style: apply automated linter fixes

Author: megalinter-bot

src/safeds/exceptions/__init__.py

@@ -16,14 +16,14 @@
 from ._ml import (
     DatasetMissesDataError,
     DatasetMissesFeaturesError,
-    TargetDataMismatchError,
     FeatureDataMismatchError,
     InputSizeError,
     InvalidModelStructureError,
     LearningError,
     ModelNotFittedError,
     PlainTableError,
     PredictionError,
+    TargetDataMismatchError,
 )
 
 

src/safeds/exceptions/_ml.py

@@ -30,7 +30,9 @@ class TargetDataMismatchError(ValueError):
     """
 
     def __init__(self, actual_target_name: str, missing_target_name: str):
-        super().__init__(f"The provided target column '{actual_target_name}' does not match the target column of the training set '{missing_target_name}'.")
+        super().__init__(
+            f"The provided target column '{actual_target_name}' does not match the target column of the training set '{missing_target_name}'.",
+        )
 
 
 class DatasetMissesDataError(ValueError):

src/safeds/ml/classical/classification/_baseline_classifier.py

@@ -6,9 +6,9 @@
 from safeds.data.labeled.containers import TabularDataset
 from safeds.exceptions import (
     DatasetMissesDataError,
-    TargetDataMismatchError,
     FeatureDataMismatchError,
     ModelNotFittedError,
+    TargetDataMismatchError,
 )
 from safeds.ml.classical.classification import (
     AdaBoostClassifier,
@@ -140,7 +140,9 @@ def predict(self, test_data: TabularDataset) -> dict[str, float]:
         if not self._feature_names == test_data.features.column_names:
             raise FeatureDataMismatchError
         if not self._target_name == test_data.target.name:
-            raise TargetDataMismatchError(actual_target_name=test_data.target.name, missing_target_name=self._target_name)
+            raise TargetDataMismatchError(
+                actual_target_name=test_data.target.name, missing_target_name=self._target_name,
+            )
         test_data_as_table = test_data.to_table()
         if test_data_as_table.row_count == 0:
             raise DatasetMissesDataError

src/safeds/ml/classical/regression/_baseline_regressor.py

@@ -6,9 +6,9 @@
 from safeds.data.labeled.containers import TabularDataset
 from safeds.exceptions import (
     DatasetMissesDataError,
-    TargetDataMismatchError,
     FeatureDataMismatchError,
     ModelNotFittedError,
+    TargetDataMismatchError,
 )
 from safeds.ml.classical.regression import (
     AdaBoostRegressor,
@@ -149,7 +149,9 @@ def predict(self, test_data: TabularDataset) -> dict[str, float]:
         if not self._feature_names == test_data.features.column_names:
             raise FeatureDataMismatchError
         if not self._target_name == test_data.target.name:
-            raise TargetDataMismatchError(actual_target_name=test_data.target.name, missing_target_name=self._target_name)
+            raise TargetDataMismatchError(
+                actual_target_name=test_data.target.name, missing_target_name=self._target_name,
+            )
         test_data_as_table = test_data.to_table()
         if test_data_as_table.row_count == 0:
             raise DatasetMissesDataError

tests/safeds/ml/classical/classification/test_baseline_classifier.py

@@ -3,9 +3,9 @@
 from safeds.exceptions import (
     ColumnTypeError,
     DatasetMissesDataError,
-    TargetDataMismatchError,
     FeatureDataMismatchError,
     ModelNotFittedError,
+    TargetDataMismatchError,
 )
 from safeds.ml.classical.classification import BaselineClassifier
 

tests/safeds/ml/classical/regression/test_baseline_regressor.py

@@ -3,9 +3,9 @@
 from safeds.exceptions import (
     ColumnTypeError,
     DatasetMissesDataError,
-    TargetDataMismatchError,
     FeatureDataMismatchError,
     ModelNotFittedError,
+    TargetDataMismatchError,
 )
 from safeds.ml.classical.regression import BaselineRegressor