From df50b1928d6d58b130d1d2b40dcaad334800bcc3 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 06:51:30 +0200 Subject: [PATCH 01/15] Fix funding fee calculation for backtesting --- freqtrade/optimize/backtesting.py | 2 +- freqtrade/persistence/trade_model.py | 34 +++++++++++++++++++++++++--- 2 files changed, 32 insertions(+), 4 deletions(-) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 77bf3d8ad..8f6b6b332 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -686,7 +686,7 @@ class Backtesting: self.futures_data[trade.pair], amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc, + open_date=trade.date_last_filled_utc, close_date=exit_candle_time, ) diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 1f14f110e..9c9c7f381 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -65,6 +65,8 @@ class Order(_DECL_BASE): order_filled_date = Column(DateTime, nullable=True) order_update_date = Column(DateTime, nullable=True) + funding_fee = Column(Float, nullable=True) + ft_fee_base = Column(Float, nullable=True) @property @@ -72,6 +74,13 @@ class Order(_DECL_BASE): """ Order-date with UTC timezoneinfo""" return self.order_date.replace(tzinfo=timezone.utc) + @property + def order_filled_utc(self) -> Optional[datetime]: + """ last order-date with UTC timezoneinfo""" + return ( + self.order_filled_date.replace(tzinfo=timezone.utc) if self.order_filled_date else None + ) + @property def safe_price(self) -> float: return self.average or self.price @@ -179,6 +188,10 @@ class Order(_DECL_BASE): self.remaining = 0 self.status = 'closed' self.ft_is_open = False + # Assign funding fees to Order. + # Assumes backtesting will use date_last_filled_utc to calculate future funding fees. + self.funding_fee = trade.funding_fees + if (self.ft_order_side == trade.entry_side): trade.open_rate = self.price trade.recalc_trade_from_orders() @@ -346,6 +359,12 @@ class LocalTrade(): else: return self.amount + @property + def date_last_filled_utc(self): + """ Date of the last filled order""" + return max([self.open_date_utc, + max(o.order_filled_utc for o in self.orders if o.filled and not o.ft_is_open)]) + @property def open_date_utc(self): return self.open_date.replace(tzinfo=timezone.utc) @@ -843,10 +862,14 @@ class LocalTrade(): close_profit = 0.0 close_profit_abs = 0.0 profit = None - for o in self.orders: + # Reset funding fees + self.funding_fees = 0.0 + funding_fees = 0.0 + ordercount = len(self.orders) - 1 + for i, o in enumerate(self.orders): if o.ft_is_open or not o.filled: continue - + funding_fees += (o.funding_fee or 0.0) tmp_amount = FtPrecise(o.safe_amount_after_fee) tmp_price = FtPrecise(o.safe_price) @@ -861,7 +884,11 @@ class LocalTrade(): avg_price = current_stake / current_amount if is_exit: - # Process partial exits + # Process exits + if i == ordercount and is_closing: + # Apply funding fees only to the last order + self.funding_fees = funding_fees + exit_rate = o.safe_price exit_amount = o.safe_amount_after_fee profit = self.calc_profit(rate=exit_rate, amount=exit_amount, @@ -871,6 +898,7 @@ class LocalTrade(): exit_rate, amount=exit_amount, open_rate=avg_price) else: total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price) + self.funding_fees = funding_fees if close_profit: self.close_profit = close_profit From 0c6a02687a49b48c433ec841200911b21efc8f24 Mon Sep 17 00:00:00 2001 From: Matthias Date: Fri, 2 Sep 2022 20:55:13 +0200 Subject: [PATCH 02/15] Don't calculate funding fees if we're not going to use them. --- freqtrade/freqtradebot.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 37bc6dfed..95b42155f 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -726,10 +726,11 @@ class FreqtradeBot(LoggingMixin): fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker') base_currency = self.exchange.get_pair_base_currency(pair) open_date = datetime.now(timezone.utc) - funding_fees = self.exchange.get_funding_fees( - pair=pair, amount=amount, is_short=is_short, open_date=open_date) + # This is a new trade if trade is None: + funding_fees = self.exchange.get_funding_fees( + pair=pair, amount=amount, is_short=is_short, open_date=open_date) trade = Trade( pair=pair, base_currency=base_currency, From 0f483ee31f043ceafaa7a5c19eaa77ade2e1d323 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 10:06:23 +0200 Subject: [PATCH 03/15] Use "since last order" approach for live as well. --- freqtrade/freqtradebot.py | 4 ++-- freqtrade/persistence/trade_model.py | 12 +++++++++--- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 95b42155f..5323a5fc0 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -281,7 +281,7 @@ class FreqtradeBot(LoggingMixin): pair=trade.pair, amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc + open_date=trade.date_last_filled_utc ) trade.funding_fees = funding_fees else: @@ -1485,7 +1485,7 @@ class FreqtradeBot(LoggingMixin): pair=trade.pair, amount=trade.amount, is_short=trade.is_short, - open_date=trade.open_date_utc, + open_date=trade.date_last_filled_utc, ) exit_type = 'exit' exit_reason = exit_tag or exit_check.exit_reason diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 9c9c7f381..c2a87daaa 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -128,6 +128,10 @@ class Order(_DECL_BASE): self.ft_is_open = True if self.status in NON_OPEN_EXCHANGE_STATES: self.ft_is_open = False + if self.trade: + # Assign funding fee up to this point + # (represents the funding fee since the last order) + self.funding_fee = self.trade.funding_fees if (order.get('filled', 0.0) or 0.0) > 0: self.order_filled_date = datetime.now(timezone.utc) self.order_update_date = datetime.now(timezone.utc) @@ -360,10 +364,12 @@ class LocalTrade(): return self.amount @property - def date_last_filled_utc(self): + def date_last_filled_utc(self) -> datetime: """ Date of the last filled order""" - return max([self.open_date_utc, - max(o.order_filled_utc for o in self.orders if o.filled and not o.ft_is_open)]) + orders = self.select_filled_orders() + if not orders: + return self.open_date_utc + return max([self.open_date_utc, max(o.order_filled_utc for o in orders)]) @property def open_date_utc(self): From b95b3d8391f4df3bb3510173711349d7356a08ec Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 15:09:50 +0200 Subject: [PATCH 04/15] Update test to actually test funding fee appliance --- tests/test_persistence.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index 23ccc67f3..cdca3bc4d 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -615,21 +615,25 @@ def test_calc_open_close_trade_price( is_short=is_short, leverage=lev, trading_mode=trading_mode, - funding_fees=funding_fees ) entry_order = limit_order[trade.entry_side] exit_order = limit_order[trade.exit_side] trade.open_order_id = f'something-{is_short}-{lev}-{exchange}' oobj = Order.parse_from_ccxt_object(entry_order, 'ADA/USDT', trade.entry_side) - trade.orders.append(oobj) + oobj.trade = trade + oobj.update_from_ccxt_object(entry_order) trade.update_trade(oobj) + trade.funding_fees = funding_fees + oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', trade.exit_side) - trade.orders.append(oobj) + oobj.trade = trade + oobj.update_from_ccxt_object(exit_order) trade.update_trade(oobj) assert trade.is_open is False + assert trade.funding_fees == funding_fees assert pytest.approx(trade._calc_open_trade_value(trade.amount, trade.open_rate)) == open_value assert pytest.approx(trade.calc_close_trade_value(trade.close_rate)) == close_value From ed4cc18cddaaff7bdb95738ee4a3d5093530b0e0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 15:18:09 +0200 Subject: [PATCH 05/15] Migration to check order funding fee --- freqtrade/persistence/migrations.py | 10 ++++++---- freqtrade/persistence/trade_model.py | 2 +- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index 1131c88b4..1f1330ba7 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -212,17 +212,18 @@ def migrate_orders_table(engine, table_back_name: str, cols_order: List): ft_fee_base = get_column_def(cols_order, 'ft_fee_base', 'null') average = get_column_def(cols_order, 'average', 'null') stop_price = get_column_def(cols_order, 'stop_price', 'null') + funding_fee = get_column_def(cols_order, 'funding_fee', '0.0') # sqlite does not support literals for booleans with engine.begin() as connection: connection.execute(text(f""" insert into orders (id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, average, remaining, cost, - stop_price, order_date, order_filled_date, order_update_date, ft_fee_base) + stop_price, order_date, order_filled_date, order_update_date, ft_fee_base, funding_fee) select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, {average} average, remaining, cost, {stop_price} stop_price, order_date, order_filled_date, - order_update_date, {ft_fee_base} ft_fee_base + order_update_date, {ft_fee_base} ft_fee_base {funding_fee} funding_fee from {table_back_name} """)) @@ -307,9 +308,10 @@ def check_migrate(engine, decl_base, previous_tables) -> None: # Check if migration necessary # Migrates both trades and orders table! # if ('orders' not in previous_tables - # or not has_column(cols_orders, 'stop_price')): + # or not has_column(cols_orders, 'funding_fee')): migrating = False - if not has_column(cols_trades, 'contract_size'): + if not has_column(cols_orders, 'funding_fee'): + # if not has_column(cols_trades, 'contract_size'): migrating = True logger.info(f"Running database migration for trades - " f"backup: {table_back_name}, {order_table_bak_name}") diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index c2a87daaa..6127c502d 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -892,7 +892,7 @@ class LocalTrade(): if is_exit: # Process exits if i == ordercount and is_closing: - # Apply funding fees only to the last order + # Apply funding fees only to the last closing order self.funding_fees = funding_fees exit_rate = o.safe_price From 16573b19e3d478b3a5625a81d2504823dee4cdf8 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 3 Sep 2022 19:34:38 +0200 Subject: [PATCH 06/15] Fix migration syntax error --- freqtrade/persistence/migrations.py | 4 ++-- freqtrade/persistence/trade_model.py | 3 ++- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index 1f1330ba7..a54c5570f 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -223,7 +223,7 @@ def migrate_orders_table(engine, table_back_name: str, cols_order: List): select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, symbol, order_type, side, price, amount, filled, {average} average, remaining, cost, {stop_price} stop_price, order_date, order_filled_date, - order_update_date, {ft_fee_base} ft_fee_base {funding_fee} funding_fee + order_update_date, {ft_fee_base} ft_fee_base, {funding_fee} funding_fee from {table_back_name} """)) @@ -310,8 +310,8 @@ def check_migrate(engine, decl_base, previous_tables) -> None: # if ('orders' not in previous_tables # or not has_column(cols_orders, 'funding_fee')): migrating = False - if not has_column(cols_orders, 'funding_fee'): # if not has_column(cols_trades, 'contract_size'): + if not has_column(cols_orders, 'funding_fee'): migrating = True logger.info(f"Running database migration for trades - " f"backup: {table_back_name}, {order_table_bak_name}") diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index 6127c502d..ea60796a4 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -369,7 +369,8 @@ class LocalTrade(): orders = self.select_filled_orders() if not orders: return self.open_date_utc - return max([self.open_date_utc, max(o.order_filled_utc for o in orders)]) + return max([self.open_date_utc, + max(o.order_filled_utc for o in orders if o.order_filled_utc)]) @property def open_date_utc(self): From 9f5642fd972affbf12f16859e391a3f243bc45ad Mon Sep 17 00:00:00 2001 From: Italo <45588475+italodamato@users.noreply.github.com> Date: Mon, 5 Sep 2022 18:12:19 +0200 Subject: [PATCH 07/15] fix hyperopt df preprocessing --- freqtrade/optimize/hyperopt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index fea2a672f..4c8613a7a 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -423,7 +423,7 @@ class Hyperopt: # Trim startup period from analyzed dataframe to get correct dates for output. processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) self.min_date, self.max_date = get_timerange(processed) - return processed + return preprocessed def prepare_hyperopt_data(self) -> None: HyperoptStateContainer.set_state(HyperoptState.DATALOAD) From 4628bfa580c49d8f80bf1372b66c95f6557b683c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Sep 2022 17:30:55 +0000 Subject: [PATCH 08/15] Bump jsonschema from 4.14.0 to 4.15.0 Bumps [jsonschema](https://github.com/python-jsonschema/jsonschema) from 4.14.0 to 4.15.0. - [Release notes](https://github.com/python-jsonschema/jsonschema/releases) - [Changelog](https://github.com/python-jsonschema/jsonschema/blob/main/CHANGELOG.rst) - [Commits](https://github.com/python-jsonschema/jsonschema/compare/v4.14.0...v4.15.0) --- updated-dependencies: - dependency-name: jsonschema dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 8b994cb88..fdbe6ac28 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,7 +12,7 @@ arrow==1.2.3 cachetools==4.2.2 requests==2.28.1 urllib3==1.26.12 -jsonschema==4.14.0 +jsonschema==4.15.0 TA-Lib==0.4.24 technical==1.3.0 tabulate==0.8.10 From 689b193240a77dc2e9619583a9bef3c9c7f07b56 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 20:57:42 +0200 Subject: [PATCH 09/15] improve clarity on data download requirements --- docs/freqai.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/docs/freqai.md b/docs/freqai.md index 3646362c3..d04d2fa6b 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -280,7 +280,7 @@ The FreqAI strategy requires the user to include the following lines of code in Notice how the `populate_any_indicators()` is where the user adds their own features ([more information](#feature-engineering)) and labels ([more information](#setting-classifier-targets)). See a full example at `templates/FreqaiExampleStrategy.py`. ### Setting the `startup_candle_count` -Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md/#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). +Users need to take care to set the `startup_candle_count` in their strategy the same way they would for any normal Freqtrade strategy (see details [here](strategy-customization.md#strategy-startup-period)). This value is used by Freqtrade to ensure that a sufficient amount of data is provided when calling on the `dataprovider` to avoid any NaNs at the beginning of the first training. Users can easily set this value by identifying the longest period (in candle units) that they pass to their indicator creation functions (e.g. talib functions). In the present example, the user would pass 20 to as this value (since it is the maximum value in their `indicators_periods_candles`). !!! Note Typically it is best for users to be safe and multiply their expected `startup_candle_count` by 2. There are instances where the talib functions actually require more data than just the passed `period`. Anecdotally, multiplying the `startup_candle_count` by 2 always leads to a fully NaN free training dataset. Look out for this log message to confirm that your data is clean: @@ -515,10 +515,11 @@ and if a full `live_retrain_hours` has elapsed since the end of the loaded model The FreqAI backtesting module can be executed with the following command: ```bash -freqtrade backtesting --strategy FreqaiExampleStrategy --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 +freqtrade download-data --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates -t 3m 15m 1h --timerange 20210315-20210701 +freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 ``` -Backtesting mode requires the user to have the data pre-downloaded (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). +Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration). If this command has never been executed with the existing config file, it will train a new model for each pair, for each backtesting window within the expanded `--timerange`. @@ -546,7 +547,7 @@ FreqAI will train have trained 8 separate models at the end of `--timerange` (be Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run. ### Downloading data for backtesting -Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download/#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by taking subtracting `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. +Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange. As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange). From 1ea703d527b341322a64d0f8e2327117a2bca7a8 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Mon, 5 Sep 2022 22:20:38 +0200 Subject: [PATCH 10/15] remove download-data command --- docs/freqai.md | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/freqai.md b/docs/freqai.md index d04d2fa6b..303c2f151 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -515,7 +515,6 @@ and if a full `live_retrain_hours` has elapsed since the end of the loaded model The FreqAI backtesting module can be executed with the following command: ```bash -freqtrade download-data --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates -t 3m 15m 1h --timerange 20210315-20210701 freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701 ``` From 4dec19de9f9ca55565c7972c62eb65afa33d1f48 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 06:52:50 +0200 Subject: [PATCH 11/15] Add comment to explain why we use the non-trimmed DF --- freqtrade/optimize/hyperopt.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 4c8613a7a..3becf857f 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -421,8 +421,9 @@ class Hyperopt: preprocessed = self.backtesting.strategy.advise_all_indicators(data) # Trim startup period from analyzed dataframe to get correct dates for output. - processed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) - self.min_date, self.max_date = get_timerange(processed) + trimmed = trim_dataframes(preprocessed, self.timerange, self.backtesting.required_startup) + self.min_date, self.max_date = get_timerange(trimmed) + # Real trimming will happen as part of backtesting. return preprocessed def prepare_hyperopt_data(self) -> None: From 8597b52e345abca6111869bb5da71c01ce7d4107 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 16:29:24 +0200 Subject: [PATCH 12/15] Slightly update docs to link to full sample --- docs/strategy-customization.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index a452b8f05..2b6e1fb2f 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -824,6 +824,8 @@ Options: - Merge the dataframe without lookahead bias - Forward-fill (optional) +For a full sample, please refer to the [complete data provider example](#complete-data-provider-sample) below. + All columns of the informative dataframe will be available on the returning dataframe in a renamed fashion: !!! Example "Column renaming" From f2f811a2feed0a8ff427d638ac773d6aea670eaa Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 19:55:18 +0200 Subject: [PATCH 13/15] Fix telegram bug with open partial exit orders --- freqtrade/rpc/rpc.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 11311f671..05599074c 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -261,11 +261,15 @@ class RPC: profit_str += f" ({fiat_profit:.2f})" fiat_profit_sum = fiat_profit if isnan(fiat_profit_sum) \ else fiat_profit_sum + fiat_profit + open_order = (trade.select_order_by_order_id( + trade.open_order_id) if trade.open_order_id else None) + detail_trade = [ f'{trade.id} {direction_str}', - trade.pair + ('*' if (trade.open_order_id is not None - and trade.close_rate_requested is None) else '') - + ('**' if (trade.close_rate_requested is not None) else ''), + trade.pair + ('*' if (open_order + and open_order.ft_order_side == trade.entry_side) else '') + + ('**' if (open_order and + open_order.ft_order_side == trade.exit_side is not None) else ''), shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)), profit_str ] From 90ec336c70e02e0ae8156a768bf69b4ac0fa55b5 Mon Sep 17 00:00:00 2001 From: th0rntwig <107926911+th0rntwig@users.noreply.github.com> Date: Tue, 6 Sep 2022 19:58:25 +0200 Subject: [PATCH 14/15] Update+correct descriptions and figure (#7323) --- docs/assets/freqai_weight-factor.jpg | Bin 195825 -> 189828 bytes docs/freqai.md | 14 +++++++------- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/docs/assets/freqai_weight-factor.jpg b/docs/assets/freqai_weight-factor.jpg index 4f8b23e1849588058fa8a55d5adf67466ca90c86..c7580787de79862f2af2539eb904682050614a53 100644 GIT binary patch literal 189828 zcmdqJ2UL^G*EbqOMUi3w>7XK@RO!+Jiu5KRy@~WLEl9TkDkajTMtTh$LPwhPgx-4# zJwOPM0O7_{Jm>#@@4f4O-(7dzGR%6ODbGx1ezRxqJ$q(2A3vW5TvwJ?k_QkG0RTjV 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z#ZcWc=hoF_6!LuIsOU=Qo)8^PE!lgsT3|yYzvm_w`GjW=Y3hSwa#G3|s67E@hRXj1 qd;rIVUxwWG+`l!D;}0<(d0nwzph`z&{6c>~1k#EKXesjV^nU@S$(@M+ diff --git a/docs/freqai.md b/docs/freqai.md index 303c2f151..c0844bf32 100644 --- a/docs/freqai.md +++ b/docs/freqai.md @@ -112,15 +112,15 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `DI_threshold` | Activates the Dissimilarity Index for outlier detection when > 0. See details about how it works [here](#removing-outliers-with-the-dissimilarity-index).
**Datatype:** Positive float (typically < 1). | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Boolean. | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary. -| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean. -| `outlier_protection_percentage` | If more than `outlier_protection_percentage` fraction of points are removed as outliers, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact.
**Datatype:** float. Default: `30` -| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
**Datatype:** bool. Default: False +| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean. +| `outlier_protection_percentage` | If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact. If the outlier protection is triggered, no predictions will be made based on the training data.
**Datatype:** Float. Default: `30` +| `reverse_train_test_order` | If true, FreqAI will train on the latest data split and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, users should be careful to understand unorthodox nature of this parameter before employing it.
**Datatype:** Boolean. Default: False | | **Data split parameters** | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website).
**Datatype:** Dictionary. | `test_size` | Fraction of data that should be used for testing instead of training.
**Datatype:** Positive float < 1. -| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
+| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`.
**Datatype:** Boolean. | | **Model training parameters** -| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
**Datatype:** Dictionary.**Datatype:** Boolean. +| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected model library. For example, if the user uses `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If the user selects a different model, this dictionary can contain any parameter from that model.
**Datatype:** Dictionary. | `n_estimators` | The number of boosted trees to fit in regression.
**Datatype:** Integer. | `learning_rate` | Boosting learning rate during regression.
**Datatype:** Float. | `n_jobs`, `thread_count`, `task_type` | Set the number of threads for parallel processing and the `task_type` (`gpu` or `cpu`). Different model libraries use different parameter names.
**Datatype:** Float. @@ -738,7 +738,7 @@ Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters ![dbscan](assets/freqai_dbscan.jpg) -FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as double the no. of user-defined features, and `eps` ($\varepsilon$) taken as the longest distance in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. +FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](#https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)) with `min_samples` ($N$) taken as 1/4 of the no. of time points in the feature set, and `eps` ($\varepsilon$) taken as the elbow point in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set. ## Additional information @@ -763,5 +763,5 @@ Code review, software architecture brainstorming: @xmatthias Beta testing and bug reporting: -@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm +@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm, Juha Nykänen @suikula, Wagner Costa @wagnercosta From dc4a4bdf09cfc3ecb588cdabb3877e07b5762ab0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Tue, 6 Sep 2022 20:25:46 +0200 Subject: [PATCH 15/15] Wrap cleanup in try/finally handler If a database has errors, the database cleanups would fail, causing cleanup to be incomplete. closes #7364 --- freqtrade/freqtradebot.py | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index f7dca1d75..1d171ae89 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -142,17 +142,20 @@ class FreqtradeBot(LoggingMixin): :return: None """ logger.info('Cleaning up modules ...') + try: + # Wrap db activities in shutdown to avoid problems if database is gone, + # and raises further exceptions. + if self.config['cancel_open_orders_on_exit']: + self.cancel_all_open_orders() - if self.config['cancel_open_orders_on_exit']: - self.cancel_all_open_orders() + self.check_for_open_trades() - self.check_for_open_trades() + finally: + self.strategy.ft_bot_cleanup() - self.strategy.ft_bot_cleanup() - - self.rpc.cleanup() - Trade.commit() - self.exchange.close() + self.rpc.cleanup() + Trade.commit() + self.exchange.close() def startup(self) -> None: """