From 8c793bbe99f019c3d6def1c07b7c6444b4d09eb5 Mon Sep 17 00:00:00 2001 From: Sergei Pakulin Date: Fri, 1 Sep 2023 16:24:39 +0500 Subject: [PATCH] typings --- .../data_operations/categorical_encoders.py | 12 ++++++------ fedot/core/operations/operation.py | 2 +- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/fedot/core/operations/evaluation/operation_implementations/data_operations/categorical_encoders.py b/fedot/core/operations/evaluation/operation_implementations/data_operations/categorical_encoders.py index 0888843268..dce9296c12 100644 --- a/fedot/core/operations/evaluation/operation_implementations/data_operations/categorical_encoders.py +++ b/fedot/core/operations/evaluation/operation_implementations/data_operations/categorical_encoders.py @@ -22,10 +22,10 @@ def __init__(self, params: Optional[OperationParameters] = None): 'handle_unknown': 'ignore' } self.encoder = OneHotEncoder(**{**default_params, **self.params.to_dict()}) - self.categorical_ids = None - self.non_categorical_ids = None - self.encoded_ids = None - self.new_numerical_idx = None + self.categorical_ids: List[int] = [] + self.non_categorical_ids: List[int] = [] + self.encoded_ids: List[int] = [] + self.new_numerical_idx: List[int] = [] def fit(self, input_data: InputData): """ Method for fit encoder with automatic determination of categorical features @@ -104,8 +104,8 @@ def __init__(self, params: Optional[OperationParameters] = None): super().__init__(params) # LabelEncoder has no parameters self.encoders = {} - self.categorical_ids: List[int] = None - self.non_categorical_ids: List[int] = None + self.categorical_ids: List[int] = [] + self.non_categorical_ids: List[int] = [] def fit(self, input_data: InputData): feature_type_ids = input_data.supplementary_data.col_type_ids['features'] diff --git a/fedot/core/operations/operation.py b/fedot/core/operations/operation.py index da44065277..3625425c7c 100644 --- a/fedot/core/operations/operation.py +++ b/fedot/core/operations/operation.py @@ -26,7 +26,7 @@ def __init__(self, operation_type: str, **kwargs): self.operation_type = operation_type self._eval_strategy = None - self.operations_repo: OperationTypesRepository = None + self.operations_repo: Optional[OperationTypesRepository] = None self.fitted_operation = None self.log = default_log(self)