Not really an issue, it’s MIT licensed, worst case there can just be a community fork.

high performance computing

Pure python will likely never be used for that, but python already is used in HPC mostly as a DSL over native code.

There’s really no reason why you couldn’t write a bunch of python that produces a lazy compute graph that can be compiled or optimized under the hood for HPC right now.

The removal of the GIL just makes some stuff a lot easier to parallelize at the python level. Multiprocessing can have a lot of overhead and this would be a nice way to scale up a little.

I’m personally using pixi and ruff. Pixi is the first tool in the python ecosystem to solve all my package management woes (and runs fast). They’re conda based though (but they’re working on doing solves across pypi and conda).

I see typechecking as the next natural extension to this. Won’t be easy, it’s probably the trickiest thing to do well, but it would be the ultimate python tool if it did that. It’s a natural extension point as well, since they have the parsing down.