Numba is an accelerator library for Python, which just-in time compiles Python code into fast machine code. If used right, its performance can be close to optimized C code. Moreover, it supports offloading of kernels to GPU devices and shared memory parallelism.
The following example from the Numba homepage provides a very first idea of what Numba does.
from numba import njit, jitfrom numpy import arange# jit decorator tells Numba to compile this function.# The argument types will be inferred by Numba when function is called.@jit(nopython=True)def sum2d(arr): M, N = arr.shape result = 0.0 for i in range(M): for j in range(N): result += arr[i,j] return resulta = arange(9).