celery
NATS
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celery | NATS | |
---|---|---|
43 | 104 | |
23,299 | 14,561 | |
1.4% | 2.4% | |
9.6 | 9.8 | |
about 16 hours ago | 6 days ago | |
Python | Go | |
GNU General Public License v3.0 or later | 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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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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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)
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Dedicated backend resources per client
A different approach would be to have a main web application which would communicate with worker processes for time intensive operations as you describe. The web app would communicate with workers via some form of MQ or even database. Many solutions exists for that in different languages, one such solution is [Celery](https://github.com/celery/celery) primarily developed for Python but these days it also supports Node, Go, PHP and Rust.
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Alternative for Django Celery.
Django-q2 only requires one dependency (except for Django itself). Celery, requires quite a few: https://github.com/celery/celery/blob/master/requirements/default.txt
NATS
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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 !
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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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High-Performance server for NATS.io, the cloud and edge native messaging system
Ahh, they may work on QUIC this year: https://github.com/nats-io/nats-server/issues/457
TIBCO Rednezvous, https://www.tibco.com/products/tibco-rendezvous, is the first thing that came to my mind from previous experience in the financial industry working with real-time market data. Although I'm not sure if it has built-in KV support for dealing with large payloads like NATS does, TIBCO RV and their related software packages are worth checking out to see what an long time established commercial product offers. Which leads me to...
... the protocol is text-based like HTTP with CR LF for field both for the client, https://docs.nats.io/reference/reference-protocols/nats-prot..., and cluster protocols, https://docs.nats.io/reference/reference-protocols/nats-serv... -- which means encoding overhead if your payloads are binary. So depending on your definition of performance, ymmv.
I really do not see how implementing an API across multiple languages is easier by making a new linefeed-based protocol, https://github.com/nats-io/nats-server/blob/0421c65c888bf381..., than just using code-generated JSON or gRPC (Protobuf or Flatbuffers). One could then write subscriptions/clustering algorithms in a protocol-neutral library.
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Message broker for simple strings, sockets
NATS https://nats.io
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The power of PURISTA TypeScript Framework v1.7
PURISTA v1.7 integrates NATS, a lightweight and high-performance messaging system, as a message broker option. This integration simplifies message transmission and enhances the overall messaging capabilities of your application. Say goodbye to communication bottlenecks and hello to seamless microservice interactions.
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Small EDA/Micro service Project
Nats is a good one
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
Apache Kafka - Mirror of Apache Kafka
huey - a little task queue for python
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
rq - Simple job queues for Python
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
ZeroMQ - ZeroMQ core engine in C++, implements ZMTP/3.1
Apache ActiveMQ - Mirror of Apache ActiveMQ
nsq - A realtime distributed messaging platform
kombu - Messaging library for Python.
arq - Fast job queuing and RPC in python with asyncio and redis.