requests-html VS Scrapy

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.

BeautifulSoup4 Scrapy

While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects.

If you're looking for a turn-key solution, I'd have to dig a little. I generally write a scraper in python that dumps into a database or flat file (depending on number of records I'm hunting).

Scraping is a separate subject, but once you write one you can generally reuse relevant portions for many others. If you can get adept at a scraping framework like Scrapy you can do it fairly quickly, but there aren't many tools that work out of the box for every site you'll encounter.

Once you've written the spider, it's generally able to be rerun for updates unless the site code is dramatically altered. It really comes down to how brittle the spider is coded (i.e. hunting for specific heading sizes or fonts or something) instead of grabbing the underlying JSON/XHR that doesn't usually change frequently.

1. https://scrapy.org

Scrapy capitalizes headers for request

Scrapy is a web scraping toolkit

I know this might not be a good answer, as it's not .NET, but we use https://scrapy.org/ (Python).