watermill VS celery

I’ve successfully worked on projects using an asynchronous event-driven way of connecting services. I really like the decoupling of business logic and the events triggering it. I highly recommend https://github.com/ThreeDotsLabs/watermill to be more flexible when it comes to choosing the actual technology driving the async patter. It might be NATS today but requirements might change and you need to change. Watermill prepares you for this.

Highly recommend https://watermill.io lib for building async apps (using among others pub/sub patterns). It greatly decouples your code from the underlying technology and gives you the freedom to choose depending on the environment (e.g dev, prod). For dev or small scale purposes, it supports pub/sub purely based on go channels.

Look at this library: https://github.com/ThreeDotsLabs/watermill

Watermill is a good pubsub abstraction. You can start with native go channels and grow into a cloud pubsub or Kafka/Pulsar if you need to.

These conditions have led me to discover two packages watermill.io and go-kit. Both of these seem to do what I want and I am thinking of implementing the project using watermill and go Chanels and deploying to a server or some sort.

github.com/ThreeDotsLabs/watermill package provides a framework for building event-driven applications. It allows easy communication between independent components by decoupling the sender and the receiver.

My personal favorite tools: - https://github.com/go-kit/ for building services (although it's not necessary a great tool for prototyping) - https://github.com/gorilla/mux router (although it's been recently deprecated, so I'm looking for a similar, maintained library) - https://entgo.io/ ORM - https://watermill.io/ for messaging

Checkout https://watermill.io/

So this might be my understanding, but stuff like celery is more like an orchestrator that chunks up workloads (think Hadoop with multiple nodes).

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

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

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

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.

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

You can use celery to process the file for extraction, saving and creating rar/zip.

Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)