Rqueue
celery
| Rqueue | celery | |
|---|---|---|
| 1 | 43 | |
| 301 | 23,550 | |
| - | 1.1% | |
| 5.4 | 9.5 | |
| about 2 months ago | 3 days ago | |
| Java | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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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.
Rqueue
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Asynchronous task execution using Redis and Spring(Boot)
Rqueue is a broker built for the spring framework that stores data in Redis and provides a mechanism to execute a task at any arbitrary delay. Rqueue is backed by Redis since Redis has some advantages over the widely used queuing systems like Kafka, SQS. In most web applications backend, Redis is used to store either cache data orother purposese. In today's world, 8.4% of web applications are using the Redis database.
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?
EventBus - Event bus for Android and Java that simplifies communication between Activities, Fragments, Threads, Services, etc. Less code, better quality.
dramatiq - A fast and reliable background task processing library for Python 3.
RabbitMQ Java client - RabbitMQ Java client
Apache Kafka - Mirror of Apache Kafka
NATS client - Java client for NATS
huey - a little task queue for python
incubator-dolphinscheduler - Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
Apache Qpid - Mirror of Apache Qpid
rq - Simple job queues for Python
db-queue - Worker-queue implementation on top of Java and database
kombu - Messaging library for Python.