In this video I introduce the absolute minimum you need to know about Numba which is a just in time compiler for a subset of Python and Numpy. The first half of the video is dedicated to a basic intro and to highlighting a number of very common mistakes people make when using Numba. The remaining video presents a real world-ish simulation problem, shows up to a 1000x acceleration with Numba in both single and multithreaded cases, and concludes with a “reading list” for learning more about Numba.

Channel github:

Find the notebook here:

Deeper topics to discover here

Supported python and numpy features

Important differences from python

Defining types to compile at definition time:

Function factories

Experimental version of jitted classes


Dealing with types

Ahead of time compilation for deployment

Using approximate fastmath

Deeper control of threading via tbb and/or omp

Easily put your computation on a GPU!


#numba #programming #python

#python #programming

Numba makes Python 1000x faster!
77.45 GEEK