[adgjlsfhk1]

IMO the python JIT support won't help very much. Python currently is ~50x slower than "fast" languages, so even if the JIT provides a 3x speedup, pure python will still be too slow for anything that needs performance. Sure it will help on the margins, but a JIT can't magically make python fast.

[catgary]

I’m only really thinking about ML/scientific computing workflows where all the heavy lifting happens in jax/torch/polars.

[adgjlsfhk1]

right and in those cases, a python JIT will do nothing for your performance because all the computation is happening in C/CUDA anyway.

[physicsguy]

It depends on whether you’re transforming data out of files or whatever to get it into these libraries to start with to be fair. Overall I wouldn’t expect that to have an effect on a long-running computation but when starting up a project it can be a bit slow.