Merge pull request #42 from ayushmorbar/JWOC-2023

Issue #3 Update every print statements to f-string
sagnik1511 · Feb 17, 2023 · da20afc · da20afc
2 parents ac94419 + 498fa03
commit da20afc
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/tab_automl/automl/datasets.py b/tab_automl/automl/datasets.py
@@ -29,7 +29,7 @@ def __init__(self, path):
         elif path.endswith(".csv"):
             self.data = pd.read_csv(path)
         else:
-            print("File type not supported")
+            print(f"File type not supported")
         # storing the columns overview
         self.columns = pd.Series([str(self.data[feature].dtype) for feature in self.data.columns])
         self.labels = None
@@ -81,7 +81,7 @@ def __init__(self, path):
         elif path.endswith(".csv"):
             self.data = pd.read_csv(path)
         else:
-            print("File type not supported")
+            print(f"File type not supported")
 
         # storing the columns overview
         self.columns = pd.Series([str(self.data[feature].dtype) for feature in self.data.columns])
@@ -131,7 +131,7 @@ def __init__(self, path):
         elif path.endswith(".csv"):
             self.data = pd.read_csv(path)
         else:
-            print("File type not supported")
+            print(f"File type not supported")
         # storing the columns overview
         self.columns = pd.Series([str(self.data[feature].dtype) for feature in self.data.columns])
         self.labels = None

diff --git a/tab_automl/automl/training.py b/tab_automl/automl/training.py
@@ -79,7 +79,7 @@ def single_model_trainer(self, x_train, y_train,
             metric_scores = fetch_metric_scores((x_train, y_train),
                                                 (x_val, y_val), metrics=metric_list,
                                                 trained_model=model)
-            print("Model Metrics :")
+            print(f"Model Metrics :")
             print({k: '%.5f'%v[0] for k, v in metric_scores.items()})
             self.model_checkpoint(metric_scores, model_name, model)
 
@@ -108,7 +108,7 @@ def model_checkpoint(self, metric_dict, model_name, model):
                 flag = False
         else:
             if self.best_score < metric_dict[f"{self.check_on}_{self.result_monitor}"][0]:
-                cprint("Model Updated...", "green")
+                cprint(f"Model Updated...", "green")
                 cprint(f"Current best model : {model_name}", "green")
                 self.best_score = metric_dict[f"{self.check_on}_{self.result_monitor}"][0]
                 self.best_model_name = model_name
@@ -118,4 +118,4 @@ def model_checkpoint(self, metric_dict, model_name, model):
                 flag = False
 
         if flag:
-            cprint("Model update failed...", "red")
+            cprint(f"Model update failed...", "red")