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is it any different or comparable to numba or pyjion? Not following python closely in recent years but I recount those two projects with huge potential



I don’t know Pyjion, but I have used Numba for real work. It’s a great package and can lead to massive speed-ups.

However, last time I used it, it (1) didn’t work with many third-party libraries (e.g. SciPy was important for me), and (2) didn’t work with object-oriented code (all your @njit code had to be wrapped in functions without classes). Those two has limited for which projects I could adopt Numba in practice, despite loving it in the cases it worked.

I don’t know what limitations the built-in Python JIT has, but hopefully it might be a more general JIT that works for all Python code.


FWIW, I use numba's (experimental) jitclass pretty successfully in my projects.

(Actually a monkey-patched version to be able to set njit arguments)




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