[pre-commit.ci] pre-commit autoupdate (#963)

.pre-commit-config.yaml

@@ -1,10 +1,10 @@
 repos:
   - repo: https://github.com/psf/black
-    rev: 22.8.0
+    rev: 23.11.0
     hooks:
       - id: black
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
+    rev: v4.5.0
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
@@ -15,6 +15,6 @@ repos:
       - id: no-commit-to-branch
         args: [--branch, master, --branch, develop]
   - repo: https://github.com/PyCQA/flake8
-    rev: 5.0.4
+    rev: 6.1.0
     hooks:
       - id: flake8

src/ml_tooling/plots/utils.py

@@ -123,7 +123,6 @@ def _plot_barh(
 
     if add_label:
         for i, (x, y) in enumerate(_generate_text_labels(ax, horizontal=True)):
-
             ax.annotate(
                 f"{values.ravel()[i]:.1%}"
                 if is_percent

src/ml_tooling/storage/artifactory.py

@@ -43,7 +43,6 @@ def __init__(
         apikey: Optional[str] = None,
         auth: Optional[Tuple[str, str]] = None,
     ):
-
         if not _has_artifactory:
             raise MLToolingError(
                 "Artifactory not installed - run pip install dohq-artifactory"

src/ml_tooling/transformers/feature_union.py

@@ -24,7 +24,7 @@ def __init__(self, transformer_list: list):
         self.transformer_list = transformer_list
 
     def fit(self, X: pd.DataFrame, y=None):
-        for (name, t) in self.transformer_list:
+        for name, t in self.transformer_list:
             t.fit(X, y)
         return self
 

src/ml_tooling/transformers/fillna.py

@@ -46,7 +46,6 @@ def __init__(
         }
 
     def _validate_parameters(self):
-
         if self.value is None and self.strategy is None:
             raise TransformerError(
                 "Both value and strategy are set to None."
@@ -68,7 +67,6 @@ def _col_is_categorical_and_is_missing_category(
         return False
 
     def fit(self, X: pd.DataFrame, y=None):
-
         self._validate_parameters()
 
         if self.strategy:

tests/test_baseclass.py

@@ -330,7 +330,6 @@ def test_to_dict_serializes_correctly_with_feature_union(
     def test_from_yaml_serializes_correctly_with_feature_union(
         self, feature_union_classifier: DFFeatureUnion, tmp_path: pathlib.Path
     ):
-
         model = Model(feature_union_classifier)
         result = model.to_dict()
 
@@ -677,7 +676,6 @@ def test_gridsearch_model_returns_as_expected(
     def test_gridsearch_best_model_is_not_fitted_if_refit_is_not_true(
         self, pipeline_logistic: Pipeline, train_iris_dataset: Dataset
     ):
-
         model = Model(pipeline_logistic)
         model, results = model.gridsearch(
             train_iris_dataset,
@@ -771,7 +769,6 @@ def test_randomsearch_model_returns_as_expected(
     def test_randomsearch_best_model_is_not_fitted_if_refit_is_not_true(
         self, pipeline_logistic: Pipeline, train_iris_dataset: Dataset
     ):
-
         model = Model(pipeline_logistic)
         model, results = model.randomsearch(
             train_iris_dataset,
@@ -890,7 +887,6 @@ def test_bayessearc_model_returns_as_expected(
     def test_bayessearch_best_model_is_not_fitted_if_refit_is_not_true(
         self, pipeline_logistic: Pipeline, train_iris_dataset: Dataset
     ):
-
         model = Model(pipeline_logistic)
         model, results = model.bayesiansearch(
             train_iris_dataset,

tests/test_visualizations/test_target_feature_distribution.py

@@ -44,7 +44,6 @@ def test_target_correlation_uses_pipeline_when_passed(
     def test_target_feature_distribution_works_as_expected(
         self, australian_dataset: Dataset
     ):
-
         ax = australian_dataset.plot.target_feature_distribution(feature_name="A4")
 
         assert [text.get_text() for text in ax.texts] == ["0.28", "0.50", "1.00"]