From 20fc52177128ee24b3812b5cf9235dd941a23611 Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Sat, 15 Oct 2022 23:30:12 +0200 Subject: [PATCH 01/80] 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 033c5bd441b941a9b7de45b236f0fe66568f18ba Mon Sep 17 00:00:00 2001 From: th0rntwig Date: Tue, 18 Oct 2022 12:55:47 +0200 Subject: [PATCH 02/80] 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 295ba21389565948268756829949cc7657098afd Mon Sep 17 00:00:00 2001 From: Mark Regan Date: Thu, 20 Oct 2022 12:05:37 +0100 Subject: [PATCH 03/80] 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 04/80] 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 05/80] 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 06/80] 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 07/80] 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 08/80] 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 09/80] 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 10/80] 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 11/80] 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 12/80] 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 13/80] 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 5ee3b8cbbb89c8a57cb42cc3253001e47720991b Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 21 Oct 2022 19:48:26 -0600 Subject: [PATCH 14/80] update config recording to use all configs, fix tests --- freqtrade/freqai/freqai_interface.py | 21 ++++++++++++++++----- tests/freqai/test_freqai_interface.py | 21 ++++++++++++--------- 2 files changed, 28 insertions(+), 14 deletions(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index db0d4c379..fef5df40f 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -61,15 +61,16 @@ class IFreqaiModel(ABC): "data_split_parameters", {}) self.model_training_parameters: Dict[str, Any] = config.get("freqai", {}).get( "model_training_parameters", {}) + self.identifier: str = self.freqai_info.get("identifier", "no_id_provided") self.retrain = False self.first = True self.set_full_path() + self.record_configs() self.follow_mode: bool = self.freqai_info.get("follow_mode", False) self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", True) if self.save_backtest_models: logger.info('Backtesting module configured to save all models.') self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode) - self.identifier: str = self.freqai_info.get("identifier", "no_id_provided") self.scanning = False self.ft_params = self.freqai_info["feature_parameters"] self.keras: bool = self.freqai_info.get("keras", False) @@ -526,14 +527,24 @@ class IFreqaiModel(ABC): return file_exists def set_full_path(self) -> None: + """ + Creates and sets the full path for the identifier + """ self.full_path = Path( self.config["user_data_dir"] / "models" / f"{self.freqai_info['identifier']}" ) self.full_path.mkdir(parents=True, exist_ok=True) - shutil.copy( - self.config["config_files"][0], - Path(self.full_path, Path(self.config["config_files"][0]).name), - ) + + def record_configs(self) -> None: + """ + Records configs in the full path for reproducibility + """ + self.config_record_path = self.full_path / Path("configs") + self.config_record_path.mkdir(parents=True, exist_ok=True) + + for config in self.config["config_files"]: + dest_config_path = self.config_record_path / Path(config).name + shutil.copyfile(config, dest_config_path) def extract_data_and_train_model( self, diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py index b619c0611..66eb6d696 100644 --- a/tests/freqai/test_freqai_interface.py +++ b/tests/freqai/test_freqai_interface.py @@ -19,7 +19,7 @@ from tests.freqai.conftest import get_patched_freqai_strategy def is_arm() -> bool: machine = platform.machine() - return "arm" in machine or "aarch64" in machine + return "arm" in machine or "aarch74" in machine def is_mac() -> bool: @@ -160,12 +160,12 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model): @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") + ("LightGBMRegressor", 7, "freqai_test_strat"), + ("XGBoostRegressor", 7, "freqai_test_strat"), + ("CatboostRegressor", 7, "freqai_test_strat"), + ("XGBoostClassifier", 7, "freqai_test_classifier"), + ("LightGBMClassifier", 7, "freqai_test_classifier"), + ("CatboostClassifier", 7, "freqai_test_classifier") ], ) def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog): @@ -200,6 +200,7 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog) freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] + # Changed from 6 to 7 because of the /configs directory assert len(model_folders) == num_files assert log_has_re( "Removed features ", @@ -234,7 +235,9 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf): metadata = {"pair": "LTC/BTC"} freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] - assert len(model_folders) == 9 + + # Changed from 9 to 10 because of the /configs dir + assert len(model_folders) == 10 shutil.rmtree(Path(freqai.dk.full_path)) @@ -260,7 +263,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog): freqai.start_backtesting(df, metadata, freqai.dk) model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()] - assert len(model_folders) == 6 + assert len(model_folders) == 7 # without deleting the existing folder structure, re-run From 4464e91256d646ea6d216a9658d0f11c2741b556 Mon Sep 17 00:00:00 2001 From: Timothy Pogue Date: Fri, 21 Oct 2022 19:53:33 -0600 Subject: [PATCH 15/80] use self.identifier in full path --- freqtrade/freqai/freqai_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py index fef5df40f..4727e61af 100644 --- a/freqtrade/freqai/freqai_interface.py +++ b/freqtrade/freqai/freqai_interface.py @@ -531,7 +531,7 @@ class IFreqaiModel(ABC): Creates and sets the full path for the identifier """ self.full_path = Path( - self.config["user_data_dir"] / "models" / f"{self.freqai_info['identifier']}" + self.config["user_data_dir"] / "models" / f"{self.identifier}" ) self.full_path.mkdir(parents=True, exist_ok=True) From 0ff7a0771d1b5ca038a37b7e07368005abadae72 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 22 Oct 2022 08:37:30 +0200 Subject: [PATCH 16/80] 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 17/80] 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 18/80] 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 19/80] 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 20/80] 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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