Merge branch 'freqtrade:develop' into develop
This commit is contained in:
@@ -16,6 +16,6 @@ if 'dev' in __version__:
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from pathlib import Path
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versionfile = Path('./freqtrade_commit')
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if versionfile.is_file():
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__version__ = f"docker-{versionfile.read_text()[:8]}"
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__version__ = f"docker-{__version__}-{versionfile.read_text()[:8]}"
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except Exception:
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pass
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|
@@ -15,9 +15,9 @@ from freqtrade.commands.db_commands import start_convert_db
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from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
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start_new_strategy)
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from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
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from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets,
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start_list_strategies, start_list_timeframes,
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start_show_trades)
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from freqtrade.commands.list_commands import (start_list_exchanges, start_list_freqAI_models,
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start_list_markets, start_list_strategies,
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start_list_timeframes, start_show_trades)
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from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show,
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start_edge, start_hyperopt)
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from freqtrade.commands.pairlist_commands import start_test_pairlist
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|
@@ -41,6 +41,8 @@ ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
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ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized",
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"recursive_strategy_search"]
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ARGS_LIST_FREQAIMODELS = ["freqaimodel_path", "print_one_column", "print_colorized"]
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ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"]
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ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list"]
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@@ -106,8 +108,8 @@ ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason
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"exit_reason_list", "indicator_list"]
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NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
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"list-markets", "list-pairs", "list-strategies", "list-data",
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"hyperopt-list", "hyperopt-show", "backtest-filter",
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"list-markets", "list-pairs", "list-strategies", "list-freqaimodels",
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"list-data", "hyperopt-list", "hyperopt-show", "backtest-filter",
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"plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"]
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NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
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@@ -192,10 +194,11 @@ class Arguments:
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start_create_userdir, start_download_data, start_edge,
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start_hyperopt, start_hyperopt_list, start_hyperopt_show,
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start_install_ui, start_list_data, start_list_exchanges,
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start_list_markets, start_list_strategies,
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start_list_timeframes, start_new_config, start_new_strategy,
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start_plot_dataframe, start_plot_profit, start_show_trades,
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start_test_pairlist, start_trading, start_webserver)
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start_list_freqAI_models, start_list_markets,
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start_list_strategies, start_list_timeframes,
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start_new_config, start_new_strategy, start_plot_dataframe,
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start_plot_profit, start_show_trades, start_test_pairlist,
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start_trading, start_webserver)
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subparsers = self.parser.add_subparsers(dest='command',
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# Use custom message when no subhandler is added
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@@ -362,6 +365,15 @@ class Arguments:
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list_strategies_cmd.set_defaults(func=start_list_strategies)
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self._build_args(optionlist=ARGS_LIST_STRATEGIES, parser=list_strategies_cmd)
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# Add list-freqAI Models subcommand
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list_freqaimodels_cmd = subparsers.add_parser(
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'list-freqaimodels',
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help='Print available freqAI models.',
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parents=[_common_parser],
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)
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list_freqaimodels_cmd.set_defaults(func=start_list_freqAI_models)
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self._build_args(optionlist=ARGS_LIST_FREQAIMODELS, parser=list_freqaimodels_cmd)
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# Add list-timeframes subcommand
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list_timeframes_cmd = subparsers.add_parser(
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'list-timeframes',
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|
@@ -90,6 +90,21 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
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_print_objs_tabular(strategy_objs, config.get('print_colorized', False))
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def start_list_freqAI_models(args: Dict[str, Any]) -> None:
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"""
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Print files with FreqAI models custom classes available in the directory
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"""
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config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
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from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
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model_objs = FreqaiModelResolver.search_all_objects(config, not args['print_one_column'])
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# Sort alphabetically
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model_objs = sorted(model_objs, key=lambda x: x['name'])
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if args['print_one_column']:
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print('\n'.join([s['name'] for s in model_objs]))
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else:
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_print_objs_tabular(model_objs, config.get('print_colorized', False))
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def start_list_timeframes(args: Dict[str, Any]) -> None:
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"""
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Print timeframes available on Exchange
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|
@@ -410,11 +410,13 @@ class Exchange:
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else:
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return DataFrame()
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def get_contract_size(self, pair: str) -> float:
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def get_contract_size(self, pair: str) -> Optional[float]:
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if self.trading_mode == TradingMode.FUTURES:
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market = self.markets[pair]
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market = self.markets.get(pair, {})
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contract_size: float = 1.0
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if market['contractSize'] is not None:
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if not market:
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return None
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if market.get('contractSize') is not None:
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# ccxt has contractSize in markets as string
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contract_size = float(market['contractSize'])
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return contract_size
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@@ -1934,6 +1936,7 @@ class Exchange:
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candle_limit = self.ohlcv_candle_limit(timeframe, self._config['candle_type_def'])
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# Age out old candles
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ohlcv_df = ohlcv_df.tail(candle_limit + self._startup_candle_count)
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ohlcv_df = ohlcv_df.reset_index(drop=True)
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self._klines[(pair, timeframe, c_type)] = ohlcv_df
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else:
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self._klines[(pair, timeframe, c_type)] = ohlcv_df
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@@ -51,7 +51,7 @@ class BaseClassifierModel(IFreqaiModel):
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f"{end_date} --------------------")
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# split data into train/test data.
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data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
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if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
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if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
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dk.fit_labels()
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# normalize all data based on train_dataset only
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data_dictionary = dk.normalize_data(data_dictionary)
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@@ -50,7 +50,7 @@ class BaseRegressionModel(IFreqaiModel):
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f"{end_date} --------------------")
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# split data into train/test data.
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data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
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if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
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if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
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dk.fit_labels()
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# normalize all data based on train_dataset only
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data_dictionary = dk.normalize_data(data_dictionary)
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@@ -47,7 +47,7 @@ class BaseTensorFlowModel(IFreqaiModel):
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f"{end_date} --------------------")
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# split data into train/test data.
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data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
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if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
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if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
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dk.fit_labels()
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# normalize all data based on train_dataset only
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data_dictionary = dk.normalize_data(data_dictionary)
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@@ -971,6 +971,9 @@ class FreqaiDataKitchen:
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append_df[f"{label}_mean"] = self.data["labels_mean"][label]
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append_df[f"{label}_std"] = self.data["labels_std"][label]
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for extra_col in self.data["extra_returns_per_train"]:
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append_df["{extra_col}"] = self.data["extra_returns_per_train"][extra_col]
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append_df["do_predict"] = do_predict
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if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
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append_df["DI_values"] = self.DI_values
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@@ -1,4 +1,5 @@
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import logging
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import sys
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from pathlib import Path
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from typing import Any, Dict
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@@ -48,6 +49,7 @@ class CatboostClassifier(BaseClassifierModel):
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init_model = self.get_init_model(dk.pair)
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cbr.fit(X=train_data, eval_set=test_data, init_model=init_model)
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cbr.fit(X=train_data, eval_set=test_data, init_model=init_model,
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log_cout=sys.stdout, log_cerr=sys.stderr)
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return cbr
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|
@@ -1,4 +1,5 @@
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import logging
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import sys
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from pathlib import Path
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from typing import Any, Dict
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@@ -47,6 +48,7 @@ class CatboostRegressor(BaseRegressionModel):
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**self.model_training_parameters,
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)
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model.fit(X=train_data, eval_set=test_data, init_model=init_model)
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model.fit(X=train_data, eval_set=test_data, init_model=init_model,
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log_cout=sys.stdout, log_cerr=sys.stderr)
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return model
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|
@@ -1,4 +1,5 @@
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import logging
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import sys
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from pathlib import Path
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from typing import Any, Dict
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@@ -58,8 +59,10 @@ class CatboostRegressorMultiTarget(BaseRegressionModel):
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fit_params = []
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for i in range(len(eval_sets)):
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fit_params.append(
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{'eval_set': eval_sets[i], 'init_model': init_models[i]})
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fit_params.append({
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'eval_set': eval_sets[i], 'init_model': init_models[i],
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'log_cout': sys.stdout, 'log_cerr': sys.stderr,
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})
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model = FreqaiMultiOutputRegressor(estimator=cbr)
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thread_training = self.freqai_info.get('multitarget_parallel_training', False)
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@@ -1471,12 +1471,13 @@ class FreqtradeBot(LoggingMixin):
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)
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return cancelled
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def _safe_exit_amount(self, pair: str, amount: float) -> float:
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def _safe_exit_amount(self, trade: Trade, pair: str, amount: float) -> float:
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"""
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Get sellable amount.
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Should be trade.amount - but will fall back to the available amount if necessary.
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This should cover cases where get_real_amount() was not able to update the amount
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for whatever reason.
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:param trade: Trade we're working with
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:param pair: Pair we're trying to sell
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:param amount: amount we expect to be available
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:return: amount to sell
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@@ -1495,6 +1496,7 @@ class FreqtradeBot(LoggingMixin):
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return amount
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elif wallet_amount > amount * 0.98:
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logger.info(f"{pair} - Falling back to wallet-amount {wallet_amount} -> {amount}.")
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trade.amount = wallet_amount
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return wallet_amount
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else:
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raise DependencyException(
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@@ -1553,7 +1555,7 @@ class FreqtradeBot(LoggingMixin):
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# Emergency sells (default to market!)
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order_type = self.strategy.order_types.get("emergency_exit", "market")
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amount = self._safe_exit_amount(trade.pair, sub_trade_amt or trade.amount)
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amount = self._safe_exit_amount(trade, trade.pair, sub_trade_amt or trade.amount)
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time_in_force = self.strategy.order_time_in_force['exit']
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if (exit_check.exit_type != ExitType.LIQUIDATION
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@@ -1828,7 +1830,7 @@ class FreqtradeBot(LoggingMixin):
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never in base currency.
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"""
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self.wallets.update()
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amount_ = amount
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||||
amount_ = trade.amount
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if order_obj.ft_order_side == trade.exit_side or order_obj.ft_order_side == 'stoploss':
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# check against remaining amount!
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amount_ = trade.amount - amount
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|
@@ -151,6 +151,8 @@ class Backtesting:
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self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
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# strategies which define "can_short=True" will fail to load in Spot mode.
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self._can_short = self.trading_mode != TradingMode.SPOT
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self._position_stacking: bool = self.config.get('position_stacking', False)
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self.enable_protections: bool = self.config.get('enable_protections', False)
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self.init_backtest()
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@@ -924,7 +926,7 @@ class Backtesting:
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||||
Handling of left open trades at the end of backtesting
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"""
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||||
for pair in open_trades.keys():
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for trade in open_trades[pair]:
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||||
for trade in list(open_trades[pair]):
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||||
if trade.open_order_id and trade.nr_of_successful_entries == 0:
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||||
# Ignore trade if entry-order did not fill yet
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continue
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@@ -959,9 +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:
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self.protections.stop_per_pair(pair, current_time, side)
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||||
self.protections.global_stop(current_time, side)
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|
||||
@@ -1067,10 +1068,78 @@ class Backtesting:
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||||
return None
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||||
return row
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||||
|
||||
def backtest(self, processed: Dict, # noqa: max-complexity: 13
|
||||
def backtest_loop(
|
||||
self, row: Tuple, pair: str, current_time: datetime, end_date: datetime,
|
||||
max_open_trades: int, 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/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_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 (
|
||||
(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
|
||||
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(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, position_stacking: bool = False,
|
||||
enable_protections: bool = False) -> Dict[str, Any]:
|
||||
max_open_trades: int = 0) -> Dict[str, Any]:
|
||||
"""
|
||||
Implement backtesting functionality
|
||||
|
||||
@@ -1083,11 +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 position_stacking: do we allow position stacking?
|
||||
: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
|
||||
@@ -1098,15 +1165,12 @@ 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]
|
||||
@@ -1118,78 +1182,14 @@ class Backtesting:
|
||||
indexes[pair] = row_index
|
||||
self.dataprovider._set_dataframe_max_index(row_index)
|
||||
|
||||
for t in list(open_trades[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()
|
||||
|
||||
# 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(open_trades[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
|
||||
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]):
|
||||
# 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}")
|
||||
open_trade_count -= 1
|
||||
open_trades[pair].remove(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, open_trade_count_start)
|
||||
|
||||
# Move time one configured time_interval ahead.
|
||||
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)
|
||||
@@ -1245,8 +1245,6 @@ 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)
|
||||
results.update({
|
||||
|
@@ -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
|
||||
@@ -258,6 +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'):
|
||||
@@ -339,8 +339,6 @@ 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)
|
||||
bt_results.update({
|
||||
|
@@ -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):
|
||||
@@ -1508,3 +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=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),
|
||||
order_type=order["order_type"],
|
||||
price=order["price"],
|
||||
remaining=order["remaining"],
|
||||
)
|
||||
trade.orders.append(order_obj)
|
||||
|
||||
return trade
|
||||
|
@@ -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
|
||||
|
@@ -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
|
||||
|
@@ -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):
|
||||
|
@@ -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()
|
||||
|
@@ -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")
|
||||
|
@@ -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
|
||||
|
||||
|
@@ -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)
|
||||
|
||||
|
Reference in New Issue
Block a user