And, all of NumPy’s operations take place outside the Python runtime, so they aren’t constrained by Python’s limitations. NumPy provides a specialized array type that is optimized to work ...

NumPy gives Python users a wickedly fast library ... The checks slow down access to the array, however, because every operation has to be bounds-checked. Using the decorators disables those ...

Gommers added, "Really long-term I expect the NumPy 'execution engine' (i.e., the C and Python code that does the heavy lifting for fast array operations) to become less and less relevant ...

However, before we clap ourselves on the back and move on, can we go even faster? Let's change our script a bit and replace the Python list with a NumPy array: import numpy as np list = ...