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chore: update tests to modern typing syntax

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This commit is contained in:
Matthias
2024-10-04 07:09:51 +02:00
parent 628983d123
commit 2e0a597ee4
10 changed files with 32 additions and 40 deletions
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tests/strategy/strats/freqai_rl_test_strat.py
+4 -5
View File
@@ -1,6 +1,5 @@
import logging
from functools import reduce
from typing import Dict
import talib.abstract as ta
from pandas import DataFrame
@@ -26,19 +25,19 @@ class freqai_rl_test_strat(IStrategy):
can_short = False
def feature_engineering_expand_all(
self, dataframe: DataFrame, period: int, metadata: Dict, **kwargs
self, dataframe: DataFrame, period: int, metadata: dict, **kwargs
):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"]
return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
@@ -49,7 +48,7 @@ class freqai_rl_test_strat(IStrategy):
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["&-action"] = 0
return dataframe
tests/strategy/strats/freqai_test_classifier.py
+4 -5
View File
@@ -1,6 +1,5 @@
import logging
from functools import reduce
from typing import Dict
import numpy as np
import talib.abstract as ta
@@ -58,7 +57,7 @@ class freqai_test_classifier(IStrategy):
return informative_pairs
def feature_engineering_expand_all(
self, dataframe: DataFrame, period: int, metadata: Dict, **kwargs
self, dataframe: DataFrame, period: int, metadata: dict, **kwargs
):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@@ -66,20 +65,20 @@ class freqai_test_classifier(IStrategy):
return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"]
dataframe["%-raw_price"] = dataframe["close"]
return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs):
self.freqai.class_names = ["down", "up"]
dataframe["&s-up_or_down"] = np.where(
dataframe["close"].shift(-100) > dataframe["close"], "up", "down"
tests/strategy/strats/freqai_test_multimodel_classifier_strat.py
+4 -5
View File
@@ -1,6 +1,5 @@
import logging
from functools import reduce
from typing import Dict
import numpy as np
import talib.abstract as ta
@@ -45,7 +44,7 @@ class freqai_test_multimodel_classifier_strat(IStrategy):
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(
self, dataframe: DataFrame, period: int, metadata: Dict, **kwargs
self, dataframe: DataFrame, period: int, metadata: dict, **kwargs
):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@@ -53,20 +52,20 @@ class freqai_test_multimodel_classifier_strat(IStrategy):
return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"]
dataframe["%-raw_price"] = dataframe["close"]
return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["&s-up_or_down"] = np.where(
dataframe["close"].shift(-50) > dataframe["close"], "up", "down"
)
tests/strategy/strats/freqai_test_multimodel_strat.py
+4 -5
View File
@@ -1,6 +1,5 @@
import logging
from functools import reduce
from typing import Dict
import talib.abstract as ta
from pandas import DataFrame
@@ -44,7 +43,7 @@ class freqai_test_multimodel_strat(IStrategy):
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(
self, dataframe: DataFrame, period: int, metadata: Dict, **kwargs
self, dataframe: DataFrame, period: int, metadata: dict, **kwargs
):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@@ -52,20 +51,20 @@ class freqai_test_multimodel_strat(IStrategy):
return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"]
dataframe["%-raw_price"] = dataframe["close"]
return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["&-s_close"] = (
dataframe["close"]
.shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
tests/strategy/strats/freqai_test_strat.py
+4 -5
View File
@@ -1,6 +1,5 @@
import logging
from functools import reduce
from typing import Dict
import talib.abstract as ta
from pandas import DataFrame
@@ -44,7 +43,7 @@ class freqai_test_strat(IStrategy):
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def feature_engineering_expand_all(
self, dataframe: DataFrame, period: int, metadata: Dict, **kwargs
self, dataframe: DataFrame, period: int, metadata: dict, **kwargs
):
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
@@ -52,20 +51,20 @@ class freqai_test_strat(IStrategy):
return dataframe
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-pct-change"] = dataframe["close"].pct_change()
dataframe["%-raw_volume"] = dataframe["volume"]
dataframe["%-raw_price"] = dataframe["close"]
return dataframe
def feature_engineering_standard(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs):
dataframe["&-s_close"] = (
dataframe["close"]
.shift(-self.freqai_info["feature_parameters"]["label_period_candles"])