Fixed the type hint for _generate_inverted_hierarchy.

Removed ToDo comment based on feedback.
Added type hint to test_hierarchy_with_scikit_learn_column_transformer.

Author: dennisobrien

category_encoders/target_encoder.py

@@ -312,8 +312,7 @@ def _weighting(self, n: int) -> float:
         # sigmoid in this case, using scipy.expit for numerical stability
         return expit((n - self.min_samples_leaf) / self.smoothing)
 
-    def _generate_inverted_hierarchy(self) -> tuple[dict | pd.DataFrame, dict]:
-        # @ToDo create a function to check the hierarchy
+    def _generate_inverted_hierarchy(self) -> tuple[dict | pd.DataFrame | None, dict]:
         if isinstance(self.hierarchy, (dict, pd.DataFrame)) and self.cols is None:
             raise ValueError('Hierarchy is defined but no columns are named for encoding')
         if isinstance(self.hierarchy, dict):

tests/test_target_encoder.py

@@ -507,7 +507,7 @@ def test_hierarchy_mapping_cols_missing(self):
         with self.assertRaises(ValueError):
             enc.fit_transform(X, y)
 
-    def test_hierarchy_with_scikit_learn_column_transformer(self):
+    def test_hierarchy_with_scikit_learn_column_transformer(self) -> None:
         """Test that the encoder works with a scikit-learn ColumnTransformer."""
         features: list[str] = ["cat_feature", "int_feature"]
         target: str = "target"