Hacker News Reader

Comment by akoumjian | Hacker News Reader

Celery is great and awful at the same time. In particular, because it is many Python folks' first introduction to distributed task processing and all the things that can go wrong with it. Not to mention, debugging can be a nightmare. Some examples:

- your function arguments aren't serializable - your side effects (e.g. database writes) aren't idempotent - discovering what backpressure is and that you need it - losing queued tasks during deployment / non-compatible code changes

There's also some stuff particular to celery's runtime model that makes it incredibly prone to memory leaks and other fun stuff.

Honestly, it's a great education.

View on HN

> your side effects (e.g. database writes) aren't idempotent

What does idempotent mean in this context, or did you mean atomic/rollback on error?

I'm confused because how could a database write be idempotent in Django? Maybe if it introduced a version on each entity and used that for crdt on writes? But that'd be a significant performance impact, as it couldn't just be a single write anymore, instead they'd have to do it via multiple round trips

In the context of background jobs idempotent means that if your job gets run for a second time (and it will get run for a second time at some point, they all do at-least-once delivery) there aren't any unfortunate side effects to that. Often that's just a case of checking if the relevant database updates have already been done, maybe not firing a push notification in cases of a repeated job.

If you need idempotent db writes, then use something like Temporal. You can't really blame Celery for not having that because that is not what Celery aims to be.

With Temporal, your activity logic still needs to ensure idempotency e.g. by checking if an event id / idempotency key exists in a table. It's still at-least-once delivery. Temporal does make it easy to mint an idempotency key by concatenating workflow run id and activity id, if you don't have a one provided client-side.

Temporal requires a lot more setup than setting up a Redis instance though. That's the only problem with it. And I find the Python API a bit more difficult to grasp. But otherwise a solid piece of technology.

Here is a nice guide from AWS https://docs.aws.amazon.com/wellarchitected/latest/framework...

In my experience async job idempotency is implemented as upserts. Insert all job outputs on the first run. Do (mostly) nothing on subsequent runs. Maybe increment a counter or timestamp.

From your experience, what is a better alternative guys?

Not the comment that you replied to but I use my own Urd. It's a fancier Cron that you can stop fast. Which is imo what you normally want.

Task queues are like email. It's what everyone is used to so people ask for more of it, but it's not actually good/the right tool.

There’s no alternative (while prototyping), and anything else is better (when you properly defined your case).

DjangoQ2 is a fine alternative during early development

Reply on news.ycombinator.com