requests-cache VS requests-html

For anyone who goes with requests as your HTTP client, I would highly recommend adding requests-cache for a nice performance boost.

The hardest part is actually running a web scraper at scale and that's where many people fail. We have all of the working pieces - we can find the products and parse the raw data. Time to scale it up! Best tip here is to start off with caching. Using caching libraries like requests-cache or whatever library equivalent will speed up process significantly.

And would you be willing to add some example Terraform config? If you wouldn't mind making a PR for that, it could go under the /examples folder.

requests-html

Ya, thanks for advice. When using requests_html library, I am trying to lower down the speed using response.html.render(timeout=1000), but it raise Runtime error instead on Google Colab: https://github.com/psf/requests-html/issues/517.

For dynamic js, prefer requests-html with xpath selection.

Example: requests-html which has a rather exhaustive README.md, but their dedicated page is not that helpful, if I remember correctly, and currently the domain is suspended.

When it comes to web scraping, the usual people recommend is beautifulsoup, lxml, or selenium. But I highly recommend people check out requests-html also. Its a library that is a happy medium between ease of use as in beautifulsoup and also good enough to be used for dynamic, javascript data where it would be overkill to use a browser emulator like selenium.

Quite possible. If you look at requests-html source code, it is simply one single python file that acts as a wrapper around a bunch of other packages, like requests, chromium, parse, lxml, etc., plus a couple convenience functions. So it could easily be some sort of bad dependency resolution.

What I do is try to see if I can use requests_html first before trying selenium. requests_html is usually enough if I dont need to interact with browser widgets or if the authentication isnt too difficult to reverse engineer.