django-rq VS celery

For simple stuff, I tend to use https://github.com/rq/django-rq. Although scheduling tasks there does not work well in my experience. If I need something to run by schedule, than better just plain cron.

Performing tests on student images can be a time-consuming process, taking several minutes. Application has to download the image from the registry, create a container, wait for the application to load, and perform the test scenarios. To efficiently utilize the available hardware and handle increased server demand during peak times, a task queue was implemented using django-rq.

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

I use RQ (Redis Queue) and it's very cool! https://github.com/rq/django-rq https://python-rq.org/patterns/django/

I love the simplicity of this idea because for lots of sites the database works just fine as a queue backend and it reduces the amount of infrastructure needed. I currently use https://github.com/dabapps/django-db-queue for devmarks.io which also uses the database to store tasks instead of a dedicated queue infrastructure. `Django Q` also has an option to use the database, but I haven't tested it at all: https://django-q.readthedocs.io/en/latest/configure.html#orm. And if you are already running `redis` for your site, https://github.com/rq/django-rq is another option.

The one benefit of this package is that it is async-first which will be beneficial as Django continually adds in more async capabilities. Nice work! I'm looking forward to trying this out and seeing how it works!

https://github.com/rq/django-rq if you already have redis available or https://github.com/dabapps/django-db-queue for something even simpler. I’ve used both and vastly prefer them over celery.

if you use redis there is https://github.com/rq/django-rq as well

So this might be my understanding, but stuff like celery is more like an orchestrator that chunks up workloads (think Hadoop with multiple nodes).

In the Django world, you'd probably rely on Celery to do this for you. You're probably looking for something similar that works with Go. https://github.com/celery/celery

I've been doing some research and there doesn't seem to be much information on this issue, aditionally there's this but without a fix yet or any workaround: https://github.com/celery/celery/issues/7792

RabbitMQ Classic mirror queues are very fragile to network partitioning. They are deprecated in favor of Quorum queues, but Celery doesn't support them yet : https://github.com/celery/celery/issues/6067

The Celery package provides some number of (undocumented!) result backends to store task results in different local, network, and cloud storages. The django-celery-result package adds options to use Django-specific ORM-based result storage, as well as Django-specific cache subsystem.

I spent 3 years building a high scale crawler on top of Celery.

I can't recommend it. We found many bugs in the more advanced features of Celery (like Canvas) we also ran into some really weird issues like tasks getting duplicated for no reason [1].

The most concerning problem is that the project was abandoned. The original creator is not working on it anymore and all issues that we raised were ignored. We had to fork the project and apply our own fixes to it. This was 4 years ago so maybe things improved since them.

Celery is also extremely complex.

I would recommend https://dramatiq.io/ instead.

[1]: https://github.com/celery/celery/issues/4426

You can use celery to process the file for extraction, saving and creating rar/zip.

Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)