Every month I pull the upcoming-race calendar from runabc.co.uk and drop the details into Excel. I now want to automate that job with a simple, browser-based tool I can open, click “Run”, and immediately download the latest spreadsheet. Core workflow • The script visits runabc.co.uk, collects the race name, date, distance, and organiser for every listing currently published. • It outputs a clean .xlsx file that matches those four columns exactly. • On each run the program compares the fresh scrape to the previous file and clearly flags any new races so I can spot additions at a glance (colour fill, extra column, or other visual cue—whichever you find most robust). Requirements and environment – Must run online: a lightweight web app or hosted script I can access from any browser without installing anything on my MacBook. If you prefer, you can still package the code so I could also run it locally later. – Technology is up to you; Python with BeautifulSoup/Scrapy, Pandas, and a tiny Flask front end feels natural, but I’m open to alternatives as long as I receive the documented source code. – The solution should cope gracefully with site-structure changes; please keep the scraping logic modular so that small tweaks are easy. – Include clear setup notes plus a short README on how the change-detection works and where to drop last month’s file if the app isn’t storing history automatically. Deliverables 1. Fully commented source code. 2. Deployed online instance or deployment script (Docker, Heroku, etc.). 3. Sample Excel output demonstrating the “new entry” highlight. 4. Quick user guide. If you have experience with similar web-data extractors and Excel automation, I’d love to see a brief example. Let me know your proposed stack and timeline and we can get started right away.