Python in data is similar to C in systems: it's not the best language for the job, but it was good
enough at a critical point in history that it became the standard by happenstance—there weren't enough things wrong with it to repel the Brownian motion of developers from seeding the ecosystem—and now it's the best language for the job because it's the standard.
> These are rather disingenuous criticisms of python. The utility of any language is measured by its use as a means to some end. It's clear that Python's ecosystem has prospered not just because it's a fad, but because it's actually useful. Not perfect, but useful.
Your criticisms of OP's argument are more disingenuous than OP: no one said Python was a fad or that the ecosystem wasn't useful. See here:
> Python is where all the action is when it comes to data science, llms, and all the rest. So it's the path of the least resistance. And there's a great argument to not challenge that and just do what everybody else does and put your head down and not criticize any of that. Which is why I use it on a few projects. The library ecosystem is great.
They're just saying that Python-the-language isn't their favorite (largely subjective but with a lot of agreement from much of the community) and they mention offhand that Python's package management is a disaster (which is 100% accurate).