django-concurrency
Optimistic lock implementation for Django. Prevents users from doing concurrent editing. (by saxix)
arq
Fast job queuing and RPC in python with asyncio and redis. (by samuelcolvin)
django-concurrency | arq | |
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1 | 4 | |
424 | 1,959 | |
- | - | |
6.7 | 6.9 | |
4 months ago | 11 days ago | |
Python | Python | |
MIT License | 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.
django-concurrency
Posts with mentions or reviews of django-concurrency.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Any way to buffer or prevent additional client requests until a response is received?
Also a package that might be worth checking out (I've not tried it): https://github.com/saxix/django-concurrency
arq
Posts with mentions or reviews of arq.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-22.
- Future Plan for Arq
- The Many Problems with Celery
-
I made a simple async queueing framework called SAQ! It includes a built in web UI to manage jobs.
I need to process a lot of long running IO heavy jobs with background workers. I've been using ARQ for a while but decided to take a crack at writing my own distributed queue.
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Boilerplates for integration services when you need to sync API resources or databases
Lately I've been writing asynchronous python code and yes, the resource integration problem has come again. Because now from version 1.4 SQLAlchemy has become asynchronous a new boilerplate was created. Now, as a scheduler, I took a completely asynchronous Arq. Considering the specifics of the service, long I/O operations, it seems that the service turned out to be more optimal in asynchronous execution. I haven't measured the performance yet, but I think I'll write another post about it.
What are some alternatives?
When comparing django-concurrency and arq you can also consider the following projects:
celery - Distributed Task Queue (development branch)
saq - Simple Async Queues
celery-sqlalchemy-boilerplate - Boilerplate for services with Celery, SQLAlchemy, Docker, Alembic and Pytest
faust - Python Stream Processing. A Faust fork
Flask-RQ2 - A Flask extension for RQ.
SQLAlchemy - The Database Toolkit for Python
think-async - 🌿 Exploring cooperative concurrency primitives in Python
arq-sqlalchemy-boilerplate
sdk-python - Temporal Python SDK
procrastinate - PostgreSQL-based Task Queue for Python
tasktiger - Python task queue using Redis
msgpack-ruby - MessagePack implementation for Ruby / msgpack.org[Ruby]