For instance, if we wanted to take x1 and use np.add to sum the array, ... with specializations for things like NumPy. Loops in Python over NumPy arrays can be optimized automatically this way.

Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in matrixes. If you want, for instance, ...

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, and the ...

NumPY also uses external standard, optimized libraries written in C or FORTRAN to handle many of the actual manipulations on these array data types. This is handled by libraries like BLAS or lapack.