Fixes

fedot/core/data/data_split.py

@@ -117,7 +117,7 @@ def _are_stratification_allowed(data: Union[InputData, MultiModalData], split_ra
     try:
         # fast way
         classes = np.unique(data.target, return_counts=True)
-    except:
+    except Exception:
         # slow way
         from collections import Counter
         classes = Counter(data.target)

fedot/core/optimisers/objective/data_source_splitter.py

@@ -53,10 +53,10 @@ def build(self, data: Union[InputData, MultiModalData]) -> DataSource:
 
         # Check cv_folds
         if self.cv_folds is not None:
-            if not isinstance(self.cv_folds, int):
-                if self.cv_folds % 1 != 0:
-                    raise ValueError(f"cv_folds is not integer: {self.cv_folds}")
+            try:
                 self.cv_folds = int(self.cv_folds)
+            except ValueError:
+                raise ValueError(f"cv_folds is not integer: {self.cv_folds}")
             if self.cv_folds < 2:
                 self.cv_folds = None
             if self.cv_folds > data.target.shape[0] - 1:

test/integration/api/test_api_utils.py

@@ -32,7 +32,7 @@ def test_output_binary_classification_correct():
     task_type = 'classification'
 
     data = get_binary_classification_data()
-    
+
     train_data, test_data = train_test_data_setup(data, shuffle=True)
 
     model = Fedot(problem=task_type, seed=1, timeout=0.1)

test/unit/validation/test_table_cv.py

@@ -4,7 +4,6 @@
 import pytest
 
 from golem.core.tuning.simultaneous import SimultaneousTuner
-from sklearn.metrics import roc_auc_score as roc_auc
 
 from fedot.api.main import Fedot
 from fedot.core.data.data import InputData