Refine player ID handling in grab_contest_data function for improved formatting

- Adjusted the combination of player positions and IDs to ensure consistent spacing around player IDs, enhancing the readability of the output.
- Updated the player ID mapping to include spaces, ensuring uniform formatting across the application.
- These changes contribute to ongoing efforts to improve data integrity and user experience within the application.

global_func/grab_contest_data.py

@@ -16,15 +16,14 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
         
         # Check if the number of IDs matches the number of positions
         if len(player_ids) != len(positions):
-            # Handle potential errors - maybe return the original hash or log a warning
             print(f"Warning: Mismatch for hash {lineup_hash}. IDs: {len(player_ids)}, Positions: {len(positions)}")
-            return lineup_hash # Or some other error indication
+            return lineup_hash
 
-        # Combine positions and player IDs
-        combined_parts = [pos + pid for pos, pid in zip(positions, player_ids)]
+        # Combine positions and player IDs, ensuring spaces around player IDs
+        combined_parts = [f"{pos}{pid} " for pos, pid in zip(positions, player_ids)]
         
-        # Join them into a single string
-        return "".join(combined_parts)
+        # Join them into a single string and strip trailing space
+        return "".join(combined_parts).rstrip()
 
     lineups_json = requests.get(lineups_url).json()
     data_json = requests.get(data_url).json()
@@ -47,7 +46,7 @@ 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).apply(lambda x: f" {x} "), players_df['Player']))
 
     for lineup_hash, lineup_info in lineups_json['lineups'].items():
         lineup_data.append({