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Comment by l0b0 | Hacker News Reader

Some big Python shops will move to faster languages with static types, stable package management, stable configuration management and well-defined change management.

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I hope that we'll see a raise of crystal (https://crystal-lang.org/) and a serious progress in mypyc (https://github.com/python/mypy/tree/master/mypyc) which provide a nice middle ground.

Similarly Nim (https://nim-lang.org/).

I hope to see Jon Blow's Jai lang released. He's a bright guy who's been griping about performance for years and decided to do something about it. The language has lots of cool features like a way to "compose structs" as well as declare a structure AOS or SOA and have it just work. He's doing private betas and writing a game in it, so by the time it's done, it should be pretty solid. Complies >100k LOC in <1s last I checked.

Except deep learning, most of the exploratory machine learning and data science done with Python is later implemented in Java/Scala.

I've been exploring Swift recently and it has a bunch of advantages: interoparability with Python, statically typed, strong capabilities for defining values, automatic differentiation. There's a lot of inertia though.

Is there a reason to expect this in 2021 more so than in previous years?

Nope, as Python continues to be popular it just increases the rise of tools to manage Python (e.g. Poetry), increase the scalability (e.g. Dash), executable distribution (e.g. python-build-standalone), improve speed for hot code (e.g. numba.jit, mypyc, Cython), etc..

The more people use a language the more they want to solve the weak points of that language by using that language.

That's not going to go away for Python until people joining fields that make Python popular (data science, automation, web api/back-ends) have another language that's more approachable.

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