backtest_live_models - refactoring after PR review
This commit is contained in:
Wagner Costa Santos
parent
df0927cdee
commit
6845a5c6ea
@ -671,7 +671,6 @@ AVAILABLE_CLI_OPTIONS = {
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"freqai_backtest_live_models": Arg(
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'--freqai-backtest-live-models',
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help='Run backtest with ready models.',
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action='store_true',
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default=False,
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action='store_true'
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),
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}
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@ -84,7 +84,7 @@ 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_model_path(self.config)
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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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@ -118,7 +118,7 @@ class FreqaiDataKitchen:
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metadata: dict = strategy furnished pair metadata
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trained_timestamp: int = timestamp of most recent training
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"""
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self.full_path = freqai_util.get_full_model_path(self.config)
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self.full_path = freqai_util.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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@ -459,17 +459,15 @@ class FreqaiDataKitchen:
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) -> Tuple[list, list]:
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tr_backtesting_list_timerange = []
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pair = self.pair.split("/")[0].split(":")[0]
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if pair not in self.backtest_live_models_data["pairs_end_dates"]:
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asset = self.pair.split("/")[0]
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if asset not in self.backtest_live_models_data["assets_end_dates"]:
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raise OperationalException(
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f"Model not available for pair {self.pair}. "
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"Please, try again after removing this pair from the configuration file."
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)
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pair_data = self.backtest_live_models_data["pairs_end_dates"][pair]
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model_end_dates = []
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asset_data = self.backtest_live_models_data["assets_end_dates"][asset]
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backtesting_timerange = self.backtest_live_models_data["backtesting_timerange"]
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for end_date in pair_data:
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model_end_dates.append(end_date)
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model_end_dates = [x for x in asset_data]
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model_end_dates.append(backtesting_timerange.stopts)
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model_end_dates.sort()
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for index, item in enumerate(model_end_dates):
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@ -1291,11 +1289,11 @@ class FreqaiDataKitchen:
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def set_timerange_from_ready_models(self):
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backtesting_timerange, \
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backtesting_string_timerange, \
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pairs_end_dates = freqai_util.get_timerange_from_ready_models(self.full_path)
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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.backtest_live_models_data = {
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"backtesting_timerange": backtesting_timerange,
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"backtesting_string_timerange": backtesting_string_timerange,
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"pairs_end_dates": pairs_end_dates
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"assets_end_dates": assets_end_dates
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}
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return
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@ -264,12 +264,9 @@ class IFreqaiModel(ABC):
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tr_backtest_stopts_str = datetime.fromtimestamp(
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tr_backtest.stopts,
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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logger.info(
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f"No data found for pair {pair} "
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f" from {tr_backtest_startts_str} "
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f"to {tr_backtest_stopts_str}. "
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"Probably more than one training within the same candle period."
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)
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logger.info(f"No data found for pair {pair} from {tr_backtest_startts_str} "
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f" from {tr_backtest_startts_str} to {tr_backtest_stopts_str}. "
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"Probably more than one training within the same candle period.")
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continue
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trained_timestamp = tr_train
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@ -305,12 +302,6 @@ class IFreqaiModel(ABC):
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dk.append_predictions(append_df)
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else:
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if not self.model_exists(dk):
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if dk.backtest_live_models:
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raise OperationalException(
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"Training models is not allowed "
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"in backtest_live_models backtesting "
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"mode"
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)
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dk.find_features(dataframe_train)
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dk.find_labels(dataframe_train)
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self.model = self.train(dataframe_train, pair, dk)
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@ -603,7 +594,7 @@ class IFreqaiModel(ABC):
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model = self.train(unfiltered_dataframe, pair, dk)
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self.dd.pair_dict[pair]["trained_timestamp"] = new_trained_timerange.stopts
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dk.set_new_model_names(pair, int(new_trained_timerange.stopts))
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dk.set_new_model_names(pair, new_trained_timerange.stopts)
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self.dd.save_data(model, pair, dk)
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if self.plot_features:
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@ -14,7 +14,7 @@ from freqtrade.exceptions import OperationalException
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logger = logging.getLogger(__name__)
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def get_full_model_path(config: Config) -> Path:
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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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@ -25,20 +25,19 @@ def get_full_model_path(config: Config) -> Path:
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)
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def get_timerange_from_ready_models(models_path: Path) -> Tuple[TimeRange, str, Dict[str, Any]]:
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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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:returns: a Tuple with (backtesting_timerange: Timerange calculated from directory,
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backtesting_string_timerange: str timerange calculated from
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directory (format example '20020822-20220830'), \
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pairs_end_dates: Dict with pair and model end training dates info)
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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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pairs_end_dates: Dict[str, Any] = get_pairs_timestamps_training_from_ready_models(models_path)
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for key in pairs_end_dates:
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for model_end_date in pairs_end_dates[key]:
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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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@ -64,34 +63,27 @@ def get_timerange_from_ready_models(models_path: Path) -> Tuple[TimeRange, str,
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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 = datetime.fromtimestamp(min(all_models_end_dates), tz=timezone.utc)
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stop = datetime.fromtimestamp(max(all_models_end_dates), tz=timezone.utc)
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end_date_string_timerange = stop
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if (
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finish_timestamp < int(datetime.now(tz=timezone.utc).timestamp()) and
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datetime.now(tz=timezone.utc).strftime('%Y%m%d') != stop.strftime('%Y%m%d')
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):
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start_date = (datetime(*datetime.fromtimestamp(min(all_models_end_dates)).timetuple()[:3],
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tzinfo=timezone.utc))
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end_date = (datetime(*datetime.fromtimestamp(max(all_models_end_dates)).timetuple()[:3],
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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_string_timerange = stop + timedelta(days=1)
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backtesting_string_timerange = (
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f"{start.strftime('%Y%m%d')}-{end_date_string_timerange.strftime('%Y%m%d')}"
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)
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end_date = end_date + timedelta(days=1)
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backtesting_timerange = TimeRange(
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'date', 'date', min(all_models_end_dates), max(all_models_end_dates)
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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, backtesting_string_timerange, pairs_end_dates
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return backtesting_timerange, assets_end_dates
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def get_pairs_timestamps_training_from_ready_models(models_path: Path) -> Dict[str, Any]:
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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 pairs end training dates (timestamp)
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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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:returns:
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:pairs_end_dates: Dict with pair and model end training dates info
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:return: a Dict with asset and model end training dates info
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"""
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pairs_end_dates: Dict[str, Any] = {}
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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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@ -100,7 +92,7 @@ def get_pairs_timestamps_training_from_ready_models(models_path: Path) -> Dict[s
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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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pair = model_dir.name.split("_")[0].replace("sub-train-", "")
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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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@ -108,8 +100,23 @@ def get_pairs_timestamps_training_from_ready_models(models_path: Path) -> Dict[s
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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 pair not in pairs_end_dates:
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pairs_end_dates[pair] = []
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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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pairs_end_dates[pair].append(model_end_date)
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return pairs_end_dates
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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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@ -25,7 +25,6 @@ from freqtrade.enums import (BacktestState, CandleType, ExitCheckTuple, ExitType
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from freqtrade.exceptions import DependencyException, OperationalException
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from freqtrade.exchange import (amount_to_contract_precision, price_to_precision,
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timeframe_to_minutes, timeframe_to_seconds)
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from freqtrade.freqai import freqai_util
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from freqtrade.mixins import LoggingMixin
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from freqtrade.optimize.backtest_caching import get_strategy_run_id
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from freqtrade.optimize.bt_progress import BTProgress
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@ -136,10 +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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freqai_model_path = freqai_util.get_full_model_path(self.config)
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_, live_models_timerange, _ = freqai_util.get_timerange_from_ready_models(
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freqai_model_path)
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self.config['timerange'] = live_models_timerange
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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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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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@ -7,9 +7,10 @@ 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 freqtrade.freqai.data_kitchen import FreqaiDataKitchen
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from freqtrade.freqai.freqai_util import (get_full_model_path,
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get_pairs_timestamps_training_from_ready_models,
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get_timerange_from_ready_models)
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from freqtrade.freqai.freqai_util import (get_assets_timestamps_training_from_ready_models,
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get_full_models_path,
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get_timerange_and_assets_end_dates_from_ready_models,
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get_timerange_backtest_live_models)
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from tests.conftest import get_patched_exchange
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from tests.freqai.conftest import get_patched_freqai_strategy
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@ -48,17 +49,17 @@ def test_get_full_model_path(mocker, freqai_conf, model):
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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 = get_full_model_path(freqai_conf)
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model_path = get_full_models_path(freqai_conf)
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assert model_path.is_dir() is True
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def test_get_pairs_timestamp_validation(mocker, freqai_conf):
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model_path = get_full_model_path(freqai_conf)
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model_path = 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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get_pairs_timestamps_training_from_ready_models(model_path)
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get_assets_timestamps_training_from_ready_models(model_path)
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@pytest.mark.parametrize('model', [
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@ -94,12 +95,13 @@ def test_get_timerange_from_ready_models(mocker, freqai_conf, model):
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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 = get_full_model_path(freqai_conf)
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model_path = get_full_models_path(freqai_conf)
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(backtesting_timerange,
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backtesting_string_timerange,
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pairs_end_dates) = get_timerange_from_ready_models(models_path=model_path)
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pairs_end_dates) = get_timerange_and_assets_end_dates_from_ready_models(models_path=model_path)
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assert len(pairs_end_dates["ADA"]) == 2
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assert backtesting_string_timerange == '20180122-20180127'
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assert backtesting_timerange.startts == 1516579200
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assert backtesting_timerange.startts == 1516492800
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assert backtesting_timerange.stopts == 1516924800
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backtesting_string_timerange = get_timerange_backtest_live_models(freqai_conf)
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assert backtesting_string_timerange == '20180121-20180126'
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