Acceleration || branching from #68

The issue of acceleration came up in #68 , either by numba or by cython. It seems like we should branch the discussion off into its own issue.

Cython

• Pro: minimal dependencies, pip installable, wheels
• Con: packaging can be tricky, significant developer time required

Numba

• Pro: minimal developer time required
• Con: not pip installable due to LLVM dependency

My two cents: despite the dependency chain problem, I’d prefer numba over cython because it would be easier to deploy across the entire module.

In librosa, we handled this by making the numba dependency optional, and providing a dummy decorator optional_jit that does a no-op if numba is not available, and jit-compilation if it is. That way, everything still works, but if you want to get the acceleration benefits, it’s on you to install numba.

Side note: if we also add conda(-forge) package distribution, we can easily add numba as a hard dependency there.

What do y’all think?

[bmcfee]

Btw, numba now has wheels on pypi, so we probably could make it a hard dependency.

[stefan-balke]

:complain:

😄