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()'
