But that's the same with Excel: massive usage for throwaway projects with loose or non-existing requirements or performance bounds that end-up in production. Python is widely used, but not for substantial programming in large projects - say, projects over 100 kloc. Python hit the "quick and dirty" sweet spot of programming.

This is absolutely not true. I’ve made my living working with Python and there’s an astounding amount of large Python codebases. Onstage and YouTube alone have millions of lines of code. Hedge funds and fintechs base their entire data processing workflows around Python batch jobs. Django is about as popular as Rails and powers millions of websites and backends.

None of those applications are toys. I have no idea where your misperception is coming from.

I guess I'm more than a little prejudiced from trying to maintain all sorts of CI tools, web applications and other largeish programs somebody initially hacked in Python in an afternoon and which grew to become "vital infrastructure". The lack of typing bytes you hard and the optional typing that has been shoehorned into the language is irrelevant in practice.

All sorts of problems would simply have not existed if the proper language was used from the beginning, as opposed to the one where anyone can hack most easily.