parsel VS colly

variable.css(".X5PpBb::text").get() # returns a text value variable.css(".gs_a").xpath("normalize-space()").get() # https://github.com/scrapy/parsel/issues/192#issuecomment-1042301716 variable.css(".gSGphe img::attr(srcset)").get() # returns a attribute value variable.css(".I9Jtec::text").getall() # returns a list of strings values variable.xpath('th/text()').get() # returns text value using xpath

Something I don't see discussed when this topic is brought up is that Scrapy's HTML parsing library, parsel, can be installed separately from scrapy itself. You can use it in place of beautifulsoup and, imo, it's much easier to use.

github.com/gocolly/colly - popular and widely-used library for web scraping in Go. It provides a higher-level API than net/http and makes it easier to extract information from websites. It also provides features such as concurrency, automatic request retries, and support for cookies and sessions.

http://go-colly.org/ is excellent

I wrote a script in Go to scrape jobs from these companies. If you are interested in writing scraper with Go, check out http://go-colly.org/ a potent tool for scraping in Go. I scrape every day just to keep up to date with the jobs.

Website: https://go-colly.org/

in addition the article mention that "Also, C++ is not good for creating web crawlers, is programming language is great for simple web scraping" but in reality when you need a fast and performant crawler C++ will be beat languages like ruby and python from performance perspective , the same for golang programming language which will perform better most of the programming languages written on the article and has bunch of very good libraries like http://go-colly.org/ in addition to the https://pkg.go.dev/net/http which comes part of the core

Strange that the author didn’t mention the most popular and, frankly, convenient way: Colly.