NumPy is the fundamental package needed for scientific computing with Python.

• Website: https://www.numpy.org
• Documentation: http://docs.scipy.org/
• Mailing list: https://mail.python.org/mailman/listinfo/numpy-discussion
• Source code: https://github.com/numpy/numpy
• Contributing: https://www.numpy.org/devdocs/dev/index.html
• Bug reports: https://github.com/numpy/numpy/issues
• Report a security vulnerability: https://tidelift.com/docs/security

It provides:

• a powerful N-dimensional array object
• sophisticated (broadcasting) functions
• tools for integrating C/C++ and Fortran code
• useful linear algebra, Fourier transform, and random number capabilities

Testing:

• NumPy versions ≥ 1.15 require pytest
• NumPy versions < 1.15 require nose

Tests can then be run after installation with:

python -c 'import numpy; numpy.test()'