gevent
gunicorn
gevent | gunicorn | |
---|---|---|
5 | 17 | |
6,163 | 9,517 | |
0.2% | - | |
8.7 | 8.0 | |
3 months ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
gevent
-
Is anyone using PyPy for real work?
A sub-question for the folks here: is anyone using the combination of gevent and PyPy for a production application? Or, more generally, other libraries that do deep monkey-patching across the Python standard library?
Things like https://github.com/gevent/gevent/issues/676 and the fix at https://github.com/gevent/gevent/commit/f466ec51ea74755c5bee... indicate to me that there are subtleties on how PyPy's memory management interacts with low-level tweaks like gevent that have relied on often-implicit historical assumptions about memory management timing.
Not sure if this is limited to gevent, either - other libraries like Sentry, NewRelic, and OpenTelemetry also have low-level monkey-patched hooks, and it's unclear whether they're low-level enough that they might run into similar issues.
For a stack without any monkey-patching I'd be overjoyed to use PyPy - but between gevent and these monitoring tools, practically every project needs at least some monkey-patching, and I think that there's a lack of clarity on how battle-tested PyPy is with tools like these.
- SynchronousOnlyOperation from celery task using gevent execution pool on django orm
-
How to Choose the Right Python Concurrency API
I'm not sure how much it replicates the CSP model, but the closest thing I've found to Go-style concurrency in Python is gevent: https://github.com/gevent/gevent
I personally still prefer to use it in all my projects.
-
I have a problem with installing Ajenti on a 64bit Ubuntu 21.04 server
Greenlet seems to have some troubles compiling with Python 3.9. https://github.com/gevent/gevent/issues/1627
gunicorn
-
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
-
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
-
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.
-
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
-
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.
-
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.
-
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?
eventlet - Concurrent networking library for Python
waitress - Waitress - A WSGI server for Python 3
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Werkzeug - The comprehensive WSGI web application library.
Faust - Python Stream Processing
bjoern - A screamingly fast Python 2/3 WSGI server written in C.
Thespian Actor Library - Python Actor concurrency library
uwsgi - Official uWSGI docs, examples, tutorials, tips and tricks
kombu - Messaging library for Python.
meinheld - Meinheld is a high performance asynchronous WSGI Web Server (based on picoev)
Tomorrow - Magic decorator syntax for asynchronous code in Python
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.