Update app.py

app.py

@@ -36,10 +36,6 @@ def process_data(file: gr.File, progress=gr.Progress()) -> Tuple[str, str, pd.Da
 
         # Extract filename without extension
         base_filename = os.path.splitext(os.path.basename(file.name))[0]
-        
-        # Define output paths
-        final_file_path = f'mailmerge {base_filename}.xlsx'
-        base_path = 'mailmerge'
 
         # Step 1: Extract User Information
         user_info = raw_data[['user_id', 'lastname']].drop_duplicates().copy()
@@ -63,9 +59,9 @@ def process_data(file: gr.File, progress=gr.Progress()) -> Tuple[str, str, pd.Da
 
         progress(0.6, desc="Calculating grand totals")
 
-        # Step 4: Generate Filenames and Paths
+        # Step 4: Generate Filenames and Paths (for reference only, not creating actual files)
         user_info['File'] = 'User_' + user_info['Username'] + '_data.csv'
-        user_info['Path'] = user_info['File'].apply(lambda x: os.path.join(base_path, x))
+        user_info['Path'] = 'mailmerge/' + user_info['File']
 
         # Remove extra columns and summary rows
         user_info = user_info[['Username', 'Name', 'Courses', 'Grand Total', 'Email', 'File', 'Path']]
@@ -73,13 +69,7 @@ def process_data(file: gr.File, progress=gr.Progress()) -> Tuple[str, str, pd.Da
         user_info.drop_duplicates(subset=['Username'], inplace=True)
         user_info.sort_values(by='Username', inplace=True)
 
-        progress(0.8, desc="Generating individual CSV files")
-
-        # Generate individual CSV files for each user
-        required_columns = ['course_id', 'course_pk1', 'data', 'event_type', 'internal_handle', 'lastname', 'session_id', 'timestamp', 'user_id', 'system_role']
-        missing_columns = [col for col in required_columns if col not in raw_data.columns]
-        if missing_columns:
-            raise ValueError(f"Missing columns for individual CSV files: {', '.join(missing_columns)}")
+        progress(0.8, desc="Generating output files")
 
         # Create a BytesIO object to store the zip file
         zip_buffer = io.BytesIO()
@@ -88,7 +78,7 @@ def process_data(file: gr.File, progress=gr.Progress()) -> Tuple[str, str, pd.Da
             # Save individual CSV files
             for user_id in user_info['Username'].unique():
                 user_data = raw_data[raw_data['user_id'] == user_id][required_columns]
-                user_file_path = f'{base_path}/User_{user_id}_data.csv'
+                user_file_path = f'mailmerge/User_{user_id}_data.csv'
                 zip_file.writestr(user_file_path, user_data.to_csv(index=False))
 
             # Save the final Excel file
@@ -103,7 +93,7 @@ def process_data(file: gr.File, progress=gr.Progress()) -> Tuple[str, str, pd.Da
                 worksheet.write(f'C{last_row + 1}', user_info['Courses'].sum())
                 worksheet.write(f'D{last_row + 1}', user_info['Grand Total'].sum())
             
-            zip_file.writestr(final_file_path, excel_buffer.getvalue())
+            zip_file.writestr(f'mailmerge {base_filename}.xlsx', excel_buffer.getvalue())
 
         zip_buffer.seek(0)
         progress(1.0, desc="Processing complete")
@@ -171,7 +161,10 @@ def update_insights(df: pd.DataFrame, zip_file: Union[io.BytesIO, None]) -> List
         
         user_table = gr.DataFrame(value=df)
         
-        download_button = gr.File(value=zip_file, visible=(zip_file is not None), label="Download Results")
+        if zip_file:
+            download_button = gr.File(value=zip_file, filename="gradebook_results.zip", visible=True, label="Download Results")
+        else:
+            download_button = gr.File(visible=False, label="Download Results")
         
         return [stats_md, users_activity_chart, users_courses_chart, scatter_plot, user_table, download_button]
     except Exception as e: