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chore: Further reduce mutable default usage

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This commit is contained in:
Matthias 2024-05-05 19:42:03 +02:00
parent 6b889814ad
commit aa81c75bef
2 changed files with 10 additions and 6 deletions
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8
freqtrade/freqai/data_kitchen.py
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@ -214,7 +214,7 @@ class FreqaiDataKitchen:
self,
unfiltered_df: DataFrame,
training_feature_list: List,
label_list: List = list(),
label_list: Optional[List] = None,
training_filter: bool = True,
) -> Tuple[DataFrame, DataFrame]:
"""
@ -244,7 +244,7 @@ class FreqaiDataKitchen:
# we don't care about total row number (total no. datapoints) in training, we only care
# about removing any row with NaNs
# if labels has multiple columns (user wants to train multiple modelEs), we detect here
labels = unfiltered_df.filter(label_list, axis=1)
labels = unfiltered_df.filter(label_list or [], axis=1)
drop_index_labels = pd.isnull(labels).any(axis=1)
drop_index_labels = (
drop_index_labels.replace(True, 1).replace(False, 0).infer_objects(copy=False)
@ -654,8 +654,8 @@ class FreqaiDataKitchen:
pair: str,
tf: str,
strategy: IStrategy,
corr_dataframes: dict = {},
base_dataframes: dict = {},
corr_dataframes: dict,
base_dataframes: dict,
is_corr_pairs: bool = False,
) -> DataFrame:
"""

8
tests/freqai/test_freqai_datakitchen.py
View File

@ -151,7 +151,9 @@ def test_get_pair_data_for_features_with_prealoaded_data(mocker, freqai_conf):
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
_, base_df = freqai.dd.get_base_and_corr_dataframes(timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.get_pair_data_for_features("LTC/BTC", "5m", strategy, base_dataframes=base_df)
df = freqai.dk.get_pair_data_for_features(
"LTC/BTC", "5m", strategy, {}, base_dataframes=base_df
)
assert df is base_df["5m"]
assert not df.empty
@ -171,7 +173,9 @@ def test_get_pair_data_for_features_without_preloaded_data(mocker, freqai_conf):
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
base_df = {"5m": pd.DataFrame()}
df = freqai.dk.get_pair_data_for_features("LTC/BTC", "5m", strategy, base_dataframes=base_df)
df = freqai.dk.get_pair_data_for_features(
"LTC/BTC", "5m", strategy, {}, base_dataframes=base_df
)
assert df is not base_df["5m"]
assert not df.empty