Numba has support for fast indexing and understands NumPy arrays and infers types for various calls of the NumPy API.


Unfortunately, there are a few pitfalls. We hope to resolve these in the future, and to document them in the meantime:

Operation Example
Boundschecking array[N], with N < 0 or N > array.shape[0]
Wraparound array[-1]
Calls to imported functions

Importing things from numpy

from numpy import zeros

def func():
    array = zeros(...)
Calling without a dtype

Calling zeros, ones or empty without a dtype or with lists

np.zeros((M, N))                  # No dtype!
np.zeros([M, N], dtype=np.double) # Not a tuple or int!

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