CofeehousePy/deps/numpy
Netkas 43c9aa1cac Added numpy 2021-01-12 22:41:40 -05:00
..
.circleci Added numpy 2021-01-12 22:41:40 -05:00
.dependabot Added numpy 2021-01-12 22:41:40 -05:00
.github Added numpy 2021-01-12 22:41:40 -05:00
benchmarks Added numpy 2021-01-12 22:41:40 -05:00
doc Added numpy 2021-01-12 22:41:40 -05:00
numpy Added numpy 2021-01-12 22:41:40 -05:00
tools Added numpy 2021-01-12 22:41:40 -05:00
.codecov.yml Added numpy 2021-01-12 22:41:40 -05:00
.coveragerc Added numpy 2021-01-12 22:41:40 -05:00
.ctags.d Added numpy 2021-01-12 22:41:40 -05:00
.gitattributes Added numpy 2021-01-12 22:41:40 -05:00
.gitignore Added numpy 2021-01-12 22:41:40 -05:00
.gitmodules Added numpy 2021-01-12 22:41:40 -05:00
.lgtm.yml Added numpy 2021-01-12 22:41:40 -05:00
.mailmap Added numpy 2021-01-12 22:41:40 -05:00
.travis.yml Added numpy 2021-01-12 22:41:40 -05:00
INSTALL.rst.txt Added numpy 2021-01-12 22:41:40 -05:00
LICENSE.txt Added numpy 2021-01-12 22:41:40 -05:00
LICENSES_bundled.txt Added numpy 2021-01-12 22:41:40 -05:00
MANIFEST.in Added numpy 2021-01-12 22:41:40 -05:00
README.md Added numpy 2021-01-12 22:41:40 -05:00
THANKS.txt Added numpy 2021-01-12 22:41:40 -05:00
__init__.py Added numpy 2021-01-12 22:41:40 -05:00
azure-pipelines.yml Added numpy 2021-01-12 22:41:40 -05:00
azure-steps-windows.yml Added numpy 2021-01-12 22:41:40 -05:00
doc_requirements.txt Added numpy 2021-01-12 22:41:40 -05:00
pavement.py Added numpy 2021-01-12 22:41:40 -05:00
pyproject.toml Added numpy 2021-01-12 22:41:40 -05:00
pytest.ini Added numpy 2021-01-12 22:41:40 -05:00
runtests.py Added numpy 2021-01-12 22:41:40 -05:00
setup.py Added numpy 2021-01-12 22:41:40 -05:00
shippable.yml Added numpy 2021-01-12 22:41:40 -05:00
site.cfg.example Added numpy 2021-01-12 22:41:40 -05:00
test_requirements.txt Added numpy 2021-01-12 22:41:40 -05:00
tox.ini Added numpy 2021-01-12 22:41:40 -05:00

README.md

NumPy

Travis Azure codecov

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

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()'

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.

Powered by NumFOCUS