celery
gunicorn
celery | gunicorn | |
---|---|---|
43 | 17 | |
23,498 | 9,517 | |
0.8% | - | |
9.5 | 8.0 | |
7 days ago | 6 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" 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.
celery
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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).
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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
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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
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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
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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.
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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
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Processing input and letting user download the result
You can use celery to process the file for extraction, saving and creating rar/zip.
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RQ-Scheduler for tasks in far future?
Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)
gunicorn
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Nginx Unit – Universal web app server
I'm hoping so – gunicorn has a long-open pull request that would fix `--reuse-port`, which currently does nothing
https://github.com/benoitc/gunicorn/pull/2938
- SynchronousOnlyOperation from celery task using gevent execution pool on django orm
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Deploying Django when using python-socketio
However, I'm curious about the best way to deploy, specifically with regard to WSGI. I've tried using the raw eventlet WSGI server (`eventlet.wsgi.server(eventlet.listen(("", 8000)), application)`). I then start it with `python manage.py runserver`. This has worked okay, but I'm unsure about how scalable it is. It seems like the standard stack is Django + Gunicorn + NGINX. Based on `python-socketio` documentation, this should be possible. I tried django + eventlet + gunicorn, but it seems like gunicorn a) [doesn't play nice with eventlet](https://github.com/benoitc/gunicorn/pull/2581) and b) only supports one worker. Gevent + Gunicorn doesn't have this bug, but still only supports one worker. Also, I'm not sure how actively maintained gevent is. So I'm not sure how scalable either Gunicorn + eventlet or Gunicorn + geventlet is as a WSGI server. So I'm not sure if Gunicorn is my best bet, or if it's too limited.
- The Django ecosystem is not so good
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3 cool project ideas for Python programmers
For building your API, I recommend using the Flask library. It is very beginner-friendly, and you will be able to build a simple API in a matter of minutes! Keep in mind that, for a more serious project, you should definitely use something like gunicorn to run you API as a production server.
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Django 4.1 Released
Interesting looks like it might actually be a python bug. Somehow just changing from sys.exit(0) -> os._exit(0) apparently fixes it.
https://github.com/benoitc/gunicorn/pull/2820
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Serverless Templates for AWS and Python
The cool thing is that you can easily migrate your WSGI- application such as Flask, Django, or Gunicorn to AWS.
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Scope of database threads + connections + sessions
Yeah, that's kind of the impression I was getting. I stumbled across a github issue for gunicorn along these lines.
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Running Django with Gunicorn - Best Practice
Taking a glimpse at gunicorn's code it looks like they pretty much all do the same: 2. seems to be creating a wsgi app using django's internals, and 3. uses 2.
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
waitress - Waitress - A WSGI server for Python 3
Apache Kafka - Mirror of Apache Kafka
Werkzeug - The comprehensive WSGI web application library.
huey - a little task queue for python
bjoern - A screamingly fast Python 2/3 WSGI server written in C.
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
uwsgi - Official uWSGI docs, examples, tutorials, tips and tricks
rq - Simple job queues for Python
meinheld - Meinheld is a high performance asynchronous WSGI Web Server (based on picoev)
kombu - Messaging library for Python.
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.