colly VS rq

SerpApi focuses on scraping search results. That's why we need extra help to scrape individual sites. We'll use GoColly package.

Interesting. Can you compare it to colly? [0]

Last time I looked it was the most popular choice for scraping in Go and I have some projects using it.

Is it similar? Does it have more/less features or is it more suited for a different use case? (Which one?)

[0] https://github.com/gocolly/colly

Sounds cool, but how is this different from Colly: https://github.com/gocolly/colly?

We could write some snippets mixing all these, but the best option in real life is to use a tool with it all, like Scrapy, pyspider, node-crawler (Node.js), or Colly (Go).

Unless you're specifically trying to do it using net/http, I recommend using colly. I've used it in a few scrappers and I love it!

In this blog, we will be covering the basics of web scraping in Go using the Fiber and Colly frameworks. Colly is an open-source web scraping framework written in Go. It provides a simple and flexible API for performing web scraping tasks, making it a popular choice among Go developers. Colly uses Go's concurrency features to efficiently handle multiple requests and extract data from websites. It offers a wide range of customization options, including the ability to set request headers, handle cookies, follow redirects, and more

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.

That's pretty cool. Reckon it would work with existing code that calls Redis over the wire for RQ?

  https://python-rq.org

https://github.com/rq/rq is to the rescue.

We use RQ[0], it has Redis as a dependency. It’s pretty straightforward and we’re very happy with it. If you are using Django you may want to look at Django RQ[1] as well. RQ has built in scheduling capabilities these days, but historically it did not so we used (and still use) RQ Scheduler[2] which I think still has some advantages over the built in stuff.

[0] https://python-rq.org/

Also had a similar experience using RabbitMQ with Django+Celery. Extremely complicated and workers/queues would just stop for no reason.

Moved to Python-RQ [1] + Redis and been rock solid for years now.

[1] https://python-rq.org/

Yep, rq is simple and good: https://python-rq.org/ It also has a Django wrapper: https://github.com/rq/django-rq

We have a GPU (G5) instance that uses Python RQ (https://python-rq.org/).