# <img alt="NumPy" src="https://cdn.rawgit.com/numpy/numpy/master/branding/icons/numpylogo.svg" height="60">

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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 &ge; 1.15 require `pytest`
- NumPy versions &lt; 1.15 require `nose`

Tests can then be run after installation with:

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

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