I guess I generally do like the pythonic paradigm of an interpreted glue language orchestrating precompiled functions written in other languages. I don’t need or want to compile the entire pipeline end to end after every edit, that slows my development iteration cycle times.
I just want to write my own fast compiled functions to insert into the pipeline on the rare occasions I need something bespoke that doesn’t already exist in the extended python ecosystem. It seems like a lower level language would be optimal for that?
If you just need to fill a small and slow gap maybe something like numba is also a good option to stay within python.
Going all the way to a low level language would require the compilation, the glue code and expertise in both languages. Probably that slows down the development pipeline more than the JIT compilation from julia or numba.
Anyway, any opportunity to learn/practice some rust is also great!
That way you leverage a more developed data ecosystem, can call python when necessary and avoid writing low level code.
Depends on the task of course.