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Async Django in Production (jonathanadly.com)
3 points by jonathan-adly 2 hours ago | hide | past | web | 1 comment | favorite





We have traditionally used Django in all our projects. We believe it is one of the most underrated, beautifully designed, rock solid framework out there.

However, if we are to be honest, the history of async usage in Django wasn't very impressive. You could argue that for most products, you don’t really need async. It was just an extra layer of complexity without any significant practical benefit.

Over the last couple of years, AI use-cases have changed that perception. Many AI products have calling external APIs over the network as their bottleneck. This makes the complexity from async Python worth considering. FastAPI with its intuitive async usage and simplicity have risen to be the default API/web layer for AI projects.

I wrote about using async Django in a relatively complex AI open source project here: https://jonathanadly.com/is-async-django-ready-for-prime-tim...

tldr: Async django is ready! there is a couple of gotcha's here and there, but there should be no performance loss when using async Django instead of FastAPI for the same tasks. Django's built-in features greatly simplify and enhance the developer experience.

So - go ahead and use async Django in your next project. It should be a lot smoother that it was a year or even six months ago.




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