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

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


  • 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()'

Call for Contributions

NumPy appreciates help from a wide range of different backgrounds. Work such as high level documentation or website improvements are valuable and we would like to grow our team with people filling these roles. Small improvements or fixes are always appreciated and issues labeled as easy may be a good starting point. If you are considering larger contributions outside the traditional coding work, please contact us through the mailing list.

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