huey VS Streamz

I've considered using Nextflow for bioinformatics pipelines but have yet to take the plunge. At work, I develop a proteomics pipeline that is composed of huey¹ tasks (Python library; simple alternative to Celery) which either use subprocess to call out to some external tool, or are just pure python. It runs in a worker container which is created by docker swarm, and all containers pull jobs from redis. For our scale, it works great. However, I don't have control over the resource utilization of individual steps, and in the past I've had issues with the pipeline blocking as a result of how I was chaining tasks together. I think something like Nextflow would remove these limitations, but one thing I think I would miss is the ability to debug individual pipeline steps locally with an interactive debugger. As far as I can tell, Nextflow has logging/tracing facilities but nothing quite like an interactive debugger. I'd be happy to be told I'm wrong, or even that I'm doing it wrong.

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¹ https://github.com/coleifer/huey/

Other options are DjangoQ and Huey, which tend to work ok. Of the two I prefer DjangoQ. Database backed, don't require the Redis/Celery rigmarole.

Funny, just this moment i finally switched from Celery to huey. And so far I don't regret. huey looks very promising, has good documentation and is well integrated into DJango. You should give it a try: https://github.com/coleifer/huey

huey – a little task queue for python

Huey -> Same again?

Huey: https://github.com/coleifer/huey

I just want to add that a couple celery alternatives worth looking at include huey and dramatiq.

huey

same, I ran into an issue cos of django-background-tasks. I am thinking to replace it with huey

Hi everyone, I am looking into building data pipelines in a way that is as pythonic as possible, I found out about this Streamz project and it integrates well with Dask. Does anyone have any experience using this? My main use would be for fairly simple accumulator pipelines. https://github.com/python-streamz/streamz

The best candidate so far is 'streamz', which is simple and lays out a processor in a pipeline. But it doesn't quite have the same level as built in monitoring as apache camel, for better or worse.

I use https://github.com/python-streamz/streamz + Dask for 100% python distributed mini batch real time processing, so we can import any python libraries and less hustle to deploy the server in production. We processed average 120 GB everyday, CDC from Debezium dan Kafka Connect Oracle Big Data Golden Gate.