ensure pytest passes
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freqtrade/freqai/spice_rack/test_config.json
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30
freqtrade/freqai/spice_rack/test_config.json
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{
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"freqai": {
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"enabled": true,
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"purge_old_models": true,
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"train_period_days": 4,
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"backtest_period_days": 2,
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"identifier": "spicy-id",
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"feature_parameters": {
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"include_timeframes": [
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"5m"
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],
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"include_corr_pairlist": ["ADA/BTC", "DASH/BTC"],
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"label_period_candles": 20,
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"include_shifted_candles": 1,
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"DI_threshold": 0.9,
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"weight_factor": 0.9,
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"indicator_periods_candles": [
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10
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]
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},
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"data_split_parameters": {
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"test_size": 0,
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"random_state": 1
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},
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"model_training_parameters": {
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"n_estimators": 800
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}
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}
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}
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115
tests/strategy/strats/freqai_test_spice_rack.py
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tests/strategy/strats/freqai_test_spice_rack.py
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import logging
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from functools import reduce
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import pandas as pd
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import talib.abstract as ta
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from pandas import DataFrame
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from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, merge_informative_pair
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logger = logging.getLogger(__name__)
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class freqai_test_spice_rack(IStrategy):
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"""
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Test strategy - used for testing freqAI functionalities.
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DO not use in production.
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"""
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minimal_roi = {"0": 0.1, "240": -1}
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plot_config = {
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"main_plot": {},
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"subplots": {
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"prediction": {"prediction": {"color": "blue"}},
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"target_roi": {
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"target_roi": {"color": "brown"},
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},
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"do_predict": {
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"do_predict": {"color": "brown"},
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},
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},
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}
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process_only_new_candles = True
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stoploss = -0.05
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use_exit_signal = True
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startup_candle_count: int = 300
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can_short = False
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linear_roi_offset = DecimalParameter(
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0.00, 0.02, default=0.005, space="sell", optimize=False, load=True
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)
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max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
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def informative_pairs(self):
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whitelist_pairs = self.dp.current_whitelist()
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corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
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informative_pairs = []
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for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
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for pair in whitelist_pairs:
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informative_pairs.append((pair, tf))
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for pair in corr_pairs:
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if pair in whitelist_pairs:
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continue # avoid duplication
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informative_pairs.append((pair, tf))
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return informative_pairs
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# Example of how to use the freqai.spice_rack. User treats it the same as any
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# typical talib indicator. They set a new column in their dataframe
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dataframe['dissimilarity_index'] = self.freqai.spice_rack(
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'DI_values', dataframe, metadata, self)
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dataframe['maxima'] = self.freqai.spice_rack(
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'&s-maxima', dataframe, metadata, self)
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dataframe['minima'] = self.freqai.spice_rack(
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'&s-minima', dataframe, metadata, self)
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self.freqai.close_spice_rack() # user must close the spicerack
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dataframe['rsi'] = ta.RSI(dataframe)
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return dataframe
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def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
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df.loc[
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(
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(df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising
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(df['dissimilarity_index'] < 1) &
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(df['maxima'] > 0.1)
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),
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'enter_long'] = 1
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df.loc[
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(
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(df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling
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(df['dissimilarity_index'] < 1) &
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(df['minima'] > 0.1)
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),
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'enter_short'] = 1
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return df
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def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
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df.loc[
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(
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(df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling
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(df['dissimilarity_index'] < 1) &
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(df['maxima'] > 0.1)
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),
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'exit_long'] = 1
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df.loc[
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(
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(df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising
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(df['dissimilarity_index'] < 1) &
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(df['minima'] > 0.1)
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),
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'exit_short'] = 1
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return df
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@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed():
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directory = Path(__file__).parent / "strats"
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strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
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assert isinstance(strategies, list)
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assert len(strategies) == 9
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assert len(strategies) == 10
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assert isinstance(strategies[0], dict)
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@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed():
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directory = Path(__file__).parent / "strats"
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strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
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assert isinstance(strategies, list)
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assert len(strategies) == 10
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assert len(strategies) == 11
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# with enum_failed=True search_all_objects() shall find 2 good strategies
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# and 1 which fails to load
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assert len([x for x in strategies if x['class'] is not None]) == 9
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assert len([x for x in strategies if x['class'] is not None]) == 10
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assert len([x for x in strategies if x['class'] is None]) == 1
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directory = Path(__file__).parent / "strats_nonexistingdir"
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