celery
RabbitMQ
celery | RabbitMQ | |
---|---|---|
43 | 92 | |
23,498 | 11,608 | |
0.8% | 1.0% | |
9.5 | 10.0 | |
7 days ago | 4 days ago | |
Python | Starlark | |
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)
RabbitMQ
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Building Llama as a Service (LaaS)
Although they did not make it into production, I experimented with the RabbitMQ message broker, Python (Django, Flask), Kubernetes + minikube, JWT, and NGINX. This was a hobby project, but I intended to learn about microservices along the way.
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A Developer's Journal: Simplifying the Twelve-Factor App
Messaging/Queueing Systems (Amazon SQS, RabbitMQ, Beanstalkd)
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FastStream: Python's framework for Efficient Message Queue Handling
Later, we discovered Propan, a library created by Nikita Pastukhov, which solved similar problems but for RabbitMQ. Recognizing the potential for collaboration, we joined forces with Nikita to build a unified library that could work seamlessly with both Kafka and RabbitMQ. And that's how FastStream came to be—a solution born out of the need for simplicity and efficiency in microservices development.
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The Complete Microservices Guide
Inter-Service Communication: Middleware provides communication channels and protocols that enable microservices to communicate with each other. This can include message brokers like RabbitMQ, Apache Kafka, RPC frameworks like gRPC, or RESTful APIs.
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Project Structure Review [.Net] [Console]
This is an implementation of pub/sub. The publisher is on a separate project. The message broker is Azure Service Bus. We use NServiceBus for code implementation. I use rabbitMQ broker for local tests. Nothing I can do about the tech stack. This is more of a high level single project structure review 😅
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The Role of Queues in Building Efficient Distributed Applications
RabbitMQ is a robust and highly configurable open-source message broker that implements the Advanced Message Queuing Protocol (AMQP).
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Should I chain calls in backend?
When using third-party services, especially within a "transaction", it's often a good idea to use a persistent Message Queue (MQ) system like RabbitMQ. Go through all their tutorials to get a really good understanding of how message queues work and how they can be used to solve your problem.
- Node still seems better than python after all this time for web server speed but..
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Delayed events pattern, no more crons
The best technical solution to provide the event queues is to use a message-broker technology like RabbitMQ.
- RabbitMQ 3.12.0 Released
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
Apache Kafka - Mirror of Apache Kafka
mosquitto - Eclipse Mosquitto - An open source MQTT broker
huey - a little task queue for python
MediatR - Simple, unambitious mediator implementation in .NET
nsq - A realtime distributed messaging platform
rq - Simple job queues for Python
BeanstalkD - Beanstalk is a simple, fast work queue.
kombu - Messaging library for Python.