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Latest commit 26af0ce @njsmith njsmith Merge pull request #7105 from seberg/writeable-as-strided
DEP: Deprecate as_strided returning a writable array as default
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benchmarks BENCH: Add some benchmarks for `matmul`.
branding/icons add .gitattributes and fix line endings
doc DOC: update sphinxext to numpydoc 0.6.0
numpy Merge pull request #7105 from seberg/writeable-as-strided
tools TST: test installing from sdist on TravisCI.
.gitattributes TST: Add tests for Python2, Python3 *.npy compatibility.
.gitignore BLD: finish handling of setuptools commands.
.gitmodules Add Numpydoc as a git submodule
.mailmap MAINT: Update the git .mailmap file.
.travis.yml TST: Bump `virtualenv` to 14.0.6. MAINT give pointers to coding style and dev environment
INSTALL.rst.txt DOC: update Python versions requirements in the install docs
LICENSE.txt Updated copyright to 2016 BUG: fix TravisCI test issues when using setuptools unconditionally. DOC: update min nose version in import error message, and add note to…
THANKS.txt ENH: core: Start einsum function, add copyright notices to files
appveyor.yml TST: Enable AppVeyor failure to be reported. REL: Update master branch after 1.12.x branch has been made. TST: de-uglify the setuptools appeasement in a bit. BLD/BUG: revert usage of setuptools when building an sdist.
site.cfg.example ENH: enabled extra_link_args in OpenBLAS segment
tox.ini TST: Add Python 3.4 to Tox environments


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:

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