Add create_position_export_dict function in app.py to generate position-specific export dictionaries from CSV files, enhancing player data handling and mapping in export functionality.

app.py

@@ -32,6 +32,42 @@ 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):
+    """
+    Create a position-specific export dictionary based on the column name.
+    Strips numbers from column names to get the position (e.g., 'SP1' -> 'SP', 'G2' -> 'G')
+    """
+    try:
+        # Remove any numbers from the column name to get the position
+        import re
+        position_filter = re.sub(r'\d+', '', column_name)
+        
+        # Filter CSV file by position
+        if 'Position' in csv_file.columns:
+            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
+        
+        # Create the export dictionary for this position
+        
+        try:
+            filtered_df = filtered_df.sort_values(by='Salary', ascending=False).drop_duplicates(subset=['Name'])
+            return dict(zip(filtered_df['Name'], filtered_df['Name + ID']))
+        except:
+            try:
+                filtered_df = filtered_df.sort_values(by='Salary', ascending=False).drop_duplicates(subset=['Nickname'])
+                return dict(zip(filtered_df['Nickname'], filtered_df['Id']))
+            except:
+                # Final fallback
+                return {}
+                
+    except Exception as e:
+        st.error(f"Error creating position export dict for {column_name}: {str(e)}")
+        return {}
+
 with st.container():
     
     col1, col2, col3, col4 = st.columns(4)
@@ -1549,7 +1585,9 @@ with tab2:
                 
                 for col in st.session_state['export_file'].columns:
                     if col not in excluded_cols:
-                        st.session_state['export_file'][col] = st.session_state['export_file'][col].map(st.session_state['export_dict'])
+                        # Create position-specific export dictionary on the fly
+                        position_dict = create_position_export_dict(col, st.session_state['csv_file'])
+                        st.session_state['export_file'][col] = st.session_state['export_file'][col].map(position_dict)
             
             if 'export_file' in st.session_state:
                 download_port, merge_port, partial_col, clear_export, blank_export_col = st.columns([1, 1, 1, 1, 8])