Indeed! Converting one's entire code base to a different language ecosystem, finding equivalents to each of your third-party dependencies, is less painful than employing a library to selectively compile a few performance bottlenecks in your code.

(Modules like PyJulia facilitate a more incremental approach.)

/s

That's why you should switch before creating the codebase in the first place.

I don't recommend Julia for anything critical to production.

I would. It's much safer than Python which has a package ecosystem that is known to be critically unsafe. https://pytorch.org/blog/compromised-nightly-dependency/ is just the latest example of security issues it's been having, https://moyix.blogspot.com/2022/09/someones-been-messing-wit... is general numerical incorrectness which is non-local and cannot be turned off, and that's not even getting to the specific inaccuracies of Numba. I'd switch away from a numerically incorrect security issue today!