Refactor grab_contest_data function to streamline data processing

- Removed debug print statements to clean up the code and improve performance.
- Simplified the creation of the player ID mapping by eliminating unnecessary formatting and directly associating player IDs with their respective positions.
- These changes enhance the clarity and efficiency of the data handling process within the application.

global_func/grab_contest_data.py

@@ -14,10 +14,6 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
         # Remove the leading colon and split by the remaining colons
         player_ids = lineup_hash.lstrip(':').split(':')
         
-        # Print example of what we're working with
-        print(f"Example lineup_hash: {lineup_hash}")
-        print(f"Split player_ids: {player_ids}")
-        
         # Check if the number of IDs matches the number of positions
         if len(player_ids) != len(positions):
             print(f"Warning: Mismatch for hash {lineup_hash}. IDs: {len(player_ids)}, Positions: {len(positions)}")
@@ -25,11 +21,7 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
 
         # Combine positions and player IDs
         combined_parts = [pos + pid for pos, pid in zip(positions, player_ids)]
-        result = "".join(combined_parts)
-        
-        # Print example of the result
-        print(f"Formatted result: {result}")
-        return result
+        return "".join(combined_parts)
 
     lineups_json = requests.get(lineups_url).json()
     data_json = requests.get(data_url).json()
@@ -52,11 +44,11 @@ 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).apply(lambda x: f" {x} "), players_df['Player']))
-    print("Example pid_map entries:")
-    for i, (pid, name) in enumerate(pid_map.items()):
-        if i < 3:  # Print first 3 entries
-            print(f"ID: '{pid}' -> Name: '{name}'")
+    pid_map = {}
+    for pos in ['1B', '2B', '3B', 'C', 'OF', 'P', 'SS']:
+        for pid, name in zip(players_df['playerId'].astype(str), players_df['Player']):
+            # Create entries for each position format
+            pid_map[f"{pos} {pid}"] = f"{pos} {name}"
 
     for lineup_hash, lineup_info in lineups_json['lineups'].items():
         lineup_data.append({
@@ -75,12 +67,7 @@ def grab_contest_data(sport, contest_name, contest_id_map, contest_date):
     lineups_df = lineups_df.rename(columns={'index': 'Rank', 'points': 'Points', 'entryNameList': 'EntryName', 'lineupHash': 'Lineup'})
     lineups_df['EntryName'] = lineups_df['EntryName'] + ' (1/1)'
     lineups_df['Lineup'] = lineups_df['Lineup'].apply(lambda x: format_lineup_string(x, position_inserts))
-    # Print example before and after replacement
-    print("\nExample before replacement:")
-    print(lineups_df['Lineup'].iloc[0])
     lineups_df['Lineup'] = lineups_df['Lineup'].replace(pid_map, regex=False)
-    print("\nExample after replacement:")
-    print(lineups_df['Lineup'].iloc[0])
     lineups_df = lineups_df[['Rank', 'EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup']]
 
     total_data = lineups_df.merge(players_df, how='left', left_index=True, right_index=True)