The wrong way to speed up your code with Numba
If your NumPy-based code is too slow, you can sometimes use Numba to
speed it up. Numba is a compiled language that uses the same syntax as
Python, and it compiles at runtime, so it’s very easy to write. And
because it re-implements a large part of the NumPy APIs, it can also
easily be used with existing NumPy-based code.
However, Numba’s NumPy support can be a trap: it can lead you to missing
huge optimization opportunities by sticking to NumPy-style code. So in
this article we’ll show an example of:
- The wrong way to use Numba, writing NumPy-style full array transforms.
- The right way to use Numba, namely
forloops.
An example: converting color images to grayscale
Consider a color image encoded with red,