celery VS huey

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)

I've considered using Nextflow for bioinformatics pipelines but have yet to take the plunge. At work, I develop a proteomics pipeline that is composed of huey¹ tasks (Python library; simple alternative to Celery) which either use subprocess to call out to some external tool, or are just pure python. It runs in a worker container which is created by docker swarm, and all containers pull jobs from redis. For our scale, it works great. However, I don't have control over the resource utilization of individual steps, and in the past I've had issues with the pipeline blocking as a result of how I was chaining tasks together. I think something like Nextflow would remove these limitations, but one thing I think I would miss is the ability to debug individual pipeline steps locally with an interactive debugger. As far as I can tell, Nextflow has logging/tracing facilities but nothing quite like an interactive debugger. I'd be happy to be told I'm wrong, or even that I'm doing it wrong.

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¹ https://github.com/coleifer/huey/

Other options are DjangoQ and Huey, which tend to work ok. Of the two I prefer DjangoQ. Database backed, don't require the Redis/Celery rigmarole.

Funny, just this moment i finally switched from Celery to huey. And so far I don't regret. huey looks very promising, has good documentation and is well integrated into DJango. You should give it a try: https://github.com/coleifer/huey

huey – a little task queue for python

Huey -> Same again?

Huey: https://github.com/coleifer/huey

I just want to add that a couple celery alternatives worth looking at include huey and dramatiq.

huey

same, I ran into an issue cos of django-background-tasks. I am thinking to replace it with huey