Refactor player data handling in grab_contest_data and load_contest_file functions

- Restored the player ID mapping logic in grab_contest_data to ensure accurate player identification.
- Updated the combination of player positions and IDs to handle empty slots more effectively, improving output clarity.
- Added logic in load_contest_file to replace None values with '-1', enhancing data consistency.
- These changes contribute to ongoing efforts to improve data integrity and user experience within the application.

global_func/grab_contest_data.py

@@ -23,16 +23,16 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
             print(f"Warning: Mismatch for hash {lineup_hash}. IDs: {len(player_ids)}, Positions: {len(actual_positions)}")
             return lineup_hash
 
-        # # Combine positions and player IDs, only for valid player IDs
-        # combined_parts = []
-        # for pos, pid in zip(actual_positions, player_ids):
-        #     if pid == '-1':  # Handle empty slots
-        #         combined_parts.append(pos + '')
-        #     else:
-        #         combined_parts.append(pos + pid_map.get(pid, pid))
+        # Combine positions and player IDs, only for valid player IDs
+        combined_parts = []
+        for pos, pid in zip(actual_positions, player_ids):
+            if pid == '-1':  # Handle empty slots
+                combined_parts.append(pos + '')
+            else:
+                combined_parts.append(pos + pid_map.get(pid, pid))
         
-        # Just combine positions and PIDs without name mapping
-        combined_parts = [pos + pid for pos, pid in zip(actual_positions, player_ids)]
+        # # Just combine positions and PIDs without name mapping
+        # combined_parts = [pos + pid for pos, pid in zip(actual_positions, player_ids)]
         
         # Join them into a single string
         return "".join(combined_parts)
@@ -58,7 +58,7 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
     players_df = pd.DataFrame(player_data)
     players_df = players_df.sort_values(by='ownership', ascending=False).reset_index(drop=True)
     players_df = players_df.rename(columns={'fullName': 'Player', 'rosterPosition': 'Roster Position', 'ownership': '%Drafted', 'actualPoints': 'FPTS', 'salary': 'Salary', 'currentTeam': 'Team'})
-    # pid_map = dict(zip(players_df['playerId'].astype(str), players_df['Player']))
+    pid_map = dict(zip(players_df['playerId'].astype(str), players_df['Player']))
 
     for lineup_hash, lineup_info in lineups_json['lineups'].items():
         lineup_data.append({

global_func/load_contest_file.py

@@ -43,6 +43,8 @@ def load_contest_file(upload, sport):
                 df[i] = df['Lineup'].str.split(',').str[i].str.strip()
                 # Remove position indicators from the end of each entry
                 df[i] = df[i].str.replace(r'\s+(' + '|'.join(pos_values) + r')$', '', regex=True)
+                # Replace None with -1
+                df[i] = df[i].fillna('-1')
             
             if sport == 'MLB':
                 df = df.rename(columns={1: '1B', 2: '2B', 3: '3B', 4: 'C', 5: 'OF1', 6: 'OF2', 7: 'OF3', 8: 'SP1', 9: 'SP2', 10: 'SS'})