diff --git a/examples/automl_example/api_example/time_series/ts_classification/tmp.py b/examples/automl_example/api_example/time_series/ts_classification/tmp.py
index 37e444d53..e49dbd454 100644
--- a/examples/automl_example/api_example/time_series/ts_classification/tmp.py
+++ b/examples/automl_example/api_example/time_series/ts_classification/tmp.py
@@ -21,8 +21,8 @@ def multiclass_classification():
     pdc.fit(X, y)
     print('score:', pdc.score(X, y))
 
-    y_pred = pdc.predict(X)
-    proba_pred = pdc.predict_proba(X)
+    pdc.predict(X)
+    pdc.predict_proba(X)
 
     assert pdc.score(X, y) == 1.0
 
diff --git a/fedot_ind/api/main.py b/fedot_ind/api/main.py
index e735b36b4..be57fa31d 100644
--- a/fedot_ind/api/main.py
+++ b/fedot_ind/api/main.py
@@ -324,7 +324,7 @@ def get_metrics(self,
                     predicted_probs=probs,
                     rounding_order=rounding_order,
                     metric_names=metric_names) for strategy,
-                                                   probs in self.predicted_probs.items()}
+                probs in self.predicted_probs.items()}
 
         else:
             metric_dict = self._metric_evaluation_loop(
diff --git a/fedot_ind/core/repository/constanst_repository.py b/fedot_ind/core/repository/constanst_repository.py
index b95e0f7b3..be3a70280 100644
--- a/fedot_ind/core/repository/constanst_repository.py
+++ b/fedot_ind/core/repository/constanst_repository.py
@@ -409,6 +409,7 @@ class FedotOperationConstant(Enum):
         "catboostreg": FedotCatBoostRegressionImplementation
     }
 
+
 class ModelCompressionConstant(Enum):
     ENERGY_THR = [0.9, 0.95, 0.99, 0.999]
     DECOMPOSE_MODE = 'channel'