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By mswatcher
via jakevdp.github.io
Submitted: May 10 2014 / 05:35

We've all heard it before: Python is slow. When I teach courses on Python for scientific computing, I make this point very early in the course, and tell the students why: it boils down to Python being a dynamically typed, interpreted language, where values are stored not in dense buffers but in scattered objects. And then I talk about how to get around this by using NumPy, SciPy, and related tools for vectorization of operations and calling into compiled code, and go on from there.
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