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| rq | KQ | |
|---|---|---|
| 27 | 1 | |
| 9,518 | 567 | |
| 1.2% | - | |
| 8.3 | 0.0 | |
| 5 days ago | about 2 years 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.
-
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 -
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
KQ
Posts with mentions or reviews of KQ.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Microservice design question
I would start with https://kq.readthedocs.io/ this for background task. I would also try using some asyncio stack as next option.
What are some alternatives?
When comparing rq and KQ you can also consider the following projects:
celery - Distributed Task Queue (development branch)
huey - a little task queue for python
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
Streamz - Real-time stream processing for python
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
procrastinate - PostgreSQL-based Task Queue for Python
django-background-tasks - A database-backed work queue for Django
Apache Kafka - Mirror of Apache Kafka
kombu - Messaging library for Python.