Add position mapping and eligibility checks in load_contest_file function

- Implemented a position mapping dictionary to associate players with their respective positions.
- Added logic to create empty columns for MLB positions and fill them based on player eligibility.
- Enhanced lineup processing to ensure accurate assignment of players to required positions, improving data integrity and user experience.
- These changes contribute to ongoing efforts to refine player data handling within the application.

global_func/load_contest_file.py

@@ -57,6 +57,54 @@ def load_contest_file(upload, sport):
             salary_df = df[['Player', 'Salary']]
             team_df = df[['Player', 'Team']]
             pos_df = df[['Player', 'Pos']]
+            
+            # Create position mapping dictionary
+            pos_dict = dict(zip(pos_df['Player'], pos_df['Pos']))
+            
+            # Create empty columns for each position
+            if sport == 'MLB':
+                position_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+                for col in position_columns:
+                    df[col] = None
+                
+                # Function to check if player is eligible for position
+                def is_eligible_for_position(player, target_pos):
+                    if player not in pos_dict:
+                        return False
+                    player_positions = pos_dict[player].split('/')
+                    # Handle special cases
+                    if target_pos.startswith('SP') and 'P' in player_positions:
+                        return True
+                    if target_pos.startswith('OF') and 'OF' in player_positions:
+                        return True
+                    return target_pos in player_positions
+                
+                # Process each lineup
+                for idx, row in df.iterrows():
+                    # Get all players in the lineup
+                    players = row['Lineup'].split(',')
+                    players = [p.strip() for p in players if p.strip()]
+                    
+                    # First pass: fill required positions (SP1, SP2, C, 1B, 2B, 3B, SS)
+                    required_positions = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS']
+                    for pos in required_positions:
+                        for player in players:
+                            if is_eligible_for_position(player, pos):
+                                df.at[idx, pos] = player
+                                players.remove(player)
+                                break
+                    
+                    # Second pass: fill OF positions with remaining players
+                    of_positions = ['OF1', 'OF2', 'OF3']
+                    for pos in of_positions:
+                        for player in players:
+                            if is_eligible_for_position(player, 'OF'):
+                                df.at[idx, pos] = player
+                                players.remove(player)
+                                break
+                        if not players:  # If no more players, fill with -1
+                            df.at[idx, pos] = '-1'
+            
             cleaned_df = df.drop(columns=['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Pos', 'Own', 'FPTS', 'Salary', 'Team'])
             cleaned_df = cleaned_df[['BaseName', 'EntryCount', 'SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']]
             entry_list = list(set(df['BaseName']))