celery
NATS
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celery | NATS | |
---|---|---|
43 | 106 | |
23,439 | 14,720 | |
1.4% | 2.4% | |
9.5 | 9.8 | |
8 days ago | 6 days ago | |
Python | Go | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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)
NATS
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Implementing OTel Trace Context Propagation Through Message Brokers with Go
Several message brokers, such as NATS and database queues, are not supported by OpenTelemetry (OTel) SDKs. This article will guide you on how to use context propagation explicitly with these message queues.
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NATS: First Impressions
https://nats.io/ (Tracker removed)
> Connective Technology for Adaptive Edge & Distributed Systems
> An Introduction to NATS - The first screencast
I guess I don't need to know what it is
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Interview with Sebastian Holstein, Founder of Qaze
During our interview, we referred to NATS quite a few times! If you want to learn more about it, Sebastian suggests this tutorial series.
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Sequential and parallel execution of long-running shell commands
Pueue dumps the state of the queue to the disk as JSON every time the state changes, so when you have a lot of queued jobs this results in considerable disk io. I actually changed it to compress the state file via zstd which helped quite a bit but then eventually just moved on to running NATS [1] locally.
[1] https://nats.io/
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Revolutionizing Real-Time Alerts with AI, NATs and Streamlit
Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.
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New scalable, fault-tolerant, and efficient open-source MQTT broker
Why wasn't NATS[1] used ?
Written in Go, single-binary deployment... there's a lot to love about NATS !
[1]https://nats.io/
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Scripting with NATS.io support
require nats.io
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Introducing “Database Performance at Scale”: A Free, Open Source Book
About cost, see [1]. Also, S3 prices have been increasing and there's been a bunch of alternative offers for object store from other companies. I think people in here (HN) comment often about increasing costs of AWS offerings.
Distributed systems and consensus are inherently hard problem, but there are a lot of implementations that you can study (like Etcd that you mention, or NATS [2], which I've been playing with and looks super cool so far :-p) if you want to understand the internals, on top of many books and papers released.
Again, I never said it was "easy" to build distributed systems, I just don't think there's any esoteric knowledge to what S3 provides.
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1: https://en.wikipedia.org/wiki/Economies_of_scale
2: https://nats.io/
- NATS: Connective Technology for Adaptive Edge and Distributed Systems
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Is it an antipattern to use the response channel as identifier
I am in a project were nats.io is used. Someone thought, it would be a great idea to link data in an event with data in a response using the response channel name.
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
Apache Kafka - Mirror of Apache Kafka
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
huey - a little task queue for python
ZeroMQ - ZeroMQ core engine in C++, implements ZMTP/3.1
rq - Simple job queues for Python
Apache ActiveMQ - Mirror of Apache ActiveMQ
kombu - Messaging library for Python.
nsq - A realtime distributed messaging platform
arq - Fast job queuing and RPC in python with asyncio and redis.