refactoring - remove unnecessary config file
This commit is contained in:
Wagner Costa Santos
parent
52b60c5cbb
commit
6606a0113f
@ -1,7 +1,7 @@
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import copy
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import logging
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import shutil
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from datetime import datetime, timezone
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from datetime import datetime, timedelta, timezone
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from math import cos, sin
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from pathlib import Path
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from typing import Any, Dict, List, Tuple
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@ -21,7 +21,6 @@ from freqtrade.configuration import TimeRange
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from freqtrade.constants import Config
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import timeframe_to_seconds
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from freqtrade.freqai import freqai_util
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from freqtrade.strategy.interface import IStrategy
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@ -84,16 +83,17 @@ class FreqaiDataKitchen:
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self.backtest_live_models = config.get("freqai_backtest_live_models", False)
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if not self.live:
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self.full_path = freqai_util.get_full_models_path(self.config)
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self.full_timerange = self.create_fulltimerange(
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self.config["timerange"], self.freqai_config.get("train_period_days", 0)
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)
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self.full_path = self.get_full_models_path(self.config)
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if self.backtest_live_models:
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if self.pair:
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self.set_timerange_from_ready_models()
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(self.training_timeranges,
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self.backtesting_timeranges) = self.split_timerange_live_models()
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else:
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self.full_timerange = self.create_fulltimerange(
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self.config["timerange"], self.freqai_config.get("train_period_days", 0)
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)
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(self.training_timeranges, self.backtesting_timeranges) = self.split_timerange(
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self.full_timerange,
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config["freqai"]["train_period_days"],
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@ -117,7 +117,7 @@ class FreqaiDataKitchen:
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:param metadata: dict = strategy furnished pair metadata
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:param trained_timestamp: int = timestamp of most recent training
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"""
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self.full_path = freqai_util.get_full_models_path(self.config)
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self.full_path = self.get_full_models_path(self.config)
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self.data_path = Path(
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self.full_path
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/ f"sub-train-{pair.split('/')[0]}_{trained_timestamp}"
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@ -1300,10 +1300,102 @@ class FreqaiDataKitchen:
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def set_timerange_from_ready_models(self):
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backtesting_timerange, \
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assets_end_dates = (
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freqai_util.get_timerange_and_assets_end_dates_from_ready_models(self.full_path))
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self.get_timerange_and_assets_end_dates_from_ready_models(self.full_path))
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self.backtest_live_models_data = {
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"backtesting_timerange": backtesting_timerange,
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"assets_end_dates": assets_end_dates
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}
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return
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def get_full_models_path(self, config: Config) -> Path:
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"""
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Returns default FreqAI model path
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:param config: Configuration dictionary
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"""
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freqai_config: Dict[str, Any] = config["freqai"]
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return Path(
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config["user_data_dir"] / "models" / str(freqai_config.get("identifier"))
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)
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def get_timerange_and_assets_end_dates_from_ready_models(
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self, models_path: Path) -> Tuple[TimeRange, Dict[str, Any]]:
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"""
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Returns timerange information based on a FreqAI model directory
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:param models_path: FreqAI model path
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:return: a Tuple with (Timerange calculated from directory and
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a Dict with pair and model end training dates info)
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"""
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all_models_end_dates = []
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assets_end_dates: Dict[str, Any] = self.get_assets_timestamps_training_from_ready_models(
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models_path)
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for key in assets_end_dates:
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for model_end_date in assets_end_dates[key]:
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if model_end_date not in all_models_end_dates:
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all_models_end_dates.append(model_end_date)
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if len(all_models_end_dates) == 0:
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raise OperationalException(
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'At least 1 saved model is required to '
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'run backtest with the freqai-backtest-live-models option'
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)
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if len(all_models_end_dates) == 1:
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logger.warning(
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"Only 1 model was found. Backtesting will run with the "
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"timerange from the end of the training date to the current date"
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)
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finish_timestamp = int(datetime.now(tz=timezone.utc).timestamp())
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if len(all_models_end_dates) > 1:
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# After last model end date, use the same period from previous model
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# to finish the backtest
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all_models_end_dates.sort(reverse=True)
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finish_timestamp = all_models_end_dates[0] + \
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(all_models_end_dates[0] - all_models_end_dates[1])
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all_models_end_dates.append(finish_timestamp)
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all_models_end_dates.sort()
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start_date = (datetime(*datetime.fromtimestamp(min(all_models_end_dates),
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timezone.utc).timetuple()[:3], tzinfo=timezone.utc))
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end_date = (datetime(*datetime.fromtimestamp(max(all_models_end_dates),
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timezone.utc).timetuple()[:3], tzinfo=timezone.utc))
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# add 1 day to string timerange to ensure BT module will load all dataframe data
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end_date = end_date + timedelta(days=1)
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backtesting_timerange = TimeRange(
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'date', 'date', int(start_date.timestamp()), int(end_date.timestamp())
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)
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return backtesting_timerange, assets_end_dates
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def get_assets_timestamps_training_from_ready_models(
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self, models_path: Path) -> Dict[str, Any]:
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"""
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Scan the models path and returns all assets end training dates (timestamp)
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:param models_path: FreqAI model path
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:return: a Dict with asset and model end training dates info
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"""
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assets_end_dates: Dict[str, Any] = {}
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if not models_path.is_dir():
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raise OperationalException(
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'Model folders not found. Saved models are required '
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'to run backtest with the freqai-backtest-live-models option'
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)
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for model_dir in models_path.iterdir():
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if str(model_dir.name).startswith("sub-train"):
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model_end_date = int(model_dir.name.split("_")[1])
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asset = model_dir.name.split("_")[0].replace("sub-train-", "")
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model_file_name = (
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f"cb_{str(model_dir.name).replace('sub-train-', '').lower()}"
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"_model.joblib"
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)
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model_path_file = Path(model_dir / model_file_name)
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if model_path_file.is_file():
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if asset not in assets_end_dates:
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assets_end_dates[asset] = []
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assets_end_dates[asset].append(model_end_date)
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return assets_end_dates
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@ -1,122 +0,0 @@
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"""
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FreqAI generic functions
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"""
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import logging
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from datetime import datetime, timedelta, timezone
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from pathlib import Path
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from typing import Any, Dict, Tuple
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import Config
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from freqtrade.exceptions import OperationalException
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logger = logging.getLogger(__name__)
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def get_full_models_path(config: Config) -> Path:
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"""
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Returns default FreqAI model path
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:param config: Configuration dictionary
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"""
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freqai_config: Dict[str, Any] = config["freqai"]
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return Path(
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config["user_data_dir"] / "models" / str(freqai_config.get("identifier"))
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)
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def get_timerange_and_assets_end_dates_from_ready_models(
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models_path: Path) -> Tuple[TimeRange, Dict[str, Any]]:
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"""
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Returns timerange information based on a FreqAI model directory
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:param models_path: FreqAI model path
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:return: a Tuple with (Timerange calculated from directory and
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a Dict with pair and model end training dates info)
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"""
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all_models_end_dates = []
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assets_end_dates: Dict[str, Any] = get_assets_timestamps_training_from_ready_models(models_path)
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for key in assets_end_dates:
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for model_end_date in assets_end_dates[key]:
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if model_end_date not in all_models_end_dates:
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all_models_end_dates.append(model_end_date)
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if len(all_models_end_dates) == 0:
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raise OperationalException(
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'At least 1 saved model is required to '
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'run backtest with the freqai-backtest-live-models option'
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)
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if len(all_models_end_dates) == 1:
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logger.warning(
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"Only 1 model was found. Backtesting will run with the "
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"timerange from the end of the training date to the current date"
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)
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finish_timestamp = int(datetime.now(tz=timezone.utc).timestamp())
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if len(all_models_end_dates) > 1:
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# After last model end date, use the same period from previous model
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# to finish the backtest
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all_models_end_dates.sort(reverse=True)
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finish_timestamp = all_models_end_dates[0] + \
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(all_models_end_dates[0] - all_models_end_dates[1])
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all_models_end_dates.append(finish_timestamp)
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all_models_end_dates.sort()
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start_date = (datetime(*datetime.fromtimestamp(min(all_models_end_dates),
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timezone.utc).timetuple()[:3], tzinfo=timezone.utc))
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end_date = (datetime(*datetime.fromtimestamp(max(all_models_end_dates),
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timezone.utc).timetuple()[:3], tzinfo=timezone.utc))
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# add 1 day to string timerange to ensure BT module will load all dataframe data
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end_date = end_date + timedelta(days=1)
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backtesting_timerange = TimeRange(
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'date', 'date', int(start_date.timestamp()), int(end_date.timestamp())
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)
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return backtesting_timerange, assets_end_dates
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def get_assets_timestamps_training_from_ready_models(models_path: Path) -> Dict[str, Any]:
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"""
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Scan the models path and returns all assets end training dates (timestamp)
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:param models_path: FreqAI model path
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:return: a Dict with asset and model end training dates info
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"""
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assets_end_dates: Dict[str, Any] = {}
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if not models_path.is_dir():
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raise OperationalException(
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'Model folders not found. Saved models are required '
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'to run backtest with the freqai-backtest-live-models option'
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)
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for model_dir in models_path.iterdir():
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if str(model_dir.name).startswith("sub-train"):
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model_end_date = int(model_dir.name.split("_")[1])
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asset = model_dir.name.split("_")[0].replace("sub-train-", "")
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model_file_name = (
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f"cb_{str(model_dir.name).replace('sub-train-', '').lower()}"
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"_model.joblib"
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)
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model_path_file = Path(model_dir / model_file_name)
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if model_path_file.is_file():
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if asset not in assets_end_dates:
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assets_end_dates[asset] = []
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assets_end_dates[asset].append(model_end_date)
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return assets_end_dates
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def get_timerange_backtest_live_models(config: Config):
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"""
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Returns a formated timerange for backtest live/ready models
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:param config: Configuration dictionary
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:return: a string timerange (format example: '20220801-20220822')
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"""
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models_path = get_full_models_path(config)
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timerange, _ = get_timerange_and_assets_end_dates_from_ready_models(models_path)
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start_date = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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end_date = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
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tr = f"{start_date.strftime('%Y%m%d')}-{end_date.strftime('%Y%m%d')}"
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return tr
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@ -191,3 +191,19 @@ def plot_feature_importance(model: Any, pair: str, dk: FreqaiDataKitchen,
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fig.update_layout(title_text=f"Best and worst features by importance {pair}")
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label = label.replace('&', '').replace('%', '') # escape two FreqAI specific characters
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store_plot_file(fig, f"{dk.model_filename}-{label}.html", dk.data_path)
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def get_timerange_backtest_live_models(config: Config):
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"""
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Returns a formated timerange for backtest live/ready models
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:param config: Configuration dictionary
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:return: a string timerange (format example: '20220801-20220822')
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"""
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dk = FreqaiDataKitchen(config)
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models_path = dk.get_full_models_path(config)
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timerange, _ = dk.get_timerange_and_assets_end_dates_from_ready_models(models_path)
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start_date = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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end_date = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
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tr = f"{start_date.strftime('%Y%m%d')}-{end_date.strftime('%Y%m%d')}"
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return tr
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@ -135,8 +135,8 @@ class Backtesting:
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self.precision_mode = self.exchange.precisionMode
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if self.config.get('freqai_backtest_live_models', False):
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from freqtrade.freqai import freqai_util
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self.config['timerange'] = freqai_util.get_timerange_backtest_live_models(self.config)
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from freqtrade.freqai import utils
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self.config['timerange'] = utils.get_timerange_backtest_live_models(self.config)
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self.timerange = TimeRange.parse_timerange(
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None if self.config.get('timerange') is None else str(self.config.get('timerange')))
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@ -1,13 +1,18 @@
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import shutil
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from datetime import datetime, timedelta, timezone
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from pathlib import Path
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from unittest.mock import MagicMock
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import pytest
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from freqtrade.configuration import TimeRange
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.exceptions import OperationalException
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from tests.conftest import log_has_re
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from tests.freqai.conftest import (get_patched_data_kitchen, make_data_dictionary,
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make_unfiltered_dataframe)
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from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
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from freqtrade.freqai.utils import get_timerange_backtest_live_models
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from tests.conftest import get_patched_exchange, log_has_re
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from tests.freqai.conftest import (get_patched_data_kitchen, get_patched_freqai_strategy,
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make_data_dictionary, make_unfiltered_dataframe)
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@pytest.mark.parametrize(
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@ -158,3 +163,98 @@ def test_make_train_test_datasets(mocker, freqai_conf):
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assert data_dictionary
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assert len(data_dictionary) == 7
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assert len(data_dictionary['train_features'].index) == 1916
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def test_get_pairs_timestamp_validation(mocker, freqai_conf):
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exchange = get_patched_exchange(mocker, freqai_conf)
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strategy = get_patched_freqai_strategy(mocker, freqai_conf)
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strategy.dp = DataProvider(freqai_conf, exchange)
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strategy.freqai_info = freqai_conf.get("freqai", {})
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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freqai_conf['freqai'].update({"identifier": "invalid_id"})
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model_path = freqai.dk.get_full_models_path(freqai_conf)
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with pytest.raises(
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OperationalException,
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match=r'.*required to run backtest with the freqai-backtest-live-models.*'
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):
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freqai.dk.get_assets_timestamps_training_from_ready_models(model_path)
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@pytest.mark.parametrize('model', [
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'LightGBMRegressor'
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])
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def test_get_timerange_from_ready_models(mocker, freqai_conf, model):
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freqai_conf.update({"freqaimodel": model})
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freqai_conf.update({"timerange": "20180110-20180130"})
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freqai_conf.update({"strategy": "freqai_test_strat"})
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strategy = get_patched_freqai_strategy(mocker, freqai_conf)
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exchange = get_patched_exchange(mocker, freqai_conf)
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strategy.dp = DataProvider(freqai_conf, exchange)
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strategy.freqai_info = freqai_conf.get("freqai", {})
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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timerange = TimeRange.parse_timerange("20180101-20180130")
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freqai.dd.load_all_pair_histories(timerange, freqai.dk)
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freqai.dd.pair_dict = MagicMock()
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data_load_timerange = TimeRange.parse_timerange("20180101-20180130")
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# 1516233600 (2018-01-18 00:00) - Start Training 1
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# 1516406400 (2018-01-20 00:00) - End Training 1 (Backtest slice 1)
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# 1516579200 (2018-01-22 00:00) - End Training 2 (Backtest slice 2)
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# 1516838400 (2018-01-25 00:00) - End Timerange
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new_timerange = TimeRange("date", "date", 1516233600, 1516406400)
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freqai.extract_data_and_train_model(
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new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
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new_timerange = TimeRange("date", "date", 1516406400, 1516579200)
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freqai.extract_data_and_train_model(
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new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
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model_path = freqai.dk.get_full_models_path(freqai_conf)
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(backtesting_timerange,
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pairs_end_dates) = freqai.dk.get_timerange_and_assets_end_dates_from_ready_models(
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models_path=model_path)
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assert len(pairs_end_dates["ADA"]) == 2
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assert backtesting_timerange.startts == 1516406400
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assert backtesting_timerange.stopts == 1516838400
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backtesting_string_timerange = get_timerange_backtest_live_models(freqai_conf)
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assert backtesting_string_timerange == '20180120-20180125'
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@pytest.mark.parametrize('model', [
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'LightGBMRegressor'
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])
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def test_get_full_model_path(mocker, freqai_conf, model):
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freqai_conf.update({"freqaimodel": model})
|
||||
freqai_conf.update({"timerange": "20180110-20180130"})
|
||||
freqai_conf.update({"strategy": "freqai_test_strat"})
|
||||
|
||||
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
||||
exchange = get_patched_exchange(mocker, freqai_conf)
|
||||
strategy.dp = DataProvider(freqai_conf, exchange)
|
||||
strategy.freqai_info = freqai_conf.get("freqai", {})
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
freqai.dd.pair_dict = MagicMock()
|
||||
|
||||
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
new_timerange = TimeRange.parse_timerange("20180120-20180130")
|
||||
|
||||
freqai.extract_data_and_train_model(
|
||||
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
|
||||
|
||||
model_path = freqai.dk.get_full_models_path(freqai_conf)
|
||||
assert model_path.is_dir() is True
|
||||
|
||||
@ -1,112 +0,0 @@
|
||||
import platform
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
from freqtrade.configuration import TimeRange
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
|
||||
from freqtrade.freqai.freqai_util import (get_assets_timestamps_training_from_ready_models,
|
||||
get_full_models_path,
|
||||
get_timerange_and_assets_end_dates_from_ready_models,
|
||||
get_timerange_backtest_live_models)
|
||||
from tests.conftest import get_patched_exchange
|
||||
from tests.freqai.conftest import get_patched_freqai_strategy
|
||||
|
||||
|
||||
def is_arm() -> bool:
|
||||
machine = platform.machine()
|
||||
return "arm" in machine or "aarch64" in machine
|
||||
|
||||
|
||||
@pytest.mark.parametrize('model', [
|
||||
'LightGBMRegressor'
|
||||
])
|
||||
def test_get_full_model_path(mocker, freqai_conf, model):
|
||||
if is_arm() and model == 'CatboostRegressor':
|
||||
pytest.skip("CatBoost is not supported on ARM")
|
||||
|
||||
freqai_conf.update({"freqaimodel": model})
|
||||
freqai_conf.update({"timerange": "20180110-20180130"})
|
||||
freqai_conf.update({"strategy": "freqai_test_strat"})
|
||||
|
||||
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
||||
exchange = get_patched_exchange(mocker, freqai_conf)
|
||||
strategy.dp = DataProvider(freqai_conf, exchange)
|
||||
strategy.freqai_info = freqai_conf.get("freqai", {})
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
freqai.dd.pair_dict = MagicMock()
|
||||
|
||||
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
new_timerange = TimeRange.parse_timerange("20180120-20180130")
|
||||
|
||||
freqai.extract_data_and_train_model(
|
||||
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
|
||||
|
||||
model_path = get_full_models_path(freqai_conf)
|
||||
assert model_path.is_dir() is True
|
||||
|
||||
|
||||
def test_get_pairs_timestamp_validation(mocker, freqai_conf):
|
||||
model_path = get_full_models_path(freqai_conf)
|
||||
with pytest.raises(
|
||||
OperationalException,
|
||||
match=r'.*required to run backtest with the freqai-backtest-live-models.*'
|
||||
):
|
||||
get_assets_timestamps_training_from_ready_models(model_path)
|
||||
|
||||
|
||||
@pytest.mark.parametrize('model', [
|
||||
'LightGBMRegressor'
|
||||
])
|
||||
def test_get_timerange_from_ready_models(mocker, freqai_conf, model):
|
||||
if is_arm() and model == 'CatboostRegressor':
|
||||
pytest.skip("CatBoost is not supported on ARM")
|
||||
|
||||
freqai_conf.update({"freqaimodel": model})
|
||||
freqai_conf.update({"timerange": "20180110-20180130"})
|
||||
freqai_conf.update({"strategy": "freqai_test_strat"})
|
||||
|
||||
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
||||
exchange = get_patched_exchange(mocker, freqai_conf)
|
||||
strategy.dp = DataProvider(freqai_conf, exchange)
|
||||
strategy.freqai_info = freqai_conf.get("freqai", {})
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
timerange = TimeRange.parse_timerange("20180101-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
freqai.dd.pair_dict = MagicMock()
|
||||
|
||||
data_load_timerange = TimeRange.parse_timerange("20180101-20180130")
|
||||
|
||||
# 1516233600 (2018-01-18 00:00) - Start Training 1
|
||||
# 1516406400 (2018-01-20 00:00) - End Training 1 (Backtest slice 1)
|
||||
# 1516579200 (2018-01-22 00:00) - End Training 2 (Backtest slice 2)
|
||||
# 1516838400 (2018-01-25 00:00) - End Timerange
|
||||
|
||||
new_timerange = TimeRange("date", "date", 1516233600, 1516406400)
|
||||
freqai.extract_data_and_train_model(
|
||||
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
|
||||
|
||||
new_timerange = TimeRange("date", "date", 1516406400, 1516579200)
|
||||
freqai.extract_data_and_train_model(
|
||||
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
|
||||
|
||||
model_path = get_full_models_path(freqai_conf)
|
||||
(backtesting_timerange,
|
||||
pairs_end_dates) = get_timerange_and_assets_end_dates_from_ready_models(models_path=model_path)
|
||||
|
||||
assert len(pairs_end_dates["ADA"]) == 2
|
||||
assert backtesting_timerange.startts == 1516406400
|
||||
assert backtesting_timerange.stopts == 1516838400
|
||||
|
||||
backtesting_string_timerange = get_timerange_backtest_live_models(freqai_conf)
|
||||
assert backtesting_string_timerange == '20180120-20180125'
|
||||
Loading…
Reference in New Issue
Block a user