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> things I think are done most poorly in Python

For ML stuff there’s no way around using Python (pytorch, TensorFlow, etc. etc.). While I appreciate that ML researchers make their models available to run locally, if you’ve ever run LLMs or SD, it’s very clear the focus is on getting models out of the door before others. But man is it a hot mess: every model needs its own Python version/installation from various sources (OS provided, github, package repos, python.org downloads, etc.), the code bases being rife with dozens of module and environment managers and other meta crap that obviously doesn’t cut it, Python devs using a dynamic language but then want types/annotations badly, etc etc. Sorry but from a SW engineering PoV, Python is pure and utter trash (it started life as a better BASIC for learning after all). I’m particularly puzzled by developers choosing/advocating Python for system administration and as shell replacement who now have to ship a locked–down Python version and package repo such as RedHat and Apple.

Perl 5 code, by virtue of being frozen for over ten years in anticipation of what’s now called Raku, has a slightly better chance to run OOTB. But there’s no guarantee: recently came accross 2000ish Perl code using jcode (lib for Shift-JIS and other CJK two byte encoding) that I couldn’t run because jcode uses hashing sigills that were removed from Perl since or something.




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