Python has huge uptake outside of the ML domain. I can't see an AI winter affecting the many people using Numpy for non-ML purposes (i.e., scientists in academia, most of whom still deal with normal numerical and data analytical modeling, not ML) much less Django.
I'm...aware. I think a lot of us that aren't using NumPy or ML stuff are rather looking for a good excuse to get away from what the ecosystem has become. (Yeah, I'm still bitter about Py3...Python user since the 1.5.2 days)
I thought the whole Python 3 thing was a huge problem. Lately I've been doing JS/Typescript dev and breaking changes like this happen continually and no one blinks.
The problem was never your code, really, it was the dependencies.
Wasn't that hard for quite a while to find situations where dependency A was Py3 compatible and B was not (and the incompatibility went both ways, especially in early 3.x releases, you could NOT have one codebase that worked with both).
Sometimes A dropped Py2 support before B gained Py3.
Pain pain pain.
Then add the increasing level of insanity as the answer to "python packaging sucks" was repeatedly to add yet another layer.
Plenty of other options out there if you've fallen out of love with Python and don't need good numerical libraries. Give JS, Elixir, or Crystal a try if you want something more dynamic. Nim if you want something a bit off the beaten path. Go, Rust, Java, Kotlin, and Scala if you want something more static.
I meant more like dynamically re-evaluating specific functions without having to restart the process. Haven't done much Erlang, but my experience is around doing so in lisp rather, which definitely can do that.
