celery
Sidekiq
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celery | Sidekiq | |
---|---|---|
43 | 89 | |
23,439 | 12,931 | |
1.4% | 0.4% | |
9.5 | 8.9 | |
2 days ago | 4 days ago | |
Python | Ruby | |
GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
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.
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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)
Sidekiq
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Redis Re-Implemented with SQLite
That depends on how the `maxmemory-policy` is configured, and queue systems based on Redis will tell you not to allow eviction. https://github.com/sidekiq/sidekiq/wiki/Using-Redis#memory (it even logs a warnings if it detects your Redis is misconfigured IIRC).
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3 one-person million dollar online businesses
Sidekiq https://sidekiq.org/: This one started as an open source project, once it got enough traction, the developer made a premium version of it, and makes money by selling licenses to businesses.
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Choose Postgres Queue Technology
Sidekiq will drop in-progress jobs when a worker crashes. Sidekiq Pro can recover those jobs but with a large delay. Sidekiq is excellent overall but it’s not suitable for processing critical jobs with a low latency guarantee.
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We built the fastest CI in the world. It failed
> I'm not sure feature withholding has traditionally worked out well in the developer space.
I think it's worked out well for Sidekiq (https://sidekiq.org). I really like their model of layering valuable features between the OSS / Pro / Enterprise licenses.
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Exploring concurrent rate limiters, mutexes, semaphores
I was studying Sidekiq's page on rate limiters. The first type of rate limiting mentioned is the concurrent limiter: only n tasks are allowed to run at any point in time. Note that this is independent of time units (e.g. per second), or how long they take to run. The only limitation is the number of concurrent tasks/requests.
- Ask HN: What are some of the most elegant codebases in your favorite language?
- Sidekiq and managing resumable jobs?
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Organize Business Logic in Your Ruby on Rails Application
The code above isn't idempotent. If you run it twice, it will create two copies, which is probably not what you intended. Why is this important? Because most backend job processors like Sidekiq don't make any guarantees that your jobs will run exactly once.
- How to mitigate being rate limited by a third party API?
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How to use Sidekiq in Rails 7: Background Jobs
In this blog, we'll explore how to use background jobs with Sidekiq in Rails 7 to handle long-running tasks, including:
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
Resque - Resque is a Redis-backed Ruby library for creating background jobs, placing them on multiple queues, and processing them later.
Apache Kafka - Mirror of Apache Kafka
Sneakers - A fast background processing framework for Ruby and RabbitMQ
huey - a little task queue for python
Shoryuken - A super efficient Amazon SQS thread based message processor for Ruby
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
Sucker Punch - Sucker Punch is a Ruby asynchronous processing library using concurrent-ruby, heavily influenced by Sidekiq and girl_friday.
rq - Simple job queues for Python
kombu - Messaging library for Python.
good_job - Multithreaded, Postgres-based, Active Job backend for Ruby on Rails.