Refactor player ID mapping in grab_contest_data for improved efficiency

- Simplified the creation of the player ID mapping by using a dictionary comprehension, enhancing code readability and performance.
- Updated the replacement logic for lineup strings to utilize regex, ensuring accurate formatting of player IDs in the output.
- These changes contribute to ongoing efforts to streamline data processing and improve user experience within the application.

global_func/grab_contest_data.py

@@ -21,6 +21,8 @@ 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)]
+        
+        # Join them into a single string
         return "".join(combined_parts)
 
     lineups_json = requests.get(lineups_url).json()
@@ -44,11 +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 = {}
-    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}"
+    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({
@@ -67,7 +65,7 @@ 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))
-    lineups_df['Lineup'] = lineups_df['Lineup'].replace(pid_map, regex=False)
+    lineups_df['Lineup'] = lineups_df['Lineup'].replace(pid_map, regex=True)  # Note: back to regex=True
     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)