node-crawler VS rq

web crawlers: these are applications that systematically map all of the links on websites, and create a searchable index. A popular JS tool here is node-crawler.

Before you write your own library for crawling, try some of the options out there. Many great Open Source libraries can achieve it: Scrapy, pyspider, node-crawler (Node.js), or Colly (Go). And many companies and services that provide you with scraping and crawling solutions.

We could write some snippet mixing all of 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). The idea being the snippets is to understand each problem on its own. But for large-scale, real-life projects, handling everything on our own would be too complicated.

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/).