SCOOP (Scalable COncurrent Operations in Python)
gevent
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| SCOOP (Scalable COncurrent Operations in Python) | gevent | |
|---|---|---|
| - | 5 | |
| 616 | 6,160 | |
| - | 0.3% | |
| 0.0 | 8.7 | |
| about 1 year ago | 2 months ago | |
| Python | Python | |
| LGPL | GNU General Public License v3.0 or later |
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SCOOP (Scalable COncurrent Operations in Python)
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Tracking mentions began in Dec 2020.
gevent
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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
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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.
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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
What are some alternatives?
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.
eventlet - Concurrent networking library for Python
Thespian Actor Library - Python Actor concurrency library
Wallaroo - Distributed Stream Processing
Faust - Python Stream Processing
pyeventbus - Python Eventbus
kombu - Messaging library for Python.
aiochan - CSP-style concurrency for Python
Tomorrow - Magic decorator syntax for asynchronous code in Python