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Python’s popularity seems to me driven by ML and data science.

Personally, I can’t take seriously any language without a good type system and, no, optional type hints don’t count. Such a type system should express nullability and collection parameterization (ie genetics).

I simply won’t write a lot of code in any language where a typo or misspelling is a runtime error.

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I think you got it backwards: Python was used in ML and data science because it was already one of the preferred languages. A single line can do the work of whole functions in other languages, while remaining clear.

Also, the tooling is abundant and of great quality, it made it the logical choice.

I've been working with python professionally for just over a year now and the main difference from having come from a .net background seems to be that tests are far easier to write and more prevalent in our codebase. I'm sure some of that is cultural, but "runtime" errors are quickly found by any reasonable test suite.

That said, it always saddens me that ML (as in oCaml and F#) don't get more love. They basically can hit all the same bases with ease of readability, multi paradigm, module first programming that python can but just never got the same love.

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