ruff safe linting

Author: SamoraHunter

ml_grid/model_classes/H2OAutoMLClassifier.py

@@ -1,11 +1,11 @@
-import h2o
-import numpy as np
-import pandas as pd
 import logging
+
+import pandas as pd
 from h2o.automl import H2OAutoML
-from .H2OBaseClassifier import H2OBaseClassifier
 from h2o.estimators import H2OGeneralizedLinearEstimator
 
+from .H2OBaseClassifier import H2OBaseClassifier
+
 logger = logging.getLogger(__name__)
 
 

ml_grid/model_classes/H2OBaseClassifier.py

@@ -1,14 +1,16 @@
 import inspect
-from typing import Any, Dict, List, Optional, Tuple
 import logging
-import h2o
-import numpy as np
 import os
-import tempfile
 import shutil
+import tempfile
+from typing import Any, Dict, List, Optional, Tuple
+
+import h2o
+import numpy as np
 import pandas as pd
 from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.utils.validation import check_is_fitted
+
 from ml_grid.util.global_params import global_parameters
 
 # Configure logging
@@ -67,7 +69,7 @@ def __init__(self, estimator_class=None, **kwargs):
             # CRITICAL: Never allow 'model' as a parameter - it conflicts with 'model_'
             if key == "model":
                 self.logger.warning(
-                    f"Rejecting 'model' parameter in __init__ - this conflicts with fitted attribute 'model_'"
+                    "Rejecting 'model' parameter in __init__ - this conflicts with fitted attribute 'model_'"
                 )
                 continue
             setattr(self, key, value)

ml_grid/model_classes/H2ODeepLearningClassifier.py

@@ -1,10 +1,12 @@
-from h2o.estimators import H2ODeepLearningEstimator
-from .H2OBaseClassifier import H2OBaseClassifier
+
 import pandas as pd
-import logging
-from skopt.space import Categorical, Real, Integer
+from h2o.estimators import H2ODeepLearningEstimator
+from skopt.space import Categorical, Integer, Real
+
 from ml_grid.util.global_params import global_parameters
 
+from .H2OBaseClassifier import H2OBaseClassifier
+
 PARAM_SPACE_GRID = {
     "xsmall": {
         "epochs": [5],

ml_grid/model_classes/H2OGAMClassifier.py

@@ -1,14 +1,14 @@
 import logging
+from typing import Any, Dict
+
+import numpy as np
+import pandas as pd
 from h2o.estimators import (
     H2OGeneralizedAdditiveEstimator,
     H2OGeneralizedLinearEstimator,
 )
-from typing import Any, Dict, List, Tuple
+
 from .H2OBaseClassifier import H2OBaseClassifier
-import pandas as pd
-import numpy as np
-import h2o
-from sklearn.utils.validation import check_is_fitted
 
 logger = logging.getLogger(__name__)  # Use module-level logger for consistency
 

ml_grid/model_classes/H2OGBMClassifier.py

@@ -1,6 +1,7 @@
-from h2o.estimators import H2OGradientBoostingEstimator
 import pandas as pd
-from skopt.space import Real, Integer
+from h2o.estimators import H2OGradientBoostingEstimator
+from skopt.space import Integer, Real
+
 from ml_grid.util.global_params import global_parameters
 
 from .H2OBaseClassifier import H2OBaseClassifier

ml_grid/model_classes/H2OGLMClassifier.py

@@ -1,7 +1,8 @@
+
+import pandas as pd
 from h2o.estimators import H2OGeneralizedLinearEstimator
+
 from .H2OBaseClassifier import H2OBaseClassifier
-import pandas as pd
-from typing import Any, Dict
 
 
 class H2OGLMClassifier(H2OBaseClassifier):

ml_grid/model_classes/H2ONaiveBayesClassifier.py

@@ -4,6 +4,7 @@
 """
 
 from h2o.estimators import H2ONaiveBayesEstimator
+
 from .H2OBaseClassifier import H2OBaseClassifier
 
 

ml_grid/model_classes/H2ORuleFitClassifier.py

@@ -3,9 +3,10 @@
 This module provides a scikit-learn compatible wrapper for H2O's RuleFitEstimator.
 """
 
+import pandas as pd
 from h2o.estimators import H2ORuleFitEstimator
+
 from .H2OBaseClassifier import H2OBaseClassifier
-import pandas as pd
 
 
 class H2ORuleFitClassifier(H2OBaseClassifier):

ml_grid/model_classes/H2OStackedEnsembleClassifier.py

@@ -1,7 +1,8 @@
 import logging
-import pandas as pd
 from typing import List
 
+import pandas as pd
+
 # Import H2O estimators
 try:
     from h2o.estimators import H2OStackedEnsembleEstimator

ml_grid/model_classes/H2OXGBoostClassifier.py

@@ -4,8 +4,8 @@
 """
 
 from h2o.estimators import H2OXGBoostEstimator
+
 from .H2OBaseClassifier import H2OBaseClassifier
-import pandas as pd
 
 
 class H2OXGBoostClassifier(H2OBaseClassifier):