rq-scheduler
celery
Our great sponsors
rq-scheduler | celery | |
---|---|---|
4 | 43 | |
1,386 | 23,498 | |
1.1% | 1.6% | |
2.2 | 9.5 | |
about 2 months ago | about 23 hours ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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-scheduler
- Keep the Monolith, but Split the Workloads
-
RQ-Scheduler for tasks in far future?
RQ-Scheduler is another simpler alternative (rq/rq-scheduler: A lightweight library that adds job scheduling capabilities to RQ (Redis Queue) (github.com)) that appears to be good for such purposes. It's not immediately clear if it would suffer from the same issues, but it seems not (Redis manages issues with data loss well, a separate queue is used for the scheduled tasks, etc.). Is anyone aware of any drawbacks to using RQ-Scheduler for something like this?
- Need direction on how to add asynchronous / scheduled tasks on my flask app running on aws beanstalk
-
Some advice: will my setup be production ready?
Some thoughts: - Storing API keys in Redis with AOF and RDB persistence turned on is going to be way faster than storing those keys in Mongo. - Did you mean RQ (redis-queue)/django-rq? If so, it works well as long as you don't need a scheduler for cron-like tasks, which it doesn't include. You can add rq-scheduler for that though: https://github.com/rq/rq-scheduler - Make sure your redis instance has a password -- redis 6 supports ACLs as well - The problem with slow requests is that they tie up app server processes and usually also database connections. That may be fine with a small number of consumers, but if you point your web site at this API, you may run into problems. Consider that if an app server serving web site traffic is waiting for a slow request to your API, then both app servers are affected -- you're now holding resources on the web site and the API, effectively. - HTTP clients often use a default timeout value for requests, and it's a best practice to use such a timeout -- so you'll need to coach your partners consuming this API not to use timeouts for your API.
celery
-
Streaming responses to websockets with multiple LLMs, am I going about this wrong?
So this might be my understanding, but stuff like celery is more like an orchestrator that chunks up workloads (think Hadoop with multiple nodes).
-
Examples of using task scheduler with Go?
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
- SynchronousOnlyOperation from celery task using gevent execution pool on django orm
-
FastAPI + Celery problem: Celery task is still getting exectued even though I'm raising an exception on task_prerun
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
-
Taskiq: async celery alternative
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
-
Use Celery with any Django Storage as a Result Backend
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.
-
Django Styleguide
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
-
Processing input and letting user download the result
You can use celery to process the file for extraction, saving and creating rar/zip.
-
RQ-Scheduler for tasks in far future?
Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)
What are some alternatives?
fastapi-cloud-tasks - GCP's Cloud Tasks + Cloud Scheduler + FastAPI = Partial replacement for celery.
dramatiq - A fast and reliable background task processing library for Python 3.
django-rq - A simple app that provides django integration for RQ (Redis Queue)
Apache Kafka - Mirror of Apache Kafka
Flask-RQ2 - A Flask extension for RQ.
huey - a little task queue for python
django-rq - A simple app that provides django integration for RQ (Redis Queue) [Moved to: https://github.com/rq/django-rq]
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
supervisor - Supervisor process control system for Unix (supervisord)
rq - Simple job queues for Python
NiceHash-Mining-Scheduler - Schedule the start and stop of your NiceHash miners using this script.
kombu - Messaging library for Python.