django-rq VS huey

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

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.

____

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