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Update function signatures in all templates

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add typehints to help the user's editor suggest the right things.
This commit is contained in:
Matthias 2023-02-04 20:04:16 +01:00
parent 0dd2472385
commit 801714a588
8 changed files with 67 additions and 45 deletions
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18
freqtrade/strategy/interface.py
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@ -614,8 +614,8 @@ class IStrategy(ABC, HyperStrategyMixin):
""" """
return df return df
def feature_engineering_expand_all(self, dataframe: DataFrame, def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
period: int, **kwargs): metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -634,14 +634,14 @@ class IStrategy(ABC, HyperStrategyMixin):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param period: period of the indicator - usage example: :param period: period of the indicator - usage example:
:param metadata: metadata of current pair :param metadata: metadata of current pair
dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period) dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
""" """
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -663,14 +663,14 @@ class IStrategy(ABC, HyperStrategyMixin):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair :param metadata: metadata of current pair
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200) dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200)
""" """
return dataframe return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This optional function will be called once with the dataframe of the base timeframe. This optional function will be called once with the dataframe of the base timeframe.
@ -688,13 +688,13 @@ class IStrategy(ABC, HyperStrategyMixin):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair :param metadata: metadata of current pair
usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7 usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7
""" """
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
Required function to set the targets for the model. Required function to set the targets for the model.
@ -704,7 +704,7 @@ class IStrategy(ABC, HyperStrategyMixin):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the targets :param dataframe: strategy dataframe which will receive the targets
:param metadata: metadata of current pair :param metadata: metadata of current pair
usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"] usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"]
""" """

22
freqtrade/templates/FreqaiExampleHybridStrategy.py
View File

@ -1,4 +1,5 @@
import logging import logging
from typing import Dict
import numpy as np import numpy as np
import pandas as pd import pandas as pd
@ -95,7 +96,8 @@ class FreqaiExampleHybridStrategy(IStrategy):
short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True) short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True)
exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -114,8 +116,9 @@ class FreqaiExampleHybridStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param period: period of the indicator - usage example: :param period: period of the indicator - usage example:
:param metadata: metadata of current pair
dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period) dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
""" """
@ -148,7 +151,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -170,7 +173,8 @@ class FreqaiExampleHybridStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200) dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200)
""" """
@ -179,7 +183,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
dataframe["%-raw_price"] = dataframe["close"] dataframe["%-raw_price"] = dataframe["close"]
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This optional function will be called once with the dataframe of the base timeframe. This optional function will be called once with the dataframe of the base timeframe.
@ -197,14 +201,15 @@ class FreqaiExampleHybridStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair
usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7 usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7
""" """
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
Required function to set the targets for the model. Required function to set the targets for the model.
@ -214,7 +219,8 @@ class FreqaiExampleHybridStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the targets :param dataframe: strategy dataframe which will receive the targets
:param metadata: metadata of current pair
usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"] usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"]
""" """
dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-50) > dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-50) >

22
freqtrade/templates/FreqaiExampleStrategy.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
@ -46,7 +47,8 @@ class FreqaiExampleStrategy(IStrategy):
std_dev_multiplier_sell = CategoricalParameter( std_dev_multiplier_sell = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], space="sell", default=1.25, optimize=True) [0.75, 1, 1.25, 1.5, 1.75], space="sell", default=1.25, optimize=True)
def feature_engineering_expand_all(self, dataframe, period, metadata, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -69,8 +71,9 @@ class FreqaiExampleStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param period: period of the indicator - usage example: :param period: period of the indicator - usage example:
:param metadata: metadata of current pair
dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period) dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
""" """
@ -103,7 +106,7 @@ class FreqaiExampleStrategy(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe, metadata, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined This function will automatically expand the defined features on the config defined
@ -129,7 +132,8 @@ class FreqaiExampleStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features https://www.freqtrade.io/en/latest/freqai-feature-engineering/#defining-the-features
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200) dataframe["%-ema-200"] = ta.EMA(dataframe, timeperiod=200)
""" """
@ -138,7 +142,7 @@ class FreqaiExampleStrategy(IStrategy):
dataframe["%-raw_price"] = dataframe["close"] dataframe["%-raw_price"] = dataframe["close"]
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, metadata, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
This optional function will be called once with the dataframe of the base timeframe. This optional function will be called once with the dataframe of the base timeframe.
@ -160,14 +164,15 @@ class FreqaiExampleStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the features :param dataframe: strategy dataframe which will receive the features
:param metadata: metadata of current pair
usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7 usage example: dataframe["%-day_of_week"] = (dataframe["date"].dt.dayofweek + 1) / 7
""" """
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, metadata, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
""" """
*Only functional with FreqAI enabled strategies* *Only functional with FreqAI enabled strategies*
Required function to set the targets for the model. Required function to set the targets for the model.
@ -181,7 +186,8 @@ class FreqaiExampleStrategy(IStrategy):
https://www.freqtrade.io/en/latest/freqai-feature-engineering https://www.freqtrade.io/en/latest/freqai-feature-engineering
:param df: strategy dataframe which will receive the targets :param dataframe: strategy dataframe which will receive the targets
:param metadata: metadata of current pair
usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"] usage example: dataframe["&-target"] = dataframe["close"].shift(-1) / dataframe["close"]
""" """
dataframe["&-s_close"] = ( dataframe["&-s_close"] = (

10
tests/strategy/strats/freqai_rl_test_strat.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
@ -24,20 +25,21 @@ class freqai_rl_test_strat(IStrategy):
startup_candle_count: int = 300 startup_candle_count: int = 300
can_short = False can_short = False
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period) dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"] dataframe["%-raw_volume"] = dataframe["volume"]
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
@ -49,7 +51,7 @@ class freqai_rl_test_strat(IStrategy):
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["&-action"] = 0 dataframe["&-action"] = 0

10
tests/strategy/strats/freqai_test_classifier.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import numpy as np import numpy as np
import talib.abstract as ta import talib.abstract as ta
@ -56,7 +57,8 @@ class freqai_test_classifier(IStrategy):
informative_pairs.append((pair, tf)) informative_pairs.append((pair, tf))
return informative_pairs return informative_pairs
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period) dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period) dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@ -64,7 +66,7 @@ class freqai_test_classifier(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"] dataframe["%-raw_volume"] = dataframe["volume"]
@ -72,14 +74,14 @@ class freqai_test_classifier(IStrategy):
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-100) > dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-100) >
dataframe["close"], 'up', 'down') dataframe["close"], 'up', 'down')

10
tests/strategy/strats/freqai_test_multimodel_classifier_strat.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import numpy as np import numpy as np
import talib.abstract as ta import talib.abstract as ta
@ -43,7 +44,8 @@ class freqai_test_multimodel_classifier_strat(IStrategy):
) )
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period) dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period) dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@ -51,7 +53,7 @@ class freqai_test_multimodel_classifier_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"] dataframe["%-raw_volume"] = dataframe["volume"]
@ -59,14 +61,14 @@ class freqai_test_multimodel_classifier_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-50) > dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-50) >
dataframe["close"], 'up', 'down') dataframe["close"], 'up', 'down')

10
tests/strategy/strats/freqai_test_multimodel_strat.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
@ -42,7 +43,8 @@ class freqai_test_multimodel_strat(IStrategy):
) )
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period) dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period) dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@ -50,7 +52,7 @@ class freqai_test_multimodel_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"] dataframe["%-raw_volume"] = dataframe["volume"]
@ -58,14 +60,14 @@ class freqai_test_multimodel_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["&-s_close"] = ( dataframe["&-s_close"] = (
dataframe["close"] dataframe["close"]

10
tests/strategy/strats/freqai_test_strat.py
View File

@ -1,5 +1,6 @@
import logging import logging
from functools import reduce from functools import reduce
from typing import Dict
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
@ -42,7 +43,8 @@ class freqai_test_strat(IStrategy):
) )
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(self, dataframe, period, **kwargs): def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period) dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period) dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@ -50,7 +52,7 @@ class freqai_test_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, **kwargs): def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change() dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"] dataframe["%-raw_volume"] = dataframe["volume"]
@ -58,14 +60,14 @@ class freqai_test_strat(IStrategy):
return dataframe return dataframe
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe return dataframe
def set_freqai_targets(self, dataframe, **kwargs): def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
dataframe["&-s_close"] = ( dataframe["&-s_close"] = (
dataframe["close"] dataframe["close"]