A tiny 1000 line LLVM-based numeric specializer for scientific Python code.

You really shouldn't use this for anything serious, it's just to demonstrate how you might build one of these things from scratch. There's a lot of untapped potential and low hanging fruit around selective embedded JIT specialization for array expression languages in the SciPython space.

Numpile requires numpy and llvmlite (the latter includes needed LLVM libraries). You can either try to install them using your OS package manager, or alternatively, using pip:

$ pip install llvmlite
$ pip install numpy

import numpy as np
from numpile import autojit


@autojit
def dot(a, b):
    c = 0
    n = a.shape[0]
    for i in range(n):
        c += a[i] * b[i]
    return c


a = np.arange(100, 200, dtype='int32')
b = np.arange(300, 400, dtype='int32')
result = dot(a, b) 
print(result)

Released under the MIT License. Copyright (c) 2015, Stephen Diehl