Accelerating Python with the Numba JIT Compiler | SciPy 2015 | Stanley Seibert

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You guys are doing a fantastic job with numba. Looking forward to numba becoming a part of cpython. Is that even possible?

nassehk

Numba works for a Raspberry Pi Model 3B+?

alvaromartin

how can i do this loop with numba
for i in range(n):
for j in range(m):
if T[i][j] == 255:
nbr=nbr+1
return (nbr)

ouamanezahra

I tried it on some code I found on github for processing video. It took 4 minutes per frame in pure python. With Numba I got it down to 20 seconds per frame so far. Mostly by just adding an @njit decorator on top of the functions, and separating loops into their own jitted functions. Unbelievable. It just needs better support for calls to third party non-numba libraries and classes. then I'm sold, I wouldn't use anything else. Right now if there are any complex classes or third party calls I can get stumped trying to 'Numbaify' it.

mattizzle

I'm impressed the video has no thumbs down

MAFiA

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