NumPy, the Python package for scientific computing, is an adolescent with prospects for a prolific maturity.

Learn how this popular Python library accelerates math at scale, especially when paired with tools like Cython and Numba.

Unlike R, Python has no clear “winning” IDE. We recommend Spyder because it is well-designed for scientific computing and the popular packages associated with this type of work (NumPy, SciPy, pandas, ...

[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and ...