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rq | huey | |
---|---|---|
27 | 10 | |
9,518 | 4,890 | |
1.2% | - | |
8.3 | 6.6 | |
5 days ago | 21 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rq
Posts with mentions or reviews of rq.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-14.
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Redis Re-Implemented with SQLite
That's pretty cool. Reckon it would work with existing code that calls Redis over the wire for RQ?
https://python-rq.org
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The Many Problems with Celery
https://github.com/rq/rq is to the rescue.
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Keep the Monolith, but Split the Workloads
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/
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SQL Maxis: Why We Ditched RabbitMQ and Replaced It with a Postgres Queue
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/
- Ask HN: Redis Queue Hacks and Questions
- What libraries do you use the most alongside django?
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Recommendations other than celery to send an API processing in background, which would only take 5 mins to process and API usage would be once a month or so.
Yep, rq is simple and good: https://python-rq.org/ It also has a Django wrapper: https://github.com/rq/django-rq
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GPU instance crashes when two python processes use the same pt file
We have a GPU (G5) instance that uses Python RQ (https://python-rq.org/).
- Dynamically update periodic tasks in Celery and Django
- Celery + RabbitMQ alternatives
huey
Posts with mentions or reviews of huey.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-10.
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Nextflow: Data-Driven Computational Pipelines
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/
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Background jobs with Django
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.
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What's the best thing you've learned about Django this year?
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
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This Week in Python
huey – a little task queue for python
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What is your favourite task queuing framework?
Huey -> Same again?
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5 background scheduling libraries in Python you must know
Huey: https://github.com/coleifer/huey
- Celery in production: Three more years of fixing bugs
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Not sure if I should use celery or asyncio
I just want to add that a couple celery alternatives worth looking at include huey and dramatiq.
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What is the best option for a (Python 3) task queue on Windows now that Celery 4 has dropped Windows support?
huey
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Django 4.0 released
same, I ran into an issue cos of django-background-tasks. I am thinking to replace it with huey
What are some alternatives?
When comparing rq and huey you can also consider the following projects:
celery - Distributed Task Queue (development branch)
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
dramatiq - A fast and reliable background task processing library for Python 3.
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
procrastinate - PostgreSQL-based Task Queue for Python
Apache Kafka - Mirror of Apache Kafka
KQ - Kafka-based Job Queue for Python
Flask-RQ2 - A Flask extension for RQ.
django-background-tasks - A database-backed work queue for Django