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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 requirepytest
• NumPy versions < 1.15 requirenose

Tests can then be run after installation with:

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