Enhance the existing Python-based automation project to improve performance, efficiency, reporting, and handling of large datasets in a live environment. Optimize the current Python project build to reduce the size of the generated .exe file. Remove unnecessary dependencies and unused libraries. Use efficient packaging methods (e.g., minimizing bundlefiles, compression techniques). The automation currently reads data from Excel. Modify the system to: Continuously update and maintain a real-time processing report in Excel. Log each processed record with status (Success / Failed / Pending). Ensure data integrity (no duplication or overwriting issues). Skip Already Processed Records Before processing, the system should: Check the Excel report/log file. Identify records that are already processed. Skip those records automatically. Only unprocessed or failed records should be picked in the next run. Full Portal Data Processing (All Pages) The automation must: Process all available records on the portal. Handle multiple pages (pagination) automatically. Ensure no data is skipped due to page limits. Smooth & Stable Execution Improve overall stability and performance: Handle exceptions and errors properly. Add retry mechanisms where required. Avoid crashes or freezing during execution. Optimize speed without overloading the system Logging & Monitoring Maintain a proper logging system: Execution logs (start time, end time, errors). Record-level logs. Logs should help in debugging and tracking issues easily. Expected Outcome Smaller EXE file size. Faster and smoother automation execution. Reliable Excel reporting system. No duplicate processing. Complete coverage of all portal records across pages.