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But Julia doesn't have a good story for anything else besides that.

You can take a Python web server process, have a request call a task that uses NumPy and OpenCV and scikit-learn, get that back, and you're done, all in the same language.

Julia's community does not seem to have aspirations beyond high-performance math code, which is great for its use, but I'm not going to learn Julia just for that when I can implement the entirety of a development pipeline in Python and have all the other niceties that come with it.



That's just not true.

https://github.com/GenieFramework/Genie.jl https://github.com/JuliaWeb/HTTP.jl https://www.youtube.com/watch?v=xsxJt4prFG4

And with upcoming improvements to binary size and structured concurrency (it already does go-like lightweight threads) it will get even better.


A notebook doesn't make for a line-of-business web app.


And the two other links?


I don't know why I didn't see them. I read through the docs with Genie; it seems to be about where Django was 12 years ago as far as feature development goes. Enough to be very productive for some use cases, not sufficiently productive to consider it a step up from the existing tech that's out there.




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