Refactor position export dictionary logic to remove dynamic column renaming, simplifying the handling of player names and IDs for Draftkings and other sites.

app.py

@@ -34,9 +34,6 @@ all_column_stack_sports = ['LOL', 'NCAAF', 'WNBA', 'NBA', 'CS2']
 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']
 
-name_column_list = ['Name', 'Nickname', 'NickName', 'name', 'nickname', 'nickName']
-id_column_list = ['ID', 'id', 'Id', 'iD', 'player_ID', 'Player_ID', 'player_id', 'Player_id']
-
 st.markdown("""
 <style>
     /* Tab styling */
@@ -119,25 +116,9 @@ def create_position_export_dict(column_name, csv_file, site_var, type_var, sport
         # Create the export dictionary for this position
         if site_var == 'Draftkings':
             filtered_df = filtered_df.sort_values(by='Salary', ascending=False).drop_duplicates(subset=['Name'])
-            for name_column in name_column_list:
-                if name_column in filtered_df.columns:
-                    filtered_df = filtered_df.rename(columns={name_column: 'Name'})
-                    break
-            for id_column in id_column_list:
-                if id_column in filtered_df.columns:
-                    filtered_df = filtered_df.rename(columns={id_column: 'ID'})
-                    break
-            return dict(zip(filtered_df['Name + ID'], filtered_df['ID']))
+            return dict(zip(filtered_df['Name'], filtered_df['Name + ID']))
         else:
             filtered_df = filtered_df.sort_values(by='Salary', ascending=False).drop_duplicates(subset=['Nickname'])
-            for name_column in name_column_list:
-                if name_column in filtered_df.columns:
-                    filtered_df = filtered_df.rename(columns={name_column: 'Nickname'})
-                    break
-            for id_column in id_column_list:
-                if id_column in filtered_df.columns:
-                    filtered_df = filtered_df.rename(columns={id_column: 'ID'})
-                    break
             return dict(zip(filtered_df['Nickname'], filtered_df['ID']))
                 
     except Exception as e:
@@ -233,8 +214,10 @@ if selected_tab == 'Data Load':
             if 'csv_file' in st.session_state:
                 del st.session_state['csv_file']
         with csv_template_col:
-
-            csv_template_df = pd.DataFrame(columns=['Name', 'ID', 'Roster Position', 'Salary'])
+            if site_var == 'Draftkings':
+                csv_template_df = pd.DataFrame(columns=['Name', 'ID', 'Roster Position', 'Salary'])
+            else:
+                csv_template_df = pd.DataFrame(columns=['Nickname', 'Id', 'Roster Position', 'Salary'])
 
             st.download_button(
                 label="CSV Template",