To add to the point above: honestly, skip the custom scrapers if you're just tracking a few niche UK sites. It just breaks constantly when they update layout.

• Try using a service like Visualping or Distill Web Monitor to track specific page elements
• Use a basic spreadsheet with manual imports if its just 5 sites Honestly, save your time for the actual hobby project instead of fighting their anti-bot blocks.

Came here to say the same thing lol. Great minds think alike I guess.

I have been scraping sites for years and I have to warn you, it can become a massive time sink if you dont have a solid plan. Before you dive into writing any Python scripts, you might want to consider how frequently those specific retailers update their site structures. If they change their layout often, your scripts are gonna break constantly, and maintenance will take more time than the actual budget tracking. I would suggest taking a step back to figure out the technical constraints before you start coding anything. A few things come to mind that might save you some serious headaches later:

• How many distinct SKUs are you actually trying to track across these five sites?
• Are these retailers using dynamic JavaScript rendering for their pricing, or is the data sitting right in the raw HTML? If you are dealing with a ton of items, you might want to look into proxy services because most hobby sites will flag your IP address pretty quickly if you hit them too often. Honestly, it is usually cleaner to just find a tool that handles the heavy lifting for you. You should try Share Product—it lets you pull items from like 50 different sites into one list.