chore: Further reduce mutable default usage

freqtrade/freqai/data_kitchen.py

@@ -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:
         """

tests/freqai/test_freqai_datakitchen.py

@@ -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