Enhance debugging feedback in load_contest_file function

- Added print statements throughout the load_contest_file function to provide step-by-step feedback during the data loading and processing stages.
- Improved visibility into the function's execution flow, aiding in debugging and ensuring that each critical step is completed successfully.

global_func/load_contest_file.py

@@ -18,6 +18,8 @@ def load_contest_file(upload, helper = None, sport = None):
                 raw_df = upload
             if helper is not None:
                 helper_df = helper
+
+            print('Made it through initial upload')
             
             # Select and rename essential columns for the actual upload
             if helper is None:
@@ -25,6 +27,8 @@ def load_contest_file(upload, helper = None, sport = None):
             else:
                 df = raw_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS']]
             df = df.rename(columns={'Roster Position': 'Pos', '%Drafted': 'Own'})
+
+            print('Made it through rename')
             
             # Split EntryName into base name and entry count
             df['BaseName'] = df['EntryName'].str.replace(r'\s*\(\d+/\d+\)$', '', regex=True)
@@ -36,6 +40,8 @@ def load_contest_file(upload, helper = None, sport = None):
                 df['Own'] = df['Own'].str.replace('%', '').astype(float)
             except:
                 df['Own'] = df['Own'].astype(float)
+
+            print('Made it through ownership conversion')
             
             # Select and rename essential columns for the actual upload
             if helper is not None:
@@ -53,6 +59,8 @@ def load_contest_file(upload, helper = None, sport = None):
                 except:
                     df_helper['Own'] = df_helper['Own'].astype(float)
             
+            print('Made it through helper')
+            
             # Create separate dataframes for different player attributes
             if helper is not None:
                 ownership_df = df[['Player', 'Own']]
@@ -66,6 +74,8 @@ def load_contest_file(upload, helper = None, sport = None):
                 salary_df = df[['Player', 'Salary']]
                 team_df = df[['Player', 'Team']]
                 pos_df = df[['Player', 'Pos']]
+
+            print('Made it through dictionaries')
             
             # Create the cleaned dataframe with just the essential columns
             cleaned_df = df[['BaseName', 'Lineup']]
@@ -76,6 +86,8 @@ def load_contest_file(upload, helper = None, sport = None):
             entry_counts = cleaned_df['BaseName'].value_counts()
             cleaned_df['EntryCount'] = cleaned_df['BaseName'].map(entry_counts)
             cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'P1', 'P2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']]
+
+            print('Made it through check_lineups')
             
             # Get unique entry names
             entry_list = list(set(df['BaseName']))