATCH 078/258] isort --- tests/freqai/test_freqai_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 7921659bc..a61853c47 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -10,11 +10,11 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import RunMode from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.utils import download_all_data_for_training, get_required_data_timerange +from freqtrade.optimize.backtesting import Backtesting from freqtrade.persistence import Trade from freqtrade.plugins.pairlistmanager import PairListManager from tests.conftest import get_patched_exchange, log_has_re from tests.freqai.conftest import get_patched_freqai_strategy -from freqtrade.optimize.backtesting import Backtesting def is_arm() -> bool: From 0d67afe15b75fc433ef962bb84c8fa8b1672ba2e Mon Sep 17 00:00:00 2001 From: robcaulk Date: Wed, 5 Oct 2022 14:38:50 +0200 Subject: [PATCH 079/258] allow less precision, ensure regex is catching the right chars --- tests/freqai/test_freqai_datakitchen.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/freqai/test_freqai_datakitchen.py b/tests/freqai/test_freqai_datakitchen.py index 023193818..f60b29bf1 100644 --- a/tests/freqai/test_freqai_datakitchen.py +++ b/tests/freqai/test_freqai_datakitchen.py @@ -71,7 +71,7 @@ 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(r"DBSCAN found eps of 1.75", caplog) + assert log_has_re(r"DBSCAN found eps of 1\.7\d\.", caplog) def test_compute_distances(mocker, freqai_conf): From 7dbb78da955463164eabf3eb9fb6107937aca7e6 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 13:14:36 +0000 Subject: [PATCH 080/258] Losely pin pydantic to avoid dependency problems closes #7537 --- requirements.txt | 1 + setup.py | 1 + 2 files changed, 2 insertions(+) diff --git a/requirements.txt b/requirements.txt index 3cc830290..4f4b30d0c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -38,6 +38,7 @@ sdnotify==0.3.2 # API Server fastapi==0.85.0 +pydantic>=1.8.0 uvicorn==0.18.3 pyjwt==2.5.0 aiofiles==22.1.0 diff --git a/setup.py b/setup.py index d3f9ea7c0..b3693c9f9 100644 --- a/setup.py +++ b/setup.py @@ -75,6 +75,7 @@ setup( 'joblib>=1.2.0', 'pyarrow; platform_machine != "armv7l"', 'fastapi', + 'pydantic>=1.8.0', 'uvicorn', 'psutil', 'pyjwt', From 9b1fb02df84f2af68ef764c9542511861d41843d Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 18:09:26 +0200 Subject: [PATCH 081/258] Refactor generic data generation to conftest --- tests/conftest.py | 22 ++++++++++++++++++++++ tests/strategy/test_strategy_helpers.py | 25 ++----------------------- 2 files changed, 24 insertions(+), 23 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index a9eeb481e..f87fa59c5 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -10,6 +10,7 @@ from unittest.mock import MagicMock, Mock, PropertyMock import arrow import numpy as np +import pandas as pd import pytest from telegram import Chat, Message, Update @@ -19,6 +20,7 @@ from freqtrade.data.converter import ohlcv_to_dataframe from freqtrade.edge import PairInfo from freqtrade.enums import CandleType, MarginMode, RunMode, SignalDirection, TradingMode from freqtrade.exchange import Exchange +from freqtrade.exchange.exchange import timeframe_to_minutes from freqtrade.freqtradebot import FreqtradeBot from freqtrade.persistence import LocalTrade, Order, Trade, init_db from freqtrade.resolvers import ExchangeResolver @@ -82,6 +84,26 @@ def get_args(args): return Arguments(args).get_parsed_arg() +def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'): + np.random.seed(42) + tf_mins = timeframe_to_minutes(timeframe) + + base = np.random.normal(20, 2, size=size) + + date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC') + df = pd.DataFrame({ + 'date': date, + 'open': base, + 'high': base + np.random.normal(2, 1, size=size), + 'low': base - np.random.normal(2, 1, size=size), + 'close': base + np.random.normal(0, 1, size=size), + 'volume': np.random.normal(200, size=size) + } + ) + df = df.dropna() + return df + + # Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines # TODO: This should be replaced with AsyncMock once support for python 3.7 is dropped. def get_mock_coro(return_value=None, side_effect=None): diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py index 8cb990e87..f42f9e681 100644 --- a/tests/strategy/test_strategy_helpers.py +++ b/tests/strategy/test_strategy_helpers.py @@ -5,29 +5,8 @@ import pytest from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import CandleType from freqtrade.resolvers.strategy_resolver import StrategyResolver -from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open, - timeframe_to_minutes) -from tests.conftest import get_patched_exchange - - -def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'): - np.random.seed(42) - tf_mins = timeframe_to_minutes(timeframe) - - base = np.random.normal(20, 2, size=size) - - date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC') - df = pd.DataFrame({ - 'date': date, - 'open': base, - 'high': base + np.random.normal(2, 1, size=size), - 'low': base - np.random.normal(2, 1, size=size), - 'close': base + np.random.normal(0, 1, size=size), - 'volume': np.random.normal(200, size=size) - } - ) - df = df.dropna() - return df +from freqtrade.strategy import merge_informative_pair, stoploss_from_absolute, stoploss_from_open +from tests.conftest import generate_test_data, get_patched_exchange def test_merge_informative_pair(): From edb942f6624957c46ec4cf83618e2f2b2301ef6f Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 3 Oct 2022 20:47:26 +0200 Subject: [PATCH 082/258] Add typing import to sampleStrategy --- freqtrade/templates/sample_strategy.py | 1 + 1 file changed, 1 insertion(+) diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index 1eb3d4256..fd81570fe 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -5,6 +5,7 @@ import numpy as np # noqa import pandas as pd # noqa from pandas import DataFrame +from typing import Optional, Union from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter, IStrategy, IntParameter) From 02e238a944d7a87a207d6f552e97f6e2b3771eac Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 3 Oct 2022 20:49:54 +0200 Subject: [PATCH 083/258] Combine ohlcv data in exchange class for live mode --- freqtrade/exchange/exchange.py | 49 +++++++++++++++++++++++----------- 1 file changed, 34 insertions(+), 15 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index cb9cbebbd..4f869f994 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -18,12 +18,12 @@ import ccxt.async_support as ccxt_async from cachetools import TTLCache from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision from dateutil import parser -from pandas import DataFrame +from pandas import DataFrame, concat from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell, Config, EntryExit, ListPairsWithTimeframes, MakerTaker, PairWithTimeframe) -from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list +from freqtrade.data.converter import clean_ohlcv_dataframe, ohlcv_to_dataframe, trades_dict_to_list from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError, InvalidOrderException, OperationalException, PricingError, @@ -1850,10 +1850,14 @@ class Exchange: return pair, timeframe, candle_type, data def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType, - since_ms: Optional[int]) -> Coroutine: + since_ms: Optional[int], cache: bool) -> Coroutine: + not_all_data = self.required_candle_call_count > 1 + if cache and (pair, timeframe, candle_type) in self._klines: + # Not in cache - force multi-calls + not_all_data = False if (not since_ms - and (self._ft_has["ohlcv_require_since"] or self.required_candle_call_count > 1)): + and (self._ft_has["ohlcv_require_since"] or not_all_data)): # Multiple calls for one pair - to get more history one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type, since_ms) @@ -1890,8 +1894,9 @@ class Exchange: if ((pair, timeframe, candle_type) not in self._klines or not cache or self._now_is_time_to_refresh(pair, timeframe, candle_type)): - input_coroutines.append(self._build_coroutine( - pair, timeframe, candle_type=candle_type, since_ms=since_ms)) + + input_coroutines.append( + self._build_coroutine(pair, timeframe, candle_type, since_ms, cache)) else: logger.debug( @@ -1901,6 +1906,25 @@ class Exchange: return input_coroutines, cached_pairs + def _process_ohlcv_df(self, pair: str, timeframe: str, c_type: CandleType, ticks: List[List], + cache: bool, drop_incomplete: bool) -> DataFrame: + # keeping last candle time as last refreshed time of the pair + if ticks: + self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[-1][0] // 1000 + # keeping parsed dataframe in cache + ohlcv_df = ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True, + drop_incomplete=drop_incomplete) + if cache: + if (pair, timeframe, c_type) in self._klines: + old = self._klines[(pair, timeframe, c_type)] + # Reassign so we return the updated, combined df + ohlcv_df = clean_ohlcv_dataframe(concat([old, ohlcv_df], axis=0), timeframe, pair, + fill_missing=True, drop_incomplete=False) + self._klines[(pair, timeframe, c_type)] = ohlcv_df + else: + self._klines[(pair, timeframe, c_type)] = ohlcv_df + return ohlcv_df + def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *, since_ms: Optional[int] = None, cache: bool = True, drop_incomplete: Optional[bool] = None @@ -1937,16 +1961,11 @@ class Exchange: continue # Deconstruct tuple (has 4 elements) pair, timeframe, c_type, ticks = res - # keeping last candle time as last refreshed time of the pair - if ticks: - self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[-1][0] // 1000 - # keeping parsed dataframe in cache - ohlcv_df = ohlcv_to_dataframe( - ticks, timeframe, pair=pair, fill_missing=True, - drop_incomplete=drop_incomplete) + ohlcv_df = self._process_ohlcv_df( + pair, timeframe, c_type, ticks, cache, drop_incomplete) + results_df[(pair, timeframe, c_type)] = ohlcv_df - if cache: - self._klines[(pair, timeframe, c_type)] = ohlcv_df + # Return cached klines for pair, timeframe, c_type in cached_pairs: results_df[(pair, timeframe, c_type)] = self.klines( From b7f26e4f96c444f15025a83e5fcb11529b611f85 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 20:23:20 +0200 Subject: [PATCH 084/258] Update some formatting issues --- freqtrade/exchange/exchange.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 4f869f994..5b7ab1f7f 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1882,10 +1882,8 @@ class Exchange: input_coroutines = [] cached_pairs = [] for pair, timeframe, candle_type in set(pair_list): - if ( - timeframe not in self.timeframes - and candle_type in (CandleType.SPOT, CandleType.FUTURES) - ): + if (timeframe not in self.timeframes + and candle_type in (CandleType.SPOT, CandleType.FUTURES)): logger.warning( f"Cannot download ({pair}, {timeframe}) combination as this timeframe is " f"not available on {self.name}. Available timeframes are " From cea017e79fbcd0d0a630d60d70a38dad844a2ab1 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 4 Oct 2022 20:48:04 +0200 Subject: [PATCH 085/258] Age out old candles --- freqtrade/exchange/exchange.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 5b7ab1f7f..278b216ad 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -184,8 +184,9 @@ class Exchange: # Initial markets load self._load_markets() self.validate_config(config) + self._startup_candle_count: int = config.get('startup_candle_count', 0) self.required_candle_call_count = self.validate_required_startup_candles( - config.get('startup_candle_count', 0), config.get('timeframe', '')) + self._startup_candle_count, config.get('timeframe', '')) # Converts the interval provided in minutes in config to seconds self.markets_refresh_interval: int = exchange_config.get( @@ -1918,6 +1919,9 @@ class Exchange: # Reassign so we return the updated, combined df ohlcv_df = clean_ohlcv_dataframe(concat([old, ohlcv_df], axis=0), timeframe, pair, fill_missing=True, drop_incomplete=False) + candle_limit = self.ohlcv_candle_limit(timeframe, self._config['candle_type_def']) + # Age out old candles + ohlcv_df = ohlcv_df.tail(candle_limit + self._startup_candle_count) self._klines[(pair, timeframe, c_type)] = ohlcv_df else: self._klines[(pair, timeframe, c_type)] = ohlcv_df From 678272e2efbf86805286f4447fd7c6951815085b Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 07:03:06 +0200 Subject: [PATCH 086/258] Improve test formatting --- tests/exchange/test_exchange.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 37ba2ca97..50ff4ae04 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2083,7 +2083,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_ def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None: ohlcv = [ [ - (arrow.utcnow().int_timestamp - 1) * 1000, # unix timestamp ms + (arrow.utcnow().shift(minutes=-5).int_timestamp) * 1000, # unix timestamp ms 1, # open 2, # high 3, # low @@ -2159,6 +2159,7 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None assert exchange._api_async.fetch_ohlcv.call_count == 3 exchange._api_async.fetch_ohlcv.reset_mock() caplog.clear() + # Call with invalid timeframe res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '3m', candle_type)], cache=False) if candle_type != CandleType.MARK: From 638515bce5bcd244e253b3f8980fabb248786e18 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 07:08:40 +0200 Subject: [PATCH 087/258] Test advanced caching --- tests/exchange/test_exchange.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 50ff4ae04..bf9c1ae72 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2140,10 +2140,22 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None assert len(res) == len(pairs) assert exchange._api_async.fetch_ohlcv.call_count == 0 - exchange.required_candle_call_count = 1 assert log_has(f"Using cached candle (OHLCV) data for {pairs[0][0]}, " f"{pairs[0][1]}, {candle_type} ...", caplog) + caplog.clear() + # Reset refresh times - must do 1 call per pair (even though required_calls is 2) + exchange._pairs_last_refresh_time = {} + res = exchange.refresh_latest_ohlcv( + [('IOTA/ETH', '5m', candle_type), ('XRP/ETH', '5m', candle_type)]) + assert len(res) == len(pairs) + + assert exchange._api_async.fetch_ohlcv.call_count == 2 + + # cache - but disabled caching + exchange._api_async.fetch_ohlcv.reset_mock() + exchange.required_candle_call_count = 1 + pairlist = [ ('IOTA/ETH', '5m', candle_type), ('XRP/ETH', '5m', candle_type), From f475c6c3053b67b98da62450adead0cb16240420 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 5 Oct 2022 19:39:28 +0200 Subject: [PATCH 088/258] Add Specific, time-sensitive test-case for new behavior --- tests/conftest.py | 7 +++ tests/exchange/test_exchange.py | 76 ++++++++++++++++++++++++++++++++- 2 files changed, 82 insertions(+), 1 deletion(-) diff --git a/tests/conftest.py b/tests/conftest.py index f87fa59c5..9f71709f1 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -104,6 +104,13 @@ def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'): return df +def generate_test_data_raw(timeframe: str, size: int, start: str = '2020-07-05'): + """ Generates data in the ohlcv format used by ccxt """ + df = generate_test_data(timeframe, size, start) + df['date'] = df.loc[:, 'date'].view(np.int64) // 1000 // 1000 + return list(list(x) for x in zip(*(df[x].values.tolist() for x in df.columns))) + + # Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines # TODO: This should be replaced with AsyncMock once support for python 3.7 is dropped. def get_mock_coro(return_value=None, side_effect=None): diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index bf9c1ae72..bcd1473c6 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -22,7 +22,8 @@ from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, API_RETRY_CO calculate_backoff, remove_credentials) from freqtrade.exchange.exchange import amount_to_contract_precision from freqtrade.resolvers.exchange_resolver import ExchangeResolver -from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re, num_log_has_re +from tests.conftest import (generate_test_data_raw, get_mock_coro, get_patched_exchange, log_has, + log_has_re, num_log_has_re) # Make sure to always keep one exchange here which is NOT subclassed!! @@ -2182,6 +2183,79 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None assert len(res) == 1 +@pytest.mark.parametrize('candle_type', [CandleType.FUTURES, CandleType.MARK, CandleType.SPOT]) +def test_refresh_latest_ohlcv_cache(mocker, default_conf, candle_type, time_machine) -> None: + start = datetime(2021, 8, 1, 0, 0, 0, 0, tzinfo=timezone.utc) + ohlcv = generate_test_data_raw('1h', 100, start.strftime('%Y-%m-%d')) + time_machine.move_to(start + timedelta(hours=99, minutes=30)) + + exchange = get_patched_exchange(mocker, default_conf) + exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv) + pair1 = ('IOTA/ETH', '1h', candle_type) + pair2 = ('XRP/ETH', '1h', candle_type) + pairs = [pair1, pair2] + + # No caching + assert not exchange._klines + res = exchange.refresh_latest_ohlcv(pairs, cache=False) + assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert len(res) == 2 + assert len(res[pair1]) == 99 + assert len(res[pair2]) == 99 + assert not exchange._klines + exchange._api_async.fetch_ohlcv.reset_mock() + + # With caching + res = exchange.refresh_latest_ohlcv(pairs) + assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert len(res) == 2 + assert len(res[pair1]) == 99 + assert len(res[pair2]) == 99 + assert exchange._klines + assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 + exchange._api_async.fetch_ohlcv.reset_mock() + + # Returned from cache + res = exchange.refresh_latest_ohlcv(pairs) + assert exchange._api_async.fetch_ohlcv.call_count == 0 + assert len(res) == 2 + assert len(res[pair1]) == 99 + assert len(res[pair2]) == 99 + assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 + + # Move time 1 candle further but result didn't change yet + time_machine.move_to(start + timedelta(hours=101)) + res = exchange.refresh_latest_ohlcv(pairs) + assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert len(res) == 2 + assert len(res[pair1]) == 99 + assert len(res[pair2]) == 99 + assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 + refresh_pior = exchange._pairs_last_refresh_time[pair1] + + # New candle on exchange - only return 50 candles (but one candle further) + new_startdate = (start + timedelta(hours=51)).strftime('%Y-%m-%d %H:%M') + ohlcv = generate_test_data_raw('1h', 50, new_startdate) + exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv) + res = exchange.refresh_latest_ohlcv(pairs) + assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert len(res) == 2 + assert len(res[pair1]) == 100 + assert len(res[pair2]) == 100 + assert refresh_pior != exchange._pairs_last_refresh_time[pair1] + + assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 + assert exchange._pairs_last_refresh_time[pair2] == ohlcv[-1][0] // 1000 + exchange._api_async.fetch_ohlcv.reset_mock() + + # Retry same call - no action. + res = exchange.refresh_latest_ohlcv(pairs) + assert exchange._api_async.fetch_ohlcv.call_count == 0 + assert len(res) == 2 + assert len(res[pair1]) == 100 + assert len(res[pair2]) == 100 + + @pytest.mark.asyncio @pytest.mark.parametrize("exchange_name", EXCHANGES) async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_name): From 92a1d58df8687bfeda5ed0f57a8736152430fce4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 6 Oct 2022 06:41:56 +0200 Subject: [PATCH 089/258] Evict cache if we didn't get new candles for X hours --- freqtrade/exchange/exchange.py | 8 ++++++-- tests/exchange/test_exchange.py | 4 ++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 278b216ad..914f67e60 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1854,8 +1854,12 @@ class Exchange: since_ms: Optional[int], cache: bool) -> Coroutine: not_all_data = self.required_candle_call_count > 1 if cache and (pair, timeframe, candle_type) in self._klines: - # Not in cache - force multi-calls - not_all_data = False + candle_limit = self.ohlcv_candle_limit(timeframe, candle_type) + min_date = date_minus_candles(timeframe, candle_limit - 5).timestamp() + # Check if 1 call can get us updated candles without hole in the data. + if min_date < self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0): + # Cache can be used - do one-off call. + not_all_data = False if (not since_ms and (self._ft_has["ohlcv_require_since"] or not_all_data)): diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index bcd1473c6..d8f5b832c 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2145,13 +2145,13 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None f"{pairs[0][1]}, {candle_type} ...", caplog) caplog.clear() - # Reset refresh times - must do 1 call per pair (even though required_calls is 2) + # Reset refresh times - must do 2 call per pair as cache is expired exchange._pairs_last_refresh_time = {} res = exchange.refresh_latest_ohlcv( [('IOTA/ETH', '5m', candle_type), ('XRP/ETH', '5m', candle_type)]) assert len(res) == len(pairs) - assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert exchange._api_async.fetch_ohlcv.call_count == 4 # cache - but disabled caching exchange._api_async.fetch_ohlcv.reset_mock() From 7c702dd1069bbbe9f7208c8085faa113acc667f3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 6 Oct 2022 14:43:45 +0000 Subject: [PATCH 090/258] Add cache eviction --- freqtrade/exchange/exchange.py | 5 +++++ tests/exchange/test_exchange.py | 12 ++++++++++++ 2 files changed, 17 insertions(+) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 914f67e60..64ea3a5ca 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1860,6 +1860,11 @@ class Exchange: if min_date < self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0): # Cache can be used - do one-off call. not_all_data = False + else: + # Time jump detected, evict cache + logger.info( + f"Time jump detected. Evicting cache for {pair}, {timeframe}, {candle_type}") + del self._klines[(pair, timeframe, candle_type)] if (not since_ms and (self._ft_has["ohlcv_require_since"] or not_all_data)): diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index d8f5b832c..673dc7594 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2255,6 +2255,18 @@ def test_refresh_latest_ohlcv_cache(mocker, default_conf, candle_type, time_mach assert len(res[pair1]) == 100 assert len(res[pair2]) == 100 + # Move to distant future (so a 1 call would cause a hole in the data) + time_machine.move_to(start + timedelta(hours=2000)) + ohlcv = generate_test_data_raw('1h', 100, start + timedelta(hours=1900)) + exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv) + res = exchange.refresh_latest_ohlcv(pairs) + + assert exchange._api_async.fetch_ohlcv.call_count == 2 + assert len(res) == 2 + # Cache eviction - new data. + assert len(res[pair1]) == 99 + assert len(res[pair2]) == 99 + @pytest.mark.asyncio @pytest.mark.parametrize("exchange_name", EXCHANGES) From 86c781798a53d14ef973c3fb84827a42d1007a42 Mon Sep 17 00:00:00 2001 From: initrv Date: Thu, 6 Oct 2022 19:59:35 +0300 Subject: [PATCH 091/258] =?UTF-8?q?Add=20=D1=81atboost=20train=5Fdir=20for?= =?UTF-8?q?=20tensorboard?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- freqtrade/freqai/prediction_models/CatboostClassifier.py | 3 ++- freqtrade/freqai/prediction_models/CatboostRegressor.py | 3 ++- .../freqai/prediction_models/CatboostRegressorMultiTarget.py | 3 ++- 3 files changed, 6 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 60536e6de..31a865a8d 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -32,8 +32,9 @@ class CatboostClassifier(BaseClassifierModel): ) cbr = CatBoostClassifier( - allow_writing_files=False, + allow_writing_files=True, loss_function='MultiClass', + train_dir=dk.data_path, **self.model_training_parameters, ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index 73cf6c88a..a04649d93 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -41,7 +41,8 @@ class CatboostRegressor(BaseRegressionModel): init_model = self.get_init_model(dk.pair) model = CatBoostRegressor( - allow_writing_files=False, + allow_writing_files=True, + train_dir=dk.data_path, **self.model_training_parameters, ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index 7fa4e293e..292ad600a 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -26,7 +26,8 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): """ cbr = CatBoostRegressor( - allow_writing_files=False, + allow_writing_files=True, + train_dir=dk.data_path, **self.model_training_parameters, ) From a9d5e04a4320f321e9f19862e2c88be3c2b05f7b Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Thu, 6 Oct 2022 19:26:33 +0200 Subject: [PATCH 092/258] Remove constant labels from prediction --- freqtrade/freqai/data_kitchen.py | 12 ++++++++++++ freqtrade/freqai/freqai_interface.py | 2 ++ tests/freqai/conftest.py | 2 ++ tests/freqai/test_freqai_interface.py | 10 ++++++++++ 4 files changed, 26 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7ea2daf02..23bba3f1a 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -460,6 +460,18 @@ class FreqaiDataKitchen: return df + def check_pred_labels(self, df_predictions: DataFrame) -> None: + """ + Check that prediction feature labels match training feature labels. + :params: + :df_predictions: incoming predictions + """ + train_labels = self.data_dictionary["train_features"].columns + pred_labels = df_predictions.columns + if len(train_labels.difference(pred_labels)) != 0: + self.data_dictionary["prediction_features"] = df_predictions[train_labels] + return + 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 5ac7bc32c..62c814c72 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -492,6 +492,8 @@ class IFreqaiModel(ABC): # ensure user is feeding the correct indicators to the model self.check_if_feature_list_matches_strategy(dk) + dk.check_pred_labels(dk.data_dictionary['prediction_features']) + if ft_params.get('inlier_metric_window', 0): dk.compute_inlier_metric(set_='predict') diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 026b45afc..df61b284a 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -107,6 +107,8 @@ def make_unfiltered_dataframe(mocker, freqai_conf): unfiltered_dataframe = freqai.dk.use_strategy_to_populate_indicators( strategy, corr_dataframes, base_dataframes, freqai.dk.pair ) + for i in range(5): + unfiltered_dataframe[f'constant_{i}'] = i unfiltered_dataframe = freqai.dk.slice_dataframe(new_timerange, unfiltered_dataframe) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index a61853c47..238c0418c 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -181,6 +181,8 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") + for i in range(5): + df[f'constant_{i}'] = i metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) @@ -208,6 +210,8 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") + for i in range(5): + df[f'constant_{i}'] = i metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) @@ -233,6 +237,8 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") + for i in range(5): + df[f'constant_{i}'] = i metadata = {"pair": "ADA/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) @@ -256,6 +262,8 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") + for i in range(5): + df[f'constant_{i}'] = i freqai.start_backtesting(df, metadata, freqai.dk) assert log_has_re( @@ -312,6 +320,8 @@ def test_follow_mode(mocker, freqai_conf): freqai.dd.load_all_pair_histories(timerange, freqai.dk) df = strategy.dp.get_pair_dataframe('ADA/BTC', '5m') + for i in range(5): + df[f'constant_{i}'] = i freqai.start_live(df, metadata, strategy, freqai.dk) assert len(freqai.dk.return_dataframe.index) == 5702 From 6e179c7699163ce6fe01a0bbd5b982ee6c87c325 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 6 Oct 2022 14:56:38 +0000 Subject: [PATCH 093/258] Only store tick refresh time if we cache --- freqtrade/exchange/exchange.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 64ea3a5ca..e06f5c7c6 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1866,8 +1866,7 @@ class Exchange: f"Time jump detected. Evicting cache for {pair}, {timeframe}, {candle_type}") del self._klines[(pair, timeframe, candle_type)] - if (not since_ms - and (self._ft_has["ohlcv_require_since"] or not_all_data)): + if (not since_ms and (self._ft_has["ohlcv_require_since"] or not_all_data)): # Multiple calls for one pair - to get more history one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type, since_ms) @@ -1917,7 +1916,7 @@ class Exchange: def _process_ohlcv_df(self, pair: str, timeframe: str, c_type: CandleType, ticks: List[List], cache: bool, drop_incomplete: bool) -> DataFrame: # keeping last candle time as last refreshed time of the pair - if ticks: + if ticks and cache: self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[-1][0] // 1000 # keeping parsed dataframe in cache ohlcv_df = ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True, From 3e08c6e5409d3e1b9c6f787415869e3e49289a00 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 6 Oct 2022 14:12:44 -0600 Subject: [PATCH 094/258] testing/debugging ws client script --- scripts/ws_client.py | 318 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 318 insertions(+) create mode 100644 scripts/ws_client.py diff --git a/scripts/ws_client.py b/scripts/ws_client.py new file mode 100644 index 000000000..63a980069 --- /dev/null +++ b/scripts/ws_client.py @@ -0,0 +1,318 @@ +#!/usr/bin/env python3 +""" +Simple command line client for Testing/debugging +a Freqtrade bot's message websocket + +Should not import anything from freqtrade, +so it can be used as a standalone script. +""" +import argparse +import time +import websockets +import socket +import asyncio +import logging +import rapidjson +import pandas +import orjson +import sys +from pathlib import Path +from dateutil.relativedelta import relativedelta + + +logger = logging.getLogger("WebSocketClient") + + +# --------------------------------------------------------------------------- + +def setup_logging(filename: str): + logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', + handlers=[ + logging.FileHandler(filename), + logging.StreamHandler() + ] + ) + + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument( + '-c', + '--config', + help='Specify configuration file (default: %(default)s). ', + dest='config', + type=str, + metavar='PATH', + default='config.json' + ) + parser.add_argument( + '-l', + '--logfile', + help='The filename to log to.', + dest='logfile', + type=str, + default='ws_client.log' + ) + + args = parser.parse_args() + return vars(args) + + +def load_config(configfile): + file = Path(configfile) + if file.is_file(): + with file.open("r") as f: + config = rapidjson.load(f, parse_mode=rapidjson.PM_COMMENTS | + rapidjson.PM_TRAILING_COMMAS) + return config + else: + logger.warning(f"Could not load config file {file}.") + sys.exit(1) + + +def readable_timedelta(delta): + """ + Convert a dateutil.relativedelta to a readable format + + :param delta: A dateutil.relativedelta + :returns: The readable time difference string + """ + attrs = ['years', 'months', 'days', 'hours', 'minutes', 'seconds', 'microseconds'] + return ", ".join([ + '%d %s' % (getattr(delta, attr), attr if getattr(delta, attr) > 1 else attr[:-1]) + for attr in attrs if getattr(delta, attr) + ]) + +# ---------------------------------------------------------------------------- + + +def json_serialize(message): + """ + Serialize a message to JSON using orjson + :param message: The message to serialize + """ + return str(orjson.dumps(message), "utf-8") + + +def json_deserialize(message): + """ + Deserialize JSON to a dict + :param message: The message to deserialize + """ + def json_to_dataframe(data: str) -> pandas.DataFrame: + dataframe = pandas.read_json(data, orient='split') + if 'date' in dataframe.columns: + dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True) + + return dataframe + + def _json_object_hook(z): + if z.get('__type__') == 'dataframe': + return json_to_dataframe(z.get('__value__')) + return z + + return rapidjson.loads(message, object_hook=_json_object_hook) + + +# --------------------------------------------------------------------------- + + +class ClientProtocol: + logger = logging.getLogger("WebSocketClient.Protocol") + _MESSAGE_COUNT = 0 + _LAST_RECEIVED_AT = 0 # The epoch we received a message most recently + + async def on_connect(self, websocket): + # On connection we have to send our initial requests + initial_requests = [ + { + "type": "subscribe", # The subscribe request should always be first + "data": ["analyzed_df", "whitelist"] # The message types we want + }, + { + "type": "whitelist", + "data": None, + }, + { + "type": "analyzed_df", + "data": {"limit": 1500} + } + ] + + for request in initial_requests: + await websocket.send(json_serialize(request)) + + async def on_message(self, websocket, name, message): + deserialized = json_deserialize(message) + + message_size = sys.getsizeof(message) + message_type = deserialized.get('type') + message_data = deserialized.get('data') + + self.logger.info( + f"Received message of type {message_type} [{message_size} bytes] @ [{name}]" + ) + + time_difference = self._calculate_time_difference() + + if self._MESSAGE_COUNT > 0: + self.logger.info(f"Time since last message: {time_difference}") + + message_handler = getattr(self, f"_handle_{message_type}", None) or self._handle_default + await message_handler(name, message_type, message_data) + + self._MESSAGE_COUNT += 1 + self.logger.info(f"[{self._MESSAGE_COUNT}] total messages..") + self.logger.info("-" * 80) + + def _calculate_time_difference(self): + old_last_received_at = self._LAST_RECEIVED_AT + self._LAST_RECEIVED_AT = time.time() + time_delta = relativedelta(seconds=(self._LAST_RECEIVED_AT - old_last_received_at)) + + return readable_timedelta(time_delta) + + async def _handle_whitelist(self, name, type, data): + self.logger.info(data) + + async def _handle_default(self, name, type, data): + key, la, df = data['key'], data['la'], data['df'] + + columns = ", ".join([str(column) for column in df.columns]) + + self.logger.info(key) + self.logger.info(f"Last analyzed datetime: {la}") + self.logger.info(f"Latest candle datetime: {df.iloc[-1]['date']}") + self.logger.info(f"DataFrame length: {len(df)}") + self.logger.info(f"DataFrame columns: {columns}") + + +async def create_client( + host, + port, + token, + name='default', + protocol=ClientProtocol(), + sleep_time=10, + ping_timeout=10, + wait_timeout=30, + **kwargs +): + """ + Create a websocket client and listen for messages + :param host: The host + :param port: The port + :param token: The websocket auth token + :param name: The name of the producer + :param **kwargs: Any extra kwargs passed to websockets.connect + """ + + while 1: + try: + websocket_url = f"ws://{host}:{port}/api/v1/message/ws?token={token}" + logger.info(f"Attempting to connect to {name} @ {host}:{port}") + + async with websockets.connect(websocket_url, **kwargs) as ws: + logger.info("Connection successful...") + await protocol.on_connect(ws) + + # Now listen for messages + while 1: + try: + message = await asyncio.wait_for( + ws.recv(), + timeout=wait_timeout + ) + + await protocol.on_message(ws, name, message) + + except ( + asyncio.TimeoutError, + websockets.exceptions.ConnectionClosed + ): + # Try pinging + try: + pong = ws.ping() + await asyncio.wait_for( + pong, + timeout=ping_timeout + ) + logger.info("Connection still alive...") + + continue + + except asyncio.TimeoutError: + logger.error(f"Ping timed out, retrying in {sleep_time}s") + await asyncio.sleep(sleep_time) + + break + + except ( + socket.gaierror, + ConnectionRefusedError, + websockets.exceptions.InvalidStatusCode, + websockets.exceptions.InvalidMessage + ) as e: + logger.error(f"Connection Refused - {e} retrying in {sleep_time}s") + await asyncio.sleep(sleep_time) + + continue + + except ( + websockets.exceptions.ConnectionClosedError, + websockets.exceptions.ConnectionClosedOK + ): + # Just keep trying to connect again indefinitely + await asyncio.sleep(sleep_time) + + continue + + except Exception as e: + # An unforseen error has occurred, log and try reconnecting again + logger.error("Unexpected error has occurred:") + logger.exception(e) + + continue + + +# --------------------------------------------------------------------------- + + +async def _main(args): + setup_logging(args['logfile']) + config = load_config(args['config']) + + emc_config = config.get('external_message_consumer', {}) + + producers = emc_config.get('producers', []) + producer = producers[0] + + wait_timeout = emc_config.get('wait_timeout', 300) + ping_timeout = emc_config.get('ping_timeout', 10) + sleep_time = emc_config.get('sleep_time', 10) + message_size_limit = (emc_config.get('message_size_limit', 8) << 20) + + await create_client( + producer['host'], + producer['port'], + producer['ws_token'], + producer['name'], + sleep_time=sleep_time, + ping_timeout=ping_timeout, + wait_timeout=wait_timeout, + max_size=message_size_limit + ) + + +def main(): + args = parse_args() + try: + asyncio.run(_main(args)) + except KeyboardInterrupt: + logger.info("Exiting...") + + +if __name__ == "__main__": + main() From b92b98af29efbe73c2877f4761ab88685342225a Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 6 Oct 2022 14:33:04 -0600 Subject: [PATCH 095/258] fix formatting --- scripts/ws_client.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/scripts/ws_client.py b/scripts/ws_client.py index 63a980069..51ba0ee83 100644 --- a/scripts/ws_client.py +++ b/scripts/ws_client.py @@ -7,16 +7,17 @@ Should not import anything from freqtrade, so it can be used as a standalone script. """ import argparse -import time -import websockets -import socket import asyncio import logging -import rapidjson -import pandas -import orjson +import socket import sys +import time from pathlib import Path + +import orjson +import pandas +import rapidjson +import websockets from dateutil.relativedelta import relativedelta From 1595e5fd8a69de366c8b4710e75e7099a91db027 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Thu, 6 Oct 2022 21:00:28 -0600 Subject: [PATCH 096/258] small fix in protocol --- scripts/ws_client.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/scripts/ws_client.py b/scripts/ws_client.py index 51ba0ee83..0cc076641 100644 --- a/scripts/ws_client.py +++ b/scripts/ws_client.py @@ -181,13 +181,14 @@ class ClientProtocol: async def _handle_default(self, name, type, data): key, la, df = data['key'], data['la'], data['df'] - columns = ", ".join([str(column) for column in df.columns]) + if not df.empty: + columns = ", ".join([str(column) for column in df.columns]) - self.logger.info(key) - self.logger.info(f"Last analyzed datetime: {la}") - self.logger.info(f"Latest candle datetime: {df.iloc[-1]['date']}") - self.logger.info(f"DataFrame length: {len(df)}") - self.logger.info(f"DataFrame columns: {columns}") + self.logger.info(key) + self.logger.info(f"Last analyzed datetime: {la}") + self.logger.info(f"Latest candle datetime: {df.iloc[-1]['date']}") + self.logger.info(f"DataFrame length: {len(df)}") + self.logger.info(f"DataFrame columns: {columns}") async def create_client( @@ -275,6 +276,7 @@ async def create_client( logger.error("Unexpected error has occurred:") logger.exception(e) + await asyncio.sleep(sleep_time) continue From fab6b2f1052ad479b95905f9b183fbff274858c4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 14:00:04 +0200 Subject: [PATCH 097/258] Align datetime import in fiat_convert --- freqtrade/rpc/fiat_convert.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py index cbe4c0045..512e0947a 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -3,8 +3,8 @@ Module that define classes to convert Crypto-currency to FIAT e.g BTC to USD """ -import datetime import logging +from datetime import datetime from typing import Dict, List from cachetools import TTLCache @@ -67,7 +67,7 @@ class CryptoToFiatConverter(LoggingMixin): logger.warning( "Too many requests for CoinGecko API, backing off and trying again later.") # Set backoff timestamp to 60 seconds in the future - self._backoff = datetime.datetime.now().timestamp() + 60 + self._backoff = datetime.now().timestamp() + 60 return # If the request is not a 429 error we want to raise the normal error logger.error( @@ -81,7 +81,7 @@ class CryptoToFiatConverter(LoggingMixin): def _get_gekko_id(self, crypto_symbol): if not self._coinlistings: - if self._backoff <= datetime.datetime.now().timestamp(): + if self._backoff <= datetime.now().timestamp(): self._load_cryptomap() # Still not loaded. if not self._coinlistings: From a5bf34587a41ebbd4af9cc2fc2b2e92b408a20eb Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 15:41:42 +0200 Subject: [PATCH 098/258] Improve fiat-convert behavior in case of coingecko outage --- freqtrade/rpc/fiat_convert.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py index 512e0947a..24c34af72 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -46,7 +46,9 @@ class CryptoToFiatConverter(LoggingMixin): if CryptoToFiatConverter.__instance is None: CryptoToFiatConverter.__instance = object.__new__(cls) try: - CryptoToFiatConverter._coingekko = CoinGeckoAPI() + # Limit retires to 1 (0 and 1) + # otherwise we risk bot impact if coingecko is down. + CryptoToFiatConverter._coingekko = CoinGeckoAPI(retries=1) except BaseException: CryptoToFiatConverter._coingekko = None return CryptoToFiatConverter.__instance From d42fb156086122c9031354740d7e491fc0d4f165 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 16:05:41 +0200 Subject: [PATCH 099/258] Improve generic exception handler --- freqtrade/freqai/freqai_interface.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 5ac7bc32c..394b98e94 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -211,7 +211,8 @@ class IFreqaiModel(ABC): new_trained_timerange, pair, strategy, dk, data_load_timerange ) except Exception as msg: - logger.warning(f'Training {pair} raised exception {msg}, skipping.') + logger.warning(f"Training {pair} raised exception {msg.__class__.__name__}. " + f"Message: {msg}, skipping.") self.train_timer('stop') From ec7af83c8733dfa7ff294c041689529f9c12a92b Mon Sep 17 00:00:00 2001 From: initrv Date: Fri, 7 Oct 2022 17:13:19 +0300 Subject: [PATCH 100/258] add tensorboard to freqai reqs --- requirements-freqai.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements-freqai.txt b/requirements-freqai.txt index cf0d2eb07..c78b3b25e 100644 --- a/requirements-freqai.txt +++ b/requirements-freqai.txt @@ -7,3 +7,4 @@ joblib==1.2.0 catboost==1.1; platform_machine != 'aarch64' lightgbm==3.3.2 xgboost==1.6.2 +tensorboard==2.10.1 From 8fcb80df69f0e898529674be4cf570b189f77a23 Mon Sep 17 00:00:00 2001 From: froggleston Date: Fri, 7 Oct 2022 16:06:30 +0100 Subject: [PATCH 101/258] Add support for dp.send_msg() to webhooks --- docs/configuration.md | 2 ++ docs/webhook-config.md | 23 +++++++++++++++++++++++ freqtrade/rpc/rpc_manager.py | 11 +++++++---- 3 files changed, 32 insertions(+), 4 deletions(-) diff --git a/docs/configuration.md b/docs/configuration.md index 556414e21..8fe6b7620 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -215,6 +215,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `telegram.balance_dust_level` | Dust-level (in stake currency) - currencies with a balance below this will not be shown by `/balance`.
**Datatype:** float | `telegram.reload` | Allow "reload" buttons on telegram messages.
*Defaults to `True`.
**Datatype:** boolean | `telegram.notification_settings.*` | Detailed notification settings. Refer to the [telegram documentation](telegram-usage.md) for details.
**Datatype:** dictionary +| `telegram.allow_custom_messages` | Enable the sending of Telegram messages from strategies via the dataprovider.send_msg() function.
**Datatype:** Boolean | | **Webhook** | `webhook.enabled` | Enable usage of Webhook notifications
**Datatype:** Boolean | `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String @@ -225,6 +226,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String | `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String | `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.allow_custom_messages` | Enable the sending of Webhook messages from strategies via the dataprovider.send_msg() function.
**Datatype:** Boolean | | **Rest API / FreqUI / Producer-Consumer** | `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** Boolean | `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** IPv4 diff --git a/docs/webhook-config.md b/docs/webhook-config.md index 3677ebe89..2793bd1eb 100644 --- a/docs/webhook-config.md +++ b/docs/webhook-config.md @@ -94,6 +94,19 @@ Optional parameters are available to enable automatic retries for webhook messag }, ``` +Custom messages can be sent to Webhook endpoints via the dataprovider.send_msg() function. To enable this, set the `allow_custom_messages` option to `true`: + +```json + "webhook": { + "enabled": true, + "url": "https://", + "allow_custom_messages": true, + "webhookstatus": { + "status": "Status: {status}" + } + }, +``` + Different payloads can be configured for different events. Not all fields are necessary, but you should configure at least one of the dicts, otherwise the webhook will never be called. ### Webhookentry @@ -288,3 +301,13 @@ Available fields correspond to the fields for webhooks and are documented in the The notifications will look as follows by default. ![discord-notification](assets/discord_notification.png) + +Custom messages can be sent from a strategy to Discord endpoints via the dataprovider.send_msg() function. To enable this, set the `allow_custom_messages` option to `true`: + +```json + "discord": { + "enabled": true, + "webhook_url": "https://discord.com/api/webhooks/", + "allow_custom_messages": true, + }, +``` diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index e3b31d225..bc13c1654 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -88,10 +88,13 @@ class RPCManager: """ while queue: msg = queue.popleft() - self.send_msg({ - 'type': RPCMessageType.STRATEGY_MSG, - 'msg': msg, - }) + + for mod in self.registered_modules: + if mod._config.get(mod.name, {}).get('allow_custom_messages', False): + mod.send_msg({ + 'type': RPCMessageType.STRATEGY_MSG, + 'msg': msg, + }) def startup_messages(self, config: Config, pairlist, protections) -> None: if config['dry_run']: From 0460f362fb5b9160d065bdbadef00cb69dd73dfa Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 7 Oct 2022 10:41:06 -0600 Subject: [PATCH 102/258] typo in handle func name --- scripts/ws_client.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/scripts/ws_client.py b/scripts/ws_client.py index 0cc076641..83182ae9e 100644 --- a/scripts/ws_client.py +++ b/scripts/ws_client.py @@ -170,15 +170,15 @@ class ClientProtocol: def _calculate_time_difference(self): old_last_received_at = self._LAST_RECEIVED_AT - self._LAST_RECEIVED_AT = time.time() - time_delta = relativedelta(seconds=(self._LAST_RECEIVED_AT - old_last_received_at)) + self._LAST_RECEIVED_AT = time.time() * 1000 + time_delta = relativedelta(microseconds=(self._LAST_RECEIVED_AT - old_last_received_at)) return readable_timedelta(time_delta) async def _handle_whitelist(self, name, type, data): self.logger.info(data) - async def _handle_default(self, name, type, data): + async def _handle_analyzed_df(self, name, type, data): key, la, df = data['key'], data['la'], data['df'] if not df.empty: @@ -189,6 +189,12 @@ class ClientProtocol: self.logger.info(f"Latest candle datetime: {df.iloc[-1]['date']}") self.logger.info(f"DataFrame length: {len(df)}") self.logger.info(f"DataFrame columns: {columns}") + else: + self.logger.info("Empty DataFrame") + + async def _handle_default(self, name, type, data): + self.logger.info("Unkown message of type {type} received...") + self.logger.info(data) async def create_client( From e337d4b78ae39d992e937b4fa06205b787a82871 Mon Sep 17 00:00:00 2001 From: Emre Date: Fri, 7 Oct 2022 19:05:49 +0300 Subject: [PATCH 103/258] Reset dataframe index after slice --- freqtrade/freqai/data_drawer.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index cde72bfb5..31c76a68e 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -618,7 +618,8 @@ class FreqaiDataDrawer: ) for tf in self.freqai_info["feature_parameters"].get("include_timeframes"): - base_dataframes[tf] = dk.slice_dataframe(timerange, historic_data[pair][tf]) + base_dataframes[tf] = dk.slice_dataframe( + timerange, historic_data[pair][tf]).reset_index(drop=True) if pairs: for p in pairs: if pair in p: @@ -627,7 +628,7 @@ class FreqaiDataDrawer: corr_dataframes[p] = {} corr_dataframes[p][tf] = dk.slice_dataframe( timerange, historic_data[p][tf] - ) + ).reset_index(drop=True) return corr_dataframes, base_dataframes From fb2f2d9a39fec6388f9c8a2de2cc588a87135c0c Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 20:44:47 +0200 Subject: [PATCH 104/258] Allow webhook message setting directly --- freqtrade/constants.py | 5 ++++- freqtrade/rpc/rpc_manager.py | 2 +- freqtrade/rpc/webhook.py | 7 +++++-- tests/rpc/test_rpc_manager.py | 5 +++-- 4 files changed, 13 insertions(+), 6 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index e0eb5e288..27968bb1b 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -5,7 +5,7 @@ bot constants """ from typing import Any, Dict, List, Literal, Tuple -from freqtrade.enums import CandleType +from freqtrade.enums import CandleType, RPCMessageType DEFAULT_CONFIG = 'config.json' @@ -282,6 +282,7 @@ CONF_SCHEMA = { 'enabled': {'type': 'boolean'}, 'token': {'type': 'string'}, 'chat_id': {'type': 'string'}, + 'allow_custom_messages': {'type': 'boolean', 'default': True}, 'balance_dust_level': {'type': 'number', 'minimum': 0.0}, 'notification_settings': { 'type': 'object', @@ -344,6 +345,8 @@ CONF_SCHEMA = { 'format': {'type': 'string', 'enum': WEBHOOK_FORMAT_OPTIONS, 'default': 'form'}, 'retries': {'type': 'integer', 'minimum': 0}, 'retry_delay': {'type': 'number', 'minimum': 0}, + **dict([(x, {'type': 'object'}) for x in RPCMessageType]), + # Below -> Deprecated 'webhookentry': {'type': 'object'}, 'webhookentrycancel': {'type': 'object'}, 'webhookentryfill': {'type': 'object'}, diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index bc13c1654..9c25723b0 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -88,7 +88,7 @@ class RPCManager: """ while queue: msg = queue.popleft() - + logger.info('Sending rpc strategy_msg: %s', msg) for mod in self.registered_modules: if mod._config.get(mod.name, {}).get('allow_custom_messages', False): mod.send_msg({ diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py index bb3b3922f..b46addee5 100644 --- a/freqtrade/rpc/webhook.py +++ b/freqtrade/rpc/webhook.py @@ -45,6 +45,7 @@ class Webhook(RPCHandler): """ Send a message to telegram channel """ try: whconfig = self._config['webhook'] + # Deprecated 2022.10 - only keep generic method. if msg['type'] in [RPCMessageType.ENTRY]: valuedict = whconfig.get('webhookentry') elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]: @@ -61,6 +62,9 @@ class Webhook(RPCHandler): RPCMessageType.STARTUP, RPCMessageType.WARNING): valuedict = whconfig.get('webhookstatus') + elif msg['type'].value in whconfig: + # Allow all types ... + valuedict = whconfig.get(msg['type'].value) elif msg['type'] in ( RPCMessageType.PROTECTION_TRIGGER, RPCMessageType.PROTECTION_TRIGGER_GLOBAL, @@ -69,8 +73,7 @@ class Webhook(RPCHandler): RPCMessageType.STRATEGY_MSG): # Don't fail for non-implemented types return - else: - raise NotImplementedError('Unknown message type: {}'.format(msg['type'])) + if not valuedict: logger.info("Message type '%s' not configured for webhooks", msg['type']) return diff --git a/tests/rpc/test_rpc_manager.py b/tests/rpc/test_rpc_manager.py index d71f38259..21c8b0813 100644 --- a/tests/rpc/test_rpc_manager.py +++ b/tests/rpc/test_rpc_manager.py @@ -99,6 +99,7 @@ def test_send_msg_telegram_error(mocker, default_conf, caplog) -> None: def test_process_msg_queue(mocker, default_conf, caplog) -> None: telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg') + default_conf['telegram']['allow_custom_messages'] = True mocker.patch('freqtrade.rpc.telegram.Telegram._init') freqtradebot = get_patched_freqtradebot(mocker, default_conf) @@ -108,8 +109,8 @@ def test_process_msg_queue(mocker, default_conf, caplog) -> None: queue.append('Test message 2') rpc_manager.process_msg_queue(queue) - assert log_has("Sending rpc message: {'type': strategy_msg, 'msg': 'Test message'}", caplog) - assert log_has("Sending rpc message: {'type': strategy_msg, 'msg': 'Test message 2'}", caplog) + assert log_has("Sending rpc strategy_msg: Test message", caplog) + assert log_has("Sending rpc strategy_msg: Test message 2", caplog) assert telegram_mock.call_count == 2 From ed12cddf3fc4c5e250fe504b821b50d8b8d190af Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 20:45:15 +0200 Subject: [PATCH 105/258] Update docs with new wording for webhook settings --- docs/configuration.md | 14 +++++----- docs/deprecated.md | 14 +++++----- docs/strategy_migration.md | 12 ++++----- docs/telegram-usage.md | 2 ++ docs/webhook-config.md | 53 +++++++++++++++++++------------------- 5 files changed, 48 insertions(+), 47 deletions(-) diff --git a/docs/configuration.md b/docs/configuration.md index 8fe6b7620..e773e1878 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -219,13 +219,13 @@ Mandatory parameters are marked as **Required**, which means that they are requi | | **Webhook** | `webhook.enabled` | Enable usage of Webhook notifications
**Datatype:** Boolean | `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookentry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookentrycancel` | Payload to send on entry order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookentryfill` | Payload to send on entry order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookexit` | Payload to send on exit. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String -| `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.entry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.entry_cancel` | Payload to send on entry order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.entry_fill` | Payload to send on entry order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.exit` | Payload to send on exit. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.exit_cancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.exit_fill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String +| `webhook.status` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String | `webhook.allow_custom_messages` | Enable the sending of Webhook messages from strategies via the dataprovider.send_msg() function.
**Datatype:** Boolean | | **Rest API / FreqUI / Producer-Consumer** | `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** Boolean diff --git a/docs/deprecated.md b/docs/deprecated.md index beceb12ab..3b5b28b81 100644 --- a/docs/deprecated.md +++ b/docs/deprecated.md @@ -66,11 +66,11 @@ We will keep a compatibility layer for 1-2 versions (so both `buy_tag` and `ente #### Naming changes -Webhook terminology changed from "sell" to "exit", and from "buy" to "entry". +Webhook terminology changed from "sell" to "exit", and from "buy" to "entry", removing "webhook" in the process. -* `webhookbuy` -> `webhookentry` -* `webhookbuyfill` -> `webhookentryfill` -* `webhookbuycancel` -> `webhookentrycancel` -* `webhooksell` -> `webhookexit` -* `webhooksellfill` -> `webhookexitfill` -* `webhooksellcancel` -> `webhookexitcancel` +* `webhookbuy`, `webhookentry` -> `entry` +* `webhookbuyfill`, `webhookentryfill` -> `entry_fill` +* `webhookbuycancel`, `webhookentrycancel` -> `entry_cancel` +* `webhooksell`, `webhookexit` -> `exit` +* `webhooksellfill`, `webhookexitfill` -> `exit_fill` +* `webhooksellcancel`, `webhookexitcancel` -> `exit_cancel` diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md index ac65abff4..b971b81ea 100644 --- a/docs/strategy_migration.md +++ b/docs/strategy_migration.md @@ -50,12 +50,12 @@ Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `fo * `force_sell` -> `force_exit` * `emergency_sell` -> `emergency_exit` * Webhook terminology changed from "sell" to "exit", and from "buy" to entry - * `webhookbuy` -> `webhookentry` - * `webhookbuyfill` -> `webhookentryfill` - * `webhookbuycancel` -> `webhookentrycancel` - * `webhooksell` -> `webhookexit` - * `webhooksellfill` -> `webhookexitfill` - * `webhooksellcancel` -> `webhookexitcancel` + * `webhookbuy` -> `entry` + * `webhookbuyfill` -> `entry_fill` + * `webhookbuycancel` -> `entry_cancel` + * `webhooksell` -> `exit` + * `webhooksellfill` -> `exit_fill` + * `webhooksellcancel` -> `exit_cancel` * Telegram notification settings * `buy` -> `entry` * `buy_fill` -> `entry_fill` diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md index 055512f26..db4a309d0 100644 --- a/docs/telegram-usage.md +++ b/docs/telegram-usage.md @@ -77,6 +77,7 @@ Example configuration showing the different settings: "enabled": true, "token": "your_telegram_token", "chat_id": "your_telegram_chat_id", + "allow_custom_messages": true, "notification_settings": { "status": "silent", "warning": "on", @@ -115,6 +116,7 @@ Example configuration showing the different settings: `show_candle` - show candle values as part of entry/exit messages. Only possible values are `"ohlc"` or `"off"`. `balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown. +`allow_custom_messages` completely disable strategy messages. `reload` allows you to disable reload-buttons on selected messages. ## Create a custom keyboard (command shortcut buttons) diff --git a/docs/webhook-config.md b/docs/webhook-config.md index 2793bd1eb..00c369919 100644 --- a/docs/webhook-config.md +++ b/docs/webhook-config.md @@ -10,37 +10,37 @@ Sample configuration (tested using IFTTT). "webhook": { "enabled": true, "url": "https://maker.ifttt.com/trigger//with/key//", - "webhookentry": { + "entry": { "value1": "Buying {pair}", "value2": "limit {limit:8f}", "value3": "{stake_amount:8f} {stake_currency}" }, - "webhookentrycancel": { + "entry_cancel": { "value1": "Cancelling Open Buy Order for {pair}", "value2": "limit {limit:8f}", "value3": "{stake_amount:8f} {stake_currency}" }, - "webhookentryfill": { + "entry_fill": { "value1": "Buy Order for {pair} filled", "value2": "at {open_rate:8f}", "value3": "" }, - "webhookexit": { + "exit": { "value1": "Exiting {pair}", "value2": "limit {limit:8f}", "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})" }, - "webhookexitcancel": { + "exit_cancel": { "value1": "Cancelling Open Exit Order for {pair}", "value2": "limit {limit:8f}", "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})" }, - "webhookexitfill": { + "exit_fill": { "value1": "Exit Order for {pair} filled", "value2": "at {close_rate:8f}.", "value3": "" }, - "webhookstatus": { + "status": { "value1": "Status: {status}", "value2": "", "value3": "" @@ -57,7 +57,7 @@ You can set the POST body format to Form-Encoded (default), JSON-Encoded, or raw "enabled": true, "url": "https://.cloud.mattermost.com/hooks/", "format": "json", - "webhookstatus": { + "status": { "text": "Status: {status}" } }, @@ -88,30 +88,30 @@ Optional parameters are available to enable automatic retries for webhook messag "url": "https://", "retries": 3, "retry_delay": 0.2, - "webhookstatus": { + "status": { "status": "Status: {status}" } }, ``` -Custom messages can be sent to Webhook endpoints via the dataprovider.send_msg() function. To enable this, set the `allow_custom_messages` option to `true`: +Custom messages can be sent to Webhook endpoints via the `self.dp.send_msg()` function from within the strategy. To enable this, set the `allow_custom_messages` option to `true`: ```json "webhook": { "enabled": true, "url": "https://", "allow_custom_messages": true, - "webhookstatus": { - "status": "Status: {status}" + "strategy_msg": { + "status": "StrategyMessage: {msg}" } }, ``` Different payloads can be configured for different events. Not all fields are necessary, but you should configure at least one of the dicts, otherwise the webhook will never be called. -### Webhookentry +### Entry -The fields in `webhook.webhookentry` are filled when the bot executes a long/short. Parameters are filled using string.format. +The fields in `webhook.entry` are filled when the bot executes a long/short. Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -131,9 +131,9 @@ Possible parameters are: * `current_rate` * `enter_tag` -### Webhookentrycancel +### Entry cancel -The fields in `webhook.webhookentrycancel` are filled when the bot cancels a long/short order. Parameters are filled using string.format. +The fields in `webhook.entry_cancel` are filled when the bot cancels a long/short order. Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -152,9 +152,9 @@ Possible parameters are: * `current_rate` * `enter_tag` -### Webhookentryfill +### Entry fill -The fields in `webhook.webhookentryfill` are filled when the bot filled a long/short order. Parameters are filled using string.format. +The fields in `webhook.entry_fill` are filled when the bot filled a long/short order. Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -173,9 +173,9 @@ Possible parameters are: * `current_rate` * `enter_tag` -### Webhookexit +### Exit -The fields in `webhook.webhookexit` are filled when the bot exits a trade. Parameters are filled using string.format. +The fields in `webhook.exit` are filled when the bot exits a trade. Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -197,9 +197,9 @@ Possible parameters are: * `open_date` * `close_date` -### Webhookexitfill +### Exit fill -The fields in `webhook.webhookexitfill` are filled when the bot fills a exit order (closes a Trade). Parameters are filled using string.format. +The fields in `webhook.exit_fill` are filled when the bot fills a exit order (closes a Trade). Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -222,9 +222,9 @@ Possible parameters are: * `open_date` * `close_date` -### Webhookexitcancel +### Exit cancel -The fields in `webhook.webhookexitcancel` are filled when the bot cancels a exit order. Parameters are filled using string.format. +The fields in `webhook.exit_cancel` are filled when the bot cancels a exit order. Parameters are filled using string.format. Possible parameters are: * `trade_id` @@ -247,9 +247,9 @@ Possible parameters are: * `open_date` * `close_date` -### Webhookstatus +### Status -The fields in `webhook.webhookstatus` are used for regular status messages (Started / Stopped / ...). Parameters are filled using string.format. +The fields in `webhook.status` are used for regular status messages (Started / Stopped / ...). Parameters are filled using string.format. The only possible value here is `{status}`. @@ -293,7 +293,6 @@ You can configure this as follows: } ``` - The above represents the default (`exit_fill` and `entry_fill` are optional and will default to the above configuration) - modifications are obviously possible. Available fields correspond to the fields for webhooks and are documented in the corresponding webhook sections. From 1aedf08ba52e70963301a27584d587ab44b7439a Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 20:45:50 +0200 Subject: [PATCH 106/258] Update tests --- tests/rpc/test_rpc_webhook.py | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py index 3bbb85d54..d06d2dade 100644 --- a/tests/rpc/test_rpc_webhook.py +++ b/tests/rpc/test_rpc_webhook.py @@ -3,7 +3,6 @@ from datetime import datetime, timedelta from unittest.mock import MagicMock -import pytest from requests import RequestException from freqtrade.enums import ExitType, RPCMessageType @@ -356,15 +355,6 @@ def test_exception_send_msg(default_conf, mocker, caplog): assert log_has("Problem calling Webhook. Please check your webhook configuration. " "Exception: 'DEADBEEF'", caplog) - msg_mock = MagicMock() - mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock) - msg = { - 'type': 'DEADBEEF', - 'status': 'whatever' - } - with pytest.raises(NotImplementedError): - webhook.send_msg(msg) - # Test no failure for not implemented but known messagetypes for e in RPCMessageType: msg = { From df5ae6625295e1c86b2b16b4b938124629636aa1 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 20:52:14 +0200 Subject: [PATCH 107/258] Refactor webhook method --- freqtrade/rpc/webhook.py | 65 +++++++++++++++++++---------------- tests/rpc/test_rpc_webhook.py | 13 ++----- 2 files changed, 38 insertions(+), 40 deletions(-) diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py index b46addee5..19c4166b3 100644 --- a/freqtrade/rpc/webhook.py +++ b/freqtrade/rpc/webhook.py @@ -3,7 +3,7 @@ This module manages webhook communication """ import logging import time -from typing import Any, Dict +from typing import Any, Dict, Optional from requests import RequestException, post @@ -41,38 +41,43 @@ class Webhook(RPCHandler): """ pass + def _get_value_dict(self, msg: Dict[str, Any]) -> Optional[Dict[str, Any]]: + whconfig = self._config['webhook'] + # Deprecated 2022.10 - only keep generic method. + if msg['type'] in [RPCMessageType.ENTRY]: + valuedict = whconfig.get('webhookentry') + elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]: + valuedict = whconfig.get('webhookentrycancel') + elif msg['type'] in [RPCMessageType.ENTRY_FILL]: + valuedict = whconfig.get('webhookentryfill') + elif msg['type'] == RPCMessageType.EXIT: + valuedict = whconfig.get('webhookexit') + elif msg['type'] == RPCMessageType.EXIT_FILL: + valuedict = whconfig.get('webhookexitfill') + elif msg['type'] == RPCMessageType.EXIT_CANCEL: + valuedict = whconfig.get('webhookexitcancel') + elif msg['type'] in (RPCMessageType.STATUS, + RPCMessageType.STARTUP, + RPCMessageType.WARNING): + valuedict = whconfig.get('webhookstatus') + elif msg['type'].value in whconfig: + # Allow all types ... + valuedict = whconfig.get(msg['type'].value) + elif msg['type'] in ( + RPCMessageType.PROTECTION_TRIGGER, + RPCMessageType.PROTECTION_TRIGGER_GLOBAL, + RPCMessageType.WHITELIST, + RPCMessageType.ANALYZED_DF, + RPCMessageType.STRATEGY_MSG): + # Don't fail for non-implemented types + return None + return valuedict + def send_msg(self, msg: Dict[str, Any]) -> None: """ Send a message to telegram channel """ try: - whconfig = self._config['webhook'] - # Deprecated 2022.10 - only keep generic method. - if msg['type'] in [RPCMessageType.ENTRY]: - valuedict = whconfig.get('webhookentry') - elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]: - valuedict = whconfig.get('webhookentrycancel') - elif msg['type'] in [RPCMessageType.ENTRY_FILL]: - valuedict = whconfig.get('webhookentryfill') - elif msg['type'] == RPCMessageType.EXIT: - valuedict = whconfig.get('webhookexit') - elif msg['type'] == RPCMessageType.EXIT_FILL: - valuedict = whconfig.get('webhookexitfill') - elif msg['type'] == RPCMessageType.EXIT_CANCEL: - valuedict = whconfig.get('webhookexitcancel') - elif msg['type'] in (RPCMessageType.STATUS, - RPCMessageType.STARTUP, - RPCMessageType.WARNING): - valuedict = whconfig.get('webhookstatus') - elif msg['type'].value in whconfig: - # Allow all types ... - valuedict = whconfig.get(msg['type'].value) - elif msg['type'] in ( - RPCMessageType.PROTECTION_TRIGGER, - RPCMessageType.PROTECTION_TRIGGER_GLOBAL, - RPCMessageType.WHITELIST, - RPCMessageType.ANALYZED_DF, - RPCMessageType.STRATEGY_MSG): - # Don't fail for non-implemented types - return + + valuedict = self._get_value_dict(msg) if not valuedict: logger.info("Message type '%s' not configured for webhooks", msg['type']) diff --git a/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py index d06d2dade..a8fd0c34b 100644 --- a/tests/rpc/test_rpc_webhook.py +++ b/tests/rpc/test_rpc_webhook.py @@ -336,20 +336,13 @@ def test_exception_send_msg(default_conf, mocker, caplog): caplog) default_conf["webhook"] = get_webhook_dict() - default_conf["webhook"]["webhookentry"]["value1"] = "{DEADBEEF:8f}" + default_conf["webhook"]["strategy_msg"] = {"value1": "{DEADBEEF:8f}"} msg_mock = MagicMock() mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock) webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf) msg = { - 'type': RPCMessageType.ENTRY, - 'exchange': 'Binance', - 'pair': 'ETH/BTC', - 'limit': 0.005, - 'order_type': 'limit', - 'stake_amount': 0.8, - 'stake_amount_fiat': 500, - 'stake_currency': 'BTC', - 'fiat_currency': 'EUR' + 'type': RPCMessageType.STRATEGY_MSG, + 'msg': 'hello world', } webhook.send_msg(msg) assert log_has("Problem calling Webhook. Please check your webhook configuration. " From 9454fb8f7bccc119dd4127b5c838dd535a7db96d Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 7 Oct 2022 20:59:49 +0200 Subject: [PATCH 108/258] Fix discord message sending --- freqtrade/rpc/discord.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py index c48508300..f6a044318 100644 --- a/freqtrade/rpc/discord.py +++ b/freqtrade/rpc/discord.py @@ -11,13 +11,12 @@ logger = logging.getLogger(__name__) class Discord(Webhook): def __init__(self, rpc: 'RPC', config: Config): - # super().__init__(rpc, config) + self._config = config self.rpc = rpc - self.config = config self.strategy = config.get('strategy', '') self.timeframe = config.get('timeframe', '') - self._url = self.config['discord']['webhook_url'] + self._url = config['discord']['webhook_url'] self._format = 'json' self._retries = 1 self._retry_delay = 0.1 @@ -31,19 +30,21 @@ class Discord(Webhook): def send_msg(self, msg) -> None: - if msg['type'].value in self.config['discord']: + if msg['type'].value in self._config['discord']: logger.info(f"Sending discord message: {msg}") msg['strategy'] = self.strategy msg['timeframe'] = self.timeframe - fields = self.config['discord'].get(msg['type'].value) + fields = self._config['discord'].get(msg['type'].value) color = 0x0000FF if msg['type'] in (RPCMessageType.EXIT, RPCMessageType.EXIT_FILL): profit_ratio = msg.get('profit_ratio') color = (0x00FF00 if profit_ratio > 0 else 0xFF0000) - + title = msg['type'].value + if 'pair' in msg: + title = f"Trade: {msg['pair']} {msg['type'].value}" embeds = [{ - 'title': f"Trade: {msg['pair']} {msg['type'].value}", + 'title': title, 'color': color, 'fields': [], From 4daf0000c7f3619563dfe640ca40fd9880fe5366 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Sat, 8 Oct 2022 16:15:48 +0200 Subject: [PATCH 109/258] Move check and add log warning --- freqtrade/freqai/data_kitchen.py | 15 +++++++++++---- freqtrade/freqai/freqai_interface.py | 2 -- tests/freqai/test_freqai_interface.py | 22 ++++++++++++---------- 3 files changed, 23 insertions(+), 16 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 23bba3f1a..de4a53a50 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -241,6 +241,7 @@ class FreqaiDataKitchen: self.data["filter_drop_index_training"] = drop_index else: + filtered_df = self.check_pred_labels(filtered_df) # 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_df).any(axis=1) @@ -460,7 +461,7 @@ class FreqaiDataKitchen: return df - def check_pred_labels(self, df_predictions: DataFrame) -> None: + def check_pred_labels(self, df_predictions: DataFrame) -> DataFrame: """ Check that prediction feature labels match training feature labels. :params: @@ -468,9 +469,15 @@ class FreqaiDataKitchen: """ train_labels = self.data_dictionary["train_features"].columns pred_labels = df_predictions.columns - if len(train_labels.difference(pred_labels)) != 0: - self.data_dictionary["prediction_features"] = df_predictions[train_labels] - return + num_diffs = len(pred_labels.difference(train_labels)) + if num_diffs != 0: + df_predictions = df_predictions[train_labels] + logger.warning( + f"Removed {num_diffs} features from prediction features, " + f"these were likely considered constant values during most recent training." + ) + + return df_predictions def principal_component_analysis(self) -> None: """ diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 62c814c72..5ac7bc32c 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -492,8 +492,6 @@ class IFreqaiModel(ABC): # ensure user is feeding the correct indicators to the model self.check_if_feature_list_matches_strategy(dk) - dk.check_pred_labels(dk.data_dictionary['prediction_features']) - if ft_params.get('inlier_metric_window', 0): dk.compute_inlier_metric(set_='predict') diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 238c0418c..c8444067a 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -157,7 +157,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): ("CatboostClassifier", 6, "freqai_test_classifier") ], ) -def test_start_backtesting(mocker, freqai_conf, model, num_files, strat): +def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog): freqai_conf.get("freqai", {}).update({"save_backtest_models": True}) freqai_conf['runmode'] = RunMode.BACKTEST Trade.use_db = False @@ -182,13 +182,21 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat): df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") for i in range(5): - df[f'constant_{i}'] = i + df.loc[:, f'%-constant_{i}'] = i 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) == num_files + assert log_has_re( + "Removed features ", + caplog, + ) + assert log_has_re( + "Removed 5 features from prediction features, ", + caplog, + ) Backtesting.cleanup() shutil.rmtree(Path(freqai.dk.full_path)) @@ -210,8 +218,6 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") - for i in range(5): - df[f'constant_{i}'] = i metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) @@ -237,8 +243,6 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") - for i in range(5): - df[f'constant_{i}'] = i metadata = {"pair": "ADA/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) @@ -262,8 +266,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") - for i in range(5): - df[f'constant_{i}'] = i + freqai.start_backtesting(df, metadata, freqai.dk) assert log_has_re( @@ -320,8 +323,7 @@ def test_follow_mode(mocker, freqai_conf): freqai.dd.load_all_pair_histories(timerange, freqai.dk) df = strategy.dp.get_pair_dataframe('ADA/BTC', '5m') - for i in range(5): - df[f'constant_{i}'] = i + freqai.start_live(df, metadata, strategy, freqai.dk) assert len(freqai.dk.return_dataframe.index) == 5702 From 8e3a4eca4198e157e794d2d2b1ef936764c9d615 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 9 Oct 2022 09:15:11 +0200 Subject: [PATCH 110/258] Remove unused type:ignore --- freqtrade/rpc/discord.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py index f6a044318..8be0eab68 100644 --- a/freqtrade/rpc/discord.py +++ b/freqtrade/rpc/discord.py @@ -52,7 +52,7 @@ class Discord(Webhook): for f in fields: for k, v in f.items(): v = v.format(**msg) - embeds[0]['fields'].append( # type: ignore + embeds[0]['fields'].append( {'name': k, 'value': v, 'inline': True}) # Send the message to discord channel From db1132bebd872c4ef12644510272584b8f67a2cd Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 9 Oct 2022 09:29:37 +0200 Subject: [PATCH 111/258] ensure required_candle_call_count is always set closes #7552 --- freqtrade/exchange/exchange.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index e06f5c7c6..b3da57d20 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -179,7 +179,7 @@ class Exchange: exchange_config, ccxt_async, ccxt_kwargs=ccxt_async_config) logger.info(f'Using Exchange "{self.name}"') - + self.required_candle_call_count = 1 if validate: # Initial markets load self._load_markets() @@ -1852,7 +1852,7 @@ class Exchange: def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType, since_ms: Optional[int], cache: bool) -> Coroutine: - not_all_data = self.required_candle_call_count > 1 + not_all_data = cache and self.required_candle_call_count > 1 if cache and (pair, timeframe, candle_type) in self._klines: candle_limit = self.ohlcv_candle_limit(timeframe, candle_type) min_date = date_minus_candles(timeframe, candle_limit - 5).timestamp() From 4f967fed97e2ca7abc2bae7a363d355225365ada Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 9 Oct 2022 10:52:01 +0200 Subject: [PATCH 112/258] Improve ccxt tests --- tests/exchange/test_ccxt_compat.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 6798cd2f7..9ff65cdc4 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -268,9 +268,8 @@ 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 ccxt__async_get_candle_history(self, exchange, exchangename, pair, timeframe): + def ccxt__async_get_candle_history(self, exchange, exchangename, pair, timeframe, candle_type): - candle_type = CandleType.SPOT timeframe_ms = timeframe_to_msecs(timeframe) now = timeframe_to_prev_date( timeframe, datetime.now(timezone.utc)) @@ -302,7 +301,8 @@ class TestCCXTExchange(): return pair = EXCHANGES[exchangename]['pair'] timeframe = EXCHANGES[exchangename]['timeframe'] - self.ccxt__async_get_candle_history(exchange, exchangename, pair, timeframe) + self.ccxt__async_get_candle_history( + exchange, exchangename, pair, timeframe, CandleType.SPOT) def test_ccxt__async_get_candle_history_futures(self, exchange_futures): exchange, exchangename = exchange_futures @@ -311,7 +311,8 @@ class TestCCXTExchange(): return pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) timeframe = EXCHANGES[exchangename]['timeframe'] - self.ccxt__async_get_candle_history(exchange, exchangename, pair, timeframe) + self.ccxt__async_get_candle_history( + exchange, exchangename, pair, timeframe, CandleType.FUTURES) def test_ccxt_fetch_funding_rate_history(self, exchange_futures): exchange, exchangename = exchange_futures From 4623c3ec1dad36c50d31c5e3ac47ef20987ce04b Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 9 Oct 2022 10:55:38 +0200 Subject: [PATCH 113/258] Improve test resiliance --- freqtrade/exchange/exchange.py | 4 ++-- tests/exchange/test_binance.py | 4 ++-- tests/exchange/test_exchange.py | 6 ++++-- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index b3da57d20..c41a84450 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -2018,8 +2018,8 @@ class Exchange: candle_limit = self.ohlcv_candle_limit( timeframe, candle_type=candle_type, since_ms=since_ms) - if candle_type != CandleType.SPOT: - params.update({'price': candle_type}) + if candle_type and candle_type != CandleType.SPOT: + params.update({'price': candle_type.value}) if candle_type != CandleType.FUNDING_RATE: data = await self._api_async.fetch_ohlcv( pair, timeframe=timeframe, since=since_ms, diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py index ef5cb1240..75aaa0081 100644 --- a/tests/exchange/test_binance.py +++ b/tests/exchange/test_binance.py @@ -5,7 +5,7 @@ from unittest.mock import MagicMock, PropertyMock import ccxt import pytest -from freqtrade.enums import MarginMode, TradingMode +from freqtrade.enums import CandleType, MarginMode, TradingMode from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException from tests.conftest import get_mock_coro, get_patched_exchange, log_has_re from tests.exchange.test_exchange import ccxt_exceptionhandlers @@ -542,7 +542,7 @@ def test__set_leverage_binance(mocker, default_conf): @pytest.mark.asyncio -@pytest.mark.parametrize('candle_type', ['mark', '']) +@pytest.mark.parametrize('candle_type', [CandleType.MARK, '']) async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, candle_type): ohlcv = [ [ diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 673dc7594..b07892f72 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2339,7 +2339,8 @@ async def test__async_kucoin_get_candle_history(default_conf, mocker, caplog): for _ in range(3): with pytest.raises(DDosProtection, match=r'429 Too Many Requests'): await exchange._async_get_candle_history( - "ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3) + "ETH/BTC", "5m", CandleType.SPOT, + since_ms=(arrow.utcnow().int_timestamp - 2000) * 1000, count=3) assert num_log_has_re(msg, caplog) == 3 caplog.clear() @@ -2355,7 +2356,8 @@ async def test__async_kucoin_get_candle_history(default_conf, mocker, caplog): for _ in range(3): with pytest.raises(DDosProtection, match=r'429 Too Many Requests'): await exchange._async_get_candle_history( - "ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3) + "ETH/BTC", "5m", CandleType.SPOT, + (arrow.utcnow().int_timestamp - 2000) * 1000, count=3) # Expect the "returned exception" message 12 times (4 retries * 3 (loop)) assert num_log_has_re(msg, caplog) == 12 assert num_log_has_re(msg2, caplog) == 9 From a10b2d003f99f684e2457724e95547e680e4d05c Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 9 Oct 2022 14:36:12 +0200 Subject: [PATCH 114/258] Add freqai timeframe validation (incl. test) closes #7543 --- freqtrade/configuration/config_validation.py | 21 ++++++++++++++++ tests/freqai/test_freqai_backtesting.py | 2 +- tests/test_configuration.py | 25 ++++++++++++++++++++ 3 files changed, 47 insertions(+), 1 deletion(-) diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py index 7055d9551..98f69c030 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -86,6 +86,7 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False) _validate_unlimited_amount(conf) _validate_ask_orderbook(conf) _validate_freqai_hyperopt(conf) + _validate_freqai_include_timeframes(conf) _validate_consumers(conf) validate_migrated_strategy_settings(conf) @@ -334,6 +335,26 @@ def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None: 'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.') +def _validate_freqai_include_timeframes(conf: Dict[str, Any]) -> None: + freqai_enabled = conf.get('freqai', {}).get('enabled', False) + if freqai_enabled: + main_tf = conf.get('timeframe', '5m') + freqai_include_timeframes = conf.get('freqai', {}).get('feature_parameters', {} + ).get('include_timeframes', []) + + from freqtrade.exchange import timeframe_to_seconds + main_tf_s = timeframe_to_seconds(main_tf) + offending_lines = [] + for tf in freqai_include_timeframes: + tf_s = timeframe_to_seconds(tf) + if tf_s < main_tf_s: + offending_lines.append(tf) + if offending_lines: + raise OperationalException( + f"Main timeframe of {main_tf} must be smaller or equal to FreqAI " + f"`include_timeframes`.Offending include-timeframes: {', '.join(offending_lines)}") + + def _validate_consumers(conf: Dict[str, Any]) -> None: emc_conf = conf.get('external_message_consumer', {}) if emc_conf.get('enabled', False): diff --git a/tests/freqai/test_freqai_backtesting.py b/tests/freqai/test_freqai_backtesting.py index b1881b2f5..5b9d3aefd 100644 --- a/tests/freqai/test_freqai_backtesting.py +++ b/tests/freqai/test_freqai_backtesting.py @@ -26,7 +26,7 @@ def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir, c '--config', 'config.json', '--datadir', str(testdatadir), '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'), - '--timeframe', '1h', + '--timeframe', '1m', '--strategy-list', CURRENT_TEST_STRATEGY ] args = get_args(args) diff --git a/tests/test_configuration.py b/tests/test_configuration.py index 2336e3585..ed3c84b1e 100644 --- a/tests/test_configuration.py +++ b/tests/test_configuration.py @@ -1028,6 +1028,31 @@ def test__validate_pricing_rules(default_conf, caplog) -> None: validate_config_consistency(conf) +def test__validate_freqai_include_timeframes(default_conf, caplog) -> None: + conf = deepcopy(default_conf) + conf.update({ + "freqai": { + "enabled": True, + "feature_parameters": { + "include_timeframes": ["1m", "5m"], + "include_corr_pairlist": [], + }, + "data_split_parameters": {}, + "model_training_parameters": {} + } + }) + with pytest.raises(OperationalException, match=r"Main timeframe of .*"): + validate_config_consistency(conf) + # Validation pass + conf.update({'timeframe': '1m'}) + validate_config_consistency(conf) + conf.update({'analyze_per_epoch': True}) + + with pytest.raises(OperationalException, + match=r"Using analyze-per-epoch .* not supported with a FreqAI strategy."): + validate_config_consistency(conf) + + def test__validate_consumers(default_conf, caplog) -> None: conf = deepcopy(default_conf) conf.update({ From 76b33359a939e8db89b55f268e9d650f78c51bf3 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 9 Oct 2022 20:22:42 +0200 Subject: [PATCH 115/258] add an optional metric tracker to collect train timings, inference timings, and cpu load data --- docs/freqai-parameter-table.md | 1 + freqtrade/constants.py | 2 + freqtrade/freqai/data_drawer.py | 55 ++++++++++++++++++++++++++-- freqtrade/freqai/freqai_interface.py | 21 ++++++++--- 4 files changed, 70 insertions(+), 9 deletions(-) diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md index 38d7ece94..4ec92521d 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -37,6 +37,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `noise_standard_deviation` | If set, FreqAI adds noise to the training features with the aim of preventing overfitting. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. `noise_standard_deviation` should be kept relative to the normalized space, i.e., between -1 and 1. In other words, since data in FreqAI is always normalized to be between -1 and 1, `noise_standard_deviation: 0.05` would result in 32% of the data being randomly increased/decreased by more than 2.5% (i.e., the percent of data falling within the first standard deviation).
**Datatype:** Integer.
Default: `0`. | `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. 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, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset.
**Datatype:** Float.
Default: `30`. | `reverse_train_test_order` | Split the feature dataset (see below) and use the latest data split for training 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, you should be careful to understand the unorthodox nature of this parameter before employing it.
**Datatype:** Boolean.
Default: `False` (no reversal). +| `write_metrics_to_disk` | Collect train timings, inference timings and cpu usage in json file.
**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` | The fraction of data that should be used for testing instead of training.
**Datatype:** Positive float < 1. diff --git a/freqtrade/constants.py b/freqtrade/constants.py index e0eb5e288..fc218772f 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -537,6 +537,8 @@ CONF_SCHEMA = { "properties": { "enabled": {"type": "boolean", "default": False}, "keras": {"type": "boolean", "default": False}, + "write_metrics_to_disk": {"type": "boolean", "default": False}, + "purge_old_models": {"type": "boolean", "default": True}, "conv_width": {"type": "integer", "default": 2}, "train_period_days": {"type": "integer", "default": 0}, "backtest_period_days": {"type": "number", "default": 7}, diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 31c76a68e..61ad6e077 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -9,6 +9,7 @@ from typing import Any, Dict, Tuple, TypedDict import numpy as np import pandas as pd +import psutil import rapidjson from joblib import dump, load from joblib.externals import cloudpickle @@ -78,25 +79,53 @@ class FreqaiDataDrawer: 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.metric_tracker_path = Path(self.full_path / "metric_tracker.json") self.follow_mode = follow_mode if follow_mode: self.create_follower_dict() self.load_drawer_from_disk() self.load_historic_predictions_from_disk() + self.load_metric_tracker_from_disk() self.training_queue: Dict[str, int] = {} self.history_lock = threading.Lock() self.save_lock = threading.Lock() self.pair_dict_lock = threading.Lock() + self.metric_tracker_lock = threading.Lock() self.old_DBSCAN_eps: Dict[str, float] = {} self.empty_pair_dict: pair_info = { "model_filename": "", "trained_timestamp": 0, "data_path": "", "extras": {}} + self.metric_tracker: Dict[str, Dict[str, list]] = {} + + def update_metric_tracker(self, metric: str, value: float, pair: str) -> None: + """ + General utility for adding and updating custom metrics. Typically used + for adding training performance, train timings, inferenc timings, cpu loads etc. + """ + with self.metric_tracker_lock: + if pair not in self.metric_tracker: + self.metric_tracker[pair] = {} + if metric not in self.metric_tracker[pair]: + self.metric_tracker[pair][metric] = [] + + self.metric_tracker[pair][metric].append(value) + + def collect_metrics(self, time_spent: float, pair: str): + """ + Add metrics to the metric tracker dictionary + """ + load1, load5, load15 = psutil.getloadavg() + cpus = psutil.cpu_count() + self.update_metric_tracker('train_time', time_spent, pair) + self.update_metric_tracker('cpu_load1min', load1 / cpus, pair) + self.update_metric_tracker('cpu_load5min', load5 / cpus, pair) + self.update_metric_tracker('cpu_load15min', load15 / cpus, pair) def load_drawer_from_disk(self): """ Locate and load a previously saved data drawer full of all pair model metadata in present model folder. - :return: bool - whether or not the drawer was located + Load any existing metric tracker that may be present. """ exists = self.pair_dictionary_path.is_file() if exists: @@ -110,7 +139,18 @@ class FreqaiDataDrawer: "sending null values back to strategy" ) - return exists + def load_metric_tracker_from_disk(self): + """ + Tries to load an existing metrics dictionary if the user + wants to collect metrics. + """ + if self.freqai_info.get('write_metrics_to_disk', False): + exists = self.metric_tracker_path.is_file() + if exists: + with open(self.metric_tracker_path, "r") as fp: + self.metric_tracker = json.load(fp) + else: + logger.info("Could not find existing metric tracker, starting from scratch") def load_historic_predictions_from_disk(self): """ @@ -146,7 +186,7 @@ class FreqaiDataDrawer: def save_historic_predictions_to_disk(self): """ - Save data drawer full of all pair model metadata in present model folder. + Save historic predictions pickle to disk """ with open(self.historic_predictions_path, "wb") as fp: cloudpickle.dump(self.historic_predictions, fp, protocol=cloudpickle.DEFAULT_PROTOCOL) @@ -154,6 +194,15 @@ class FreqaiDataDrawer: # create a backup shutil.copy(self.historic_predictions_path, self.historic_predictions_bkp_path) + def save_metric_tracker_to_disk(self): + """ + Save metric tracker of all pair metrics collected. + """ + with self.save_lock: + with open(self.metric_tracker_path, 'w') as fp: + rapidjson.dump(self.metric_tracker, fp, default=self.np_encoder, + number_mode=rapidjson.NM_NATIVE) + def save_drawer_to_disk(self): """ Save data drawer full of all pair model metadata in present model folder. diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 394b98e94..c6b79d1b5 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -144,7 +144,7 @@ class IFreqaiModel(ABC): dataframe = dk.remove_features_from_df(dk.return_dataframe) self.clean_up() if self.live: - self.inference_timer('stop') + self.inference_timer('stop', metadata["pair"]) return dataframe def clean_up(self): @@ -214,12 +214,14 @@ class IFreqaiModel(ABC): logger.warning(f"Training {pair} raised exception {msg.__class__.__name__}. " f"Message: {msg}, skipping.") - self.train_timer('stop') + self.train_timer('stop', pair) # only rotate the queue after the first has been trained. self.train_queue.rotate(-1) self.dd.save_historic_predictions_to_disk() + if self.freqai_info.get('write_metrics_to_disk', False): + self.dd.save_metric_tracker_to_disk() def start_backtesting( self, dataframe: DataFrame, metadata: dict, dk: FreqaiDataKitchen @@ -658,7 +660,7 @@ class IFreqaiModel(ABC): return - def inference_timer(self, do='start'): + def inference_timer(self, do: str = 'start', pair: str = ''): """ Timer designed to track the cumulative time spent in FreqAI for one pass through the whitelist. This will check if the time spent is more than 1/4 the time @@ -669,7 +671,10 @@ class IFreqaiModel(ABC): self.begin_time = time.time() elif do == 'stop': end = time.time() - self.inference_time += (end - self.begin_time) + time_spent = (end - self.begin_time) + if self.freqai_info.get('write_metrics_to_disk', False): + self.dd.update_metric_tracker('inference_time', time_spent, pair) + self.inference_time += time_spent if self.pair_it == self.total_pairs: logger.info( f'Total time spent inferencing pairlist {self.inference_time:.2f} seconds') @@ -680,7 +685,7 @@ class IFreqaiModel(ABC): self.inference_time = 0 return - def train_timer(self, do='start'): + def train_timer(self, do: str = 'start', pair: str = ''): """ Timer designed to track the cumulative time spent training the full pairlist in FreqAI. @@ -690,7 +695,11 @@ class IFreqaiModel(ABC): self.begin_time_train = time.time() elif do == 'stop': end = time.time() - self.train_time += (end - self.begin_time_train) + time_spent = (end - self.begin_time_train) + if self.freqai_info.get('write_metrics_to_disk', False): + self.dd.collect_metrics(time_spent, pair) + + self.train_time += time_spent if self.pair_it_train == self.total_pairs: logger.info( f'Total time spent training pairlist {self.train_time:.2f} seconds') From a4aa1b972c543b0ea256bb521f3c8d41a2585c80 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sun, 9 Oct 2022 21:11:37 +0200 Subject: [PATCH 116/258] isolate and standardize location of tensorboard files, add doc, ensure backtesting functionality --- docs/freqai-running.md | 14 ++++++++++++++ freqtrade/freqai/data_kitchen.py | 2 ++ freqtrade/freqai/freqai_interface.py | 5 +---- .../freqai/prediction_models/CatboostClassifier.py | 3 ++- .../freqai/prediction_models/CatboostRegressor.py | 3 ++- .../CatboostRegressorMultiTarget.py | 3 ++- 6 files changed, 23 insertions(+), 7 deletions(-) diff --git a/docs/freqai-running.md b/docs/freqai-running.md index b8994aed9..f6aa7b2e1 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -142,6 +142,20 @@ dataframe['outlier'] = np.where(dataframe['DI_values'] > self.di_max.value/10, 1 This specific hyperopt would help you understand the appropriate `DI_values` for your particular parameter space. +## Using Tensorboard + +Catboost models benefit from tracking training metrics via Tensorboard. You can take advantage of the FreqAI integration to track training and evaluation performance across all coins and across all retrainings. Tensorboard is activated via the following command: + +```bash +cd freqtrade +tensorboard --logdir user_data/models/unique-id +``` + +where `unique-id` is the `identifier` set in the `freqai` configuration file. This command must be run in a separate shell if the user wishes to view the output in their browser at 127.0.0.1:6060 (6060 is the default port used by Tensorboard). + +![tensorboard](assets/tensorboard.jpg) + + ## Setting up a follower You can indicate to the bot that it should not train models, but instead should look for models trained by a leader with a specific `identifier` by defining: diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7ea2daf02..b7473eacc 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -120,6 +120,8 @@ class FreqaiDataKitchen: / f"sub-train-{pair.split('/')[0]}_{trained_timestamp}" ) + Path(self.data_path / 'tensorboard').mkdir(parents=True, exist_ok=True) + return def make_train_test_datasets( diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 5ac7bc32c..58d8523a2 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -196,7 +196,6 @@ class IFreqaiModel(ABC): (_, trained_timestamp, _) = self.dd.get_pair_dict_info(pair) dk = FreqaiDataKitchen(self.config, self.live, pair) - dk.set_paths(pair, trained_timestamp) ( retrain, new_trained_timerange, @@ -267,9 +266,7 @@ class IFreqaiModel(ABC): ) trained_timestamp_int = int(trained_timestamp.stopts) - dk.data_path = Path( - dk.full_path / f"sub-train-{pair.split('/')[0]}_{trained_timestamp_int}" - ) + dk.set_paths(pair, trained_timestamp_int) dk.set_new_model_names(pair, trained_timestamp) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 31a865a8d..0565b15b5 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -1,4 +1,5 @@ import logging +from pathlib import Path from typing import Any, Dict from catboost import CatBoostClassifier, Pool @@ -34,7 +35,7 @@ class CatboostClassifier(BaseClassifierModel): cbr = CatBoostClassifier( allow_writing_files=True, loss_function='MultiClass', - train_dir=dk.data_path, + train_dir=Path(dk.data_path / 'tensorboard'), **self.model_training_parameters, ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index a04649d93..46f33a142 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -1,4 +1,5 @@ import logging +from pathlib import Path from typing import Any, Dict from catboost import CatBoostRegressor, Pool @@ -42,7 +43,7 @@ class CatboostRegressor(BaseRegressionModel): model = CatBoostRegressor( allow_writing_files=True, - train_dir=dk.data_path, + train_dir=Path(dk.data_path / 'tensorboard'), **self.model_training_parameters, ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index 292ad600a..085c13b86 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -1,4 +1,5 @@ import logging +from pathlib import Path from typing import Any, Dict from catboost import CatBoostRegressor, Pool @@ -27,7 +28,7 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): cbr = CatBoostRegressor( allow_writing_files=True, - train_dir=dk.data_path, + train_dir=Path(dk.data_path / 'tensorboard'), **self.model_training_parameters, ) From 3e8d8fd1b08e28f8ec231de9ee3be57a539b266e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 9 Oct 2022 15:04:52 -0600 Subject: [PATCH 117/258] refactor broadcasting to a queue per client --- freqtrade/rpc/api_server/api_ws.py | 24 ++++++++++++------- freqtrade/rpc/api_server/webserver.py | 1 + freqtrade/rpc/api_server/ws/channel.py | 32 ++++++++++++++++++++------ 3 files changed, 42 insertions(+), 15 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index f55b2dbd3..b60210143 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -1,6 +1,7 @@ import logging from typing import Any, Dict +import websockets from fastapi import APIRouter, Depends, WebSocketDisconnect from fastapi.websockets import WebSocket, WebSocketState from pydantic import ValidationError @@ -102,7 +103,6 @@ async def message_endpoint( """ try: channel = await channel_manager.on_connect(ws) - if await is_websocket_alive(ws): logger.info(f"Consumer connected - {channel}") @@ -115,26 +115,34 @@ async def message_endpoint( # Process the request here await _process_consumer_request(request, channel, rpc) - except WebSocketDisconnect: + except ( + WebSocketDisconnect, + websockets.exceptions.WebSocketException + ): # Handle client disconnects logger.info(f"Consumer disconnected - {channel}") - await channel_manager.on_disconnect(ws) - except Exception as e: - logger.info(f"Consumer connection failed - {channel}") - logger.exception(e) + except RuntimeError: # Handle cases like - # RuntimeError('Cannot call "send" once a closed message has been sent') + pass + except Exception as e: + logger.info(f"Consumer connection failed - {channel}") + logger.debug(e, exc_info=e) + finally: await channel_manager.on_disconnect(ws) else: + if channel: + await channel_manager.on_disconnect(ws) await ws.close() except RuntimeError: # WebSocket was closed - await channel_manager.on_disconnect(ws) - + # Do nothing + pass 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) + finally: await channel_manager.on_disconnect(ws) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 53af91477..4a09fd78e 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -245,6 +245,7 @@ class ApiServer(RPCHandler): use_colors=False, log_config=None, access_log=True if verbosity != 'error' else False, + ws_ping_interval=None # We do this explicitly ourselves ) try: self._server = UvicornServer(uvconfig) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 69a32e266..8c6c56d6e 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -1,6 +1,7 @@ +import asyncio import logging from threading import RLock -from typing import List, Optional, Type +from typing import Any, Dict, List, Optional, Type from uuid import uuid4 from fastapi import WebSocket as FastAPIWebSocket @@ -34,6 +35,8 @@ class WebSocketChannel: self._serializer_cls = serializer_cls self._subscriptions: List[str] = [] + self.queue: asyncio.Queue[Dict[str, Any]] = asyncio.Queue() + self._relay_task = asyncio.create_task(self.relay()) # Internal event to signify a closed websocket self._closed = False @@ -72,6 +75,7 @@ class WebSocketChannel: """ self._closed = True + self._relay_task.cancel() def is_closed(self) -> bool: """ @@ -95,6 +99,20 @@ class WebSocketChannel: """ return message_type in self._subscriptions + async def relay(self): + """ + Relay messages from the channel's queue and send them out. This is started + as a task. + """ + while True: + message = await self.queue.get() + try: + await self.send(message) + self.queue.task_done() + except RuntimeError: + # The connection was closed, just exit the task + return + class ChannelManager: def __init__(self): @@ -155,12 +173,12 @@ class ChannelManager: with self._lock: message_type = data.get('type') for websocket, channel in self.channels.copy().items(): - try: - if channel.subscribed_to(message_type): - await channel.send(data) - except RuntimeError: - # Handle cannot send after close cases - await self.on_disconnect(websocket) + if channel.subscribed_to(message_type): + if not channel.queue.full(): + channel.queue.put_nowait(data) + else: + logger.info(f"Channel {channel} is too far behind, disconnecting") + await self.on_disconnect(websocket) async def send_direct(self, channel, data): """ From 2f64a086238b383312dd2db9aea104690aac5a8a Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 9 Oct 2022 15:11:58 -0600 Subject: [PATCH 118/258] set channel queue maxsize to 32 --- freqtrade/rpc/api_server/ws/channel.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 8c6c56d6e..91875abfb 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -35,7 +35,7 @@ class WebSocketChannel: self._serializer_cls = serializer_cls self._subscriptions: List[str] = [] - self.queue: asyncio.Queue[Dict[str, Any]] = asyncio.Queue() + self.queue: asyncio.Queue[Dict[str, Any]] = asyncio.Queue(maxsize=32) self._relay_task = asyncio.create_task(self.relay()) # Internal event to signify a closed websocket From 2c76dd9e39c8742dfc39b82eae407f11c9be7c91 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 9 Oct 2022 15:23:56 -0600 Subject: [PATCH 119/258] change wait timeout to 30 seconds to better support reverse proxies --- 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 f5ba4b490..a182ddc57 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -62,7 +62,7 @@ class ExternalMessageConsumer: self.enabled = self._emc_config.get('enabled', False) self.producers: List[Producer] = self._emc_config.get('producers', []) - self.wait_timeout = self._emc_config.get('wait_timeout', 300) # in seconds + self.wait_timeout = self._emc_config.get('wait_timeout', 30) # 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 From 71bbffd10a0fcac0ca5992d7ab4c62e0ed6e9bf8 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 9 Oct 2022 18:49:04 -0600 Subject: [PATCH 120/258] update ws channel send to add data to queue --- freqtrade/rpc/api_server/ws/channel.py | 12 +++++++++--- freqtrade/rpc/external_message_consumer.py | 5 +++++ 2 files changed, 14 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 91875abfb..7cee95e6d 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -51,12 +51,18 @@ class WebSocketChannel: def remote_addr(self): return self._websocket.remote_addr - async def send(self, data): + async def _send(self, data): """ Send data on the wrapped websocket """ await self._wrapped_ws.send(data) + async def send(self, data): + """ + Add the data to the queue to be sent + """ + self.queue.put_nowait(data) + async def recv(self): """ Receive data on the wrapped websocket @@ -107,7 +113,7 @@ class WebSocketChannel: while True: message = await self.queue.get() try: - await self.send(message) + await self._send(message) self.queue.task_done() except RuntimeError: # The connection was closed, just exit the task @@ -175,7 +181,7 @@ class ChannelManager: for websocket, channel in self.channels.copy().items(): if channel.subscribed_to(message_type): if not channel.queue.full(): - channel.queue.put_nowait(data) + await channel.send(data) else: logger.info(f"Channel {channel} is too far behind, disconnecting") await self.on_disconnect(websocket) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index a182ddc57..88ade185e 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -174,6 +174,7 @@ class ExternalMessageConsumer: :param producer: Dictionary containing producer info :param lock: An asyncio Lock """ + channel = None while self._running: try: host, port = producer['host'], producer['port'] @@ -224,6 +225,10 @@ class ExternalMessageConsumer: logger.exception(e) continue + finally: + if channel: + await channel.close() + async def _receive_messages( self, channel: WebSocketChannel, From db8cf6c957cdf56b3c1bb7ec8f27c445a0933070 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Sun, 9 Oct 2022 18:51:52 -0600 Subject: [PATCH 121/258] disable ping interval in client --- freqtrade/rpc/external_message_consumer.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py index 88ade185e..01bc974ad 100644 --- a/freqtrade/rpc/external_message_consumer.py +++ b/freqtrade/rpc/external_message_consumer.py @@ -183,7 +183,11 @@ class ExternalMessageConsumer: ws_url = f"ws://{host}:{port}/api/v1/message/ws?token={token}" # This will raise InvalidURI if the url is bad - async with websockets.connect(ws_url, max_size=self.message_size_limit) as ws: + async with websockets.connect( + ws_url, + max_size=self.message_size_limit, + ping_interval=None + ) as ws: channel = WebSocketChannel(ws, channel_id=name) logger.info(f"Producer connection success - {channel}") From 337ea04ba0dcf92e758dc082e08b1126a6e0877b Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:02:27 +0000 Subject: [PATCH 122/258] Bump nbconvert from 7.0.0 to 7.2.1 Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 7.0.0 to 7.2.1. - [Release notes](https://github.com/jupyter/nbconvert/releases) - [Changelog](https://github.com/jupyter/nbconvert/blob/main/CHANGELOG.md) - [Commits](https://github.com/jupyter/nbconvert/compare/7.0.0...v7.2.1) --- updated-dependencies: - dependency-name: nbconvert dependency-type: direct:development update-type: version-update:semver-minor ... 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 ebe278e10..f4120dc5e 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -20,7 +20,7 @@ isort==5.10.1 time-machine==2.8.2 # Convert jupyter notebooks to markdown documents -nbconvert==7.0.0 +nbconvert==7.2.1 # mypy types types-cachetools==5.2.1 From 40afa079b12f01810cd9d48caaa416caf81801f9 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:02:31 +0000 Subject: [PATCH 123/258] Bump tabulate from 0.8.10 to 0.9.0 Bumps [tabulate](https://github.com/astanin/python-tabulate) from 0.8.10 to 0.9.0. - [Release notes](https://github.com/astanin/python-tabulate/releases) - [Changelog](https://github.com/astanin/python-tabulate/blob/master/CHANGELOG) - [Commits](https://github.com/astanin/python-tabulate/compare/v0.8.10...v0.9.0) --- updated-dependencies: - dependency-name: tabulate 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 4f4b30d0c..cf2f14c77 100644 --- a/requirements.txt +++ b/requirements.txt @@ -17,7 +17,7 @@ urllib3==1.26.12 jsonschema==4.16.0 TA-Lib==0.4.25 technical==1.3.0 -tabulate==0.8.10 +tabulate==0.9.0 pycoingecko==3.0.0 jinja2==3.1.2 tables==3.7.0 From dab2759c2194f88f03cc1bab00382c0c756a8217 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:02:43 +0000 Subject: [PATCH 124/258] Bump scipy from 1.9.1 to 1.9.2 Bumps [scipy](https://github.com/scipy/scipy) from 1.9.1 to 1.9.2. - [Release notes](https://github.com/scipy/scipy/releases) - [Commits](https://github.com/scipy/scipy/compare/v1.9.1...v1.9.2) --- 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 efa31272a..3e76a6c22 100644 --- a/requirements-hyperopt.txt +++ b/requirements-hyperopt.txt @@ -2,7 +2,7 @@ -r requirements.txt # Required for hyperopt -scipy==1.9.1 +scipy==1.9.2 scikit-learn==1.1.2 scikit-optimize==0.9.0 filelock==3.8.0 From 8bb7b94f8de4326b0ca7c4be5e2db1d3dd7d2e0b Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:02:53 +0000 Subject: [PATCH 125/258] Bump ccxt from 1.95.2 to 1.95.30 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.95.2 to 1.95.30. - [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/1.95.2...1.95.30) --- 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 4f4b30d0c..73ffed8d9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ pandas==1.5.0; platform_machine != 'armv7l' pandas==1.4.3; platform_machine == 'armv7l' pandas-ta==0.3.14b -ccxt==1.95.2 +ccxt==1.95.30 # Pin cryptography for now due to rust build errors with piwheels cryptography==38.0.1 aiohttp==3.8.3 From 9d2f281ca6c89b79f766e6a9c0658b15e7bd577c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:02:57 +0000 Subject: [PATCH 126/258] Bump pytest-mock from 3.9.0 to 3.10.0 Bumps [pytest-mock](https://github.com/pytest-dev/pytest-mock) from 3.9.0 to 3.10.0. - [Release notes](https://github.com/pytest-dev/pytest-mock/releases) - [Changelog](https://github.com/pytest-dev/pytest-mock/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pytest-dev/pytest-mock/compare/v3.9.0...v3.10.0) --- updated-dependencies: - dependency-name: pytest-mock dependency-type: direct:development update-type: version-update:semver-minor ... 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 ebe278e10..ed0b9d73c 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -13,7 +13,7 @@ pre-commit==2.20.0 pytest==7.1.3 pytest-asyncio==0.19.0 pytest-cov==4.0.0 -pytest-mock==3.9.0 +pytest-mock==3.10.0 pytest-random-order==1.0.4 isort==5.10.1 # For datetime mocking From 935adc99aed9fd1249f077a3408993275f51bc8e Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 03:03:06 +0000 Subject: [PATCH 127/258] Bump types-tabulate from 0.8.11 to 0.9.0.0 Bumps [types-tabulate](https://github.com/python/typeshed) from 0.8.11 to 0.9.0.0. - [Release notes](https://github.com/python/typeshed/releases) - [Commits](https://github.com/python/typeshed/commits) --- updated-dependencies: - dependency-name: types-tabulate dependency-type: direct:development update-type: version-update:semver-minor ... 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 ebe278e10..27a4d83a2 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -26,5 +26,5 @@ nbconvert==7.0.0 types-cachetools==5.2.1 types-filelock==3.2.7 types-requests==2.28.11 -types-tabulate==0.8.11 +types-tabulate==0.9.0.0 types-python-dateutil==2.8.19 From c1dfa837bddf6c98007a82e1c307692da5536d8e Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 04:56:43 +0000 Subject: [PATCH 128/258] Bump mypy from 0.981 to 0.982 Bumps [mypy](https://github.com/python/mypy) from 0.981 to 0.982. - [Release notes](https://github.com/python/mypy/releases) - [Commits](https://github.com/python/mypy/compare/v0.981...v0.982) --- updated-dependencies: - dependency-name: mypy dependency-type: direct:development update-type: version-update:semver-minor ... 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 f4120dc5e..f8238a07c 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -8,7 +8,7 @@ coveralls==3.3.1 flake8==5.0.4 flake8-tidy-imports==4.8.0 -mypy==0.981 +mypy==0.982 pre-commit==2.20.0 pytest==7.1.3 pytest-asyncio==0.19.0 From 3fcba2fb8d82de03fcd84936b7b4d45222bc42d8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 08:03:40 +0200 Subject: [PATCH 129/258] Remove hard-pin on python version in ci --- .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 195370339..034c5352d 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", "3.10.6"] + python-version: ["3.8", "3.9", "3.10"] steps: - uses: actions/checkout@v3 @@ -121,7 +121,7 @@ jobs: strategy: matrix: os: [ macos-latest ] - python-version: ["3.8", "3.9", "3.10.6"] + python-version: ["3.8", "3.9", "3.10"] steps: - uses: actions/checkout@v3 @@ -205,7 +205,7 @@ jobs: strategy: matrix: os: [ windows-latest ] - python-version: ["3.8", "3.9", "3.10.6"] + python-version: ["3.8", "3.9", "3.10"] steps: - uses: actions/checkout@v3 From 13529fabb19a5efaca61088c886228a261b607a7 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 08:16:26 +0200 Subject: [PATCH 130/258] types-tabulate in pre-commit --- .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 2cad0a7d3..e20f0916e 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -16,7 +16,7 @@ repos: - types-cachetools==5.2.1 - types-filelock==3.2.7 - types-requests==2.28.11 - - types-tabulate==0.8.11 + - types-tabulate==0.9.0.0 - types-python-dateutil==2.8.19 # stages: [push] From 5218fb1df5e394d791d0d1af0721451adb831180 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 10 Oct 2022 06:49:11 +0000 Subject: [PATCH 131/258] Bump types-requests from 2.28.11 to 2.28.11.2 Bumps [types-requests](https://github.com/python/typeshed) from 2.28.11 to 2.28.11.2. - [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 7ba4cc8d2..015f4509b 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -25,6 +25,6 @@ nbconvert==7.2.1 # mypy types types-cachetools==5.2.1 types-filelock==3.2.7 -types-requests==2.28.11 +types-requests==2.28.11.2 types-tabulate==0.9.0.0 types-python-dateutil==2.8.19 From f120c66987bc1cd892627c3c4861fcf1d271373c Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 08:52:38 +0200 Subject: [PATCH 132/258] types-requests - update pre-commit --- .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 e20f0916e..7abe5659a 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==2.28.11 + - types-requests==2.28.11.2 - types-tabulate==0.9.0.0 - types-python-dateutil==2.8.19 # stages: [push] From d0b163764efdcf5dca79af47108cbf3f88df02a4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 07:41:38 +0000 Subject: [PATCH 133/258] Run coveralls only when needed --- .github/workflows/ci.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 034c5352d..f7bbf23d5 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -74,7 +74,8 @@ jobs: if: matrix.python-version == '3.9' && matrix.os == 'ubuntu-22.04' - name: Coveralls - if: (runner.os == 'Linux' && matrix.python-version == '3.9') + if: (runner.os == 'Linux' && matrix.python-version == '3.10' && matrix.os == 'ubuntu-22.04' +) env: # Coveralls token. Not used as secret due to github not providing secrets to forked repositories COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu From 6be9b81f4cddfff670767dced5feb3db8b74f807 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 12:12:30 +0200 Subject: [PATCH 134/258] Fix workflow syntax error --- .github/workflows/ci.yml | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index f7bbf23d5..47b9a9279 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -74,8 +74,7 @@ jobs: if: matrix.python-version == '3.9' && matrix.os == 'ubuntu-22.04' - name: Coveralls - if: (runner.os == 'Linux' && matrix.python-version == '3.10' && matrix.os == 'ubuntu-22.04' -) + if: (runner.os == 'Linux' && matrix.python-version == '3.10' && matrix.os == 'ubuntu-22.04') env: # Coveralls token. Not used as secret due to github not providing secrets to forked repositories COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu @@ -442,4 +441,4 @@ jobs: with: severity: info details: Deploy Succeeded! - webhookUrl: ${{ secrets.DISCORD_WEBHOOK }} \ No newline at end of file + webhookUrl: ${{ secrets.DISCORD_WEBHOOK }} From d3b2b2972e9b32ec193f94b1b7c0a19b747a6658 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 11:54:13 +0000 Subject: [PATCH 135/258] Update pairlist docstring to be less missleading --- freqtrade/plugins/pairlist/AgeFilter.py | 2 +- freqtrade/plugins/pairlist/IPairList.py | 6 +++--- freqtrade/plugins/pairlist/OffsetFilter.py | 2 +- freqtrade/plugins/pairlist/PerformanceFilter.py | 2 +- freqtrade/plugins/pairlist/PrecisionFilter.py | 2 +- freqtrade/plugins/pairlist/PriceFilter.py | 2 +- freqtrade/plugins/pairlist/ProducerPairList.py | 4 ++-- freqtrade/plugins/pairlist/ShuffleFilter.py | 2 +- freqtrade/plugins/pairlist/SpreadFilter.py | 2 +- freqtrade/plugins/pairlist/StaticPairList.py | 4 ++-- freqtrade/plugins/pairlist/VolatilityFilter.py | 2 +- freqtrade/plugins/pairlist/VolumePairList.py | 4 ++-- freqtrade/plugins/pairlist/rangestabilityfilter.py | 2 +- 13 files changed, 18 insertions(+), 18 deletions(-) diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py index 70638936a..7c8cdb5ab 100644 --- a/freqtrade/plugins/pairlist/AgeFilter.py +++ b/freqtrade/plugins/pairlist/AgeFilter.py @@ -70,7 +70,7 @@ class AgeFilter(IPairList): def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: """ :param pairlist: pairlist to filter or sort - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new allowlist """ needed_pairs: ListPairsWithTimeframes = [ diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py index c02ba5ef5..60abac6a1 100644 --- a/freqtrade/plugins/pairlist/IPairList.py +++ b/freqtrade/plugins/pairlist/IPairList.py @@ -69,7 +69,7 @@ class IPairList(LoggingMixin, ABC): filter_pairlist() method. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.fetch_tickers() + :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ raise NotImplementedError() @@ -85,7 +85,7 @@ class IPairList(LoggingMixin, ABC): it will raise the exception if a Pairlist Handler is used at the first position in the chain. - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: List of pairs """ raise OperationalException("This Pairlist Handler should not be used " @@ -103,7 +103,7 @@ class IPairList(LoggingMixin, ABC): own filtration. :param pairlist: pairlist to filter or sort - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ if self._enabled: diff --git a/freqtrade/plugins/pairlist/OffsetFilter.py b/freqtrade/plugins/pairlist/OffsetFilter.py index 149befdeb..c9531ece1 100644 --- a/freqtrade/plugins/pairlist/OffsetFilter.py +++ b/freqtrade/plugins/pairlist/OffsetFilter.py @@ -47,7 +47,7 @@ class OffsetFilter(IPairList): 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ if self._offset > len(pairlist): diff --git a/freqtrade/plugins/pairlist/PerformanceFilter.py b/freqtrade/plugins/pairlist/PerformanceFilter.py index c29b4f337..4cc92175a 100644 --- a/freqtrade/plugins/pairlist/PerformanceFilter.py +++ b/freqtrade/plugins/pairlist/PerformanceFilter.py @@ -44,7 +44,7 @@ class PerformanceFilter(IPairList): Filters and sorts pairlist and returns the allowlist 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new allowlist """ # Get the trading performance for pairs from database diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py index 8f1c9b839..98cb3ba46 100644 --- a/freqtrade/plugins/pairlist/PrecisionFilter.py +++ b/freqtrade/plugins/pairlist/PrecisionFilter.py @@ -49,7 +49,7 @@ class PrecisionFilter(IPairList): Check if pair has enough room to add a stoploss to avoid "unsellable" buys of very low value pairs. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.fetch_tickers() + :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ if ticker.get('last', None) is None: diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index f2952001a..a6b400a38 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -68,7 +68,7 @@ class PriceFilter(IPairList): """ Check if if one price-step (pip) is > than a certain barrier. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.fetch_tickers() + :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ if ticker.get('last', None) is None or ticker.get('last') == 0: diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index 50b674e60..740cb4ec2 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -71,7 +71,7 @@ class ProducerPairList(IPairList): def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: List of pairs """ pairs = self._filter_pairlist(None) @@ -84,7 +84,7 @@ class ProducerPairList(IPairList): 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ return self._filter_pairlist(pairlist) diff --git a/freqtrade/plugins/pairlist/ShuffleFilter.py b/freqtrade/plugins/pairlist/ShuffleFilter.py index b6b5fc3c8..6eb4231bc 100644 --- a/freqtrade/plugins/pairlist/ShuffleFilter.py +++ b/freqtrade/plugins/pairlist/ShuffleFilter.py @@ -52,7 +52,7 @@ class ShuffleFilter(IPairList): 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ # Shuffle is done inplace diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py index 1f20af305..1f6d4f687 100644 --- a/freqtrade/plugins/pairlist/SpreadFilter.py +++ b/freqtrade/plugins/pairlist/SpreadFilter.py @@ -48,7 +48,7 @@ class SpreadFilter(IPairList): """ Validate spread for the ticker :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.fetch_tickers() + :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ if 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']: diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py index 83a0fa0c8..5b1337754 100644 --- a/freqtrade/plugins/pairlist/StaticPairList.py +++ b/freqtrade/plugins/pairlist/StaticPairList.py @@ -42,7 +42,7 @@ class StaticPairList(IPairList): def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: List of pairs """ if self._allow_inactive: @@ -58,7 +58,7 @@ class StaticPairList(IPairList): 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ pairlist_ = deepcopy(pairlist) diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py index c9af3a7b3..c06fc09ba 100644 --- a/freqtrade/plugins/pairlist/VolatilityFilter.py +++ b/freqtrade/plugins/pairlist/VolatilityFilter.py @@ -66,7 +66,7 @@ class VolatilityFilter(IPairList): """ Validate trading range :param pairlist: pairlist to filter or sort - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new allowlist """ needed_pairs: ListPairsWithTimeframes = [ diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py index b290f76aa..bfecbd62a 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -113,7 +113,7 @@ class VolumePairList(IPairList): def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: List of pairs """ # Generate dynamic whitelist @@ -150,7 +150,7 @@ class VolumePairList(IPairList): 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. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new whitelist """ if self._use_range: diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py index 1bc7ad48f..ca844f003 100644 --- a/freqtrade/plugins/pairlist/rangestabilityfilter.py +++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py @@ -64,7 +64,7 @@ class RangeStabilityFilter(IPairList): """ Validate trading range :param pairlist: pairlist to filter or sort - :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :param tickers: Tickers (from exchange.get_tickers). May be cached. :return: new allowlist """ needed_pairs: ListPairsWithTimeframes = [ From 60de192d47173f60dd666bf5c47517bc50c09bdf Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 12:13:41 +0000 Subject: [PATCH 136/258] Update Classifier docstrings --- freqtrade/freqai/prediction_models/CatboostClassifier.py | 5 ++--- freqtrade/freqai/prediction_models/LightGBMClassifier.py | 5 ++--- freqtrade/freqai/prediction_models/XGBoostClassifier.py | 5 ++--- 3 files changed, 6 insertions(+), 9 deletions(-) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 60536e6de..9a77644ed 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -20,9 +20,8 @@ class CatboostClassifier(BaseClassifierModel): 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. + :param data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. """ train_data = Pool( diff --git a/freqtrade/freqai/prediction_models/LightGBMClassifier.py b/freqtrade/freqai/prediction_models/LightGBMClassifier.py index 3eec516ba..e467ad3c1 100644 --- a/freqtrade/freqai/prediction_models/LightGBMClassifier.py +++ b/freqtrade/freqai/prediction_models/LightGBMClassifier.py @@ -20,9 +20,8 @@ class LightGBMClassifier(BaseClassifierModel): 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. + :param data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. """ if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0: diff --git a/freqtrade/freqai/prediction_models/XGBoostClassifier.py b/freqtrade/freqai/prediction_models/XGBoostClassifier.py index 8bf5d6281..3b14471c1 100644 --- a/freqtrade/freqai/prediction_models/XGBoostClassifier.py +++ b/freqtrade/freqai/prediction_models/XGBoostClassifier.py @@ -26,9 +26,8 @@ class XGBoostClassifier(BaseClassifierModel): 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. + :param data_dictionary: the dictionary constructed by DataHandler to hold + all the training and test data/labels. """ X = data_dictionary["train_features"].to_numpy() From eaae9c9e037890d38b5a6a8b1cc9883296285302 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 12:15:30 +0000 Subject: [PATCH 137/258] Update docstring format --- .../freqai/base_models/BaseClassifierModel.py | 2 +- .../freqai/base_models/BaseRegressionModel.py | 2 +- freqtrade/freqai/data_drawer.py | 20 +++---- freqtrade/freqai/data_kitchen.py | 60 +++++++++---------- freqtrade/freqai/freqai_interface.py | 10 ++-- .../prediction_models/XGBoostClassifier.py | 2 +- 6 files changed, 44 insertions(+), 52 deletions(-) diff --git a/freqtrade/freqai/base_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py index 09f1bf98c..691c27e23 100644 --- a/freqtrade/freqai/base_models/BaseClassifierModel.py +++ b/freqtrade/freqai/base_models/BaseClassifierModel.py @@ -78,7 +78,7 @@ class BaseClassifierModel(IFreqaiModel): ) -> 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. + :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 diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py index 5d89dd356..79f6f0d3c 100644 --- a/freqtrade/freqai/base_models/BaseRegressionModel.py +++ b/freqtrade/freqai/base_models/BaseRegressionModel.py @@ -77,7 +77,7 @@ class BaseRegressionModel(IFreqaiModel): ) -> 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. + :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 diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 31c76a68e..465ba27f5 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -412,9 +412,8 @@ class FreqaiDataDrawer: def save_data(self, model: Any, coin: str, dk: FreqaiDataKitchen) -> None: """ Saves all data associated with a model for a single sub-train time range - :params: - :model: User trained model which can be reused for inferencing to generate - predictions + :param model: User trained model which can be reused for inferencing to generate + predictions """ if not dk.data_path.is_dir(): @@ -532,8 +531,7 @@ class FreqaiDataDrawer: Append new candles to our stores historic data (in memory) so that we do not need to load candle history from disk and we dont need to pinging exchange multiple times for the same candle. - :params: - dataframe: DataFrame = strategy provided dataframe + :param dataframe: DataFrame = strategy provided dataframe """ feat_params = self.freqai_info["feature_parameters"] with self.history_lock: @@ -579,9 +577,8 @@ class FreqaiDataDrawer: """ Load pair histories for all whitelist and corr_pairlist pairs. Only called once upon startup of bot. - :params: - timerange: TimeRange = full timerange required to populate all indicators - for training according to user defined train_period_days + :param timerange: TimeRange = full timerange required to populate all indicators + for training according to user defined train_period_days """ history_data = self.historic_data @@ -604,10 +601,9 @@ class FreqaiDataDrawer: """ Searches through our historic_data in memory and returns the dataframes relevant to the present pair. - :params: - timerange: TimeRange = full timerange required to populate all indicators - for training according to user defined train_period_days - metadata: dict = strategy furnished pair metadata + :param timerange: TimeRange = full timerange required to populate all indicators + for training according to user defined train_period_days + :param metadata: dict = strategy furnished pair metadata """ with self.history_lock: corr_dataframes: Dict[Any, Any] = {} diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7ea2daf02..0a4dd960c 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -107,9 +107,8 @@ class FreqaiDataKitchen: ) -> None: """ Set the paths to the data for the present coin/botloop - :params: - metadata: dict = strategy furnished pair metadata - trained_timestamp: int = timestamp of most recent training + :param metadata: dict = strategy furnished pair metadata + :param trained_timestamp: int = timestamp of most recent training """ self.full_path = Path( self.config["user_data_dir"] / "models" / str(self.freqai_config.get("identifier")) @@ -129,8 +128,8 @@ class FreqaiDataKitchen: Given the dataframe for the full history for training, split the data into training and test data according to user specified parameters in configuration file. - :filtered_dataframe: cleaned dataframe ready to be split. - :labels: cleaned labels ready to be split. + :param filtered_dataframe: cleaned dataframe ready to be split. + :param labels: cleaned labels ready to be split. """ feat_dict = self.freqai_config["feature_parameters"] @@ -189,13 +188,14 @@ class FreqaiDataKitchen: remove all NaNs. Any row with a NaN is removed from training dataset or replaced with 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_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. + + :param unfiltered_df: the full dataframe for the present training period + :param training_feature_list: list, the training feature list constructed by + self.build_feature_list() according to user specified + parameters in the configuration file. + :param labels: the labels for the dataset + :param training_filter: boolean which lets the function know if it is training data or + prediction data to be filtered. :returns: :filtered_df: dataframe cleaned of NaNs and only containing the user requested feature set. @@ -285,8 +285,8 @@ class FreqaiDataKitchen: def normalize_data(self, data_dictionary: Dict) -> Dict[Any, Any]: """ Normalize all data in the data_dictionary according to the training dataset - :params: - :data_dictionary: dictionary containing the cleaned and split training/test data/labels + :param data_dictionary: dictionary containing the cleaned and + split training/test data/labels :returns: :data_dictionary: updated dictionary with standardized values. """ @@ -516,8 +516,7 @@ class FreqaiDataKitchen: def pca_transform(self, filtered_dataframe: DataFrame) -> None: """ Use an existing pca transform to transform data into components - :params: - filtered_dataframe: DataFrame = the cleaned dataframe + :param filtered_dataframe: DataFrame = the cleaned dataframe """ pca_components = self.pca.transform(filtered_dataframe) self.data_dictionary["prediction_features"] = pd.DataFrame( @@ -561,8 +560,7 @@ class FreqaiDataKitchen: """ Build/inference a Support Vector Machine to detect outliers in training data and prediction - :params: - predict: bool = If true, inference an existing SVM model, else construct one + :param predict: bool = If true, inference an existing SVM model, else construct one """ if self.keras: @@ -647,11 +645,11 @@ class FreqaiDataKitchen: Use DBSCAN to cluster training data and remove "noisy" data (read outliers). User controls this via the config param `DBSCAN_outlier_pct` which indicates the pct of training data that they want to be considered outliers. - :params: - predict: bool = If False (training), iterate to find the best hyper parameters to match - user requested outlier percent target. If True (prediction), use the parameters - determined from the previous training to estimate if the current prediction point - is an outlier. + :param predict: bool = If False (training), iterate to find the best hyper parameters + to match user requested outlier percent target. + If True (prediction), use the parameters determined from + the previous training to estimate if the current prediction point + is an outlier. """ if predict: @@ -1118,15 +1116,13 @@ class FreqaiDataKitchen: prediction_dataframe: DataFrame = pd.DataFrame(), ) -> DataFrame: """ - Use the user defined strategy for populating indicators during - retrain - :params: - strategy: IStrategy = user defined strategy object - corr_dataframes: dict = dict containing the informative pair dataframes - (for user defined timeframes) - base_dataframes: dict = dict containing the current pair dataframes - (for user defined timeframes) - metadata: dict = strategy furnished pair metadata + Use the user defined strategy for populating indicators during retrain + :param strategy: IStrategy = user defined strategy object + :param corr_dataframes: dict = dict containing the informative pair dataframes + (for user defined timeframes) + :param base_dataframes: dict = dict containing the current pair dataframes + (for user defined timeframes) + :param metadata: dict = strategy furnished pair metadata :returns: dataframe: DataFrame = dataframe containing populated indicators """ diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 394b98e94..40fbd798c 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -603,11 +603,11 @@ class IFreqaiModel(ABC): If the user reuses an identifier on a subsequent instance, this function will not be called. In that case, "real" predictions will be appended to the loaded set of historic predictions. - :param: df: DataFrame = the dataframe containing the training feature data - :param: model: Any = A model which was `fit` using a common library such as - catboost or lightgbm - :param: dk: FreqaiDataKitchen = object containing methods for data analysis - :param: pair: str = current pair + :param df: DataFrame = the dataframe containing the training feature data + :param model: Any = A model which was `fit` using a common library such as + catboost or lightgbm + :param dk: FreqaiDataKitchen = object containing methods for data analysis + :param pair: str = current pair """ self.dd.historic_predictions[pair] = pred_df diff --git a/freqtrade/freqai/prediction_models/XGBoostClassifier.py b/freqtrade/freqai/prediction_models/XGBoostClassifier.py index 3b14471c1..67c7c7783 100644 --- a/freqtrade/freqai/prediction_models/XGBoostClassifier.py +++ b/freqtrade/freqai/prediction_models/XGBoostClassifier.py @@ -64,7 +64,7 @@ class XGBoostClassifier(BaseClassifierModel): ) -> 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. + :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 From 2ad086dd7a3d9ba9af01edc2a2f8100c5972ee89 Mon Sep 17 00:00:00 2001 From: silur Date: Mon, 10 Oct 2022 14:35:07 +0200 Subject: [PATCH 138/258] add XGBoost random forest predictors to freqai --- .../prediction_models/XGBoostRFClassifier.py | 85 +++++++++++++++++++ .../prediction_models/XGBoostRFRegressor.py | 45 ++++++++++ 2 files changed, 130 insertions(+) create mode 100644 freqtrade/freqai/prediction_models/XGBoostRFClassifier.py create mode 100644 freqtrade/freqai/prediction_models/XGBoostRFRegressor.py diff --git a/freqtrade/freqai/prediction_models/XGBoostRFClassifier.py b/freqtrade/freqai/prediction_models/XGBoostRFClassifier.py new file mode 100644 index 000000000..1aba8df85 --- /dev/null +++ b/freqtrade/freqai/prediction_models/XGBoostRFClassifier.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 XGBRFClassifier + +from freqtrade.freqai.base_models.BaseClassifierModel import BaseClassifierModel +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen + + +logger = logging.getLogger(__name__) + + +class XGBoostRFClassifier(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 = XGBRFClassifier(**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/freqtrade/freqai/prediction_models/XGBoostRFRegressor.py b/freqtrade/freqai/prediction_models/XGBoostRFRegressor.py new file mode 100644 index 000000000..4c18d594d --- /dev/null +++ b/freqtrade/freqai/prediction_models/XGBoostRFRegressor.py @@ -0,0 +1,45 @@ +import logging +from typing import Any, Dict + +from xgboost import XGBRFRegressor + +from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel +from freqtrade.freqai.data_kitchen import FreqaiDataKitchen + + +logger = logging.getLogger(__name__) + + +class XGBoostRFRegressor(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. + """ + + 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"])] + eval_weights = [data_dictionary['test_weights']] + + sample_weight = data_dictionary["train_weights"] + + xgb_model = self.get_init_model(dk.pair) + + model = XGBRFRegressor(**self.model_training_parameters) + + 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 From 002a46c5a0036bcc1ff05bc27bef4296e98afb54 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 14:16:37 +0000 Subject: [PATCH 139/258] Fix typo in docstring --- freqtrade/plugins/pairlist/pairlist_helpers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/plugins/pairlist/pairlist_helpers.py b/freqtrade/plugins/pairlist/pairlist_helpers.py index 9ef3e4614..93d4fc308 100644 --- a/freqtrade/plugins/pairlist/pairlist_helpers.py +++ b/freqtrade/plugins/pairlist/pairlist_helpers.py @@ -12,7 +12,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str], :param wildcardpl: List of Pairlists, which may contain regex :param available_pairs: List of all available pairs (`exchange.get_markets().keys()`) :param keep_invalid: If sets to True, drops invalid pairs silently while expanding regexes - :return expanded pairlist, with Regexes from wildcardpl applied to match all available pairs. + :return: expanded pairlist, with Regexes from wildcardpl applied to match all available pairs. :raises: ValueError if a wildcard is invalid (like '*/BTC' - which should be `.*/BTC`) """ result = [] From ee0d90d1aac8f2ac3197c6214b6353c20836157f Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 18:03:55 +0200 Subject: [PATCH 140/258] Automatically create freqai models directory --- freqtrade/configuration/directory_operations.py | 7 ++++--- tests/test_directory_operations.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/freqtrade/configuration/directory_operations.py b/freqtrade/configuration/directory_operations.py index f70310ee1..e1313749b 100644 --- a/freqtrade/configuration/directory_operations.py +++ b/freqtrade/configuration/directory_operations.py @@ -3,7 +3,8 @@ import shutil from pathlib import Path from typing import Optional -from freqtrade.constants import USER_DATA_FILES, Config +from freqtrade.constants import (USER_DATA_FILES, USERPATH_FREQAIMODELS, USERPATH_HYPEROPTS, + USERPATH_NOTEBOOKS, USERPATH_STRATEGIES, Config) from freqtrade.exceptions import OperationalException @@ -49,8 +50,8 @@ def create_userdata_dir(directory: str, create_dir: bool = False) -> Path: :param create_dir: Create directory if it does not exist. :return: Path object containing the directory """ - sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "logs", - "notebooks", "plot", "strategies", ] + sub_dirs = ["backtest_results", "data", USERPATH_HYPEROPTS, "hyperopt_results", "logs", + USERPATH_NOTEBOOKS, "plot", USERPATH_STRATEGIES, USERPATH_FREQAIMODELS] folder = Path(directory) chown_user_directory(folder) if not folder.is_dir(): diff --git a/tests/test_directory_operations.py b/tests/test_directory_operations.py index 905b078f9..8e49aab10 100644 --- a/tests/test_directory_operations.py +++ b/tests/test_directory_operations.py @@ -25,7 +25,7 @@ def test_create_userdata_dir(mocker, default_conf, caplog) -> None: md = mocker.patch.object(Path, 'mkdir', MagicMock()) x = create_userdata_dir('/tmp/bar', create_dir=True) - assert md.call_count == 9 + assert md.call_count == 10 assert md.call_args[1]['parents'] is False assert log_has(f'Created user-data directory: {Path("/tmp/bar")}', caplog) assert isinstance(x, Path) From 5ffa3cb9ba4dfb448fb42d21eb8efd0b585c4205 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 10 Oct 2022 18:11:32 +0200 Subject: [PATCH 141/258] Update docs to mention `freqaimodels` directory closes #7570 --- docs/freqai-configuration.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index d24c60057..737f64824 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -206,6 +206,9 @@ If this value is set, FreqAI will initially use the predictions from the trainin FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `Catboost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. However, it is possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. +You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model. +Make sure to use unique names to avoid overriding built-in models. + ### Setting classifier targets FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. 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143/258] revert syntax --- tests/freqai/test_freqai_interface.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index c8444067a..445b718d2 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -182,7 +182,8 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog) df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC") for i in range(5): - df.loc[:, f'%-constant_{i}'] = i + df[f'%-constant_{i}'] = i + # df.loc[:, f'%-constant_{i}'] = i metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) From 5ada5eb54001724775cace6335fd9be64d4ec31e Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 10 Oct 2022 23:30:43 -0600 Subject: [PATCH 144/258] fix error message, update exception import --- freqtrade/rpc/api_server/api_ws.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index b60210143..46909955d 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -1,10 +1,10 @@ import logging from typing import Any, Dict -import websockets from fastapi import APIRouter, Depends, WebSocketDisconnect from fastapi.websockets import WebSocket, WebSocketState from pydantic import ValidationError +from websockets.exceptions import WebSocketException from freqtrade.enums import RPCMessageType, RPCRequestType from freqtrade.rpc.api_server.api_auth import validate_ws_token @@ -115,10 +115,7 @@ async def message_endpoint( # Process the request here await _process_consumer_request(request, channel, rpc) - except ( - WebSocketDisconnect, - websockets.exceptions.WebSocketException - ): + except (WebSocketDisconnect, WebSocketException): # Handle client disconnects logger.info(f"Consumer disconnected - {channel}") except RuntimeError: @@ -126,7 +123,7 @@ async def message_endpoint( # RuntimeError('Cannot call "send" once a closed message has been sent') pass except Exception as e: - logger.info(f"Consumer connection failed - {channel}") + logger.info(f"Consumer connection failed - {channel}: {e}") logger.debug(e, exc_info=e) finally: await channel_manager.on_disconnect(ws) From eb8c89fe3188fefc284d0c825ab29e98c59096ab Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Mon, 10 Oct 2022 23:32:10 -0600 Subject: [PATCH 145/258] move send delay to relay --- freqtrade/rpc/api_server/webserver.py | 4 ---- freqtrade/rpc/api_server/ws/channel.py | 6 ++++++ 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 4a09fd78e..c6639f1a6 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -198,10 +198,6 @@ class ApiServer(RPCHandler): logger.debug(f"Found message of type: {message.get('type')}") # Broadcast it await self._ws_channel_manager.broadcast(message) - # Limit messages per sec. - # Could cause problems with queue size if too low, and - # problems with network traffik if too high. - await asyncio.sleep(0.001) except asyncio.CancelledError: pass diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py index 7cee95e6d..e9dbd63be 100644 --- a/freqtrade/rpc/api_server/ws/channel.py +++ b/freqtrade/rpc/api_server/ws/channel.py @@ -115,6 +115,12 @@ class WebSocketChannel: try: await self._send(message) self.queue.task_done() + + # Limit messages per sec. + # Could cause problems with queue size if too low, and + # problems with network traffik if too high. + # 0.001 = 1000/s + await asyncio.sleep(0.001) except RuntimeError: # The connection was closed, just exit the task return From 16c0fef72edf529f34744552d155ff15642ad64f Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Tue, 11 Oct 2022 00:10:57 -0600 Subject: [PATCH 146/258] update timestamp calculation to correct int, remove internal ping interval --- scripts/ws_client.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/scripts/ws_client.py b/scripts/ws_client.py index 83182ae9e..23ad9296d 100644 --- a/scripts/ws_client.py +++ b/scripts/ws_client.py @@ -82,7 +82,7 @@ def readable_timedelta(delta): """ attrs = ['years', 'months', 'days', 'hours', 'minutes', 'seconds', 'microseconds'] return ", ".join([ - '%d %s' % (getattr(delta, attr), attr if getattr(delta, attr) > 1 else attr[:-1]) + '%d %s' % (getattr(delta, attr), attr if getattr(delta, attr) > 0 else attr[:-1]) for attr in attrs if getattr(delta, attr) ]) @@ -170,7 +170,7 @@ class ClientProtocol: def _calculate_time_difference(self): old_last_received_at = self._LAST_RECEIVED_AT - self._LAST_RECEIVED_AT = time.time() * 1000 + self._LAST_RECEIVED_AT = time.time() * 1e6 time_delta = relativedelta(microseconds=(self._LAST_RECEIVED_AT - old_last_received_at)) return readable_timedelta(time_delta) @@ -238,7 +238,7 @@ async def create_client( except ( asyncio.TimeoutError, - websockets.exceptions.ConnectionClosed + websockets.exceptions.WebSocketException ): # Try pinging try: @@ -298,7 +298,7 @@ async def _main(args): producers = emc_config.get('producers', []) producer = producers[0] - wait_timeout = emc_config.get('wait_timeout', 300) + wait_timeout = emc_config.get('wait_timeout', 30) ping_timeout = emc_config.get('ping_timeout', 10) sleep_time = emc_config.get('sleep_time', 10) message_size_limit = (emc_config.get('message_size_limit', 8) << 20) @@ -311,7 +311,8 @@ async def _main(args): sleep_time=sleep_time, ping_timeout=ping_timeout, wait_timeout=wait_timeout, - max_size=message_size_limit + max_size=message_size_limit, + ping_interval=None ) From 30a45bb59746a658e8f9fc970ab2467fdb00443d Mon Sep 17 00:00:00 2001 From: silur Date: Tue, 11 Oct 2022 13:17:21 +0200 Subject: [PATCH 147/258] add XGBoostRF models to freqai test interface --- tests/freqai/test_freqai_interface.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index a61853c47..2f5ada90a 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -30,6 +30,7 @@ def is_mac() -> bool: @pytest.mark.parametrize('model', [ 'LightGBMRegressor', 'XGBoostRegressor', + 'XGBoostRFRegressor', 'CatboostRegressor', ]) def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model): @@ -111,6 +112,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): 'LightGBMClassifier', 'CatboostClassifier', 'XGBoostClassifier', + 'XGBoostRFClassifier', ]) def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): if is_arm() and model == 'CatboostClassifier': From 5b5bb8aab5046c5ea6c3de01f4b319433997e76e Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 11 Oct 2022 19:05:46 +0200 Subject: [PATCH 148/258] catboost tensorboard bugfix --- freqtrade/freqai/data_kitchen.py | 1 - freqtrade/freqai/freqai_interface.py | 2 +- freqtrade/freqai/prediction_models/CatboostRegressor.py | 2 +- 3 files changed, 2 insertions(+), 3 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 89b8f2b95..4b604e281 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -119,7 +119,6 @@ class FreqaiDataKitchen: / f"sub-train-{pair.split('/')[0]}_{trained_timestamp}" ) - Path(self.data_path / 'tensorboard').mkdir(parents=True, exist_ok=True) return diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index ac980f5f1..9907a5f9f 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -201,10 +201,10 @@ class IFreqaiModel(ABC): new_trained_timerange, data_load_timerange, ) = dk.check_if_new_training_required(trained_timestamp) - dk.set_paths(pair, new_trained_timerange.stopts) if retrain: self.train_timer('start') + dk.set_paths(pair, new_trained_timerange.stopts) try: self.extract_data_and_train_model( new_trained_timerange, pair, strategy, dk, data_load_timerange diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index 46f33a142..2978f6679 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -43,7 +43,7 @@ class CatboostRegressor(BaseRegressionModel): model = CatBoostRegressor( allow_writing_files=True, - train_dir=Path(dk.data_path / 'tensorboard'), + train_dir=Path(dk.data_path), **self.model_training_parameters, ) From 88b8f186393d892ab3849f60879a6e00df940412 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 11 Oct 2022 19:24:47 +0200 Subject: [PATCH 149/258] add test for metric tracker --- tests/freqai/test_freqai_interface.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index a61853c47..759710690 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -56,9 +56,15 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model): data_load_timerange = TimeRange.parse_timerange("20180125-20180130") new_timerange = TimeRange.parse_timerange("20180127-20180130") + freqai.train_timer("start", "ADA/BTC") freqai.extract_data_and_train_model( new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) + freqai.train_timer("stop", "ADA/BTC") + freqai.dd.save_metric_tracker_to_disk() + freqai.dd.save_drawer_to_disk() + assert Path(freqai.dk.full_path / "metric_tracker.json").is_file() + assert Path(freqai.dk.full_path / "pair_dictionary.json").is_file() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.{model_save_ext}").is_file() assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").is_file() From dba1b573bc773eb952c0830e52b4bf85f64cddf0 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 11 Oct 2022 19:49:24 +0200 Subject: [PATCH 150/258] remove tensorboard dir from other pred models --- freqtrade/freqai/prediction_models/CatboostClassifier.py | 2 +- .../freqai/prediction_models/CatboostRegressorMultiTarget.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 6dab012d1..2aebc3ebf 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -34,7 +34,7 @@ class CatboostClassifier(BaseClassifierModel): cbr = CatBoostClassifier( allow_writing_files=True, loss_function='MultiClass', - train_dir=Path(dk.data_path / 'tensorboard'), + train_dir=Path(dk.data_path), **self.model_training_parameters, ) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index 085c13b86..de7a73e3a 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -28,7 +28,7 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): cbr = CatBoostRegressor( allow_writing_files=True, - train_dir=Path(dk.data_path / 'tensorboard'), + train_dir=Path(dk.data_path), **self.model_training_parameters, ) From 1e31be562e92a3e8629e918c285c4543cb7c0225 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Tue, 11 Oct 2022 21:05:42 +0200 Subject: [PATCH 151/258] remove whitespace --- freqtrade/freqai/data_kitchen.py | 1 - 1 file changed, 1 deletion(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 4b604e281..52261d341 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -119,7 +119,6 @@ class FreqaiDataKitchen: / f"sub-train-{pair.split('/')[0]}_{trained_timestamp}" ) - return def make_train_test_datasets( From afaca2167cce2531817e9f65bb0dd0343d331083 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 11 Oct 2022 19:33:02 +0000 Subject: [PATCH 152/258] use Type Alias for Ticker result to improve keyerror resiliancy --- freqtrade/exchange/exchange.py | 6 ++++-- freqtrade/exchange/kraken.py | 3 ++- freqtrade/exchange/types.py | 5 +++++ freqtrade/plugins/pairlist/AgeFilter.py | 3 ++- freqtrade/plugins/pairlist/IPairList.py | 11 ++++++----- freqtrade/plugins/pairlist/OffsetFilter.py | 3 ++- freqtrade/plugins/pairlist/PerformanceFilter.py | 3 ++- freqtrade/plugins/pairlist/PrecisionFilter.py | 7 ++++--- freqtrade/plugins/pairlist/PriceFilter.py | 7 ++++--- freqtrade/plugins/pairlist/ProducerPairList.py | 5 +++-- freqtrade/plugins/pairlist/ShuffleFilter.py | 3 ++- freqtrade/plugins/pairlist/SpreadFilter.py | 7 ++++--- freqtrade/plugins/pairlist/StaticPairList.py | 5 +++-- freqtrade/plugins/pairlist/VolatilityFilter.py | 3 ++- freqtrade/plugins/pairlist/VolumePairList.py | 7 ++++--- freqtrade/plugins/pairlist/rangestabilityfilter.py | 3 ++- freqtrade/plugins/pairlistmanager.py | 3 ++- 17 files changed, 53 insertions(+), 31 deletions(-) create mode 100644 freqtrade/exchange/types.py diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index c41a84450..3b59bdfa0 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -31,6 +31,7 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, remove_credentials, retrier, retrier_async) +from freqtrade.exchange.types import Tickers from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json, safe_value_fallback2) from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1420,14 +1421,15 @@ class Exchange: raise OperationalException(e) from e @retrier - def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict: + def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers: """ :param cached: Allow cached result :return: fetch_tickers result """ + tickers: Tickers if cached: with self._cache_lock: - tickers = self._fetch_tickers_cache.get('fetch_tickers') + tickers = self._fetch_tickers_cache.get('fetch_tickers') # type: ignore if tickers: return tickers try: diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py index 6c9b88eae..f3a9486f2 100644 --- a/freqtrade/exchange/kraken.py +++ b/freqtrade/exchange/kraken.py @@ -12,6 +12,7 @@ from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, Invali OperationalException, TemporaryError) from freqtrade.exchange import Exchange from freqtrade.exchange.common import retrier +from freqtrade.exchange.types import Tickers logger = logging.getLogger(__name__) @@ -45,7 +46,7 @@ class Kraken(Exchange): return (parent_check and market.get('darkpool', False) is False) - def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict: + def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers: # Only fetch tickers for current stake currency # Otherwise the request for kraken becomes too large. symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']])) diff --git a/freqtrade/exchange/types.py b/freqtrade/exchange/types.py new file mode 100644 index 000000000..6504381dc --- /dev/null +++ b/freqtrade/exchange/types.py @@ -0,0 +1,5 @@ +from typing import Any, Dict + + +Ticker = Dict[str, Any] +Tickers = Dict[str, Ticker] diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py index 7c8cdb5ab..f9c02e250 100644 --- a/freqtrade/plugins/pairlist/AgeFilter.py +++ b/freqtrade/plugins/pairlist/AgeFilter.py @@ -10,6 +10,7 @@ from pandas import DataFrame from freqtrade.constants import Config, ListPairsWithTimeframes from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.misc import plural from freqtrade.plugins.pairlist.IPairList import IPairList from freqtrade.util import PeriodicCache @@ -67,7 +68,7 @@ class AgeFilter(IPairList): f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}" ) if self._max_days_listed else '') - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ :param pairlist: pairlist to filter or sort :param tickers: Tickers (from exchange.get_tickers). May be cached. diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py index 60abac6a1..660d6228c 100644 --- a/freqtrade/plugins/pairlist/IPairList.py +++ b/freqtrade/plugins/pairlist/IPairList.py @@ -4,11 +4,12 @@ PairList Handler base class import logging from abc import ABC, abstractmethod, abstractproperty from copy import deepcopy -from typing import Any, Dict, List +from typing import Any, Dict, List, Optional from freqtrade.constants import Config from freqtrade.exceptions import OperationalException from freqtrade.exchange import Exchange, market_is_active +from freqtrade.exchange.types import Ticker, Tickers from freqtrade.mixins import LoggingMixin @@ -61,7 +62,7 @@ class IPairList(LoggingMixin, ABC): -> Please overwrite in subclasses """ - def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool: + def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool: """ Check one pair against Pairlist Handler's specific conditions. @@ -74,7 +75,7 @@ class IPairList(LoggingMixin, ABC): """ raise NotImplementedError() - def gen_pairlist(self, tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Tickers) -> List[str]: """ Generate the pairlist. @@ -91,7 +92,7 @@ class IPairList(LoggingMixin, ABC): raise OperationalException("This Pairlist Handler should not be used " "at the first position in the list of Pairlist Handlers.") - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the whitelist again. @@ -110,7 +111,7 @@ class IPairList(LoggingMixin, ABC): # Copy list since we're modifying this list for p in deepcopy(pairlist): # Filter out assets - if not self._validate_pair(p, tickers[p] if p in tickers else {}): + if not self._validate_pair(p, tickers[p] if p in tickers else None): pairlist.remove(p) return pairlist diff --git a/freqtrade/plugins/pairlist/OffsetFilter.py b/freqtrade/plugins/pairlist/OffsetFilter.py index c9531ece1..8f21cdd85 100644 --- a/freqtrade/plugins/pairlist/OffsetFilter.py +++ b/freqtrade/plugins/pairlist/OffsetFilter.py @@ -6,6 +6,7 @@ from typing import Any, Dict, List from freqtrade.constants import Config from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.plugins.pairlist.IPairList import IPairList @@ -42,7 +43,7 @@ class OffsetFilter(IPairList): return f"{self.name} - Taking {self._number_pairs} Pairs, starting from {self._offset}." return f"{self.name} - Offsetting pairs by {self._offset}." - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the whitelist again. Called on each bot iteration - please use internal caching if necessary diff --git a/freqtrade/plugins/pairlist/PerformanceFilter.py b/freqtrade/plugins/pairlist/PerformanceFilter.py index 4cc92175a..e7fcac1e4 100644 --- a/freqtrade/plugins/pairlist/PerformanceFilter.py +++ b/freqtrade/plugins/pairlist/PerformanceFilter.py @@ -7,6 +7,7 @@ from typing import Any, Dict, List import pandas as pd from freqtrade.constants import Config +from freqtrade.exchange.types import Tickers from freqtrade.persistence import Trade from freqtrade.plugins.pairlist.IPairList import IPairList @@ -39,7 +40,7 @@ class PerformanceFilter(IPairList): """ return f"{self.name} - Sorting pairs by performance." - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the allowlist again. Called on each bot iteration - please use internal caching if necessary diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py index 98cb3ba46..478eaec20 100644 --- a/freqtrade/plugins/pairlist/PrecisionFilter.py +++ b/freqtrade/plugins/pairlist/PrecisionFilter.py @@ -2,10 +2,11 @@ Precision pair list filter """ import logging -from typing import Any, Dict +from typing import Any, Dict, Optional from freqtrade.constants import Config from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Ticker from freqtrade.plugins.pairlist.IPairList import IPairList @@ -44,7 +45,7 @@ class PrecisionFilter(IPairList): """ return f"{self.name} - Filtering untradable pairs." - def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool: + def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool: """ Check if pair has enough room to add a stoploss to avoid "unsellable" buys of very low value pairs. @@ -52,7 +53,7 @@ class PrecisionFilter(IPairList): :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ - if ticker.get('last', None) is None: + if not ticker or ticker.get('last', None) is None: self.log_once(f"Removed {pair} from whitelist, because " "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index a6b400a38..f007c52d2 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -2,10 +2,11 @@ Price pair list filter """ import logging -from typing import Any, Dict +from typing import Any, Dict, Optional from freqtrade.constants import Config from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Ticker from freqtrade.plugins.pairlist.IPairList import IPairList @@ -64,14 +65,14 @@ class PriceFilter(IPairList): return f"{self.name} - No price filters configured." - def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool: + def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool: """ Check if if one price-step (pip) is > than a certain barrier. :param pair: Pair that's currently validated :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ - if ticker.get('last', None) is None or ticker.get('last') == 0: + if not ticker or ticker.get('last', None) is None or ticker.get('last') == 0: self.log_once(f"Removed {pair} from whitelist, because " "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) diff --git a/freqtrade/plugins/pairlist/ProducerPairList.py b/freqtrade/plugins/pairlist/ProducerPairList.py index 740cb4ec2..882d49b76 100644 --- a/freqtrade/plugins/pairlist/ProducerPairList.py +++ b/freqtrade/plugins/pairlist/ProducerPairList.py @@ -7,6 +7,7 @@ import logging from typing import Any, Dict, List, Optional from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.plugins.pairlist.IPairList import IPairList @@ -68,7 +69,7 @@ class ProducerPairList(IPairList): return pairs - def gen_pairlist(self, tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Tickers) -> List[str]: """ Generate the pairlist :param tickers: Tickers (from exchange.get_tickers). May be cached. @@ -79,7 +80,7 @@ class ProducerPairList(IPairList): pairs = self._whitelist_for_active_markets(self.verify_whitelist(pairs, logger.info)) return pairs - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the whitelist again. Called on each bot iteration - please use internal caching if necessary diff --git a/freqtrade/plugins/pairlist/ShuffleFilter.py b/freqtrade/plugins/pairlist/ShuffleFilter.py index 6eb4231bc..1bc114d4e 100644 --- a/freqtrade/plugins/pairlist/ShuffleFilter.py +++ b/freqtrade/plugins/pairlist/ShuffleFilter.py @@ -7,6 +7,7 @@ from typing import Any, Dict, List from freqtrade.constants import Config from freqtrade.enums import RunMode +from freqtrade.exchange.types import Tickers from freqtrade.plugins.pairlist.IPairList import IPairList @@ -47,7 +48,7 @@ class ShuffleFilter(IPairList): return (f"{self.name} - Shuffling pairs" + (f", seed = {self._seed}." if self._seed is not None else ".")) - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the whitelist again. Called on each bot iteration - please use internal caching if necessary diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py index 1f6d4f687..ecb21593b 100644 --- a/freqtrade/plugins/pairlist/SpreadFilter.py +++ b/freqtrade/plugins/pairlist/SpreadFilter.py @@ -2,10 +2,11 @@ Spread pair list filter """ import logging -from typing import Any, Dict +from typing import Any, Dict, Optional from freqtrade.constants import Config from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Ticker from freqtrade.plugins.pairlist.IPairList import IPairList @@ -44,14 +45,14 @@ class SpreadFilter(IPairList): return (f"{self.name} - Filtering pairs with ask/bid diff above " f"{self._max_spread_ratio:.2%}.") - def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool: + def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool: """ Validate spread for the ticker :param pair: Pair that's currently validated :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ - if 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']: + if ticker and 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']: spread = 1 - ticker['bid'] / ticker['ask'] if spread > self._max_spread_ratio: self.log_once(f"Removed {pair} from whitelist, because spread " diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py index 5b1337754..4b1961a53 100644 --- a/freqtrade/plugins/pairlist/StaticPairList.py +++ b/freqtrade/plugins/pairlist/StaticPairList.py @@ -8,6 +8,7 @@ from copy import deepcopy from typing import Any, Dict, List from freqtrade.constants import Config +from freqtrade.exchange.types import Tickers from freqtrade.plugins.pairlist.IPairList import IPairList @@ -39,7 +40,7 @@ class StaticPairList(IPairList): """ return f"{self.name}" - def gen_pairlist(self, tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Tickers) -> List[str]: """ Generate the pairlist :param tickers: Tickers (from exchange.get_tickers). May be cached. @@ -53,7 +54,7 @@ class StaticPairList(IPairList): return self._whitelist_for_active_markets( self.verify_whitelist(self._config['exchange']['pair_whitelist'], logger.info)) - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Filters and sorts pairlist and returns the whitelist again. Called on each bot iteration - please use internal caching if necessary diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py index c06fc09ba..401a2e86c 100644 --- a/freqtrade/plugins/pairlist/VolatilityFilter.py +++ b/freqtrade/plugins/pairlist/VolatilityFilter.py @@ -13,6 +13,7 @@ from pandas import DataFrame from freqtrade.constants import Config, ListPairsWithTimeframes from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.misc import plural from freqtrade.plugins.pairlist.IPairList import IPairList @@ -62,7 +63,7 @@ class VolatilityFilter(IPairList): f"{self._min_volatility}-{self._max_volatility} " f" the last {self._days} {plural(self._days, 'day')}.") - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Validate trading range :param pairlist: pairlist to filter or sort diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py index bfecbd62a..ad27a93d8 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -5,13 +5,14 @@ Provides dynamic pair list based on trade volumes """ import logging from datetime import datetime, timedelta, timezone -from typing import Any, Dict, List +from typing import Any, Dict, List, Literal from cachetools import TTLCache from freqtrade.constants import Config, ListPairsWithTimeframes from freqtrade.exceptions import OperationalException from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date +from freqtrade.exchange.types import Tickers from freqtrade.misc import format_ms_time from freqtrade.plugins.pairlist.IPairList import IPairList @@ -36,7 +37,7 @@ class VolumePairList(IPairList): self._stake_currency = config['stake_currency'] self._number_pairs = self._pairlistconfig['number_assets'] - self._sort_key = self._pairlistconfig.get('sort_key', 'quoteVolume') + self._sort_key: Literal['quoteVolume'] = self._pairlistconfig.get('sort_key', 'quoteVolume') self._min_value = self._pairlistconfig.get('min_value', 0) self._refresh_period = self._pairlistconfig.get('refresh_period', 1800) self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period) @@ -110,7 +111,7 @@ class VolumePairList(IPairList): """ return f"{self.name} - top {self._pairlistconfig['number_assets']} volume pairs." - def gen_pairlist(self, tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Tickers) -> List[str]: """ Generate the pairlist :param tickers: Tickers (from exchange.get_tickers). May be cached. diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py index ca844f003..546b026cb 100644 --- a/freqtrade/plugins/pairlist/rangestabilityfilter.py +++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py @@ -11,6 +11,7 @@ from pandas import DataFrame from freqtrade.constants import Config, ListPairsWithTimeframes from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.misc import plural from freqtrade.plugins.pairlist.IPairList import IPairList @@ -60,7 +61,7 @@ class RangeStabilityFilter(IPairList): f"{self._min_rate_of_change}{max_rate_desc} over the " f"last {plural(self._days, 'day')}.") - def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]: """ Validate trading range :param pairlist: pairlist to filter or sort diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index 5ed319e93..1e98b8485 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -11,6 +11,7 @@ from freqtrade.constants import Config, ListPairsWithTimeframes from freqtrade.data.dataprovider import DataProvider from freqtrade.enums import CandleType from freqtrade.exceptions import OperationalException +from freqtrade.exchange.types import Tickers from freqtrade.mixins import LoggingMixin from freqtrade.plugins.pairlist.IPairList import IPairList from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -76,7 +77,7 @@ class PairListManager(LoggingMixin): return [{p.name: p.short_desc()} for p in self._pairlist_handlers] @cached(TTLCache(maxsize=1, ttl=1800)) - def _get_cached_tickers(self): + def _get_cached_tickers(self) -> Tickers: return self._exchange.get_tickers() def refresh_pairlist(self) -> None: From 35f3f988d45463e923b333a2a5a34e9442929e87 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 11 Oct 2022 19:33:05 +0000 Subject: [PATCH 153/258] Improve price handling in priceFilter --- freqtrade/plugins/pairlist/PriceFilter.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index f007c52d2..da41e9239 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -77,11 +77,13 @@ class PriceFilter(IPairList): "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) return False + else: + price: float = ticker['last'] # Perform low_price_ratio check. if self._low_price_ratio != 0: - compare = self._exchange.price_get_one_pip(pair, ticker['last']) - changeperc = compare / ticker['last'] + compare = self._exchange.price_get_one_pip(pair, price) + changeperc = compare / price if changeperc > self._low_price_ratio: self.log_once(f"Removed {pair} from whitelist, " f"because 1 unit is {changeperc:.3%}", logger.info) @@ -89,7 +91,6 @@ class PriceFilter(IPairList): # Perform low_amount check if self._max_value != 0: - price = ticker['last'] market = self._exchange.markets[pair] limits = market['limits'] if (limits['amount']['min'] is not None): @@ -114,14 +115,14 @@ class PriceFilter(IPairList): # Perform min_price check. if self._min_price != 0: - if ticker['last'] < self._min_price: + if price < self._min_price: self.log_once(f"Removed {pair} from whitelist, " f"because last price < {self._min_price:.8f}", logger.info) return False # Perform max_price check. if self._max_price != 0: - if ticker['last'] > self._max_price: + if price > self._max_price: self.log_once(f"Removed {pair} from whitelist, " f"because last price > {self._max_price:.8f}", logger.info) return False From 52e9528361b73bced2f34c77d7bbbebaa1b7fa23 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 11 Oct 2022 19:33:07 +0000 Subject: [PATCH 154/258] Improve ticker type --- freqtrade/exchange/binance.py | 3 ++- freqtrade/exchange/types.py | 15 +++++++++++++-- freqtrade/plugins/pairlist/PriceFilter.py | 6 +++--- 3 files changed, 18 insertions(+), 6 deletions(-) diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py index a0d4b2d82..6d818bab9 100644 --- a/freqtrade/exchange/binance.py +++ b/freqtrade/exchange/binance.py @@ -11,6 +11,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError from freqtrade.exchange import Exchange from freqtrade.exchange.common import retrier +from freqtrade.exchange.types import Tickers from freqtrade.misc import deep_merge_dicts, json_load @@ -59,7 +60,7 @@ class Binance(Exchange): ) )) - def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict: + def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers: tickers = super().get_tickers(symbols=symbols, cached=cached) if self.trading_mode == TradingMode.FUTURES: # Binance's future result has no bid/ask values. diff --git a/freqtrade/exchange/types.py b/freqtrade/exchange/types.py index 6504381dc..a60b454d4 100644 --- a/freqtrade/exchange/types.py +++ b/freqtrade/exchange/types.py @@ -1,5 +1,16 @@ -from typing import Any, Dict +from typing import Dict, Optional, TypedDict + + +class Ticker(TypedDict): + symbol: str + ask: Optional[float] + askVolume: Optional[float] + bid: Optional[float] + bidVolume: Optional[float] + last: Optional[float] + quoteVolume: Optional[float] + baseVolume: Optional[float] + # Several more - only listing required. -Ticker = Dict[str, Any] Tickers = Dict[str, Ticker] diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index da41e9239..4d23de792 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -72,13 +72,13 @@ class PriceFilter(IPairList): :param ticker: ticker dict as returned from ccxt.fetch_ticker :return: True if the pair can stay, false if it should be removed """ - if not ticker or ticker.get('last', None) is None or ticker.get('last') == 0: + if ticker and 'last' in ticker and ticker['last'] is not None and ticker.get('last') != 0: + price: float = ticker['last'] + else: self.log_once(f"Removed {pair} from whitelist, because " "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) return False - else: - price: float = ticker['last'] # Perform low_price_ratio check. if self._low_price_ratio != 0: From a6f6a17393b069153a8e88966a8ff6167c9d639a Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 11 Oct 2022 21:42:48 +0200 Subject: [PATCH 155/258] Type fetch_ticker --- freqtrade/constants.py | 1 + freqtrade/exchange/exchange.py | 14 +++++++------- freqtrade/misc.py | 7 +++++-- 3 files changed, 13 insertions(+), 9 deletions(-) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 27968bb1b..2fdb091a7 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -656,5 +656,6 @@ LongShort = Literal['long', 'short'] EntryExit = Literal['entry', 'exit'] BuySell = Literal['buy', 'sell'] MakerTaker = Literal['maker', 'taker'] +BidAsk = Literal['bid', 'ask'] Config = Dict[str, Any] diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 3b59bdfa0..8cfe90272 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -20,8 +20,8 @@ from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision from dateutil import parser from pandas import DataFrame, concat -from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell, - Config, EntryExit, ListPairsWithTimeframes, MakerTaker, +from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BidAsk, + BuySell, Config, EntryExit, ListPairsWithTimeframes, MakerTaker, PairWithTimeframe) from freqtrade.data.converter import clean_ohlcv_dataframe, ohlcv_to_dataframe, trades_dict_to_list from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode @@ -31,7 +31,7 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, remove_credentials, retrier, retrier_async) -from freqtrade.exchange.types import Tickers +from freqtrade.exchange.types import Ticker, Tickers from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json, safe_value_fallback2) from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -1452,12 +1452,12 @@ class Exchange: # Pricing info @retrier - def fetch_ticker(self, pair: str) -> dict: + def fetch_ticker(self, pair: str) -> Ticker: try: if (pair not in self.markets or self.markets[pair].get('active', False) is False): raise ExchangeError(f"Pair {pair} not available") - data = self._api.fetch_ticker(pair) + data: Ticker = self._api.fetch_ticker(pair) return data except ccxt.DDoSProtection as e: raise DDosProtection(e) from e @@ -1508,7 +1508,7 @@ class Exchange: except ccxt.BaseError as e: raise OperationalException(e) from e - def _get_price_side(self, side: str, is_short: bool, conf_strategy: Dict) -> str: + def _get_price_side(self, side: str, is_short: bool, conf_strategy: Dict) -> BidAsk: price_side = conf_strategy['price_side'] if price_side in ('same', 'other'): @@ -1527,7 +1527,7 @@ class Exchange: def get_rate(self, pair: str, refresh: bool, side: EntryExit, is_short: bool, - order_book: Optional[dict] = None, ticker: Optional[dict] = None) -> float: + order_book: Optional[dict] = None, ticker: Optional[Ticker] = None) -> float: """ Calculates bid/ask target bid rate - between current ask price and last price diff --git a/freqtrade/misc.py b/freqtrade/misc.py index 56b3fef0e..49d33d46f 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -6,7 +6,7 @@ import logging import re from datetime import datetime from pathlib import Path -from typing import Any, Iterator, List +from typing import Any, Dict, Iterator, List, Mapping, Union from typing.io import IO from urllib.parse import urlparse @@ -186,7 +186,10 @@ def safe_value_fallback(obj: dict, key1: str, key2: str, default_value=None): return default_value -def safe_value_fallback2(dict1: dict, dict2: dict, key1: str, key2: str, default_value=None): +dictMap = Union[Dict[str, Any], Mapping[str, Any]] + + +def safe_value_fallback2(dict1: dictMap, dict2: dictMap, key1: str, key2: str, default_value=None): """ Search a value in dict1, return this if it's not None. Fall back to dict2 - return key2 from dict2 if it's not None. From 96e6c1b190e1f6285ecd8bcb6482ec83e62cde43 Mon Sep 17 00:00:00 2001 From: Joe Schr <8218910+TheJoeSchr@users.noreply.github.com> Date: Wed, 12 Oct 2022 20:05:50 +0200 Subject: [PATCH 156/258] Docs: add `ignore_buying_expired_candle_after` and `order pricing` to summary --- docs/strategy_migration.md | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md index 471ffa601..58f6b0d23 100644 --- a/docs/strategy_migration.md +++ b/docs/strategy_migration.md @@ -43,12 +43,18 @@ Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `fo * `order_time_in_force` buy -> entry, sell -> exit. * `order_types` buy -> entry, sell -> exit. * `unfilledtimeout` buy -> entry, sell -> exit. + * `ignore_buying_expired_candle_after` -> moved to root level instead of "ask_strategy/exit_pricing" * Terminology changes * Sell reasons changed to reflect the new naming of "exit" instead of sells. Be careful in your strategy if you're using `exit_reason` checks and eventually update your strategy. * `sell_signal` -> `exit_signal` * `custom_sell` -> `custom_exit` * `force_sell` -> `force_exit` * `emergency_sell` -> `emergency_exit` + * Order pricing + * `bid_strategy` -> `entry_pricing` + * `ask_strategy` -> `exit_pricing` + * `ask_last_balance` -> `price_last_balance` + * `bid_last_balance` -> `price_last_balance` * Webhook terminology changed from "sell" to "exit", and from "buy" to entry * `webhookbuy` -> `webhookentry` * `webhookbuyfill` -> `webhookentryfill` @@ -443,6 +449,7 @@ Please refer to the [pricing documentation](configuration.md#prices-used-for-ord "use_order_book": true, "order_book_top": 1, "bid_last_balance": 0.0 + "ignore_buying_expired_candle_after": 120 } } ``` @@ -466,6 +473,7 @@ after: "use_order_book": true, "order_book_top": 1, "price_last_balance": 0.0 - } + }, + "ignore_buying_expired_candle_after": 120 } ``` From 39c27cfc37650916464f267c4b814086c5f0ec01 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 04:58:02 +0000 Subject: [PATCH 157/258] Don't fail if fetchTickers is not availlable --- freqtrade/exchange/exchange.py | 2 ++ tests/exchange/test_exchange.py | 6 ++++++ 2 files changed, 8 insertions(+) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 8cfe90272..53a3960b1 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1427,6 +1427,8 @@ class Exchange: :return: fetch_tickers result """ tickers: Tickers + if not self.exchange_has('fetchTickers'): + return {} if cached: with self._cache_lock: tickers = self._fetch_tickers_cache.get('fetch_tickers') # type: ignore diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index b07892f72..07aad80ff 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -1834,6 +1834,7 @@ def test_get_tickers(default_conf, mocker, exchange_name): 'last': 41, } } + mocker.patch('freqtrade.exchange.exchange.Exchange.exchange_has', return_value=True) api_mock.fetch_tickers = MagicMock(return_value=tick) api_mock.fetch_bids_asks = MagicMock(return_value={}) exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) @@ -1883,6 +1884,11 @@ def test_get_tickers(default_conf, mocker, exchange_name): assert api_mock.fetch_tickers.call_count == 1 assert api_mock.fetch_bids_asks.call_count == (1 if exchange_name == 'binance' else 0) + api_mock.fetch_tickers.reset_mock() + api_mock.fetch_bids_asks.reset_mock() + mocker.patch('freqtrade.exchange.exchange.Exchange.exchange_has', return_value=False) + assert exchange.get_tickers() == {} + @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_fetch_ticker(default_conf, mocker, exchange_name): From 75f1a123ebe5cd4b7907c2feae11f64ec4b98e5e Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 04:58:17 +0000 Subject: [PATCH 158/258] Move "tickers_needed" check to pairlistmanager to cover all pairlists --- freqtrade/plugins/pairlist/SpreadFilter.py | 7 ------- freqtrade/plugins/pairlistmanager.py | 9 +++++++++ 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py index ecb21593b..207328d08 100644 --- a/freqtrade/plugins/pairlist/SpreadFilter.py +++ b/freqtrade/plugins/pairlist/SpreadFilter.py @@ -5,7 +5,6 @@ import logging from typing import Any, Dict, Optional from freqtrade.constants import Config -from freqtrade.exceptions import OperationalException from freqtrade.exchange.types import Ticker from freqtrade.plugins.pairlist.IPairList import IPairList @@ -23,12 +22,6 @@ class SpreadFilter(IPairList): self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005) self._enabled = self._max_spread_ratio != 0 - if not self._exchange.exchange_has('fetchTickers'): - raise OperationalException( - 'Exchange does not support fetchTickers, therefore SpreadFilter cannot be used.' - 'Please edit your config and restart the bot.' - ) - @property def needstickers(self) -> bool: """ diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index 1e98b8485..20a264fd8 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -46,6 +46,15 @@ class PairListManager(LoggingMixin): if not self._pairlist_handlers: raise OperationalException("No Pairlist Handlers defined") + if self._tickers_needed and not self._exchange.exchange_has('fetchTickers'): + invalid = ". ".join([p.name for p in self._pairlist_handlers if p.needstickers]) + + raise OperationalException( + "Exchange does not support fetchTickers, therefore the following pairlists " + "cannot be used. Please edit your config and restart the bot.\n" + f"{invalid}." + ) + refresh_period = config.get('pairlist_refresh_period', 3600) LoggingMixin.__init__(self, logger, refresh_period) From f8331e0326e12cee9ec9a84fc1c5a7ba76731ab9 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Thu, 13 Oct 2022 10:53:25 +0200 Subject: [PATCH 159/258] Add model libs info --- docs/freqai-configuration.md | 38 +++++++++++++++++++++++++++++----- docs/freqai-parameter-table.md | 2 +- docs/freqai-running.md | 4 ++-- 3 files changed, 36 insertions(+), 8 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index 737f64824..2d40918e5 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -204,17 +204,45 @@ If this value is set, FreqAI will initially use the predictions from the trainin ## Using different prediction models -FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `Catboost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. However, it is possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. +FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `CatBoost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. -You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model. +Regression and classification models differ in what targets they predict - a regression model will predict a target of continous values, for example what price BTC will be at tomorrow, whilst a classifier will predict a target of descrete values, for example if the price of BTC will go up tomorrow or not. This means that you have to specify your targets differently depending on which model type you are using (see details [below](#setting-model-targets)). + +All of the aforementioned model libraries implement gradient boosted decision tree algorithms. They all work on the principle of emsemble learning, where predictions from multiple simple learners are combined to get a final prediction that is more stable and generalized. The simple learners in this case are decision trees. Gradient boosting refers to the method of learning, where each simple learner is built in sequence - the subsequent learner is used to improve on the error from the previous learner. If you want to learn more about the different model libraries you can find the information in their respective docs: + +* CatBoost: https://catboost.ai/en/docs/ +* LightGBM: https://lightgbm.readthedocs.io/en/v3.3.2/# +* XGBoost: https://xgboost.readthedocs.io/en/stable/# + +There are also numerous online articles describing and comparing the algorithms. Some relatively light-weight examples would be [CatBoost vs. LightGBM vs. XGBoost — Which is the best algorithm?](https://towardsdatascience.com/catboost-vs-lightgbm-vs-xgboost-c80f40662924#:~:text=In%20CatBoost%2C%20symmetric%20trees%2C%20or,the%20same%20depth%20can%20differ.) and [XGBoost, LightGBM or CatBoost — which boosting algorithm should I use?](https://medium.com/riskified-technology/xgboost-lightgbm-or-catboost-which-boosting-algorithm-should-i-use-e7fda7bb36bc). Keep in mind that the performance of each model is highly dependent on the application and so any reported metrics might not be true for your particular use of the model. + +Apart from the models already vailable in FreqAI, it is also possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model. Make sure to use unique names to avoid overriding built-in models. -### Setting classifier targets +### Setting model targets -FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example: +#### Regressors + +If you are using a regressor, you need to specify a target that has continous values. FreqAI includes a variety of regressors, such as the `CatboostRegressor`via the flag `--freqaimodel CatboostRegressor`. An example of how you could set a regression target for predicting the price 100 candles into the future would be + +```python +df['&s-close_price'] = df['close'].shift(-100) +``` + +If you want to predict multiple targets, you need to define multiple labels using the same syntax as shown above. + +#### Classifiers + +If you are using a classifier, you need to specify a target that has descrete values. FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example, if you want to predict if the price 100 candles into the future goes up or down you would set ```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. +If you want to predict multiple targets you must specify all labels in the same label column. You could, for example, add the label `same` to define where the price was unchanged by setting + + +```python +df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') +df['&s-up_or_down'] = np.where( df["close"].shift(-100) == df["close"], 'same', df['&s-up_or_down']) +``` diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md index 38d7ece94..7d9864fc0 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -42,7 +42,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the | `test_size` | The 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, to not remove the chronological order of data in time-series forecasting, this is set to `False`.
**Datatype:** Boolean.
Defaut: `False`. | | **Model training parameters** -| `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `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 you select a different model, this dictionary can contain any parameter from that model.
**Datatype:** Dictionary. +| `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `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 you select a different model, this dictionary can contain any parameter from that model. A list of the currently available models can be found [here](freqai-configuration.md#using-different-prediction-models).
**Datatype:** Dictionary. | `n_estimators` | The number of boosted trees to fit in the training of the model.
**Datatype:** Integer. | `learning_rate` | Boosting learning rate during training of the model.
**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. diff --git a/docs/freqai-running.md b/docs/freqai-running.md index f6aa7b2e1..9e2b13c44 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -144,14 +144,14 @@ This specific hyperopt would help you understand the appropriate `DI_values` for ## Using Tensorboard -Catboost models benefit from tracking training metrics via Tensorboard. You can take advantage of the FreqAI integration to track training and evaluation performance across all coins and across all retrainings. Tensorboard is activated via the following command: +CatBoost models benefit from tracking training metrics via Tensorboard. You can take advantage of the FreqAI integration to track training and evaluation performance across all coins and across all retrainings. Tensorboard is activated via the following command: ```bash cd freqtrade tensorboard --logdir user_data/models/unique-id ``` -where `unique-id` is the `identifier` set in the `freqai` configuration file. This command must be run in a separate shell if the user wishes to view the output in their browser at 127.0.0.1:6060 (6060 is the default port used by Tensorboard). +where `unique-id` is the `identifier` set in the `freqai` configuration file. This command must be run in a separate shell if you wish to view the output in your browser at 127.0.0.1:6060 (6060 is the default port used by Tensorboard). ![tensorboard](assets/tensorboard.jpg) From 20457808100159f653b05b6967f18c5e9d099bfe Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 11:57:36 +0000 Subject: [PATCH 160/258] Reinstate default of 1000% for roi closes #7583 --- 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 8f803045f..96e3065c4 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -49,7 +49,7 @@ class IStrategy(ABC, HyperStrategyMixin): _ft_params_from_file: Dict # associated minimal roi - minimal_roi: Dict = {} + minimal_roi: Dict = {"0": 10.0} # associated stoploss stoploss: float From 28be784c2eb90bcb814072fcc1b5a388944b941b Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 12:17:53 +0000 Subject: [PATCH 161/258] Fix kucoin live test failure --- 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 9ff65cdc4..9f9866aba 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -56,7 +56,7 @@ EXCHANGES = { 'leverage_in_spot_market': True, }, 'kucoin': { - 'pair': 'BTC/USDT', + 'pair': 'XRP/USDT', 'stake_currency': 'USDT', 'hasQuoteVolume': True, 'timeframe': '5m', From c71c0e8da0e3326c9de12e97ffc36333baf00c3a Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 18:16:39 +0200 Subject: [PATCH 162/258] Fix some typos --- docs/freqai-configuration.md | 13 ++++++------- docs/freqai-running.md | 1 - 2 files changed, 6 insertions(+), 8 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index 2d40918e5..d162fe373 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -204,11 +204,11 @@ If this value is set, FreqAI will initially use the predictions from the trainin ## Using different prediction models -FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `CatBoost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. +FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `CatBoost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. -Regression and classification models differ in what targets they predict - a regression model will predict a target of continous values, for example what price BTC will be at tomorrow, whilst a classifier will predict a target of descrete values, for example if the price of BTC will go up tomorrow or not. This means that you have to specify your targets differently depending on which model type you are using (see details [below](#setting-model-targets)). +Regression and classification models differ in what targets they predict - a regression model will predict a target of continuous values, for example what price BTC will be at tomorrow, whilst a classifier will predict a target of discrete values, for example if the price of BTC will go up tomorrow or not. This means that you have to specify your targets differently depending on which model type you are using (see details [below](#setting-model-targets)). -All of the aforementioned model libraries implement gradient boosted decision tree algorithms. They all work on the principle of emsemble learning, where predictions from multiple simple learners are combined to get a final prediction that is more stable and generalized. The simple learners in this case are decision trees. Gradient boosting refers to the method of learning, where each simple learner is built in sequence - the subsequent learner is used to improve on the error from the previous learner. If you want to learn more about the different model libraries you can find the information in their respective docs: +All of the aforementioned model libraries implement gradient boosted decision tree algorithms. They all work on the principle of ensemble learning, where predictions from multiple simple learners are combined to get a final prediction that is more stable and generalized. The simple learners in this case are decision trees. Gradient boosting refers to the method of learning, where each simple learner is built in sequence - the subsequent learner is used to improve on the error from the previous learner. If you want to learn more about the different model libraries you can find the information in their respective docs: * CatBoost: https://catboost.ai/en/docs/ * LightGBM: https://lightgbm.readthedocs.io/en/v3.3.2/# @@ -216,14 +216,14 @@ All of the aforementioned model libraries implement gradient boosted decision tr There are also numerous online articles describing and comparing the algorithms. Some relatively light-weight examples would be [CatBoost vs. LightGBM vs. XGBoost — Which is the best algorithm?](https://towardsdatascience.com/catboost-vs-lightgbm-vs-xgboost-c80f40662924#:~:text=In%20CatBoost%2C%20symmetric%20trees%2C%20or,the%20same%20depth%20can%20differ.) and [XGBoost, LightGBM or CatBoost — which boosting algorithm should I use?](https://medium.com/riskified-technology/xgboost-lightgbm-or-catboost-which-boosting-algorithm-should-i-use-e7fda7bb36bc). Keep in mind that the performance of each model is highly dependent on the application and so any reported metrics might not be true for your particular use of the model. -Apart from the models already vailable in FreqAI, it is also possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures. You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model. +Apart from the models already available in FreqAI, it is also possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to customize various aspects of the training procedures. You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model. Make sure to use unique names to avoid overriding built-in models. ### Setting model targets #### Regressors -If you are using a regressor, you need to specify a target that has continous values. FreqAI includes a variety of regressors, such as the `CatboostRegressor`via the flag `--freqaimodel CatboostRegressor`. An example of how you could set a regression target for predicting the price 100 candles into the future would be +If you are using a regressor, you need to specify a target that has continuous values. FreqAI includes a variety of regressors, such as the `CatboostRegressor`via the flag `--freqaimodel CatboostRegressor`. An example of how you could set a regression target for predicting the price 100 candles into the future would be ```python df['&s-close_price'] = df['close'].shift(-100) @@ -233,7 +233,7 @@ If you want to predict multiple targets, you need to define multiple labels usin #### Classifiers -If you are using a classifier, you need to specify a target that has descrete values. FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example, if you want to predict if the price 100 candles into the future goes up or down you would set +If you are using a classifier, you need to specify a target that has discrete values. FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example, if you want to predict if the price 100 candles into the future goes up or down you would set ```python df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') @@ -241,7 +241,6 @@ df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'do If you want to predict multiple targets you must specify all labels in the same label column. You could, for example, add the label `same` to define where the price was unchanged by setting - ```python df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down') df['&s-up_or_down'] = np.where( df["close"].shift(-100) == df["close"], 'same', df['&s-up_or_down']) diff --git a/docs/freqai-running.md b/docs/freqai-running.md index 9e2b13c44..7972a6c92 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -155,7 +155,6 @@ where `unique-id` is the `identifier` set in the `freqai` configuration file. Th ![tensorboard](assets/tensorboard.jpg) - ## Setting up a follower You can indicate to the bot that it should not train models, but instead should look for models trained by a leader with a specific `identifier` by defining: From 7672586de9ff92f20993977802374156d533e64a Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 19:43:37 +0200 Subject: [PATCH 163/258] Fix unreliable hyperopt test --- tests/optimize/test_hyperopt.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 5666ebabc..c52bc9799 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -910,8 +910,9 @@ def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmpdir, }) hyperopt = Hyperopt(hyperopt_conf) hyperopt.backtesting.exchange.get_max_leverage = lambda *x, **xx: 1.0 - hyperopt.backtesting.exchange.get_min_pair_stake_amount = lambda *x, **xx: 1.0 + hyperopt.backtesting.exchange.get_min_pair_stake_amount = lambda *x, **xx: 0.00001 hyperopt.backtesting.exchange.get_max_pair_stake_amount = lambda *x, **xx: 100.0 + hyperopt.backtesting.exchange._markets = get_markets() assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto) assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter) From f0194710513de86e59a086be28518180dbf52cd5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 13 Oct 2022 19:30:59 +0200 Subject: [PATCH 164/258] Don't round prices if no custom prices have been used closes #7573 --- freqtrade/optimize/backtesting.py | 29 +++++++++++++++++------------ 1 file changed, 17 insertions(+), 12 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 83159dfe4..720069f84 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -617,13 +617,16 @@ class Backtesting: exit_reason = row[EXIT_TAG_IDX] # Custom exit pricing only for exit-signals if order_type == 'limit': - close_rate = strategy_safe_wrapper(self.strategy.custom_exit_price, - default_retval=close_rate)( + rate = strategy_safe_wrapper(self.strategy.custom_exit_price, + default_retval=close_rate)( pair=trade.pair, trade=trade, # type: ignore[arg-type] current_time=exit_candle_time, proposed_rate=close_rate, current_profit=current_profit, exit_tag=exit_reason) + if rate != close_rate: + close_rate = price_to_precision(rate, trade.price_precision, + self.precision_mode) # We can't place orders lower than current low. # freqtrade does not support this in live, and the order would fill immediately if trade.is_short: @@ -660,7 +663,6 @@ class Backtesting: # amount = amount or trade.amount 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, ft_trade_id=trade.id, @@ -674,12 +676,12 @@ class Backtesting: side=trade.exit_side, order_type=order_type, status="open", - price=rate, - average=rate, + price=close_rate, + average=close_rate, amount=amount, filled=0, remaining=amount, - cost=amount * rate, + cost=amount * close_rate, ) trade.orders.append(order) return trade @@ -726,18 +728,21 @@ class Backtesting: def get_valid_price_and_stake( self, pair: str, row: Tuple, propose_rate: float, stake_amount: float, direction: LongShort, current_time: datetime, entry_tag: Optional[str], - trade: Optional[LocalTrade], order_type: str + trade: Optional[LocalTrade], order_type: str, price_precision: Optional[float] ) -> Tuple[float, float, float, float]: if order_type == 'limit': - propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price, - default_retval=propose_rate)( + new_rate = strategy_safe_wrapper(self.strategy.custom_entry_price, + default_retval=propose_rate)( pair=pair, current_time=current_time, proposed_rate=propose_rate, entry_tag=entry_tag, side=direction, ) # default value is the open rate # We can't place orders higher than current high (otherwise it'd be a stop limit entry) # which freqtrade does not support in live. + if new_rate != propose_rate: + propose_rate = price_to_precision(new_rate, price_precision, + self.precision_mode) if direction == "short": propose_rate = max(propose_rate, row[LOW_IDX]) else: @@ -799,9 +804,11 @@ class Backtesting: pos_adjust = trade is not None and requested_rate is None stake_amount_ = stake_amount or (trade.stake_amount if trade else 0.0) + precision_price = self.exchange.get_precision_price(pair) + propose_rate, stake_amount, leverage, min_stake_amount = self.get_valid_price_and_stake( pair, row, row[OPEN_IDX], stake_amount_, direction, current_time, entry_tag, trade, - order_type + order_type, precision_price, ) # replace proposed rate if another rate was requested @@ -817,8 +824,6 @@ 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) From 7f05b44376bd62afd019e124b5931568ddcd5190 Mon Sep 17 00:00:00 2001 From: Emre Date: Thu, 13 Oct 2022 23:01:09 +0300 Subject: [PATCH 165/258] Add eval set to CatboostClassifier --- .../freqai/prediction_models/CatboostClassifier.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 2aebc3ebf..063c76d1b 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -30,6 +30,14 @@ class CatboostClassifier(BaseClassifierModel): label=data_dictionary["train_labels"], weight=data_dictionary["train_weights"], ) + if self.freqai_info.get("data_split_parameters", {}).get("test_size", 0.1) == 0: + test_data = None + else: + test_data = Pool( + data=data_dictionary["test_features"], + label=data_dictionary["test_labels"], + weight=data_dictionary["test_weights"], + ) cbr = CatBoostClassifier( allow_writing_files=True, @@ -40,6 +48,6 @@ class CatboostClassifier(BaseClassifierModel): init_model = self.get_init_model(dk.pair) - cbr.fit(train_data, init_model=init_model) + cbr.fit(X=train_data, eval_set=test_data, init_model=init_model) return cbr From 1d8d360a128830f5940b2fb9c145b766d7a94438 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 14:32:30 +0000 Subject: [PATCH 166/258] update _search_all_objects functioning --- freqtrade/commands/list_commands.py | 11 ++++------ freqtrade/resolvers/iresolver.py | 31 +++++++++++++++++++++++++++-- 2 files changed, 33 insertions(+), 9 deletions(-) diff --git a/freqtrade/commands/list_commands.py b/freqtrade/commands/list_commands.py index eb761eeec..7ab9202aa 100644 --- a/freqtrade/commands/list_commands.py +++ b/freqtrade/commands/list_commands.py @@ -1,7 +1,6 @@ import csv import logging import sys -from pathlib import Path from typing import Any, Dict, List import rapidjson @@ -10,7 +9,6 @@ from colorama import init as colorama_init from tabulate import tabulate from freqtrade.configuration import setup_utils_configuration -from freqtrade.constants import USERPATH_STRATEGIES from freqtrade.enums import RunMode from freqtrade.exceptions import OperationalException from freqtrade.exchange import market_is_active, validate_exchanges @@ -41,7 +39,7 @@ def start_list_exchanges(args: Dict[str, Any]) -> None: print(tabulate(exchanges, headers=['Exchange name', 'Valid', 'reason'])) -def _print_objs_tabular(objs: List, print_colorized: bool, base_dir: Path) -> None: +def _print_objs_tabular(objs: List, print_colorized: bool) -> None: if print_colorized: colorama_init(autoreset=True) red = Fore.RED @@ -55,7 +53,7 @@ def _print_objs_tabular(objs: List, print_colorized: bool, base_dir: Path) -> No names = [s['name'] for s in objs] objs_to_print = [{ 'name': s['name'] if s['name'] else "--", - 'location': s['location'].relative_to(base_dir), + 'location': s['location_rel'], 'status': (red + "LOAD FAILED" + reset if s['class'] is None else "OK" if names.count(s['name']) == 1 else yellow + "DUPLICATE NAME" + reset) @@ -76,9 +74,8 @@ def start_list_strategies(args: Dict[str, Any]) -> None: """ config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) - directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES)) strategy_objs = StrategyResolver.search_all_objects( - directory, not args['print_one_column'], config.get('recursive_strategy_search', False)) + config, not args['print_one_column'], config.get('recursive_strategy_search', False)) # Sort alphabetically strategy_objs = sorted(strategy_objs, key=lambda x: x['name']) for obj in strategy_objs: @@ -90,7 +87,7 @@ def start_list_strategies(args: Dict[str, Any]) -> None: if args['print_one_column']: print('\n'.join([s['name'] for s in strategy_objs])) else: - _print_objs_tabular(strategy_objs, config.get('print_colorized', False), directory) + _print_objs_tabular(strategy_objs, config.get('print_colorized', False)) def start_list_timeframes(args: Dict[str, Any]) -> None: diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index 9682e1c2b..df21f5a2d 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -183,9 +183,35 @@ class IResolver: ) @classmethod - def search_all_objects(cls, directory: Path, enum_failed: bool, + def search_all_objects(cls, config: Config, enum_failed: bool, recursive: bool = False) -> List[Dict[str, Any]]: """ + Searches for valid objects + :param config: Config object + :param enum_failed: If True, will return None for modules which fail. + Otherwise, failing modules are skipped. + :param recursive: Recursively walk directory tree searching for strategies + :return: List of dicts containing 'name', 'class' and 'location' entries + """ + result = [] + + abs_paths = cls.build_search_paths(config, user_subdir=cls.user_subdir) + print(abs_paths) + for path in abs_paths: + result.extend(cls._search_all_objects(path, enum_failed, recursive)) + return result + + @classmethod + def _build_rel_location(cls, directory: Path, entry: Path) -> str: + + builtin = cls.initial_search_path == directory + return f"/{entry.relative_to(directory)}" if builtin else entry.relative_to( + directory) + + @classmethod + def _search_all_objects(cls, directory: Path, enum_failed: bool, + recursive: bool = False) -> List[Dict[str, Any]]: + """ Searches a directory for valid objects :param directory: Path to search :param enum_failed: If True, will return None for modules which fail. @@ -204,7 +230,7 @@ class IResolver: and not entry.name.startswith('__') and not entry.name.startswith('.') ): - objects.extend(cls.search_all_objects(entry, enum_failed, recursive=recursive)) + objects.extend(cls._search_all_objects(entry, enum_failed, recursive=recursive)) # Only consider python files if entry.suffix != '.py': logger.debug('Ignoring %s', entry) @@ -217,5 +243,6 @@ class IResolver: {'name': obj[0].__name__ if obj is not None else '', 'class': obj[0] if obj is not None else None, 'location': entry, + 'location_rel': cls._build_rel_location(directory, entry), }) return objects From 9d4ba767c4d7514001a52a780fa348a85f6260c8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 14:41:25 +0000 Subject: [PATCH 167/258] Update usages of search_all_objects --- freqtrade/optimize/hyperopt_tools.py | 5 ++--- freqtrade/resolvers/iresolver.py | 11 ++++++----- freqtrade/resolvers/strategy_resolver.py | 8 ++++++++ freqtrade/rpc/api_server/api_v1.py | 4 +--- tests/strategy/test_strategy_loading.py | 6 +++--- 5 files changed, 20 insertions(+), 14 deletions(-) diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py index 65bdc4db5..393c055c4 100755 --- a/freqtrade/optimize/hyperopt_tools.py +++ b/freqtrade/optimize/hyperopt_tools.py @@ -12,7 +12,7 @@ import tabulate from colorama import Fore, Style from pandas import isna, json_normalize -from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES, Config +from freqtrade.constants import FTHYPT_FILEVERSION, Config 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 @@ -50,9 +50,8 @@ class HyperoptTools(): Get Strategy-location (filename) from strategy_name """ from freqtrade.resolvers.strategy_resolver import StrategyResolver - directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES)) strategy_objs = StrategyResolver.search_all_objects( - directory, False, config.get('recursive_strategy_search', False)) + config, False, config.get('recursive_strategy_search', False)) strategies = [s for s in strategy_objs if s['name'] == strategy_name] if strategies: strategy = strategies[0] diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index df21f5a2d..56376baa4 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -196,7 +196,6 @@ class IResolver: result = [] abs_paths = cls.build_search_paths(config, user_subdir=cls.user_subdir) - print(abs_paths) for path in abs_paths: result.extend(cls._search_all_objects(path, enum_failed, recursive)) return result @@ -209,8 +208,9 @@ class IResolver: directory) @classmethod - def _search_all_objects(cls, directory: Path, enum_failed: bool, - recursive: bool = False) -> List[Dict[str, Any]]: + def _search_all_objects( + cls, directory: Path, enum_failed: bool, recursive: bool = False, + basedir: Optional[Path] = None) -> List[Dict[str, Any]]: """ Searches a directory for valid objects :param directory: Path to search @@ -230,7 +230,8 @@ class IResolver: and not entry.name.startswith('__') and not entry.name.startswith('.') ): - objects.extend(cls._search_all_objects(entry, enum_failed, recursive=recursive)) + objects.extend(cls._search_all_objects( + entry, enum_failed, recursive, basedir or directory)) # Only consider python files if entry.suffix != '.py': logger.debug('Ignoring %s', entry) @@ -243,6 +244,6 @@ class IResolver: {'name': obj[0].__name__ if obj is not None else '', 'class': obj[0] if obj is not None else None, 'location': entry, - 'location_rel': cls._build_rel_location(directory, entry), + 'location_rel': cls._build_rel_location(basedir or directory, entry), }) return objects diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py index c574246ac..a1eb3d190 100644 --- a/freqtrade/resolvers/strategy_resolver.py +++ b/freqtrade/resolvers/strategy_resolver.py @@ -268,6 +268,14 @@ class StrategyResolver(IResolver): "or contains Python code errors." ) + @classmethod + def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None, + extra_dirs: List[str] = []) -> List[Path]: + + if 'strategy_path' in config: + extra_dirs = [config['strategy_path']] + extra_dirs + return super().build_search_paths(config, user_subdir, extra_dirs) + def warn_deprecated_setting(strategy: IStrategy, old: str, new: str, error=False): if hasattr(strategy, old): diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index 135892dc6..0e6f9500a 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -253,11 +253,9 @@ def plot_config(rpc: RPC = Depends(get_rpc)): @router.get('/strategies', response_model=StrategyListResponse, tags=['strategy']) def list_strategies(config=Depends(get_config)): - directory = Path(config.get( - 'strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES)) from freqtrade.resolvers.strategy_resolver import StrategyResolver strategies = StrategyResolver.search_all_objects( - directory, False, config.get('recursive_strategy_search', False)) + config, False, config.get('recursive_strategy_search', False)) strategies = sorted(strategies, key=lambda x: x['name']) return {'strategies': [x['name'] for x in strategies]} diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index adffd0875..8b9ae658b 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -32,7 +32,7 @@ def test_search_strategy(): def test_search_all_strategies_no_failed(): directory = Path(__file__).parent / "strats" - strategies = StrategyResolver.search_all_objects(directory, enum_failed=False) + strategies = StrategyResolver._search_all_objects(directory, enum_failed=False) assert isinstance(strategies, list) assert len(strategies) == 9 assert isinstance(strategies[0], dict) @@ -40,7 +40,7 @@ def test_search_all_strategies_no_failed(): def test_search_all_strategies_with_failed(): directory = Path(__file__).parent / "strats" - strategies = StrategyResolver.search_all_objects(directory, enum_failed=True) + strategies = StrategyResolver._search_all_objects(directory, enum_failed=True) assert isinstance(strategies, list) assert len(strategies) == 10 # with enum_failed=True search_all_objects() shall find 2 good strategies @@ -49,7 +49,7 @@ def test_search_all_strategies_with_failed(): assert len([x for x in strategies if x['class'] is None]) == 1 directory = Path(__file__).parent / "strats_nonexistingdir" - strategies = StrategyResolver.search_all_objects(directory, enum_failed=True) + strategies = StrategyResolver._search_all_objects(directory, enum_failed=True) assert len(strategies) == 0 From 4a8cb3359b7a8dd6676817f91efbdb51562918e4 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 14:59:55 +0000 Subject: [PATCH 168/258] Fix broken tests --- freqtrade/resolvers/iresolver.py | 4 ++-- freqtrade/resolvers/strategy_resolver.py | 2 +- freqtrade/rpc/api_server/api_v1.py | 2 -- tests/rpc/test_rpc_apiserver.py | 3 ++- tests/strategy/test_strategy_loading.py | 11 +++++------ 5 files changed, 10 insertions(+), 12 deletions(-) diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index 56376baa4..5c4ba1568 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -204,8 +204,8 @@ class IResolver: def _build_rel_location(cls, directory: Path, entry: Path) -> str: builtin = cls.initial_search_path == directory - return f"/{entry.relative_to(directory)}" if builtin else entry.relative_to( - directory) + return f"/{entry.relative_to(directory)}" if builtin else str( + entry.relative_to(directory)) @classmethod def _search_all_objects( diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py index a1eb3d190..ae27df3c5 100644 --- a/freqtrade/resolvers/strategy_resolver.py +++ b/freqtrade/resolvers/strategy_resolver.py @@ -272,7 +272,7 @@ class StrategyResolver(IResolver): def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None, extra_dirs: List[str] = []) -> List[Path]: - if 'strategy_path' in config: + if 'strategy_path' in config and config['strategy_path'] not in extra_dirs: extra_dirs = [config['strategy_path']] + extra_dirs return super().build_search_paths(config, user_subdir, extra_dirs) diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index 0e6f9500a..c0c9b8f57 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -1,13 +1,11 @@ import logging from copy import deepcopy -from pathlib import Path from typing import List, Optional from fastapi import APIRouter, Depends, Query from fastapi.exceptions import HTTPException from freqtrade import __version__ -from freqtrade.constants import USERPATH_STRATEGIES from freqtrade.data.history import get_datahandler from freqtrade.enums import CandleType, TradingMode from freqtrade.exceptions import OperationalException diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 684f68819..f0d74698e 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1443,8 +1443,9 @@ def test_api_plot_config(botclient): assert isinstance(rc.json()['subplots'], dict) -def test_api_strategies(botclient): +def test_api_strategies(botclient, tmpdir): ftbot, client = botclient + ftbot.config['user_data_dir'] = Path(tmpdir) rc = client_get(client, f"{BASE_URI}/strategies") diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index 8b9ae658b..ae5a4024c 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -77,10 +77,9 @@ def test_load_strategy_base64(dataframe_1m, caplog, default_conf): def test_load_strategy_invalid_directory(caplog, default_conf): - default_conf['strategy'] = 'StrategyTestV3' extra_dir = Path.cwd() / 'some/path' - with pytest.raises(OperationalException): - StrategyResolver._load_strategy(CURRENT_TEST_STRATEGY, config=default_conf, + with pytest.raises(OperationalException, match=r"Impossible to load Strategy.*"): + StrategyResolver._load_strategy('StrategyTestV333', config=default_conf, extra_dir=extra_dir) assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog) @@ -102,8 +101,8 @@ def test_load_strategy_noname(default_conf): StrategyResolver.load_strategy(default_conf) -@pytest.mark.filterwarnings("ignore:deprecated") -@pytest.mark.parametrize('strategy_name', ['StrategyTestV2']) +@ pytest.mark.filterwarnings("ignore:deprecated") +@ pytest.mark.parametrize('strategy_name', ['StrategyTestV2']) def test_strategy_pre_v3(dataframe_1m, default_conf, strategy_name): default_conf.update({'strategy': strategy_name}) @@ -349,7 +348,7 @@ def test_strategy_override_use_exit_profit_only(caplog, default_conf): assert log_has("Override strategy 'exit_profit_only' with value in config file: True.", caplog) -@pytest.mark.filterwarnings("ignore:deprecated") +@ pytest.mark.filterwarnings("ignore:deprecated") def test_missing_implements(default_conf, caplog): default_location = Path(__file__).parent / "strats" From fda3a2827bbebc2a34d97620e41399e57d0a866b Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 16:20:49 +0000 Subject: [PATCH 169/258] add list-freqAI models command --- freqtrade/commands/__init__.py | 6 +++--- freqtrade/commands/arguments.py | 24 ++++++++++++++++++------ freqtrade/commands/list_commands.py | 15 +++++++++++++++ 3 files changed, 36 insertions(+), 9 deletions(-) diff --git a/freqtrade/commands/__init__.py b/freqtrade/commands/__init__.py index d93ed1e09..788657cc8 100644 --- a/freqtrade/commands/__init__.py +++ b/freqtrade/commands/__init__.py @@ -15,9 +15,9 @@ from freqtrade.commands.db_commands import start_convert_db from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui, start_new_strategy) from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show -from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets, - start_list_strategies, start_list_timeframes, - start_show_trades) +from freqtrade.commands.list_commands import (start_list_exchanges, start_list_freqAI_models, + start_list_markets, start_list_strategies, + start_list_timeframes, start_show_trades) from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show, start_edge, start_hyperopt) from freqtrade.commands.pairlist_commands import start_test_pairlist diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index 97d8cc130..57689db0a 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -41,6 +41,8 @@ ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"] ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized", "recursive_strategy_search"] +ARGS_LIST_FREQAIMODELS = ["freqaimodel_path", "print_one_column", "print_colorized"] + ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"] ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list"] @@ -106,8 +108,8 @@ ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason "exit_reason_list", "indicator_list"] NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes", - "list-markets", "list-pairs", "list-strategies", "list-data", - "hyperopt-list", "hyperopt-show", "backtest-filter", + "list-markets", "list-pairs", "list-strategies", "list-freqaimodels", + "list-data", "hyperopt-list", "hyperopt-show", "backtest-filter", "plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"] NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"] @@ -192,10 +194,11 @@ class Arguments: start_create_userdir, start_download_data, start_edge, start_hyperopt, start_hyperopt_list, start_hyperopt_show, start_install_ui, start_list_data, start_list_exchanges, - start_list_markets, start_list_strategies, - start_list_timeframes, start_new_config, start_new_strategy, - start_plot_dataframe, start_plot_profit, start_show_trades, - start_test_pairlist, start_trading, start_webserver) + start_list_freqAI_models, start_list_markets, + start_list_strategies, start_list_timeframes, + start_new_config, start_new_strategy, start_plot_dataframe, + start_plot_profit, start_show_trades, start_test_pairlist, + start_trading, start_webserver) subparsers = self.parser.add_subparsers(dest='command', # Use custom message when no subhandler is added @@ -362,6 +365,15 @@ class Arguments: list_strategies_cmd.set_defaults(func=start_list_strategies) self._build_args(optionlist=ARGS_LIST_STRATEGIES, parser=list_strategies_cmd) + # Add list-freqAI Models subcommand + list_freqaimodels_cmd = subparsers.add_parser( + 'list-freqaimodels', + help='Print available freqAI models.', + parents=[_common_parser], + ) + list_freqaimodels_cmd.set_defaults(func=start_list_freqAI_models) + self._build_args(optionlist=ARGS_LIST_FREQAIMODELS, parser=list_freqaimodels_cmd) + # Add list-timeframes subcommand list_timeframes_cmd = subparsers.add_parser( 'list-timeframes', diff --git a/freqtrade/commands/list_commands.py b/freqtrade/commands/list_commands.py index 7ab9202aa..4e0623081 100644 --- a/freqtrade/commands/list_commands.py +++ b/freqtrade/commands/list_commands.py @@ -90,6 +90,21 @@ def start_list_strategies(args: Dict[str, Any]) -> None: _print_objs_tabular(strategy_objs, config.get('print_colorized', False)) +def start_list_freqAI_models(args: Dict[str, Any]) -> None: + """ + Print files with FreqAI models custom classes available in the directory + """ + config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) + from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver + model_objs = FreqaiModelResolver.search_all_objects(config, not args['print_one_column']) + # Sort alphabetically + model_objs = sorted(model_objs, key=lambda x: x['name']) + if args['print_one_column']: + print('\n'.join([s['name'] for s in model_objs])) + else: + _print_objs_tabular(model_objs, config.get('print_colorized', False)) + + def start_list_timeframes(args: Dict[str, Any]) -> None: """ Print timeframes available on Exchange From 2ef315e8c2fbd6f8e4b38b28893fa8f4aef275ea Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 18:24:15 +0200 Subject: [PATCH 170/258] Add documentation for list-freqaimodels --- docs/utils.md | 37 +++++++++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) diff --git a/docs/utils.md b/docs/utils.md index 174fa0527..ee8793159 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -169,6 +169,43 @@ Example: Search dedicated strategy path. freqtrade list-strategies --strategy-path ~/.freqtrade/strategies/ ``` +## List freqAI models + +Use the `list-freqaimodels` subcommand to see all freqAI models available. + +This subcommand is useful for finding problems in your environment with loading freqAI models: modules with models that contain errors and failed to load are printed in red (LOAD FAILED), while models with duplicate names are printed in yellow (DUPLICATE NAME). + +``` +usage: freqtrade list-freqaimodels [-h] [-v] [--logfile FILE] [-V] [-c PATH] + [-d PATH] [--userdir PATH] + [--freqaimodel-path PATH] [-1] [--no-color] + +optional arguments: + -h, --help show this help message and exit + --freqaimodel-path PATH + Specify additional lookup path for freqaimodels. + -1, --one-column Print output in one column. + --no-color Disable colorization of hyperopt results. May be + useful if you are redirecting output to a file. + +Common arguments: + -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). + --logfile FILE Log to the file specified. Special values are: + 'syslog', 'journald'. See the documentation for more + details. + -V, --version show program's version number and exit + -c PATH, --config PATH + Specify configuration file (default: + `userdir/config.json` or `config.json` whichever + exists). Multiple --config options may be used. Can be + set to `-` to read config from stdin. + -d PATH, --datadir PATH, --data-dir PATH + Path to directory with historical backtesting data. + --userdir PATH, --user-data-dir PATH + Path to userdata directory. + +``` + ## List Exchanges Use the `list-exchanges` subcommand to see the exchanges available for the bot. From 4bfe58706be2acb9d77384cc52a98fceba3bc820 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 14 Oct 2022 19:49:06 +0200 Subject: [PATCH 171/258] Generalize "path" variables for resolvers --- freqtrade/resolvers/freqaimodel_resolver.py | 2 +- freqtrade/resolvers/iresolver.py | 5 +++++ freqtrade/resolvers/strategy_resolver.py | 9 +-------- 3 files changed, 7 insertions(+), 9 deletions(-) diff --git a/freqtrade/resolvers/freqaimodel_resolver.py b/freqtrade/resolvers/freqaimodel_resolver.py index aa5228ca1..48c3facac 100644 --- a/freqtrade/resolvers/freqaimodel_resolver.py +++ b/freqtrade/resolvers/freqaimodel_resolver.py @@ -26,6 +26,7 @@ class FreqaiModelResolver(IResolver): initial_search_path = ( Path(__file__).parent.parent.joinpath("freqai/prediction_models").resolve() ) + extra_path = "freqaimodel_path" @staticmethod def load_freqaimodel(config: Config) -> IFreqaiModel: @@ -50,7 +51,6 @@ class FreqaiModelResolver(IResolver): freqaimodel_name, config, kwargs={"config": config}, - extra_dir=config.get("freqaimodel_path"), ) return freqaimodel diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index 5c4ba1568..0b484394a 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -42,6 +42,8 @@ class IResolver: object_type_str: str user_subdir: Optional[str] = None initial_search_path: Optional[Path] + # Optional config setting containing a path (strategy_path, freqaimodel_path) + extra_path: Optional[str] = None @classmethod def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None, @@ -58,6 +60,9 @@ class IResolver: for dir in extra_dirs: abs_paths.insert(0, Path(dir).resolve()) + if cls.extra_path and (extra := config.get(cls.extra_path)): + abs_paths.insert(0, Path(extra).resolve()) + return abs_paths @classmethod diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py index ae27df3c5..67df49dcb 100644 --- a/freqtrade/resolvers/strategy_resolver.py +++ b/freqtrade/resolvers/strategy_resolver.py @@ -30,6 +30,7 @@ class StrategyResolver(IResolver): object_type_str = "Strategy" user_subdir = USERPATH_STRATEGIES initial_search_path = None + extra_path = "strategy_path" @staticmethod def load_strategy(config: Config = None) -> IStrategy: @@ -268,14 +269,6 @@ class StrategyResolver(IResolver): "or contains Python code errors." ) - @classmethod - def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None, - extra_dirs: List[str] = []) -> List[Path]: - - if 'strategy_path' in config and config['strategy_path'] not in extra_dirs: - extra_dirs = [config['strategy_path']] + extra_dirs - return super().build_search_paths(config, user_subdir, extra_dirs) - def warn_deprecated_setting(strategy: IStrategy, old: str, new: str, error=False): if hasattr(strategy, old): From 93ad3810fd12f13457f3c9eb8e48ae50eed71d3d Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 15 Oct 2022 08:20:06 +0200 Subject: [PATCH 172/258] Add test for list-freqaimodels --- tests/commands/test_commands.py | 29 +++++++++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/tests/commands/test_commands.py b/tests/commands/test_commands.py index 28515a28a..d3bceb004 100644 --- a/tests/commands/test_commands.py +++ b/tests/commands/test_commands.py @@ -18,6 +18,7 @@ from freqtrade.commands import (start_backtesting_show, start_convert_data, star from freqtrade.commands.db_commands import start_convert_db from freqtrade.commands.deploy_commands import (clean_ui_subdir, download_and_install_ui, get_ui_download_url, read_ui_version) +from freqtrade.commands.list_commands import start_list_freqAI_models from freqtrade.configuration import setup_utils_configuration from freqtrade.enums import RunMode from freqtrade.exceptions import OperationalException @@ -944,6 +945,34 @@ def test_start_list_strategies(capsys): assert str(Path("broken_strats/broken_futures_strategies.py")) in captured.out +def test_start_list_freqAI_models(capsys): + + args = [ + "list-freqaimodels", + "-1" + ] + pargs = get_args(args) + pargs['config'] = None + start_list_freqAI_models(pargs) + captured = capsys.readouterr() + assert "LightGBMClassifier" in captured.out + assert "LightGBMRegressor" in captured.out + assert "XGBoostRegressor" in captured.out + assert "/LightGBMRegressor.py" not in captured.out + + args = [ + "list-freqaimodels", + ] + pargs = get_args(args) + pargs['config'] = None + start_list_freqAI_models(pargs) + captured = capsys.readouterr() + assert "LightGBMClassifier" in captured.out + assert "LightGBMRegressor" in captured.out + assert "XGBoostRegressor" in captured.out + assert "/LightGBMRegressor.py" in captured.out + + def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys): patch_exchange(mocker, mock_markets=True) mocker.patch.multiple('freqtrade.exchange.Exchange', From 498289728d0cc08e8821d83098cddb82bef9b19a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 15 Oct 2022 08:48:41 +0200 Subject: [PATCH 173/258] Fix catboost tests polluting CWD --- tests/freqai/test_freqai_interface.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index 445b718d2..6917bc64b 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -55,6 +55,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model): data_load_timerange = TimeRange.parse_timerange("20180125-20180130") new_timerange = TimeRange.parse_timerange("20180127-20180130") + freqai.dk.set_paths('ADA/BTC', None) freqai.extract_data_and_train_model( new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) @@ -93,6 +94,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") + freqai.dk.set_paths('ADA/BTC', None) freqai.extract_data_and_train_model( new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) @@ -134,6 +136,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): data_load_timerange = TimeRange.parse_timerange("20180110-20180130") new_timerange = TimeRange.parse_timerange("20180120-20180130") + freqai.dk.set_paths('ADA/BTC', None) freqai.extract_data_and_train_model(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange) From c8e6dad9cdec45493b999363032765b5fc5e0e8e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 15 Oct 2022 12:00:20 +0200 Subject: [PATCH 174/258] use exit_reason to determine left open trades --- freqtrade/optimize/optimize_reports.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 8dafe2e41..c406f866b 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -408,10 +408,10 @@ def generate_strategy_stats(pairlist: List[str], exit_reason_stats = generate_exit_reason_stats(max_open_trades=max_open_trades, results=results) - left_open_results = generate_pair_metrics(pairlist, stake_currency=stake_currency, - starting_balance=start_balance, - results=results.loc[results['is_open']], - skip_nan=True) + left_open_results = generate_pair_metrics( + pairlist, stake_currency=stake_currency, starting_balance=start_balance, + results=results.loc[results['exit_reason'] == 'force_exit'], skip_nan=True) + daily_stats = generate_daily_stats(results) trade_stats = generate_trading_stats(results) best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'], From 05ca725e4def506dd5727cd831b5ee3353eca932 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 15 Oct 2022 12:07:22 +0200 Subject: [PATCH 175/258] Remove no longer needed local state --- freqtrade/optimize/backtesting.py | 14 +++----------- 1 file changed, 3 insertions(+), 11 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 720069f84..0d5910a62 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -919,11 +919,10 @@ class Backtesting: return trade def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]], - data: Dict[str, List[Tuple]]) -> List[LocalTrade]: + data: Dict[str, List[Tuple]]) -> None: """ Handling of left open trades at the end of backtesting """ - trades = [] for pair in open_trades.keys(): if len(open_trades[pair]) > 0: for trade in open_trades[pair]: @@ -938,11 +937,6 @@ class Backtesting: trade.exit_reason = ExitType.FORCE_EXIT.value trade.close(exit_row[OPEN_IDX], show_msg=False) LocalTrade.close_bt_trade(trade) - # Deepcopy object to have wallets update correctly - trade1 = deepcopy(trade) - trade1.is_open = True - trades.append(trade1) - return trades def trade_slot_available(self, max_open_trades: int, open_trade_count: int) -> bool: # Always allow trades when max_open_trades is enabled. @@ -1094,7 +1088,6 @@ class Backtesting: :param enable_protections: Should protections be enabled? :return: DataFrame with trades (results of backtesting) """ - trades: List[LocalTrade] = [] self.prepare_backtest(enable_protections) # Ensure wallets are uptodate (important for --strategy-list) self.wallets.update() @@ -1188,7 +1181,6 @@ class Backtesting: open_trade_count -= 1 open_trades[pair].remove(trade) LocalTrade.close_bt_trade(trade) - trades.append(trade) self.wallets.update() self.run_protections( enable_protections, pair, current_time, trade.trade_direction) @@ -1197,10 +1189,10 @@ class Backtesting: self.progress.increment() current_time += timedelta(minutes=self.timeframe_min) - trades += self.handle_left_open(open_trades, data=data) + self.handle_left_open(open_trades, data=data) self.wallets.update() - results = trade_list_to_dataframe(trades) + results = trade_list_to_dataframe(LocalTrade.trades) return { 'results': results, 'config': self.strategy.config, From d81eef0b708719f28fc299bb986ad864cacba823 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 15 Oct 2022 13:23:01 +0200 Subject: [PATCH 176/258] add timestamps to each metric, use rapidjson --- freqtrade/freqai/data_drawer.py | 37 ++++++++-------------------- freqtrade/freqai/freqai_interface.py | 6 ++--- 2 files changed, 13 insertions(+), 30 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 17dc00370..5e71df3a5 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -1,9 +1,9 @@ import collections -import json import logging import re import shutil import threading +from datetime import datetime, timezone from pathlib import Path from typing import Any, Dict, Tuple, TypedDict @@ -95,7 +95,7 @@ class FreqaiDataDrawer: self.empty_pair_dict: pair_info = { "model_filename": "", "trained_timestamp": 0, "data_path": "", "extras": {}} - self.metric_tracker: Dict[str, Dict[str, list]] = {} + self.metric_tracker: Dict[str, Dict[str, Dict[str, list]]] = {} def update_metric_tracker(self, metric: str, value: float, pair: str) -> None: """ @@ -106,9 +106,11 @@ class FreqaiDataDrawer: if pair not in self.metric_tracker: self.metric_tracker[pair] = {} if metric not in self.metric_tracker[pair]: - self.metric_tracker[pair][metric] = [] + self.metric_tracker[pair][metric] = {'timestamp': [], 'value': []} - self.metric_tracker[pair][metric].append(value) + timestamp = int(datetime.now(timezone.utc).timestamp()) + self.metric_tracker[pair][metric]['value'].append(value) + self.metric_tracker[pair][metric]['timestamp'].append(timestamp) def collect_metrics(self, time_spent: float, pair: str): """ @@ -130,7 +132,7 @@ class FreqaiDataDrawer: exists = self.pair_dictionary_path.is_file() if exists: with open(self.pair_dictionary_path, "r") as fp: - self.pair_dict = json.load(fp) + self.pair_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) elif not self.follow_mode: logger.info("Could not find existing datadrawer, starting from scratch") else: @@ -148,7 +150,7 @@ class FreqaiDataDrawer: exists = self.metric_tracker_path.is_file() if exists: with open(self.metric_tracker_path, "r") as fp: - self.metric_tracker = json.load(fp) + self.metric_tracker = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) else: logger.info("Could not find existing metric tracker, starting from scratch") @@ -515,7 +517,7 @@ class FreqaiDataDrawer: presaved backtesting (prediction file loading). """ with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: - dk.data = json.load(fp) + dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) dk.training_features_list = dk.data["training_features_list"] dk.label_list = dk.data["label_list"] @@ -542,7 +544,7 @@ class FreqaiDataDrawer: ) with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: - dk.data = json.load(fp) + dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) dk.training_features_list = dk.data["training_features_list"] dk.label_list = dk.data["label_list"] @@ -676,22 +678,3 @@ class FreqaiDataDrawer: ).reset_index(drop=True) return corr_dataframes, base_dataframes - - # to be used if we want to send predictions directly to the follower instead of forcing - # follower to load models and inference - # def save_model_return_values_to_disk(self) -> None: - # with open(self.full_path / str('model_return_values.json'), "w") as fp: - # json.dump(self.model_return_values, fp, default=self.np_encoder) - - # def load_model_return_values_from_disk(self, dk: FreqaiDataKitchen) -> FreqaiDataKitchen: - # exists = Path(self.full_path / str('model_return_values.json')).resolve().exists() - # if exists: - # with open(self.full_path / str('model_return_values.json'), "r") as fp: - # self.model_return_values = json.load(fp) - # elif not self.follow_mode: - # logger.info("Could not find existing datadrawer, starting from scratch") - # else: - # logger.warning(f'Follower could not find pair_dictionary at {self.full_path} ' - # 'sending null values back to strategy') - - # return exists, dk diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index 9ae23f0d2..db0d4c379 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -7,7 +7,7 @@ from collections import deque from datetime import datetime, timezone from pathlib import Path from threading import Lock -from typing import Any, Dict, List, Tuple +from typing import Any, Dict, List, Literal, Tuple import numpy as np import pandas as pd @@ -657,7 +657,7 @@ class IFreqaiModel(ABC): return - def inference_timer(self, do: str = 'start', pair: str = ''): + def inference_timer(self, do: Literal['start', 'stop'] = 'start', pair: str = ''): """ Timer designed to track the cumulative time spent in FreqAI for one pass through the whitelist. This will check if the time spent is more than 1/4 the time @@ -682,7 +682,7 @@ class IFreqaiModel(ABC): self.inference_time = 0 return - def train_timer(self, do: str = 'start', pair: str = ''): + def train_timer(self, do: Literal['start', 'stop'] = 'start', pair: str = ''): """ Timer designed to track the cumulative time spent training the full pairlist in FreqAI. From 99dbba6cadaad9074f5276047896d895d52e03b3 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 15 Oct 2022 13:50:55 +0200 Subject: [PATCH 177/258] avoid reading from disk to instantiate large objects --- freqtrade/freqai/data_drawer.py | 26 +++++++++++++++++++------- 1 file changed, 19 insertions(+), 7 deletions(-) diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index 465ba27f5..69b3e1781 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -65,6 +65,8 @@ class FreqaiDataDrawer: self.pair_dict: Dict[str, pair_info] = {} # dictionary holding all actively inferenced models in memory given a model filename self.model_dictionary: Dict[str, Any] = {} + # all additional metadata that we want to keep in ram + self.meta_data_dictionary: Dict[str, Dict[str, Any]] = {} self.model_return_values: Dict[str, DataFrame] = {} self.historic_data: Dict[str, Dict[str, DataFrame]] = {} self.historic_predictions: Dict[str, DataFrame] = {} @@ -453,9 +455,14 @@ class FreqaiDataDrawer: ) # if self.live: + # store as much in ram as possible to increase performance self.model_dictionary[coin] = model self.pair_dict[coin]["model_filename"] = dk.model_filename self.pair_dict[coin]["data_path"] = str(dk.data_path) + if coin not in self.meta_data_dictionary: + self.meta_data_dictionary[coin] = {} + self.meta_data_dictionary[coin]["train_df"] = dk.data_dictionary["train_features"] + self.meta_data_dictionary[coin]["meta_data"] = dk.data self.save_drawer_to_disk() return @@ -492,14 +499,19 @@ class FreqaiDataDrawer: / dk.data_path.parts[-1] ) - with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: - dk.data = json.load(fp) - dk.training_features_list = dk.data["training_features_list"] - dk.label_list = dk.data["label_list"] + if coin in self.meta_data_dictionary: + dk.data = self.meta_data_dictionary[coin]["meta_data"] + dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin]["train_df"] + else: + with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: + dk.data = json.load(fp) - dk.data_dictionary["train_features"] = pd.read_pickle( - dk.data_path / f"{dk.model_filename}_trained_df.pkl" - ) + dk.data_dictionary["train_features"] = pd.read_pickle( + dk.data_path / f"{dk.model_filename}_trained_df.pkl" + ) + + dk.training_features_list = dk.data["training_features_list"] + dk.label_list = dk.data["label_list"] # try to access model in memory instead of loading object from disk to save time if dk.live and coin in self.model_dictionary: From 20fc52177128ee24b3812b5cf9235dd941a23611 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Sat, 15 Oct 2022 23:30:12 +0200 Subject: [PATCH 178/258] Fix constant PCA --- freqtrade/freqai/data_kitchen.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 52261d341..7f3e7cb01 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -206,11 +206,15 @@ class FreqaiDataKitchen: drop_index = pd.isnull(filtered_df).any(axis=1) # get the rows that have NaNs, drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement. + ft_params = self.freqai_config["feature_parameters"] 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.") + if not ft_params.get( + "principal_component_analysis", False + ): + 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 @@ -241,7 +245,10 @@ class FreqaiDataKitchen: self.data["filter_drop_index_training"] = drop_index else: - filtered_df = self.check_pred_labels(filtered_df) + if not ft_params.get( + "principal_component_analysis", False + ): + filtered_df = self.check_pred_labels(filtered_df) # 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_df).any(axis=1) From b6c096d3bc5aaf10edb08c40aa895f5612c1bd5c Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 15 Oct 2022 12:08:58 +0200 Subject: [PATCH 179/258] Simplify backtest condition --- 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 0d5910a62..0dd99aea3 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -924,19 +924,18 @@ class Backtesting: Handling of left open trades at the end of backtesting """ for pair in open_trades.keys(): - if len(open_trades[pair]) > 0: - for trade in open_trades[pair]: - if trade.open_order_id and trade.nr_of_successful_entries == 0: - # Ignore trade if entry-order did not fill yet - continue - exit_row = data[pair][-1] - self._exit_trade(trade, exit_row, exit_row[OPEN_IDX], trade.amount) - trade.orders[-1].close_bt_order(exit_row[DATE_IDX].to_pydatetime(), trade) + for trade in open_trades[pair]: + if trade.open_order_id and trade.nr_of_successful_entries == 0: + # Ignore trade if entry-order did not fill yet + continue + exit_row = data[pair][-1] + self._exit_trade(trade, exit_row, exit_row[OPEN_IDX], trade.amount) + trade.orders[-1].close_bt_order(exit_row[DATE_IDX].to_pydatetime(), trade) - trade.close_date = exit_row[DATE_IDX].to_pydatetime() - trade.exit_reason = ExitType.FORCE_EXIT.value - trade.close(exit_row[OPEN_IDX], show_msg=False) - LocalTrade.close_bt_trade(trade) + trade.close_date = exit_row[DATE_IDX].to_pydatetime() + trade.exit_reason = ExitType.FORCE_EXIT.value + trade.close(exit_row[OPEN_IDX], show_msg=False) + LocalTrade.close_bt_trade(trade) def trade_slot_available(self, max_open_trades: int, open_trade_count: int) -> bool: # Always allow trades when max_open_trades is enabled. From de9f5660f3b6702c562e208fbc7cfc651a54b870 Mon Sep 17 00:00:00 2001 From: Evgeniy Vladimirov Date: Sun, 16 Oct 2022 12:56:59 +0300 Subject: [PATCH 180/258] Fix counting available trade slots in backtesting. --- freqtrade/optimize/backtesting.py | 1 + tests/optimize/test_backtesting.py | 29 +++++++++++++++ .../strategy_test_v3_custom_entry_price.py | 37 +++++++++++++++++++ 3 files changed, 67 insertions(+) create mode 100644 tests/strategy/strats/strategy_test_v3_custom_entry_price.py diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 0dd99aea3..455dceda2 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -1123,6 +1123,7 @@ class Backtesting: if self.manage_open_orders(t, current_time, row): # Close trade open_trade_count -= 1 + open_trade_count_start -= 1 open_trades[pair].remove(t) LocalTrade.trades_open.remove(t) self.wallets.update() diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index 907e97fb7..fa59762db 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -799,6 +799,35 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: t["close_rate"], 6) < round(ln.iloc[0]["high"], 6)) +def test_backtest_timedout_entry_orders(default_conf, fee, mocker, testdatadir) -> None: + # This strategy intentionally places unfillable orders. + default_conf['strategy'] = 'StrategyTestV3CustomEntryPrice' + default_conf['startup_candle_count'] = 0 + # Cancel unfilled order after 4 minutes on 5m timeframe. + default_conf["unfilledtimeout"] = {"entry": 4} + mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) + 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) + backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) + # Testing dataframe contains 11 candles. Expecting 10 timed out orders. + timerange = TimeRange('date', 'date', 1517227800, 1517231100) + data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'], + timerange=timerange) + min_date, max_date = get_timerange(data) + + result = backtesting.backtest( + processed=deepcopy(data), + start_date=min_date, + end_date=max_date, + max_open_trades=1, + position_stacking=False, + ) + + assert result['timedout_entry_orders'] == 10 + + def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None: default_conf['use_exit_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) diff --git a/tests/strategy/strats/strategy_test_v3_custom_entry_price.py b/tests/strategy/strats/strategy_test_v3_custom_entry_price.py new file mode 100644 index 000000000..872984156 --- /dev/null +++ b/tests/strategy/strats/strategy_test_v3_custom_entry_price.py @@ -0,0 +1,37 @@ +# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement + +from datetime import datetime +from typing import Optional + +from pandas import DataFrame +from strategy_test_v3 import StrategyTestV3 + + +class StrategyTestV3CustomEntryPrice(StrategyTestV3): + """ + Strategy used by tests freqtrade bot. + Please do not modify this strategy, it's intended for internal use only. + Please look at the SampleStrategy in the user_data/strategy directory + or strategy repository https://github.com/freqtrade/freqtrade-strategies + for samples and inspiration. + """ + new_entry_price: float = 0.001 + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + return dataframe + + def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + dataframe.loc[ + dataframe['volume'] > 0, + 'enter_long'] = 1 + + return dataframe + + def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + return dataframe + + def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float, + entry_tag: Optional[str], side: str, **kwargs) -> float: + + return self.new_entry_price From b7dce8d24abd069a7830c456ca5650c6beb6cd69 Mon Sep 17 00:00:00 2001 From: Matteo Manzi <33622899+matteoettam09@users.noreply.github.com> Date: Sun, 16 Oct 2022 12:02:27 +0200 Subject: [PATCH 181/258] Update stoploss.md --- docs/stoploss.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/stoploss.md b/docs/stoploss.md index 249c40109..a8285cf04 100644 --- a/docs/stoploss.md +++ b/docs/stoploss.md @@ -87,7 +87,7 @@ At this stage the bot contains the following stoploss support modes: 2. Trailing stop loss. 3. Trailing stop loss, custom positive loss. 4. Trailing stop loss only once the trade has reached a certain offset. -5. [Custom stoploss function](strategy-advanced.md#custom-stoploss) +5. [Custom stoploss function](strategy-callbacks.md#custom-stoploss) ### Static Stop Loss From 82d75d8914567698bb9fe62091130dafb6afd2ff Mon Sep 17 00:00:00 2001 From: Evgeniy Vladimirov Date: Sun, 16 Oct 2022 14:59:55 +0300 Subject: [PATCH 182/258] Fix tests that failed due to new strategy. --- tests/rpc/test_rpc_apiserver.py | 1 + tests/strategy/test_strategy_loading.py | 7 ++++--- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index f0d74698e..6c28c1cac 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1457,6 +1457,7 @@ def test_api_strategies(botclient, tmpdir): 'InformativeDecoratorTest', 'StrategyTestV2', 'StrategyTestV3', + 'StrategyTestV3CustomEntryPrice', 'StrategyTestV3Futures', 'freqai_test_classifier', 'freqai_test_multimodel_strat', diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index ae5a4024c..2d13fc380 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver._search_all_objects(directory, enum_failed=False) assert isinstance(strategies, list) - assert len(strategies) == 9 + assert len(strategies) == 10 assert isinstance(strategies[0], dict) @@ -42,10 +42,11 @@ def test_search_all_strategies_with_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver._search_all_objects(directory, enum_failed=True) assert isinstance(strategies, list) - assert len(strategies) == 10 + assert len(strategies) == 11 # with enum_failed=True search_all_objects() shall find 2 good strategies # and 1 which fails to load - assert len([x for x in strategies if x['class'] is not None]) == 9 + assert len([x for x in strategies if x['class'] is not None]) == 10 + assert len([x for x in strategies if x['class'] is None]) == 1 directory = Path(__file__).parent / "strats_nonexistingdir" From e82baf5f60973d723ba609b7d9ea914a8c424d14 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 16 Oct 2022 13:19:42 +0200 Subject: [PATCH 183/258] Use helper-method to modify trades_open --- freqtrade/optimize/backtesting.py | 2 +- freqtrade/persistence/trade_model.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 455dceda2..68e45fae0 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -1125,7 +1125,7 @@ class Backtesting: open_trade_count -= 1 open_trade_count_start -= 1 open_trades[pair].remove(t) - LocalTrade.trades_open.remove(t) + LocalTrade.remove_bt_trade(t) self.wallets.update() # 2. Process entries. diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 6e421f33e..c632aa817 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -1077,6 +1077,10 @@ class LocalTrade(): else: LocalTrade.trades.append(trade) + @staticmethod + def remove_bt_trade(trade): + LocalTrade.trades_open.remove(trade) + @staticmethod def get_open_trades() -> List[Any]: """ From dd3f62ac137a52d0013d41baee2d33343b2bfec0 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:10 +0000 Subject: [PATCH 184/258] Bump types-python-dateutil from 2.8.19 to 2.8.19.1 Bumps [types-python-dateutil](https://github.com/python/typeshed) from 2.8.19 to 2.8.19.1. - [Release notes](https://github.com/python/typeshed/releases) - [Commits](https://github.com/python/typeshed/commits) --- updated-dependencies: - dependency-name: types-python-dateutil 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 a3ac21985..3f7277020 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -27,4 +27,4 @@ types-cachetools==5.2.1 types-filelock==3.2.7 types-requests==2.28.11.2 types-tabulate==0.9.0.0 -types-python-dateutil==2.8.19 +types-python-dateutil==2.8.19.1 From 8550eb513ef929c54e9d1bafb4bd26715003fca0 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:22 +0000 Subject: [PATCH 185/258] Bump numpy from 1.23.3 to 1.23.4 Bumps [numpy](https://github.com/numpy/numpy) from 1.23.3 to 1.23.4. - [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/v1.23.3...v1.23.4) --- 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 b7d4162b6..b13b665f2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,4 @@ -numpy==1.23.3 +numpy==1.23.4 pandas==1.5.0; platform_machine != 'armv7l' # Piwheels doesn't have 1.5.0 yet. pandas==1.4.3; platform_machine == 'armv7l' From 2ddfc7bbbae9b703753f90b28e6e36e36075cc52 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:37 +0000 Subject: [PATCH 186/258] Bump mkdocs from 1.4.0 to 1.4.1 Bumps [mkdocs](https://github.com/mkdocs/mkdocs) from 1.4.0 to 1.4.1. - [Release notes](https://github.com/mkdocs/mkdocs/releases) - [Commits](https://github.com/mkdocs/mkdocs/compare/1.4.0...1.4.1) --- updated-dependencies: - dependency-name: mkdocs 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 4ff1780cf..ad4aa7e89 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,5 +1,5 @@ markdown==3.3.7 -mkdocs==1.4.0 +mkdocs==1.4.1 mkdocs-material==8.5.6 mdx_truly_sane_lists==1.3 pymdown-extensions==9.6 From a9bb7db06c9e6e0f7b7fabb35c9393ff7c13c2f4 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:46 +0000 Subject: [PATCH 187/258] Bump sqlalchemy from 1.4.41 to 1.4.42 Bumps [sqlalchemy](https://github.com/sqlalchemy/sqlalchemy) from 1.4.41 to 1.4.42. - [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 b7d4162b6..1c60d0b71 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,7 @@ ccxt==1.95.30 # Pin cryptography for now due to rust build errors with piwheels cryptography==38.0.1 aiohttp==3.8.3 -SQLAlchemy==1.4.41 +SQLAlchemy==1.4.42 python-telegram-bot==13.14 arrow==1.2.3 cachetools==4.2.2 From 600b886241d360b951c4c6212900a376df62dc2c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:51 +0000 Subject: [PATCH 188/258] Bump lightgbm from 3.3.2 to 3.3.3 Bumps [lightgbm](https://github.com/microsoft/LightGBM) from 3.3.2 to 3.3.3. - [Release notes](https://github.com/microsoft/LightGBM/releases) - [Commits](https://github.com/microsoft/LightGBM/compare/v3.3.2...v3.3.3) --- updated-dependencies: - dependency-name: lightgbm dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] --- requirements-freqai.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-freqai.txt b/requirements-freqai.txt index c78b3b25e..201d5be1b 100644 --- a/requirements-freqai.txt +++ b/requirements-freqai.txt @@ -5,6 +5,6 @@ scikit-learn==1.1.2 joblib==1.2.0 catboost==1.1; platform_machine != 'aarch64' -lightgbm==3.3.2 +lightgbm==3.3.3 xgboost==1.6.2 tensorboard==2.10.1 From 7ec1e3b94f3d3129a1cd60668fe26c0feeb9bbbd Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 03:01:55 +0000 Subject: [PATCH 189/258] Bump fastapi from 0.85.0 to 0.85.1 Bumps [fastapi](https://github.com/tiangolo/fastapi) from 0.85.0 to 0.85.1. - [Release notes](https://github.com/tiangolo/fastapi/releases) - [Commits](https://github.com/tiangolo/fastapi/compare/0.85.0...0.85.1) --- updated-dependencies: - dependency-name: fastapi 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 b7d4162b6..11a892f40 100644 --- a/requirements.txt +++ b/requirements.txt @@ -37,7 +37,7 @@ orjson==3.8.0 sdnotify==0.3.2 # API Server -fastapi==0.85.0 +fastapi==0.85.1 pydantic>=1.8.0 uvicorn==0.18.3 pyjwt==2.5.0 From 5aeea5b14cb25bba31458a0253bea9e7bc3c4d97 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 17 Oct 2022 04:35:36 +0000 Subject: [PATCH 190/258] Bump ccxt from 1.95.30 to 2.0.25 Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.95.30 to 2.0.25. - [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/1.95.30...2.0.25) --- updated-dependencies: - dependency-name: ccxt 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 967fe113d..64d861469 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ pandas==1.5.0; platform_machine != 'armv7l' pandas==1.4.3; platform_machine == 'armv7l' pandas-ta==0.3.14b -ccxt==1.95.30 +ccxt==2.0.25 # Pin cryptography for now due to rust build errors with piwheels cryptography==38.0.1 aiohttp==3.8.3 From 0e8cf366f5f0e48dd26d50c1dd7c6f4937c9190e Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 16 Oct 2022 13:34:58 +0200 Subject: [PATCH 191/258] Keep trade state in LocalTrade --- freqtrade/optimize/backtesting.py | 21 ++++++--------------- freqtrade/persistence/trade_model.py | 14 +++++++++++++- tests/test_persistence.py | 4 +++- 3 files changed, 22 insertions(+), 17 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 68e45fae0..1908a261a 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -924,7 +924,7 @@ class Backtesting: Handling of left open trades at the end of backtesting """ for pair in open_trades.keys(): - for trade in open_trades[pair]: + for trade in list(open_trades[pair]): if trade.open_order_id and trade.nr_of_successful_entries == 0: # Ignore trade if entry-order did not fill yet continue @@ -1098,15 +1098,12 @@ class Backtesting: indexes: Dict = defaultdict(int) current_time = start_date + timedelta(minutes=self.timeframe_min) - open_trades: Dict[str, List[LocalTrade]] = defaultdict(list) - open_trade_count = 0 - self.progress.init_step(BacktestState.BACKTEST, int( (end_date - start_date) / timedelta(minutes=self.timeframe_min))) # Loop timerange and get candle for each pair at that point in time while current_time <= end_date: - open_trade_count_start = open_trade_count + open_trade_count_start = LocalTrade.bt_open_open_trade_count self.check_abort() for i, pair in enumerate(data): row_index = indexes[pair] @@ -1118,13 +1115,11 @@ class Backtesting: indexes[pair] = row_index self.dataprovider._set_dataframe_max_index(row_index) - for t in list(open_trades[pair]): + for t in list(LocalTrade.bt_trades_open_pp[pair]): # 1. Manage currently open orders of active trades if self.manage_open_orders(t, current_time, row): # Close trade - open_trade_count -= 1 open_trade_count_start -= 1 - open_trades[pair].remove(t) LocalTrade.remove_bt_trade(t) self.wallets.update() @@ -1134,7 +1129,7 @@ class Backtesting: # don't open on the last row trade_dir = self.check_for_trade_entry(row) if ( - (position_stacking or len(open_trades[pair]) == 0) + (position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0) and self.trade_slot_available(max_open_trades, open_trade_count_start) and current_time != end_date and trade_dir is not None @@ -1146,13 +1141,11 @@ class Backtesting: # This emulates previous behavior - not sure if this is correct # Prevents entering if the trade-slot was freed in this candle open_trade_count_start += 1 - open_trade_count += 1 # logger.debug(f"{pair} - Emulate creation of new trade: {trade}.") - open_trades[pair].append(trade) LocalTrade.add_bt_trade(trade) self.wallets.update() - for trade in list(open_trades[pair]): + for trade in list(LocalTrade.bt_trades_open_pp[pair]): # 3. Process entry orders. order = trade.select_order(trade.entry_side, is_open=True) if order and self._get_order_filled(order.price, row): @@ -1178,8 +1171,6 @@ class Backtesting: trade.close(order.price, show_msg=False) # logger.debug(f"{pair} - Backtesting exit {trade}") - open_trade_count -= 1 - open_trades[pair].remove(trade) LocalTrade.close_bt_trade(trade) self.wallets.update() self.run_protections( @@ -1189,7 +1180,7 @@ class Backtesting: self.progress.increment() current_time += timedelta(minutes=self.timeframe_min) - self.handle_left_open(open_trades, data=data) + self.handle_left_open(LocalTrade.bt_trades_open_pp, data=data) self.wallets.update() results = trade_list_to_dataframe(LocalTrade.trades) diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index c632aa817..73e067480 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -2,6 +2,7 @@ This module contains the class to persist trades into SQLite """ import logging +from collections import defaultdict from datetime import datetime, timedelta, timezone from math import isclose from typing import Any, Dict, List, Optional @@ -255,6 +256,9 @@ class LocalTrade(): # Trades container for backtesting trades: List['LocalTrade'] = [] trades_open: List['LocalTrade'] = [] + # Copy of trades_open - but indexed by pair + bt_trades_open_pp: Dict[str, List['LocalTrade']] = defaultdict(list) + bt_open_open_trade_count: int = 0 total_profit: float = 0 realized_profit: float = 0 @@ -538,6 +542,8 @@ class LocalTrade(): """ LocalTrade.trades = [] LocalTrade.trades_open = [] + LocalTrade.bt_trades_open_pp = defaultdict(list) + LocalTrade.bt_open_open_trade_count = 0 LocalTrade.total_profit = 0 def adjust_min_max_rates(self, current_price: float, current_price_low: float) -> None: @@ -1067,6 +1073,8 @@ class LocalTrade(): @staticmethod def close_bt_trade(trade): LocalTrade.trades_open.remove(trade) + LocalTrade.bt_trades_open_pp[trade.pair].remove(trade) + LocalTrade.bt_open_open_trade_count -= 1 LocalTrade.trades.append(trade) LocalTrade.total_profit += trade.close_profit_abs @@ -1074,12 +1082,16 @@ class LocalTrade(): def add_bt_trade(trade): if trade.is_open: LocalTrade.trades_open.append(trade) + LocalTrade.bt_trades_open_pp[trade.pair].append(trade) + LocalTrade.bt_open_open_trade_count += 1 else: LocalTrade.trades.append(trade) @staticmethod def remove_bt_trade(trade): LocalTrade.trades_open.remove(trade) + LocalTrade.bt_trades_open_pp[trade.pair].remove(trade) + LocalTrade.bt_open_open_trade_count -= 1 @staticmethod def get_open_trades() -> List[Any]: @@ -1096,7 +1108,7 @@ class LocalTrade(): if Trade.use_db: return Trade.query.filter(Trade.is_open.is_(True)).count() else: - return len(LocalTrade.trades_open) + return LocalTrade.bt_open_open_trade_count @staticmethod def stoploss_reinitialization(desired_stoploss): diff --git a/tests/test_persistence.py b/tests/test_persistence.py index e7f218c02..ae2672830 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -2406,6 +2406,8 @@ def test_Trade_object_idem(): 'get_trading_volume', ) + EXCLUDES2 = ('trades', 'trades_open', 'bt_trades_open_pp', 'bt_open_open_trade_count', + 'total_profit') # Parent (LocalTrade) should have the same attributes for item in trade: @@ -2416,7 +2418,7 @@ def test_Trade_object_idem(): # Fails if only a column is added without corresponding parent field for item in localtrade: if (not item.startswith('__') - and item not in ('trades', 'trades_open', 'total_profit') + and item not in EXCLUDES2 and type(getattr(LocalTrade, item)) not in (property, FunctionType)): assert item in trade From 8534dfb0d45f11288bc792a71e9c7a7899e1a5f9 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 16 Oct 2022 17:12:44 +0200 Subject: [PATCH 192/258] Extract backtest 1 candle from main function --- freqtrade/optimize/backtesting.py | 133 ++++++++++++++++-------------- 1 file changed, 73 insertions(+), 60 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 1908a261a..89b652e33 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -1067,6 +1067,76 @@ class Backtesting: return None return row + def backtest_loop( + self, row: Tuple, pair: str, current_time: datetime, end_date: datetime, + max_open_trades: int, position_stacking: bool, enable_protections: bool, + open_trade_count_start: int) -> int: + """ + NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized. + + Backtesting processing for one candle. + """ + for t in list(LocalTrade.bt_trades_open_pp[pair]): + # 1. Manage currently open orders of active trades + if self.manage_open_orders(t, current_time, row): + # Close trade + open_trade_count_start -= 1 + LocalTrade.remove_bt_trade(t) + self.wallets.update() + + # 2. Process entries. + # without positionstacking, we can only have one open trade per pair. + # max_open_trades must be respected + # don't open on the last row + trade_dir = self.check_for_trade_entry(row) + if ( + (position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0) + and self.trade_slot_available(max_open_trades, open_trade_count_start) + and current_time != end_date + and trade_dir is not None + and not PairLocks.is_pair_locked(pair, row[DATE_IDX], trade_dir) + ): + trade = self._enter_trade(pair, row, trade_dir) + if trade: + # TODO: hacky workaround to avoid opening > max_open_trades + # This emulates previous behavior - not sure if this is correct + # Prevents entering if the trade-slot was freed in this candle + open_trade_count_start += 1 + # logger.debug(f"{pair} - Emulate creation of new trade: {trade}.") + LocalTrade.add_bt_trade(trade) + self.wallets.update() + + for trade in list(LocalTrade.bt_trades_open_pp[pair]): + # 3. Process entry orders. + order = trade.select_order(trade.entry_side, is_open=True) + if order and self._get_order_filled(order.price, row): + order.close_bt_order(current_time, trade) + trade.open_order_id = None + self.wallets.update() + + # 4. Create exit orders (if any) + if not trade.open_order_id: + self._get_exit_trade_entry(trade, row) # Place exit order if necessary + + # 5. Process exit orders. + order = trade.select_order(trade.exit_side, is_open=True) + if order and self._get_order_filled(order.price, row): + order.close_bt_order(current_time, trade) + trade.open_order_id = None + sub_trade = order.safe_amount_after_fee != trade.amount + if sub_trade: + order.close_bt_order(current_time, trade) + trade.recalc_trade_from_orders() + else: + trade.close_date = current_time + trade.close(order.price, show_msg=False) + + # logger.debug(f"{pair} - Backtesting exit {trade}") + LocalTrade.close_bt_trade(trade) + self.wallets.update() + self.run_protections(enable_protections, pair, current_time, trade.trade_direction) + return open_trade_count_start + def backtest(self, processed: Dict, # noqa: max-complexity: 13 start_date: datetime, end_date: datetime, max_open_trades: int = 0, position_stacking: bool = False, @@ -1115,66 +1185,9 @@ class Backtesting: indexes[pair] = row_index self.dataprovider._set_dataframe_max_index(row_index) - for t in list(LocalTrade.bt_trades_open_pp[pair]): - # 1. Manage currently open orders of active trades - if self.manage_open_orders(t, current_time, row): - # Close trade - open_trade_count_start -= 1 - LocalTrade.remove_bt_trade(t) - self.wallets.update() - - # 2. Process entries. - # without positionstacking, we can only have one open trade per pair. - # max_open_trades must be respected - # don't open on the last row - trade_dir = self.check_for_trade_entry(row) - if ( - (position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0) - and self.trade_slot_available(max_open_trades, open_trade_count_start) - and current_time != end_date - and trade_dir is not None - and not PairLocks.is_pair_locked(pair, row[DATE_IDX], trade_dir) - ): - trade = self._enter_trade(pair, row, trade_dir) - if trade: - # TODO: hacky workaround to avoid opening > max_open_trades - # This emulates previous behavior - not sure if this is correct - # Prevents entering if the trade-slot was freed in this candle - open_trade_count_start += 1 - # logger.debug(f"{pair} - Emulate creation of new trade: {trade}.") - LocalTrade.add_bt_trade(trade) - self.wallets.update() - - for trade in list(LocalTrade.bt_trades_open_pp[pair]): - # 3. Process entry orders. - order = trade.select_order(trade.entry_side, is_open=True) - if order and self._get_order_filled(order.price, row): - order.close_bt_order(current_time, trade) - trade.open_order_id = None - self.wallets.update() - - # 4. Create exit orders (if any) - if not trade.open_order_id: - self._get_exit_trade_entry(trade, row) # Place exit order if necessary - - # 5. Process exit orders. - order = trade.select_order(trade.exit_side, is_open=True) - if order and self._get_order_filled(order.price, row): - order.close_bt_order(current_time, trade) - trade.open_order_id = None - sub_trade = order.safe_amount_after_fee != trade.amount - if sub_trade: - order.close_bt_order(current_time, trade) - trade.recalc_trade_from_orders() - else: - trade.close_date = current_time - trade.close(order.price, show_msg=False) - - # logger.debug(f"{pair} - Backtesting exit {trade}") - LocalTrade.close_bt_trade(trade) - self.wallets.update() - self.run_protections( - enable_protections, pair, current_time, trade.trade_direction) + open_trade_count_start = self.backtest_loop( + row, pair, current_time, end_date, max_open_trades, + position_stacking, enable_protections, open_trade_count_start) # Move time one configured time_interval ahead. self.progress.increment() From 6252ae466eb0940ba0346f74aa250751df4f5e1a Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 16 Oct 2022 17:14:23 +0200 Subject: [PATCH 193/258] Convert position_stacking to attribute of backtest --- freqtrade/optimize/backtesting.py | 15 +++++++-------- freqtrade/optimize/hyperopt.py | 2 -- tests/optimize/test_backtesting.py | 10 ---------- .../optimize/test_backtesting_adjust_position.py | 1 - tests/optimize/test_hyperopt.py | 8 ++++---- 5 files changed, 11 insertions(+), 25 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 89b652e33..9ed8b5600 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -151,6 +151,7 @@ class Backtesting: self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT) # strategies which define "can_short=True" will fail to load in Spot mode. self._can_short = self.trading_mode != TradingMode.SPOT + self._position_stacking: bool = self.config.get('position_stacking', False) self.init_backtest() @@ -1069,12 +1070,12 @@ class Backtesting: def backtest_loop( self, row: Tuple, pair: str, current_time: datetime, end_date: datetime, - max_open_trades: int, position_stacking: bool, enable_protections: bool, + max_open_trades: int, enable_protections: bool, open_trade_count_start: int) -> int: """ NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized. - Backtesting processing for one candle. + Backtesting processing for one candle/pair. """ for t in list(LocalTrade.bt_trades_open_pp[pair]): # 1. Manage currently open orders of active trades @@ -1090,7 +1091,7 @@ class Backtesting: # don't open on the last row trade_dir = self.check_for_trade_entry(row) if ( - (position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0) + (self._position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0) and self.trade_slot_available(max_open_trades, open_trade_count_start) and current_time != end_date and trade_dir is not None @@ -1137,9 +1138,9 @@ class Backtesting: self.run_protections(enable_protections, pair, current_time, trade.trade_direction) return open_trade_count_start - def backtest(self, processed: Dict, # noqa: max-complexity: 13 + def backtest(self, processed: Dict, start_date: datetime, end_date: datetime, - max_open_trades: int = 0, position_stacking: bool = False, + max_open_trades: int = 0, enable_protections: bool = False) -> Dict[str, Any]: """ Implement backtesting functionality @@ -1153,7 +1154,6 @@ class Backtesting: :param start_date: backtesting timerange start datetime :param end_date: backtesting timerange end datetime :param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited - :param position_stacking: do we allow position stacking? :param enable_protections: Should protections be enabled? :return: DataFrame with trades (results of backtesting) """ @@ -1187,7 +1187,7 @@ class Backtesting: open_trade_count_start = self.backtest_loop( row, pair, current_time, end_date, max_open_trades, - position_stacking, enable_protections, open_trade_count_start) + enable_protections, open_trade_count_start) # Move time one configured time_interval ahead. self.progress.increment() @@ -1249,7 +1249,6 @@ class Backtesting: start_date=min_date, end_date=max_date, max_open_trades=max_open_trades, - position_stacking=self.config.get('position_stacking', False), enable_protections=self.config.get('enable_protections', False), ) backtest_end_time = datetime.now(timezone.utc) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index d93bbbfc1..a25fb3b8f 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -122,7 +122,6 @@ class Hyperopt: else: logger.debug('Ignoring max_open_trades (--disable-max-market-positions was used) ...') self.max_open_trades = 0 - self.position_stacking = self.config.get('position_stacking', False) if HyperoptTools.has_space(self.config, 'sell'): # Make sure use_exit_signal is enabled @@ -339,7 +338,6 @@ class Hyperopt: start_date=self.min_date, end_date=self.max_date, max_open_trades=self.max_open_trades, - position_stacking=self.position_stacking, enable_protections=self.config.get('enable_protections', False), ) backtest_end_time = datetime.now(timezone.utc) diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index fa59762db..6bec3b5d2 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -97,7 +97,6 @@ def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'): 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 10, - 'position_stacking': False, } @@ -735,7 +734,6 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: start_date=min_date, end_date=max_date, max_open_trades=10, - position_stacking=False, ) results = result['results'] assert not results.empty @@ -822,7 +820,6 @@ def test_backtest_timedout_entry_orders(default_conf, fee, mocker, testdatadir) start_date=min_date, end_date=max_date, max_open_trades=1, - position_stacking=False, ) assert result['timedout_entry_orders'] == 10 @@ -848,7 +845,6 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None start_date=min_date, end_date=max_date, max_open_trades=1, - position_stacking=False, ) assert not results['results'].empty assert len(results['results']) == 1 @@ -880,7 +876,6 @@ def test_backtest_trim_no_data_left(default_conf, fee, mocker, testdatadir) -> N start_date=min_date, end_date=max_date, max_open_trades=10, - position_stacking=False, ) @@ -935,7 +930,6 @@ def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadi start_date=min_date, end_date=max_date, max_open_trades=10, - position_stacking=False, ) assert count == 5 @@ -979,7 +973,6 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad start_date=min_date, end_date=max_date, max_open_trades=1, - position_stacking=False, enable_protections=default_conf.get('enable_protections', False), ) assert len(results['results']) == numres @@ -1023,7 +1016,6 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir, start_date=min_date, end_date=max_date, max_open_trades=1, - position_stacking=False, enable_protections=default_conf.get('enable_protections', False), ) assert len(results['results']) == expected @@ -1136,7 +1128,6 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 3, - 'position_stacking': False, } results = backtesting.backtest(**backtest_conf) @@ -1159,7 +1150,6 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 1, - 'position_stacking': False, } results = backtesting.backtest(**backtest_conf) assert len(evaluate_result_multi(results['results'], '5m', 1)) == 0 diff --git a/tests/optimize/test_backtesting_adjust_position.py b/tests/optimize/test_backtesting_adjust_position.py index 99c160a40..135ec6b15 100644 --- a/tests/optimize/test_backtesting_adjust_position.py +++ b/tests/optimize/test_backtesting_adjust_position.py @@ -42,7 +42,6 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> start_date=min_date, end_date=max_date, max_open_trades=10, - position_stacking=False, ) results = result['results'] assert not results.empty diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index c52bc9799..5bce9f419 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -336,7 +336,7 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: assert hasattr(hyperopt.backtesting.strategy, "advise_entry") assert hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] - assert hasattr(hyperopt, "position_stacking") + assert hasattr(hyperopt.backtesting, "_position_stacking") def test_hyperopt_format_results(hyperopt): @@ -704,7 +704,7 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non assert hasattr(hyperopt.backtesting.strategy, "advise_entry") assert hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] - assert hasattr(hyperopt, "position_stacking") + assert hasattr(hyperopt.backtesting, "_position_stacking") def test_simplified_interface_all_failed(mocker, hyperopt_conf, caplog) -> None: @@ -778,7 +778,7 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: assert hasattr(hyperopt.backtesting.strategy, "advise_entry") assert hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] - assert hasattr(hyperopt, "position_stacking") + assert hasattr(hyperopt.backtesting, "_position_stacking") def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None: @@ -821,7 +821,7 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None: assert hasattr(hyperopt.backtesting.strategy, "advise_entry") assert hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] - assert hasattr(hyperopt, "position_stacking") + assert hasattr(hyperopt.backtesting, "_position_stacking") @pytest.mark.parametrize("space", [ From 6cb14148aab461a8ca6cf24af3a11227c16b5114 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 16 Oct 2022 10:36:58 +0200 Subject: [PATCH 194/258] Fix random test failure due to catboost bug https://github.com/catboost/catboost/issues/2195 --- freqtrade/freqai/prediction_models/CatboostClassifier.py | 4 +++- freqtrade/freqai/prediction_models/CatboostRegressor.py | 4 +++- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py index 063c76d1b..ca1d8ece0 100644 --- a/freqtrade/freqai/prediction_models/CatboostClassifier.py +++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py @@ -1,4 +1,5 @@ import logging +import sys from pathlib import Path from typing import Any, Dict @@ -48,6 +49,7 @@ class CatboostClassifier(BaseClassifierModel): init_model = self.get_init_model(dk.pair) - cbr.fit(X=train_data, eval_set=test_data, init_model=init_model) + cbr.fit(X=train_data, eval_set=test_data, init_model=init_model, + log_cout=sys.stdout, log_cerr=sys.stderr) return cbr diff --git a/freqtrade/freqai/prediction_models/CatboostRegressor.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py index 2978f6679..4b17a703b 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressor.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py @@ -1,4 +1,5 @@ import logging +import sys from pathlib import Path from typing import Any, Dict @@ -47,6 +48,7 @@ class CatboostRegressor(BaseRegressionModel): **self.model_training_parameters, ) - model.fit(X=train_data, eval_set=test_data, init_model=init_model) + model.fit(X=train_data, eval_set=test_data, init_model=init_model, + log_cout=sys.stdout, log_cerr=sys.stderr) return model From abe4d32eadc28fddfdc091fe3ad1691ac672581f Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 07:19:24 +0200 Subject: [PATCH 195/258] Update wording in get_analyzed_dataframe docs --- docs/strategy-customization.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index b97bd6d23..e886491b5 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -670,13 +670,13 @@ It can also be used in specific callbacks to get the signal that caused the acti ``` python # fetch current dataframe -if self.dp.runmode.value in ('live', 'dry_run'): - dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'], - timeframe=self.timeframe) +dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'], + timeframe=self.timeframe) ``` !!! Note "No data available" Returns an empty dataframe if the requested pair was not cached. + You can check for this with `if dataframe.empty:` and handle this case accordingly. This should not happen when using whitelisted pairs. ### *orderbook(pair, maximum)* From 943f5f21ff60ce9eec3082c9c379a82a1d56f660 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 07:23:44 +0200 Subject: [PATCH 196/258] Improve get_pair_dataframe doc wording --- docs/strategy-customization.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index e886491b5..f036182e3 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -655,13 +655,13 @@ This is where calling `self.dp.current_whitelist()` comes in handy. # fetch live / historical candle (OHLCV) data for the first informative pair inf_pair, inf_timeframe = self.informative_pairs()[0] informative = self.dp.get_pair_dataframe(pair=inf_pair, - timeframe=inf_timeframe) + timeframe=inf_timeframe) ``` !!! Warning "Warning about backtesting" - Be careful when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()` - for the backtesting runmode) provides the full time-range in one go, - so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode. + In backtesting, `dp.get_pair_dataframe()` behavior differs depending on where it's called. + Within `populate_*()` methods, `dp.get_pair_dataframe()` returns the full timerange. Please make sure to not "look into the future" to avoid surprises when running in dry/live mode. + Within [callbacks](strategy-callbacks.md), you'll get the full timerange up to the current (simulated) candle. ### *get_analyzed_dataframe(pair, timeframe)* From caf907e202d26d70d1c33f5129e54c9807a95220 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 08:03:52 +0200 Subject: [PATCH 197/258] Update date-util precommit types --- .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 7abe5659a..92d9dc450 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -17,7 +17,7 @@ repos: - types-filelock==3.2.7 - types-requests==2.28.11.2 - types-tabulate==0.9.0.0 - - types-python-dateutil==2.8.19 + - types-python-dateutil==2.8.19.1 # stages: [push] - repo: https://github.com/pycqa/isort From c2914feb123dd71fb15154bc8ffa96c6a562e6cb Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 09:54:58 +0000 Subject: [PATCH 198/258] Don't fail contract size repopulation if pair is no longer available --- freqtrade/exchange/exchange.py | 6 ++++-- tests/exchange/test_exchange.py | 5 +++-- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 53a3960b1..2054d44e9 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -412,9 +412,11 @@ class Exchange: def get_contract_size(self, pair: str) -> float: if self.trading_mode == TradingMode.FUTURES: - market = self.markets[pair] + market = self.markets.get(pair, {}) contract_size: float = 1.0 - if market['contractSize'] is not None: + if not market: + return None + if market.get('contractSize') is not None: # ccxt has contractSize in markets as string contract_size = float(market['contractSize']) return contract_size diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 07aad80ff..a48cb05e0 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -4341,9 +4341,10 @@ def test__fetch_and_calculate_funding_fees_datetime_called( ('XLTCUSDT', 1, 'spot'), ('LTC/USD', 1, 'futures'), ('XLTCUSDT', 0.01, 'futures'), - ('ETH/USDT:USDT', 10, 'futures') + ('ETH/USDT:USDT', 10, 'futures'), + ('TORN/USDT:USDT', None, 'futures'), # Don't fail for unavailable pairs. ]) -def est__get_contract_size(mocker, default_conf, pair, expected_size, trading_mode): +def test__get_contract_size(mocker, default_conf, pair, expected_size, trading_mode): api_mock = MagicMock() default_conf['trading_mode'] = trading_mode default_conf['margin_mode'] = 'isolated' From c8e103e4a45bf41a8e5e349cd8c628d04d7dc088 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 10:02:55 +0000 Subject: [PATCH 199/258] Adjust typehints to match return value --- 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 2054d44e9..afd154dcd 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -410,7 +410,7 @@ class Exchange: else: return DataFrame() - def get_contract_size(self, pair: str) -> float: + def get_contract_size(self, pair: str) -> Optional[float]: if self.trading_mode == TradingMode.FUTURES: market = self.markets.get(pair, {}) contract_size: float = 1.0 From b166c04cba694125506fb4544494aa70bc74d8e2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 19:29:30 +0200 Subject: [PATCH 200/258] Bring back asyncio.sleep to avoid overwelming the a consumer queue --- freqtrade/rpc/api_server/webserver.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index c6639f1a6..4a09fd78e 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -198,6 +198,10 @@ class ApiServer(RPCHandler): logger.debug(f"Found message of type: {message.get('type')}") # Broadcast it await self._ws_channel_manager.broadcast(message) + # Limit messages per sec. + # Could cause problems with queue size if too low, and + # problems with network traffik if too high. + await asyncio.sleep(0.001) except asyncio.CancelledError: pass From 441032be25dcabff2fc1bc8d0b7e7f855f7a0da8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 19:48:27 +0200 Subject: [PATCH 201/258] Fix sys.stdout bug for CatboostRegressorMultiTarget --- .../prediction_models/CatboostRegressorMultiTarget.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py index de7a73e3a..976d0b29b 100644 --- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py +++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py @@ -1,4 +1,5 @@ import logging +import sys from pathlib import Path from typing import Any, Dict @@ -58,8 +59,10 @@ class CatboostRegressorMultiTarget(BaseRegressionModel): fit_params = [] for i in range(len(eval_sets)): - fit_params.append( - {'eval_set': eval_sets[i], 'init_model': init_models[i]}) + fit_params.append({ + 'eval_set': eval_sets[i], 'init_model': init_models[i], + 'log_cout': sys.stdout, 'log_cerr': sys.stderr, + }) model = FreqaiMultiOutputRegressor(estimator=cbr) thread_training = self.freqai_info.get('multitarget_parallel_training', False) From c7fff1213c46594694350f5a1d61401579b73763 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 17 Oct 2022 20:43:32 +0200 Subject: [PATCH 202/258] Rate-limit EMC startup to avoid overwelming the queue --- freqtrade/rpc/api_server/api_ws.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py index 46909955d..2f490b8a8 100644 --- a/freqtrade/rpc/api_server/api_ws.py +++ b/freqtrade/rpc/api_server/api_ws.py @@ -1,3 +1,4 @@ +import asyncio import logging from typing import Any, Dict @@ -89,6 +90,8 @@ async def _process_consumer_request( for _, message in analyzed_df.items(): response = WSAnalyzedDFMessage(data=message) await channel.send(response.dict(exclude_none=True)) + # Throttle the messages to 50/s + await asyncio.sleep(0.02) @router.websocket("/message/ws") From c3d4fb9f1b2ee6bcd404a53dcea4c5d53542b4a7 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 18 Oct 2022 06:39:55 +0200 Subject: [PATCH 203/258] Simplify backtest calling interface --- freqtrade/optimize/backtesting.py | 21 ++++++++------------- freqtrade/optimize/hyperopt.py | 2 +- freqtrade/rpc/api_server/api_backtest.py | 1 + tests/optimize/test_backtesting.py | 2 -- 4 files changed, 10 insertions(+), 16 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 9ed8b5600..4d98f1f5a 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -152,6 +152,7 @@ class Backtesting: # strategies which define "can_short=True" will fail to load in Spot mode. self._can_short = self.trading_mode != TradingMode.SPOT self._position_stacking: bool = self.config.get('position_stacking', False) + self.enable_protections: bool = self.config.get('enable_protections', False) self.init_backtest() @@ -960,9 +961,8 @@ class Backtesting: return 'short' return None - def run_protections( - self, enable_protections, pair: str, current_time: datetime, side: LongShort): - if enable_protections: + def run_protections(self, pair: str, current_time: datetime, side: LongShort): + if self.enable_protections: self.protections.stop_per_pair(pair, current_time, side) self.protections.global_stop(current_time, side) @@ -1070,8 +1070,7 @@ class Backtesting: def backtest_loop( self, row: Tuple, pair: str, current_time: datetime, end_date: datetime, - max_open_trades: int, enable_protections: bool, - open_trade_count_start: int) -> int: + max_open_trades: int, open_trade_count_start: int) -> int: """ NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized. @@ -1135,13 +1134,12 @@ class Backtesting: # logger.debug(f"{pair} - Backtesting exit {trade}") LocalTrade.close_bt_trade(trade) self.wallets.update() - self.run_protections(enable_protections, pair, current_time, trade.trade_direction) + self.run_protections(pair, current_time, trade.trade_direction) return open_trade_count_start def backtest(self, processed: Dict, start_date: datetime, end_date: datetime, - max_open_trades: int = 0, - enable_protections: bool = False) -> Dict[str, Any]: + max_open_trades: int = 0) -> Dict[str, Any]: """ Implement backtesting functionality @@ -1154,10 +1152,9 @@ class Backtesting: :param start_date: backtesting timerange start datetime :param end_date: backtesting timerange end datetime :param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited - :param enable_protections: Should protections be enabled? :return: DataFrame with trades (results of backtesting) """ - self.prepare_backtest(enable_protections) + self.prepare_backtest(self.enable_protections) # Ensure wallets are uptodate (important for --strategy-list) self.wallets.update() # Use dict of lists with data for performance @@ -1186,8 +1183,7 @@ class Backtesting: self.dataprovider._set_dataframe_max_index(row_index) open_trade_count_start = self.backtest_loop( - row, pair, current_time, end_date, max_open_trades, - enable_protections, open_trade_count_start) + row, pair, current_time, end_date, max_open_trades, open_trade_count_start) # Move time one configured time_interval ahead. self.progress.increment() @@ -1249,7 +1245,6 @@ class Backtesting: start_date=min_date, end_date=max_date, max_open_trades=max_open_trades, - enable_protections=self.config.get('enable_protections', False), ) backtest_end_time = datetime.now(timezone.utc) results.update({ diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index a25fb3b8f..b459d59f2 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -257,6 +257,7 @@ class Hyperopt: logger.debug("Hyperopt has 'protection' space") # Enable Protections if protection space is selected. self.config['enable_protections'] = True + self.backtesting.enable_protections = True self.protection_space = self.custom_hyperopt.protection_space() if HyperoptTools.has_space(self.config, 'buy'): @@ -338,7 +339,6 @@ class Hyperopt: start_date=self.min_date, end_date=self.max_date, max_open_trades=self.max_open_trades, - enable_protections=self.config.get('enable_protections', False), ) backtest_end_time = datetime.now(timezone.utc) bt_results.update({ diff --git a/freqtrade/rpc/api_server/api_backtest.py b/freqtrade/rpc/api_server/api_backtest.py index c21828fd4..b17636a7d 100644 --- a/freqtrade/rpc/api_server/api_backtest.py +++ b/freqtrade/rpc/api_server/api_backtest.py @@ -89,6 +89,7 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac lastconfig['enable_protections'] = btconfig.get('enable_protections') lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet') + ApiServer._bt.enable_protections = btconfig.get('enable_protections', False) ApiServer._bt.strategylist = [strat] ApiServer._bt.results = {} ApiServer._bt.load_prior_backtest() diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index 6bec3b5d2..290e08455 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -973,7 +973,6 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad start_date=min_date, end_date=max_date, max_open_trades=1, - enable_protections=default_conf.get('enable_protections', False), ) assert len(results['results']) == numres @@ -1016,7 +1015,6 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir, start_date=min_date, end_date=max_date, max_open_trades=1, - enable_protections=default_conf.get('enable_protections', False), ) assert len(results['results']) == expected From 033c5bd441b941a9b7de45b236f0fe66568f18ba Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Tue, 18 Oct 2022 12:55:47 +0200 Subject: [PATCH 204/258] Make check constant pred labels agnostic --- freqtrade/freqai/data_kitchen.py | 37 +++++++++++++++----------------- 1 file changed, 17 insertions(+), 20 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 7f3e7cb01..edf6b366d 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -71,6 +71,7 @@ class FreqaiDataKitchen: self.data_path = Path() self.label_list: List = [] self.training_features_list: List = [] + self.constant_features_list: List = [] self.model_filename: str = "" self.backtesting_results_path = Path() self.backtest_predictions_folder: str = "backtesting_predictions" @@ -206,15 +207,14 @@ class FreqaiDataKitchen: drop_index = pd.isnull(filtered_df).any(axis=1) # get the rows that have NaNs, drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement. - ft_params = self.freqai_config["feature_parameters"] if (training_filter): - if not ft_params.get( - "principal_component_analysis", False - ): - 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.") + 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)) + self.constant_features_list = const_cols + logger.warning(f"Removed features {const_cols} with constant values.") + else: + self.constant_features_list = [] # 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 @@ -245,9 +245,7 @@ class FreqaiDataKitchen: self.data["filter_drop_index_training"] = drop_index else: - if not ft_params.get( - "principal_component_analysis", False - ): + if len(self.constant_features_list): filtered_df = self.check_pred_labels(filtered_df) # 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 @@ -474,15 +472,14 @@ class FreqaiDataKitchen: :params: :df_predictions: incoming predictions """ - train_labels = self.data_dictionary["train_features"].columns - pred_labels = df_predictions.columns - num_diffs = len(pred_labels.difference(train_labels)) - if num_diffs != 0: - df_predictions = df_predictions[train_labels] - logger.warning( - f"Removed {num_diffs} features from prediction features, " - f"these were likely considered constant values during most recent training." - ) + constant_labels = self.constant_features_list + df_predictions = df_predictions.filter( + df_predictions.columns.difference(constant_labels) + ) + logger.warning( + f"Removed {len(constant_labels)} features from prediction features, " + f"these were considered constant values during most recent training." + ) return df_predictions From 6e95b6667d69a861d631de20781829abb8987531 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 19 Oct 2022 11:57:05 +0200 Subject: [PATCH 205/258] Modify test ensuring we always have a 0 index --- tests/exchange/test_exchange.py | 18 ++++++++++++++---- 1 file changed, 14 insertions(+), 4 deletions(-) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index a48cb05e0..25ba294a3 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -2196,6 +2196,9 @@ def test_refresh_latest_ohlcv_cache(mocker, default_conf, candle_type, time_mach time_machine.move_to(start + timedelta(hours=99, minutes=30)) exchange = get_patched_exchange(mocker, default_conf) + mocker.patch("freqtrade.exchange.Exchange.ohlcv_candle_limit", return_value=100) + assert exchange._startup_candle_count == 0 + exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv) pair1 = ('IOTA/ETH', '1h', candle_type) pair2 = ('XRP/ETH', '1h', candle_type) @@ -2236,30 +2239,36 @@ def test_refresh_latest_ohlcv_cache(mocker, default_conf, candle_type, time_mach assert len(res) == 2 assert len(res[pair1]) == 99 assert len(res[pair2]) == 99 + assert res[pair2].at[0, 'open'] assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 refresh_pior = exchange._pairs_last_refresh_time[pair1] - # New candle on exchange - only return 50 candles (but one candle further) - new_startdate = (start + timedelta(hours=51)).strftime('%Y-%m-%d %H:%M') - ohlcv = generate_test_data_raw('1h', 50, new_startdate) + # New candle on exchange - return 100 candles - but skip one candle so we actually get 2 candles + # in one go + new_startdate = (start + timedelta(hours=2)).strftime('%Y-%m-%d %H:%M') + # mocker.patch("freqtrade.exchange.Exchange.ohlcv_candle_limit", return_value=100) + ohlcv = generate_test_data_raw('1h', 100, new_startdate) exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv) res = exchange.refresh_latest_ohlcv(pairs) assert exchange._api_async.fetch_ohlcv.call_count == 2 assert len(res) == 2 assert len(res[pair1]) == 100 assert len(res[pair2]) == 100 + # Verify index starts at 0 + assert res[pair2].at[0, 'open'] assert refresh_pior != exchange._pairs_last_refresh_time[pair1] assert exchange._pairs_last_refresh_time[pair1] == ohlcv[-1][0] // 1000 assert exchange._pairs_last_refresh_time[pair2] == ohlcv[-1][0] // 1000 exchange._api_async.fetch_ohlcv.reset_mock() - # Retry same call - no action. + # Retry same call - from cache res = exchange.refresh_latest_ohlcv(pairs) assert exchange._api_async.fetch_ohlcv.call_count == 0 assert len(res) == 2 assert len(res[pair1]) == 100 assert len(res[pair2]) == 100 + assert res[pair2].at[0, 'open'] # Move to distant future (so a 1 call would cause a hole in the data) time_machine.move_to(start + timedelta(hours=2000)) @@ -2272,6 +2281,7 @@ def test_refresh_latest_ohlcv_cache(mocker, default_conf, candle_type, time_mach # Cache eviction - new data. assert len(res[pair1]) == 99 assert len(res[pair2]) == 99 + assert res[pair2].at[0, 'open'] @pytest.mark.asyncio From 7192ed7be61376be3d7d70ae296e26dee3b7c243 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 19 Oct 2022 11:57:18 +0200 Subject: [PATCH 206/258] Fix bug with dataframe not being 0 indexed --- freqtrade/exchange/exchange.py | 1 + 1 file changed, 1 insertion(+) diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index afd154dcd..313d89e09 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -1936,6 +1936,7 @@ class Exchange: candle_limit = self.ohlcv_candle_limit(timeframe, self._config['candle_type_def']) # Age out old candles ohlcv_df = ohlcv_df.tail(candle_limit + self._startup_candle_count) + ohlcv_df = ohlcv_df.reset_index(drop=True) self._klines[(pair, timeframe, c_type)] = ohlcv_df else: self._klines[(pair, timeframe, c_type)] = ohlcv_df From 295ba21389565948268756829949cc7657098afd Mon Sep 17 00:00:00 2001 From: Mark Regan Date: Thu, 20 Oct 2022 12:05:37 +0100 Subject: [PATCH 207/258] Make extra_returns_per_train values available during backtest --- freqtrade/freqai/data_kitchen.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index 52261d341..38fe670ec 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -957,6 +957,9 @@ class FreqaiDataKitchen: append_df[f"{label}_mean"] = self.data["labels_mean"][label] append_df[f"{label}_std"] = self.data["labels_std"][label] + for extra_col in self.data["extra_returns_per_train"]: + append_df[f"{extra_col}"] = self.data["extra_returns_per_train"][extra_col] + append_df["do_predict"] = do_predict if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0: append_df["DI_values"] = self.DI_values From 073ce1659eff7923bd5468702daecc553b044d6e Mon Sep 17 00:00:00 2001 From: Mark Regan Date: Thu, 20 Oct 2022 14:26:10 +0100 Subject: [PATCH 208/258] remove un-used f-string --- 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 38fe670ec..39310a15e 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -958,7 +958,7 @@ class FreqaiDataKitchen: append_df[f"{label}_std"] = self.data["labels_std"][label] for extra_col in self.data["extra_returns_per_train"]: - append_df[f"{extra_col}"] = self.data["extra_returns_per_train"][extra_col] + append_df["{extra_col}"] = self.data["extra_returns_per_train"][extra_col] append_df["do_predict"] = do_predict if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0: From 589944055e886db9f5adc45c0eed020909c51f17 Mon Sep 17 00:00:00 2001 From: Wagner Costa Santos Date: Thu, 20 Oct 2022 12:15:41 -0300 Subject: [PATCH 209/258] fix typos - live predictions candles --- docs/freqai-configuration.md | 4 ++-- freqtrade/freqai/base_models/BaseClassifierModel.py | 2 +- freqtrade/freqai/base_models/BaseRegressionModel.py | 2 +- freqtrade/freqai/base_models/BaseTensorFlowModel.py | 2 +- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md index d162fe373..59d72e337 100644 --- a/docs/freqai-configuration.md +++ b/docs/freqai-configuration.md @@ -192,11 +192,11 @@ dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std dataframe["sell_roi"] = dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * 1.25 ``` -To consider the population of *historical predictions* for creating the dynamic target instead of information from the training as discussed above, you would set `fit_live_prediction_candles` in the config to the number of historical prediction candles you wish to use to generate target statistics. +To consider the population of *historical predictions* for creating the dynamic target instead of information from the training as discussed above, you would set `fit_live_predictions_candles` in the config to the number of historical prediction candles you wish to use to generate target statistics. ```json "freqai": { - "fit_live_prediction_candles": 300, + "fit_live_predictions_candles": 300, } ``` diff --git a/freqtrade/freqai/base_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py index 691c27e23..17bffa85b 100644 --- a/freqtrade/freqai/base_models/BaseClassifierModel.py +++ b/freqtrade/freqai/base_models/BaseClassifierModel.py @@ -51,7 +51,7 @@ class BaseClassifierModel(IFreqaiModel): f"{end_date} --------------------") # split data into train/test data. data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered) - if not self.freqai_info.get("fit_live_predictions", 0) or not self.live: + if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live: dk.fit_labels() # normalize all data based on train_dataset only data_dictionary = dk.normalize_data(data_dictionary) diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py index 79f6f0d3c..766579cb6 100644 --- a/freqtrade/freqai/base_models/BaseRegressionModel.py +++ b/freqtrade/freqai/base_models/BaseRegressionModel.py @@ -50,7 +50,7 @@ class BaseRegressionModel(IFreqaiModel): f"{end_date} --------------------") # split data into train/test data. data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered) - if not self.freqai_info.get("fit_live_predictions", 0) or not self.live: + if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live: dk.fit_labels() # normalize all data based on train_dataset only data_dictionary = dk.normalize_data(data_dictionary) diff --git a/freqtrade/freqai/base_models/BaseTensorFlowModel.py b/freqtrade/freqai/base_models/BaseTensorFlowModel.py index 00f9d6cba..b41ee0175 100644 --- a/freqtrade/freqai/base_models/BaseTensorFlowModel.py +++ b/freqtrade/freqai/base_models/BaseTensorFlowModel.py @@ -47,7 +47,7 @@ class BaseTensorFlowModel(IFreqaiModel): f"{end_date} --------------------") # split data into train/test data. data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered) - if not self.freqai_info.get("fit_live_predictions", 0) or not self.live: + if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live: dk.fit_labels() # normalize all data based on train_dataset only data_dictionary = dk.normalize_data(data_dictionary) From 60cb11a44d30c92b87117e21b12ac73f2cbb349d Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 20 Oct 2022 19:36:28 +0200 Subject: [PATCH 210/258] Add price jump warning --- docs/faq.md | 6 ++++++ freqtrade/data/converter.py | 8 ++++++++ tests/data/test_converter.py | 9 +++++---- 3 files changed, 19 insertions(+), 4 deletions(-) diff --git a/docs/faq.md b/docs/faq.md index a72268ef9..bcceaf898 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -102,6 +102,12 @@ If this happens for all pairs in the pairlist, this might indicate a recent exch Irrespectively of the reason, Freqtrade will fill up these candles with "empty" candles, where open, high, low and close are set to the previous candle close - and volume is empty. In a chart, this will look like a `_` - and is aligned with how exchanges usually represent 0 volume candles. +### I'm getting "Price jump between 2 candles detected" + +This message is a warning that the candles had a price jump of > 30%. +This might be a sign that the pair stopped trading, and some token exchange took place (e.g. COCOS in 2021 - where price jumped from 0.0000154 to 0.01621). +This message is often accompanied by ["Missing data fillup"](#im-getting-missing-data-fillup-messages-in-the-log) - as trading on such pairs is often stopped for some time. + ### I'm getting "Outdated history for pair xxx" in the log The bot is trying to tell you that it got an outdated last candle (not the last complete candle). diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py index 98ed15489..7f7e79445 100644 --- a/freqtrade/data/converter.py +++ b/freqtrade/data/converter.py @@ -119,6 +119,14 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) else: # Don't be verbose if only a small amount is missing logger.debug(message) + candle_price_gap = 0 + if not df.empty and 'close' in df.columns: + returns = df['close'].pct_change().dropna() + if len(returns): + candle_price_gap = max(abs(returns)) + if candle_price_gap > 0.3: + logger.info(f"Price jump in {pair} between two candles of {candle_price_gap:.2%} detected.") + return df diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py index f74383d15..83429bb38 100644 --- a/tests/data/test_converter.py +++ b/tests/data/test_converter.py @@ -80,10 +80,10 @@ def test_ohlcv_fill_up_missing_data2(caplog): ticks = [ [ 1511686200000, # 8:50:00 - 8.794e-05, # open - 8.948e-05, # high - 8.794e-05, # low - 8.88e-05, # close + 8.794e-07, # open + 8.948e-07, # high + 8.794e-07, # low + 8.88e-07, # close 2255, # volume (in quote currency) ], [ @@ -118,6 +118,7 @@ def test_ohlcv_fill_up_missing_data2(caplog): assert len(data) == 3 caplog.set_level(logging.DEBUG) data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC") + assert log_has_re(r"Price jump in .* between two candles .* detected\.", caplog) assert len(data2) == 4 # 3rd candle has been filled row = data2.loc[2, :] From 107845afa8be7f1a7c6927c495c8354fcaacf084 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 20 Oct 2022 19:55:42 +0200 Subject: [PATCH 211/258] Keep version number in docker versioning --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 1e62266a8..9e6670a9a 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -16,6 +16,6 @@ if 'dev' in __version__: from pathlib import Path versionfile = Path('./freqtrade_commit') if versionfile.is_file(): - __version__ = f"docker-{versionfile.read_text()[:8]}" + __version__ = f"docker-{__version__}-{versionfile.read_text()[:8]}" except Exception: pass From f4814a7d590eb0d56fcbae7c9f9b3eba99a71df0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 20 Oct 2022 19:57:56 +0200 Subject: [PATCH 212/258] Improve test resiliance to small roundings --- tests/test_integration.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_integration.py b/tests/test_integration.py index f2504c23a..01a2801ad 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -420,7 +420,7 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, leverage, fee, mocker) assert trade.open_order_id is None # Open rate is not adjusted yet assert trade.open_rate == 1.99 - assert trade.stake_amount == 60 + assert pytest.approx(trade.stake_amount) == 60 assert trade.stop_loss_pct == -0.1 assert pytest.approx(trade.stop_loss) == 1.99 * (1 - 0.1 / leverage) assert pytest.approx(trade.initial_stop_loss) == 1.99 * (1 - 0.1 / leverage) @@ -446,7 +446,7 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, leverage, fee, mocker) assert len(trade.orders) == 4 assert trade.open_order_id is not None assert trade.open_rate == 1.99 - assert trade.stake_amount == 60 + assert pytest.approx(trade.stake_amount) == 60 assert trade.orders[-1].price == 1.95 assert pytest.approx(trade.orders[-1].cost) == 120 * leverage From 0aa840792b56931fd163adea21137120010ade0b Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 20 Oct 2022 20:05:15 +0200 Subject: [PATCH 213/258] Move persistence tests to package --- tests/persistence/__init__.py | 0 tests/{ => persistence}/test_persistence.py | 0 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tests/persistence/__init__.py rename tests/{ => persistence}/test_persistence.py (100%) diff --git a/tests/persistence/__init__.py b/tests/persistence/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/test_persistence.py b/tests/persistence/test_persistence.py similarity index 100% rename from tests/test_persistence.py rename to tests/persistence/test_persistence.py From bd424a877bcc70682e39e04039770e6248ef124d Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 20 Oct 2022 20:33:08 +0200 Subject: [PATCH 214/258] Add Trade from_json method --- freqtrade/persistence/trade_model.py | 84 +++++++++++ tests/persistence/test_persistence.py | 2 +- tests/persistence/test_trade_fromjson.py | 180 +++++++++++++++++++++++ 3 files changed, 265 insertions(+), 1 deletion(-) create mode 100644 tests/persistence/test_trade_fromjson.py diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 73e067480..ec47b670b 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -1520,3 +1520,87 @@ class Trade(_DECL_BASE, LocalTrade): Order.status == 'closed' ).scalar() return trading_volume + + @staticmethod + def from_json(json_str: str) -> 'Trade': + """ + Create a Trade instance from a json string. + + Used for debugging purposes - please keep. + :param json_str: json string to parse + :return: Trade instance + """ + import rapidjson + data = rapidjson.loads(json_str) + trade = Trade( + id=data["trade_id"], + pair=data["pair"], + base_currency=data["base_currency"], + stake_currency=data["quote_currency"], + is_open=data["is_open"], + exchange=data["exchange"], + amount=data["amount"], + amount_requested=data["amount_requested"], + stake_amount=data["stake_amount"], + strategy=data["strategy"], + enter_tag=data["enter_tag"], + timeframe=data["timeframe"], + fee_open=data["fee_open"], + fee_open_cost=data["fee_open_cost"], + fee_open_currency=data["fee_open_currency"], + fee_close=data["fee_close"], + fee_close_cost=data["fee_close_cost"], + fee_close_currency=data["fee_close_currency"], + open_date=datetime.fromtimestamp(data["open_timestamp"] // 1000, tz=timezone.utc), + open_rate=data["open_rate"], + open_rate_requested=data["open_rate_requested"], + open_trade_value=data["open_trade_value"], + close_date=(datetime.fromtimestamp(data["close_timestamp"] // 1000, tz=timezone.utc) + if data["close_timestamp"] else None), + realized_profit=data["realized_profit"], + close_rate=data["close_rate"], + close_rate_requested=data["close_rate_requested"], + close_profit=data["close_profit"], + close_profit_abs=data["close_profit_abs"], + exit_reason=data["exit_reason"], + exit_order_status=data["exit_order_status"], + stop_loss=data["stop_loss_abs"], + stop_loss_pct=data["stop_loss_ratio"], + stoploss_order_id=data["stoploss_order_id"], + stoploss_last_update=(datetime.fromtimestamp(data["stoploss_last_update"] // 1000, + tz=timezone.utc) if data["stoploss_last_update"] else None), + initial_stop_loss=data["initial_stop_loss_abs"], + initial_stop_loss_pct=data["initial_stop_loss_ratio"], + min_rate=data["min_rate"], + max_rate=data["max_rate"], + leverage=data["leverage"], + interest_rate=data["interest_rate"], + liquidation_price=data["liquidation_price"], + is_short=data["is_short"], + trading_mode=data["trading_mode"], + funding_fees=data["funding_fees"], + open_order_id=data["open_order_id"], + ) + for order in data["orders"]: + + order_obj = Order( + amount=order["amount"], + ft_order_side=order["ft_order_side"], + ft_pair=order["pair"], + ft_is_open=order["is_open"], + order_id=order["order_id"], + status=order["status"], + average=order["average"], + cost=order["cost"], + filled=order["filled"], + order_date=order["order_date"], + order_filled_date=(datetime.fromtimestamp( + order["order_filled_timestamp"] // 1000, tz=timezone.utc) + if order["order_filled_timestamp"] else None), + order_type=order["order_type"], + price=order["price"], + remaining=order["remaining"], + ) + trade.orders.append(order_obj) + + return trade diff --git a/tests/persistence/test_persistence.py b/tests/persistence/test_persistence.py index ae2672830..3323dd7c6 100644 --- a/tests/persistence/test_persistence.py +++ b/tests/persistence/test_persistence.py @@ -2404,7 +2404,7 @@ def test_Trade_object_idem(): 'get_enter_tag_performance', 'get_mix_tag_performance', 'get_trading_volume', - + 'from_json', ) EXCLUDES2 = ('trades', 'trades_open', 'bt_trades_open_pp', 'bt_open_open_trade_count', 'total_profit') diff --git a/tests/persistence/test_trade_fromjson.py b/tests/persistence/test_trade_fromjson.py new file mode 100644 index 000000000..f097d5e56 --- /dev/null +++ b/tests/persistence/test_trade_fromjson.py @@ -0,0 +1,180 @@ +from datetime import datetime, timezone + +from freqtrade.persistence.trade_model import Trade + + +def test_trade_fromjson(): + """Test the Trade.from_json() method.""" + trade_string = """{ + "trade_id": 25, + "pair": "ETH/USDT", + "base_currency": "ETH", + "quote_currency": "USDT", + "is_open": false, + "exchange": "binance", + "amount": 407.0, + "amount_requested": 102.92547026, + "stake_amount": 102.7494348, + "strategy": "SampleStrategy55", + "buy_tag": "Strategy2", + "enter_tag": "Strategy2", + "timeframe": 5, + "fee_open": 0.001, + "fee_open_cost": 0.1027494, + "fee_open_currency": "ETH", + "fee_close": 0.001, + "fee_close_cost": 0.1054944, + "fee_close_currency": "USDT", + "open_date": "2022-10-18 09:12:42", + "open_timestamp": 1666084362912, + "open_rate": 0.2518998249562391, + "open_rate_requested": 0.2516, + "open_trade_value": 102.62575199, + "close_date": "2022-10-18 09:45:22", + "close_timestamp": 1666086322208, + "realized_profit": 2.76315361, + "close_rate": 0.2592, + "close_rate_requested": 0.2592, + "close_profit": 0.026865, + "close_profit_pct": 2.69, + "close_profit_abs": 2.76315361, + "trade_duration_s": 1959, + "trade_duration": 32, + "profit_ratio": 0.02686, + "profit_pct": 2.69, + "profit_abs": 2.76315361, + "sell_reason": "no longer good", + "exit_reason": "no longer good", + "exit_order_status": "closed", + "stop_loss_abs": 0.1981, + "stop_loss_ratio": -0.216, + "stop_loss_pct": -21.6, + "stoploss_order_id": null, + "stoploss_last_update": null, + "stoploss_last_update_timestamp": null, + "initial_stop_loss_abs": 0.1981, + "initial_stop_loss_ratio": -0.216, + "initial_stop_loss_pct": -21.6, + "min_rate": 0.2495, + "max_rate": 0.2592, + "leverage": 1.0, + "interest_rate": 0.0, + "liquidation_price": null, + "is_short": false, + "trading_mode": "spot", + "funding_fees": 0.0, + "open_order_id": null, + "orders": [ + { + "amount": 102.0, + "safe_price": 0.2526, + "ft_order_side": "buy", + "order_filled_timestamp": 1666084370887, + "ft_is_entry": true, + "pair": "ETH/USDT", + "order_id": "78404228", + "status": "closed", + "average": 0.2526, + "cost": 25.7652, + "filled": 102.0, + "is_open": false, + "order_date": "2022-10-18 09:12:42", + "order_timestamp": 1666084362684, + "order_filled_date": "2022-10-18 09:12:50", + "order_type": "limit", + "price": 0.2526, + "remaining": 0.0 + }, + { + "amount": 102.0, + "safe_price": 0.2517, + "ft_order_side": "buy", + "order_filled_timestamp": 1666084379056, + "ft_is_entry": true, + "pair": "ETH/USDT", + "order_id": "78405139", + "status": "closed", + "average": 0.2517, + "cost": 25.6734, + "filled": 102.0, + "is_open": false, + "order_date": "2022-10-18 09:12:57", + "order_timestamp": 1666084377681, + "order_filled_date": "2022-10-18 09:12:59", + "order_type": "limit", + "price": 0.2517, + "remaining": 0.0 + }, + { + "amount": 102.0, + "safe_price": 0.2517, + "ft_order_side": "buy", + "order_filled_timestamp": 1666084389644, + "ft_is_entry": true, + "pair": "ETH/USDT", + "order_id": "78405265", + "status": "closed", + "average": 0.2517, + "cost": 25.6734, + "filled": 102.0, + "is_open": false, + "order_date": "2022-10-18 09:13:03", + "order_timestamp": 1666084383295, + "order_filled_date": "2022-10-18 09:13:09", + "order_type": "limit", + "price": 0.2517, + "remaining": 0.0 + }, + { + "amount": 102.0, + "safe_price": 0.2516, + "ft_order_side": "buy", + "order_filled_timestamp": 1666084723521, + "ft_is_entry": true, + "pair": "ETH/USDT", + "order_id": "78405395", + "status": "closed", + "average": 0.2516, + "cost": 25.6632, + "filled": 102.0, + "is_open": false, + "order_date": "2022-10-18 09:13:13", + "order_timestamp": 1666084393920, + "order_filled_date": "2022-10-18 09:18:43", + "order_type": "limit", + "price": 0.2516, + "remaining": 0.0 + }, + { + "amount": 407.0, + "safe_price": 0.2592, + "ft_order_side": "sell", + "order_filled_timestamp": 1666086322198, + "ft_is_entry": false, + "pair": "ETH/USDT", + "order_id": "78432649", + "status": "closed", + "average": 0.2592, + "cost": 105.4944, + "filled": 407.0, + "is_open": false, + "order_date": "2022-10-18 09:45:21", + "order_timestamp": 1666086321435, + "order_filled_date": "2022-10-18 09:45:22", + "order_type": "market", + "price": 0.2592, + "remaining": 0.0 + } + ] + }""" + trade = Trade.from_json(trade_string) + + assert trade.id == 25 + assert trade.pair == 'ETH/USDT' + assert trade.open_date == datetime(2022, 10, 18, 9, 12, 42, tzinfo=timezone.utc) + assert isinstance(trade.open_date, datetime) + assert trade.exit_reason == 'no longer good' + + assert len(trade.orders) == 5 + last_o = trade.orders[-1] + assert last_o.order_filled_date == datetime(2022, 10, 18, 9, 45, 22, tzinfo=timezone.utc) From 212b511bbeaa523b110d50ff4d09ee95a1c34e07 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 21 Oct 2022 06:44:25 +0200 Subject: [PATCH 215/258] Remove explicit rateLimit setting for freqAI config --- config_examples/config_freqai.example.json | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json index db8ae7181..5e564a1fc 100644 --- a/config_examples/config_freqai.example.json +++ b/config_examples/config_freqai.example.json @@ -18,13 +18,8 @@ "name": "binance", "key": "", "secret": "", - "ccxt_config": { - "enableRateLimit": true - }, - "ccxt_async_config": { - "enableRateLimit": true, - "rateLimit": 200 - }, + "ccxt_config": {}, + "ccxt_async_config": {}, "pair_whitelist": [ "1INCH/USDT", "ALGO/USDT" From d1591883a688ee49af56490ab39788ab31207575 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 21 Oct 2022 07:01:47 +0200 Subject: [PATCH 216/258] add missing datetime conversion in fromJson --- freqtrade/persistence/trade_model.py | 2 +- tests/persistence/test_trade_fromjson.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index ec47b670b..70c460e89 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -1593,7 +1593,7 @@ class Trade(_DECL_BASE, LocalTrade): average=order["average"], cost=order["cost"], filled=order["filled"], - order_date=order["order_date"], + order_date=datetime.strptime(order["order_date"], DATETIME_PRINT_FORMAT), order_filled_date=(datetime.fromtimestamp( order["order_filled_timestamp"] // 1000, tz=timezone.utc) if order["order_filled_timestamp"] else None), diff --git a/tests/persistence/test_trade_fromjson.py b/tests/persistence/test_trade_fromjson.py index f097d5e56..529008e02 100644 --- a/tests/persistence/test_trade_fromjson.py +++ b/tests/persistence/test_trade_fromjson.py @@ -178,3 +178,4 @@ def test_trade_fromjson(): assert len(trade.orders) == 5 last_o = trade.orders[-1] assert last_o.order_filled_date == datetime(2022, 10, 18, 9, 45, 22, tzinfo=timezone.utc) + assert isinstance(last_o.order_date, datetime) From b715d9c521e21e4cff5267e6e6b74fa808dc6b17 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 21 Oct 2022 16:30:01 +0200 Subject: [PATCH 217/258] Improve fee handling closes #7586 --- freqtrade/freqtradebot.py | 8 +++++--- tests/test_freqtradebot.py | 8 +++++--- 2 files changed, 10 insertions(+), 6 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index cd111679c..ea7c2f1f9 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -1471,12 +1471,13 @@ class FreqtradeBot(LoggingMixin): ) return cancelled - def _safe_exit_amount(self, pair: str, amount: float) -> float: + def _safe_exit_amount(self, trade: Trade, pair: str, amount: float) -> float: """ Get sellable amount. Should be trade.amount - but will fall back to the available amount if necessary. This should cover cases where get_real_amount() was not able to update the amount for whatever reason. + :param trade: Trade we're working with :param pair: Pair we're trying to sell :param amount: amount we expect to be available :return: amount to sell @@ -1495,6 +1496,7 @@ class FreqtradeBot(LoggingMixin): return amount elif wallet_amount > amount * 0.98: logger.info(f"{pair} - Falling back to wallet-amount {wallet_amount} -> {amount}.") + trade.amount = wallet_amount return wallet_amount else: raise DependencyException( @@ -1553,7 +1555,7 @@ class FreqtradeBot(LoggingMixin): # Emergency sells (default to market!) order_type = self.strategy.order_types.get("emergency_exit", "market") - amount = self._safe_exit_amount(trade.pair, sub_trade_amt or trade.amount) + amount = self._safe_exit_amount(trade, trade.pair, sub_trade_amt or trade.amount) time_in_force = self.strategy.order_time_in_force['exit'] if (exit_check.exit_type != ExitType.LIQUIDATION @@ -1828,7 +1830,7 @@ class FreqtradeBot(LoggingMixin): never in base currency. """ self.wallets.update() - amount_ = amount + amount_ = trade.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 diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index c127e3850..a0d38563e 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -3969,15 +3969,17 @@ def test__safe_exit_amount(default_conf_usdt, fee, caplog, mocker, amount_wallet patch_get_signal(freqtrade) if has_err: with pytest.raises(DependencyException, match=r"Not enough amount to exit trade."): - assert freqtrade._safe_exit_amount(trade.pair, trade.amount) + assert freqtrade._safe_exit_amount(trade, trade.pair, trade.amount) else: wallet_update.reset_mock() - assert freqtrade._safe_exit_amount(trade.pair, trade.amount) == amount_wallet + assert trade.amount != amount_wallet + assert freqtrade._safe_exit_amount(trade, trade.pair, trade.amount) == amount_wallet assert log_has_re(r'.*Falling back to wallet-amount.', caplog) + assert trade.amount == amount_wallet assert wallet_update.call_count == 1 caplog.clear() wallet_update.reset_mock() - assert freqtrade._safe_exit_amount(trade.pair, amount_wallet) == amount_wallet + assert freqtrade._safe_exit_amount(trade, trade.pair, amount_wallet) == amount_wallet assert not log_has_re(r'.*Falling back to wallet-amount.', caplog) assert wallet_update.call_count == 1 From 0ff7a0771d1b5ca038a37b7e07368005abadae72 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 08:37:30 +0200 Subject: [PATCH 218/258] Move price_jump_warn to dataloading it's not relevant for live data, and should only run when loading data from disk. --- freqtrade/data/converter.py | 8 --- freqtrade/data/history/idatahandler.py | 14 +++++ tests/data/test_converter.py | 9 ++- tests/data/test_datahandler.py | 81 +++++++++++++++++++++++++- 4 files changed, 98 insertions(+), 14 deletions(-) diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py index 7f7e79445..98ed15489 100644 --- a/freqtrade/data/converter.py +++ b/freqtrade/data/converter.py @@ -119,14 +119,6 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) else: # Don't be verbose if only a small amount is missing logger.debug(message) - candle_price_gap = 0 - if not df.empty and 'close' in df.columns: - returns = df['close'].pct_change().dropna() - if len(returns): - candle_price_gap = max(abs(returns)) - if candle_price_gap > 0.3: - logger.info(f"Price jump in {pair} between two candles of {candle_price_gap:.2%} detected.") - return df diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py index 80e29f4c0..19d753043 100644 --- a/freqtrade/data/history/idatahandler.py +++ b/freqtrade/data/history/idatahandler.py @@ -335,6 +335,20 @@ class IDataHandler(ABC): "Use `freqtrade download-data` to download the data" ) return True + else: + candle_price_gap = 0 + if (candle_type in (CandleType.SPOT, CandleType.FUTURES) and + not pairdf.empty + and 'close' in pairdf.columns and 'open' in pairdf.columns): + # Detect gaps between prior close and open + gaps = ((pairdf['open'] - pairdf['close'].shift(1)) / pairdf['close'].shift(1)) + gaps = gaps.dropna() + if len(gaps): + candle_price_gap = max(abs(gaps)) + if candle_price_gap > 0.1: + logger.info(f"Price jump in {pair} between two candles of " + f"{candle_price_gap:.2%} detected.") + return False def _validate_pairdata(self, pair, pairdata: DataFrame, timeframe: str, diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py index 83429bb38..f74383d15 100644 --- a/tests/data/test_converter.py +++ b/tests/data/test_converter.py @@ -80,10 +80,10 @@ def test_ohlcv_fill_up_missing_data2(caplog): ticks = [ [ 1511686200000, # 8:50:00 - 8.794e-07, # open - 8.948e-07, # high - 8.794e-07, # low - 8.88e-07, # close + 8.794e-05, # open + 8.948e-05, # high + 8.794e-05, # low + 8.88e-05, # close 2255, # volume (in quote currency) ], [ @@ -118,7 +118,6 @@ def test_ohlcv_fill_up_missing_data2(caplog): assert len(data) == 3 caplog.set_level(logging.DEBUG) data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC") - assert log_has_re(r"Price jump in .* between two candles .* detected\.", caplog) assert len(data2) == 4 # 3rd candle has been filled row = data2.loc[2, :] diff --git a/tests/data/test_datahandler.py b/tests/data/test_datahandler.py index 5d6d60f84..4b1f9634c 100644 --- a/tests/data/test_datahandler.py +++ b/tests/data/test_datahandler.py @@ -15,7 +15,7 @@ from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, g from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler from freqtrade.data.history.parquetdatahandler import ParquetDataHandler from freqtrade.enums import CandleType, TradingMode -from tests.conftest import log_has +from tests.conftest import log_has, log_has_re def test_datahandler_ohlcv_get_pairs(testdatadir): @@ -154,6 +154,85 @@ def test_jsondatahandler_ohlcv_load(testdatadir, caplog): assert df.columns.equals(df1.columns) +def test_datahandler__check_empty_df(testdatadir, caplog): + dh = JsonDataHandler(testdatadir) + expected_text = r"Price jump in UNITTEST/USDT between" + df = DataFrame([ + [ + 1511686200000, # 8:50:00 + 8.794, # open + 8.948, # high + 8.794, # low + 8.88, # close + 2255, # volume (in quote currency) + ], + [ + 1511686500000, # 8:55:00 + 8.88, + 8.942, + 8.88, + 8.893, + 9911, + ], + [ + 1511687100000, # 9:05:00 + 8.891, + 8.893, + 8.875, + 8.877, + 2251 + ], + [ + 1511687400000, # 9:10:00 + 8.877, + 8.883, + 8.895, + 8.817, + 123551 + ] + ], columns=['date', 'open', 'high', 'low', 'close', 'volume']) + + dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True) + assert not log_has_re(expected_text, caplog) + df = DataFrame([ + [ + 1511686200000, # 8:50:00 + 8.794, # open + 8.948, # high + 8.794, # low + 8.88, # close + 2255, # volume (in quote currency) + ], + [ + 1511686500000, # 8:55:00 + 8.88, + 8.942, + 8.88, + 8.893, + 9911, + ], + [ + 1511687100000, # 9:05:00 + 889.1, # Price jump by several decimals + 889.3, + 887.5, + 887.7, + 2251 + ], + [ + 1511687400000, # 9:10:00 + 8.877, + 8.883, + 8.895, + 8.817, + 123551 + ] + ], columns=['date', 'open', 'high', 'low', 'close', 'volume']) + + dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True) + assert log_has_re(expected_text, caplog) + + @pytest.mark.parametrize('datahandler', ['feather', 'parquet']) def test_datahandler_trades_not_supported(datahandler, testdatadir, ): dh = get_datahandler(testdatadir, datahandler) From 547fd288115caddeb15632a2d2943bb3a0f6c67b Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 08:43:37 +0200 Subject: [PATCH 219/258] Price-jump detection should only run once --- freqtrade/data/history/idatahandler.py | 13 +++++++------ tests/data/test_datahandler.py | 6 +++--- 2 files changed, 10 insertions(+), 9 deletions(-) diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py index 19d753043..cbc3f1a34 100644 --- a/freqtrade/data/history/idatahandler.py +++ b/freqtrade/data/history/idatahandler.py @@ -303,7 +303,7 @@ class IDataHandler(ABC): timerange=timerange_startup, candle_type=candle_type ) - if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data): + if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True): return pairdf else: enddate = pairdf.iloc[-1]['date'] @@ -323,8 +323,9 @@ class IDataHandler(ABC): self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data) return pairdf - def _check_empty_df(self, pairdf: DataFrame, pair: str, timeframe: str, - candle_type: CandleType, warn_no_data: bool): + def _check_empty_df( + self, pairdf: DataFrame, pair: str, timeframe: str, candle_type: CandleType, + warn_no_data: bool, warn_price: bool = False) -> bool: """ Warn on empty dataframe """ @@ -335,7 +336,7 @@ class IDataHandler(ABC): "Use `freqtrade download-data` to download the data" ) return True - else: + elif warn_price: candle_price_gap = 0 if (candle_type in (CandleType.SPOT, CandleType.FUTURES) and not pairdf.empty @@ -346,8 +347,8 @@ class IDataHandler(ABC): if len(gaps): candle_price_gap = max(abs(gaps)) if candle_price_gap > 0.1: - logger.info(f"Price jump in {pair} between two candles of " - f"{candle_price_gap:.2%} detected.") + logger.info(f"Price jump in {pair}, {timeframe}, {candle_type} between two candles " + f"of {candle_price_gap:.2%} detected.") return False diff --git a/tests/data/test_datahandler.py b/tests/data/test_datahandler.py index 4b1f9634c..67eeda7d0 100644 --- a/tests/data/test_datahandler.py +++ b/tests/data/test_datahandler.py @@ -156,7 +156,7 @@ def test_jsondatahandler_ohlcv_load(testdatadir, caplog): def test_datahandler__check_empty_df(testdatadir, caplog): dh = JsonDataHandler(testdatadir) - expected_text = r"Price jump in UNITTEST/USDT between" + expected_text = r"Price jump in UNITTEST/USDT, 1h, spot between" df = DataFrame([ [ 1511686200000, # 8:50:00 @@ -192,7 +192,7 @@ def test_datahandler__check_empty_df(testdatadir, caplog): ] ], columns=['date', 'open', 'high', 'low', 'close', 'volume']) - dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True) + dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True, True) assert not log_has_re(expected_text, caplog) df = DataFrame([ [ @@ -229,7 +229,7 @@ def test_datahandler__check_empty_df(testdatadir, caplog): ] ], columns=['date', 'open', 'high', 'low', 'close', 'volume']) - dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True) + dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True, True) assert log_has_re(expected_text, caplog) From 84a194bcabc7633cf8b9795bee7d6be5e5d98b6c Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 11:45:21 +0200 Subject: [PATCH 220/258] Simplify stoploss logic by removing redundant condition --- freqtrade/strategy/interface.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 96e3065c4..05744e845 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -1085,9 +1085,7 @@ class IStrategy(ABC, HyperStrategyMixin): else: logger.warning("CustomStoploss function did not return valid stoploss") - sl_lower_long = (trade.stop_loss < (low or current_rate) and not trade.is_short) - sl_higher_short = (trade.stop_loss > (high or current_rate) and trade.is_short) - if self.trailing_stop and (sl_lower_long or sl_higher_short): + if self.trailing_stop and dir_correct: # trailing stoploss handling sl_offset = self.trailing_stop_positive_offset @@ -1101,7 +1099,7 @@ class IStrategy(ABC, HyperStrategyMixin): if self.trailing_stop_positive is not None and bound_profit > sl_offset: stop_loss_value = self.trailing_stop_positive logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} " - f"offset: {sl_offset:.4g} profit: {current_profit:.2%}") + f"offset: {sl_offset:.4g} profit: {bound_profit:.2%}") trade.adjust_stop_loss(bound or current_rate, stop_loss_value) From 3a9853db101d48978dbd7930889b19e0f702e2ba Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 12:52:13 +0200 Subject: [PATCH 221/258] use high/low for custom stoploss evaluation in backtesting --- freqtrade/strategy/interface.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 05744e845..681c5fcbb 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -1072,26 +1072,26 @@ class IStrategy(ABC, HyperStrategyMixin): trade.stop_loss > (high or current_rate) ) + # Make sure current_profit is calculated using high for backtesting. + bound = (low if trade.is_short else high) + bound_profit = current_profit if not bound else trade.calc_profit_ratio(bound) if self.use_custom_stoploss and dir_correct: stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None )(pair=trade.pair, trade=trade, current_time=current_time, - current_rate=current_rate, - current_profit=current_profit) + current_rate=(bound or current_rate), + current_profit=bound_profit) # Sanity check - error cases will return None if stop_loss_value: - # logger.info(f"{trade.pair} {stop_loss_value=} {current_profit=}") - trade.adjust_stop_loss(current_rate, stop_loss_value) + # logger.info(f"{trade.pair} {stop_loss_value=} {bound_profit=}") + trade.adjust_stop_loss(bound or current_rate, stop_loss_value) else: logger.warning("CustomStoploss function did not return valid stoploss") if self.trailing_stop and dir_correct: # trailing stoploss handling sl_offset = self.trailing_stop_positive_offset - # Make sure current_profit is calculated using high for backtesting. - bound = low if trade.is_short else high - bound_profit = current_profit if not bound else trade.calc_profit_ratio(bound) # Don't update stoploss if trailing_only_offset_is_reached is true. if not (self.trailing_only_offset_is_reached and bound_profit < sl_offset): From 47e93dd2b2346510cbbbd841bb5159859ad23da5 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 15:20:41 +0200 Subject: [PATCH 222/258] Update documentation --- docs/backtesting.md | 4 ++-- docs/strategy-callbacks.md | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/docs/backtesting.md b/docs/backtesting.md index f20a53d22..eed741a23 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -522,13 +522,13 @@ Since backtesting lacks some detailed information about what happens within a ca - ROI - exits are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the exit will be at 2%) - exits are never "below the candle", so a ROI of 2% may result in a exit at 2.4% if low was at 2.4% profit - - Forceexits caused by `=-1` ROI entries use low as exit value, unless N falls on the candle open (e.g. `120: -1` for 1h candles) + - Force-exits caused by `=-1` ROI entries use low as exit value, unless N falls on the candle open (e.g. `120: -1` for 1h candles) - Stoploss exits happen exactly at stoploss price, even if low was lower, but the loss will be `2 * fees` higher than the stoploss price - Stoploss is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` exit reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes - Low happens before high for stoploss, protecting capital first - Trailing stoploss - Trailing Stoploss is only adjusted if it's below the candle's low (otherwise it would be triggered) - - On trade entry candles that trigger trailing stoploss, the "minimum offset" (`stop_positive_offset`) is assumed (instead of high) - and the stop is calculated from this point + - On trade entry candles that trigger trailing stoploss, the "minimum offset" (`stop_positive_offset`) is assumed (instead of high) - and the stop is calculated from this point. This rule is NOT applicable to custom-stoploss scenarios, since there's no information about the stoploss logic available. - High happens first - adjusting stoploss - Low uses the adjusted stoploss (so exits with large high-low difference are backtested correctly) - ROI applies before trailing-stop, ensuring profits are "top-capped" at ROI if both ROI and trailing stop applies diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md index ea10fc472..230968fb0 100644 --- a/docs/strategy-callbacks.md +++ b/docs/strategy-callbacks.md @@ -159,6 +159,7 @@ The stoploss price can only ever move upwards - if the stoploss value returned f The method must return a stoploss value (float / number) as a percentage of the current price. E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD. +During backtesting, `current_rate` (and `current_profit`) are provided against the candle's high (or low for short trades) - while the resulting stoploss is evaluated against the candle's low (or high for short trades). The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price. 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