fluent
celery
| fluent | celery | |
|---|---|---|
| 1 | 43 | |
| 59 | 23,498 | |
| - | 0.8% | |
| 0.0 | 9.5 | |
| about 2 years ago | 7 days ago | |
| Python | Python | |
| ISC License | BSD 3-clause "New" or "Revised" License |
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.
fluent
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Easy, readable data processing in functional manner using pypely
Yes it works with MPP engines as the package is not used for orchestration purposes. It is meant to encourage a coding paradigm: functional programming. The benefit of the package is that it provides functions that make it easy to apply functional programming to data processing tasks. Similar projects with a different focus are: fluentpy and Pipe
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)
What are some alternatives?
Pipe - A Python library to use infix notation in Python
dramatiq - A fast and reliable background task processing library for Python 3.
rich - Rich is a Python library for rich text and beautiful formatting in the terminal.
Apache Kafka - Mirror of Apache Kafka
pypely - From local functions to cloud deployed pipelines
huey - a little task queue for python
kombu - Messaging library for Python.
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
rq - Simple job queues for Python
arq - Fast job queuing and RPC in python with asyncio and redis.
Sidekiq - Simple, efficient background processing for Ruby