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> And when I want Julia’s promise of fast loops, I use Numba. If all the effort gone into Julia had instead been spent on fixing remaining warts in Python workflow for science, we wouldn’t even havee this conversation.

Python is rather a mess. Code written in Python can't be sped up without pain/cost, and apparently it will never support concurrency natively. It also suffers from the bane of weakly typed languages, errors at run time instead of compile time.

I think the sweet spot for a language with most of Python's benefits that fixes many of its glaring warts is enormous.



Python supports thread and process based concurrency. Most optimizations require effort, or they wouldn’t be called optimizations.

It’s not weakly types either: you can’t add a list to a string. It’s dynamically typed.




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