Numpy main repository
C Python Other
Latest commit 90668d0 Aug 25, 2016 @charris charris committed on GitHub Merge pull request #7963 from charris/fix-microsoft-compilers
BUG: MSVCCompiler grows 'lib' & 'include' env strings exponentially.
Failed to load latest commit information.
benchmarks ENH: added axis param for np.count_nonzero Aug 5, 2016
branding/icons add .gitattributes and fix line endings Oct 31, 2010
doc DOC: add cbrt to math summary page Aug 15, 2016
numpy Merge pull request #7963 from charris/fix-microsoft-compilers Aug 25, 2016
tools Avoid NPY_ARRAY_F_CONTIGUOUS for numpy < 1.7 Jun 18, 2016
.gitattributes TST: Add tests for Python2, Python3 *.npy compatibility. Oct 12, 2014
.gitignore BLD: finish handling of setuptools commands. Jan 16, 2016
.gitmodules Add Numpydoc as a git submodule Jul 25, 2013
.mailmap MAINT: Yet more .mailmap updates for recent contributors. Mar 28, 2016
.travis.yml MAINT: use manylinux1 wheel for cython Apr 21, 2016 MAINT give pointers to coding style and dev environment Aug 28, 2015
INSTALL.rst.txt DOC: update Python versions requirements in the install docs Jan 24, 2016
LICENSE.txt Updated copyright to 2016 Jan 1, 2016 BUG: fix TravisCI test issues when using setuptools unconditionally. Jan 16, 2016 Added label icon to Travis status Mar 7, 2016
THANKS.txt ENH: core: Start einsum function, add copyright notices to files Jan 23, 2011
appveyor.yml TST: Install `pytz` in the CI. Feb 25, 2016 REL: Update master branch after 1.12.x branch has been made. Jan 20, 2016 STY: Use consistent variable convention. Jul 25, 2016 MAINT: Cleanp of random stuff May 4, 2016
site.cfg.example BLD: fix configparser.InterpolationSyntaxError Apr 28, 2016
tox.ini TST: Add Python 3.4 to Tox environments Aug 4, 2015

Travis CI Status

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

  • 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.

It derives from the old Numeric code base and can be used as a replacement for Numeric. It also adds the features introduced by numarray and can be used to replace numarray.

More information can be found at the website:

After installation, tests can be run (if nose is installed) with:

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

The most current development version is always available from our git repository: