Enhance player data handling by updating load functions in load_dk_fd_file, load_file, and load_ss_file to incorporate sport-specific headers, improving CSV and lineup processing for various sports in app.py and global functions.

app.py

@@ -32,7 +32,7 @@ stacking_sports = ['MLB', 'NHL', 'NFL', 'LOL']
 player_wrong_names_mlb = ['Enrique Hernandez', 'Joseph Cantillo', 'Mike Soroka', 'Jakob Bauers', 'Temi Fágbénlé']
 player_right_names_mlb = ['Kike Hernandez', 'Joey Cantillo', 'Michael Soroka', 'Jake Bauers', 'Temi Fagbenle']
 
-def create_position_export_dict(column_name, csv_file):
+def create_position_export_dict(column_name, csv_file, site_var, type_var, sport_var):
     try:
         # Remove any numbers from the column name to get the position
         import re
@@ -42,14 +42,32 @@ def create_position_export_dict(column_name, csv_file):
 
         # Filter CSV file by position
         if 'Position' in csv_file.columns:
-            if position_filter == 'SP':
-                filtered_df = csv_file[
-                    csv_file['Roster Position'] == 'P'
-                ]
+            if type_var == 'Showdown':
+                filtered_df = csv_file.copy()
             else:
-                filtered_df = csv_file[
-                    csv_file['Position'].str.contains(position_filter, na=False, regex=False)
-                ]
+                if position_filter == 'SP':
+                    filtered_df = csv_file[
+                        csv_file['Roster Position'] == 'P'
+                    ]
+                elif position_filter == 'CPT':
+                    filtered_df = csv_file.copy()
+                elif position_filter == 'FLEX' or position_filter == 'UTIL':
+                    if sport_var == 'NFL':
+                        filtered_df = csv_file['Position'].isin(['RB', 'WR', 'TE'])
+                    elif sport_var == 'SOC':
+                        filtered_df = csv_file['Position'].str.contains(['D', 'M', 'F'], na=False, regex=False)
+                    elif sport_var == 'NCAAF':
+                        filtered_df = csv_file['Position'].isin(['RB', 'WR'])
+                    elif sport_var == 'NHL':
+                        filtered_df = csv_file['Position'].str.contains(['C', 'W', 'D'], na=False, regex=False)
+                    else:
+                        filtered_df = csv_file.copy()
+                elif position_filter == 'SFLEX':
+                    filtered_df = csv_file.copy()
+                else:
+                    filtered_df = csv_file[
+                        csv_file['Position'].str.contains(position_filter, na=False, regex=False)
+                    ]
         else:
             # Fallback to all players if no position column found
             filtered_df = csv_file
@@ -163,22 +181,19 @@ with tab1:
         if csv_file:
             if type_var == 'Showdown':
                 st.session_state['csv_file']['Position'] = 'FLEX'
-            
-            if sport_var == 'GOLF':
-                st.session_state['csv_file']['Position'] = 'FLEX'
-                st.session_state['csv_file']['Team'] = 'GOLF'
-            elif sport_var == 'TENNIS':
-                st.session_state['csv_file']['Position'] = 'FLEX'
-                st.session_state['csv_file']['Team'] = 'TENNIS'
-            elif sport_var == 'MMA':
-                st.session_state['csv_file']['Position'] = 'FLEX'
-                st.session_state['csv_file']['Team'] = 'MMA'
-            elif sport_var == 'NASCAR':
-                st.session_state['csv_file']['Position'] = 'FLEX'
-                st.session_state['csv_file']['Team'] = 'NASCAR'
-            elif sport_var == 'F1':
-                st.session_state['csv_file']['Position'] = 'FLEX'
-                st.session_state['csv_file']['Team'] = 'F1'
+            else:
+                if sport_var == 'GOLF':
+                    st.session_state['csv_file']['Position'] = 'FLEX'
+                    st.session_state['csv_file']['Team'] = 'GOLF'
+                elif sport_var == 'TENNIS':
+                    st.session_state['csv_file']['Position'] = 'FLEX'
+                    st.session_state['csv_file']['Team'] = 'TENNIS'
+                elif sport_var == 'MMA':
+                    st.session_state['csv_file']['Position'] = 'FLEX'
+                    st.session_state['csv_file']['Team'] = 'MMA'
+                elif sport_var == 'NASCAR':
+                    st.session_state['csv_file']['Position'] = 'FLEX'
+                    st.session_state['csv_file']['Team'] = 'NASCAR'
             # st.session_state['csv_file'] = st.session_state['csv_file'].drop_duplicates(subset=['Name'])
             st.success('Projections file loaded successfully!')
             st.dataframe(st.session_state['csv_file'].head(10))
@@ -204,19 +219,19 @@ with tab1:
         if 'portfolio' not in st.session_state:
             if portfolio_file:
                 if upload_toggle == 'SaberSim (Just IDs)':
-                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_ss_file(portfolio_file, st.session_state['csv_file'])
+                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_ss_file(portfolio_file, st.session_state['csv_file'], site_var, type_var, sport_var)
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
                     st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
                     st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
                 elif upload_toggle == 'Draftkings/Fanduel (Names + IDs)':
-                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_dk_fd_file(portfolio_file, st.session_state['csv_file'])
+                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_dk_fd_file(portfolio_file, st.session_state['csv_file'], site_var, type_var, sport_var)
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
                     st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
                     st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
                 else:
-                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_file(portfolio_file)
+                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_file(portfolio_file, site_var, type_var, sport_var, 'portfolio')
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
                     st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
                     st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
@@ -259,7 +274,7 @@ with tab1:
             )
             
         if projections_file:
-            export_projections, projections = load_file(projections_file)
+            export_projections, projections = load_file(projections_file, site_var, type_var, sport_var, 'projections')
             if projections is not None:
                 st.success('Projections file loaded successfully!')
                 try:
@@ -1609,7 +1624,7 @@ with tab2:
                 for col in st.session_state['export_file'].columns:
                     if col not in excluded_cols:
                         # Create position-specific export dictionary on the fly
-                        position_dict = create_position_export_dict(col, st.session_state['csv_file'])
+                        position_dict = create_position_export_dict(col, st.session_state['csv_file'], site_var, type_var, sport_var)
                         st.session_state['export_file'][col] = st.session_state['export_file'][col].map(position_dict)
             
             if 'export_file' in st.session_state:

global_func/exposure_spread.py

@@ -99,7 +99,7 @@ def check_nascar_position_eligibility(column_name, player_positions):
         return any(pos in ['D'] for pos in player_positions)
     return True
 
-def check_cfb_position_eligibility(column_name, player_positions):
+def check_ncaaf_position_eligibility(column_name, player_positions):
     if 'QB' in column_name:
         return 'QB' in player_positions
     elif 'RB' in column_name:
@@ -108,7 +108,7 @@ def check_cfb_position_eligibility(column_name, player_positions):
         return 'WR' in player_positions
     elif 'FLEX' in column_name:
         return any(pos in ['RB', 'WR'] for pos in player_positions)
-    elif 'SUPERFLEX' in column_name:
+    elif 'SFLEX' in column_name:
         return any(pos in ['RB', 'WR', 'QB'] for pos in player_positions)
     return False
 
@@ -122,9 +122,9 @@ def check_nhl_position_eligibility(column_name, player_positions):
     elif 'G' in column_name:
         return 'G' in player_positions
     elif 'FLEX' in column_name:
-        return True  # UTIL can be any position
+        return any(pos in ['C', 'W', 'D'] for pos in player_positions)
     elif 'UTIL' in column_name:
-            return True  # UTIL can be any position
+        return any(pos in ['C', 'W', 'D'] for pos in player_positions)
     return False
 
 def check_position_eligibility(sport, column_name, player_positions):
@@ -267,11 +267,12 @@ def exposure_spread(working_frame, exposure_player, exposure_target, exposure_st
                     (projections_df['position'].apply(lambda x: has_position_overlap(x, comp_player_position)))
                 ]
                 if sport_var in stacking_sports:
-                    if row['Size'] == 5 and comp_team != row['Stack']:
-                        remove_mask = comparable_players.apply(
-                            lambda row: not any(team in list(row) for team in working_frame['Stack'][row]), axis=1
-                        )
-                        comparable_players = comparable_players[remove_mask]
+                    if sport_var in stacking_sports:
+                        if working_frame.iloc[row]['Size'] == 5 and comp_team != working_frame.iloc[row]['Stack']:
+                            remove_mask = comparable_players.apply(
+                                lambda player_row: not any(team in list(player_row) for team in [working_frame.iloc[row]['Stack']]), axis=1
+                            )
+                            comparable_players = comparable_players[remove_mask]
                 
                 if remove_teams is not None:
                     remove_mask = comparable_players.apply(
@@ -291,10 +292,11 @@ def exposure_spread(working_frame, exposure_player, exposure_target, exposure_st
                             if working_frame.iloc[row]['salary'] - projections_df[projections_df['player_names'] == row_data[col]]['salary'].iloc[0] + projections_df[projections_df['player_names'] == exposure_player]['salary'].iloc[0] <= salary_max:
                                 # Get the replacement player's positions
                                 replacement_player_positions = projections_df[projections_df['player_names'] == row_data[col]]['position'].iloc[0].split('/')
+                                exposure_player_positions = projections_df[projections_df['player_names'] == exposure_player]['position'].iloc[0].split('/')
                                 
                                 # Check if the replacement player is eligible for this column
                                 if type_var == 'Classic':
-                                    if check_position_eligibility(sport_var, col, replacement_player_positions):
+                                    if check_position_eligibility(sport_var, col, exposure_player_positions):
                                         working_frame.at[row, col] = exposure_player
                                         change_counter += 1
                                         break

global_func/load_dk_fd_file.py

@@ -5,7 +5,82 @@ import time
 from rapidfuzz import process
 import re
 
-def load_dk_fd_file(lineups, csv_file):
+sport_headers = {
+    'Draftkings': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+    'Fanduel': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+}
+
+def load_dk_fd_file(lineups, csv_file, site_var, type_var, sport_var):
     df = csv_file.copy()
     try:
         name_dict = dict(zip(df['Name + ID'], df['Name']))
@@ -34,6 +109,8 @@ def load_dk_fd_file(lineups, csv_file):
         except:
             pass
 
+        lineups_df.columns = sport_headers[site_var][type_var][sport_var]
+
         export_df = lineups_df.copy()
         
         # Map the IDs to names

global_func/load_file.py

@@ -8,7 +8,82 @@ import re
 ## import global functions
 from global_func.clean_player_name import clean_player_name
 
-def load_file(upload):
+sport_headers = {
+    'Draftkings': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+    'Fanduel': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+}
+
+def load_file(upload, site_var, type_var, sport_var, upload_type):
     if upload is not None:
         try:
             clean_name = re.sub(r' \(\d+\)', '', upload.name)
@@ -27,6 +102,9 @@ def load_file(upload):
             for col in df.columns:
                 if "Unnamed" in col:
                     df = df.drop(columns=[col])
+
+            if upload_type == 'portfolio':
+                df.columns = sport_headers[site_var][type_var][sport_var]
             
             export_df = df.copy()
             

global_func/load_ss_file.py

@@ -5,7 +5,82 @@ import time
 from rapidfuzz import process
 import re
 
-def load_ss_file(lineups, csv_file):
+sport_headers = {
+    'Draftkings': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+    'Fanduel': {
+        'Classic' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'],
+            'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'],
+            'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'],
+            'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'],
+            'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'],
+            'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'],
+            'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'],
+            'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'],
+            'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'],
+            'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'],
+        },
+        'Showdown' : {
+            'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'],
+            'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'],
+            'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+            'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'],
+        },
+    },
+}
+
+def load_ss_file(lineups, csv_file, site_var, type_var, sport_var):
     df = csv_file.copy()
     try:
         name_dict = dict(zip(df['ID'], df['Name']))
@@ -29,6 +104,7 @@ def load_ss_file(lineups, csv_file):
             st.error('Please upload either a CSV or Excel file for lineups')
             return None, None
         lineups_df = lineups_df.dropna(how='any')
+        lineups_df.columns = sport_headers[site_var][type_var][sport_var]
         export_df = lineups_df.copy()
         
         # Map the IDs to names