1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374 |
- .. image:: https://raw.githubusercontent.com/scipy/scipy/main/doc/source/_static/logo.svg
- :target: https://scipy.org
- :width: 110
- :height: 110
- :align: left
- .. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
- :target: https://numfocus.org
- .. image:: https://img.shields.io/pypi/dm/scipy.svg?label=Pypi%20downloads
- :target: https://pypi.org/project/scipy/
- .. image:: https://img.shields.io/conda/dn/conda-forge/scipy.svg?label=Conda%20downloads
- :target: https://anaconda.org/conda-forge/scipy
- .. image:: https://img.shields.io/badge/stackoverflow-Ask%20questions-blue.svg
- :target: https://stackoverflow.com/questions/tagged/scipy
- .. image:: https://img.shields.io/badge/DOI-10.1038%2Fs41592--019--0686--2-blue
- :target: https://www.nature.com/articles/s41592-019-0686-2
- SciPy (pronounced "Sigh Pie") is an open-source software for mathematics,
- science, and engineering. It includes modules for statistics, optimization,
- integration, linear algebra, Fourier transforms, signal and image processing,
- ODE solvers, and more.
- - **Website:** https://scipy.org
- - **Documentation:** https://docs.scipy.org/doc/scipy/
- - **Development version of the documentation:** https://scipy.github.io/devdocs
- - **Mailing list:** https://mail.python.org/mailman3/lists/scipy-dev.python.org/
- - **Source code:** https://github.com/scipy/scipy
- - **Contributing:** https://scipy.github.io/devdocs/dev/index.html
- - **Bug reports:** https://github.com/scipy/scipy/issues
- - **Code of Conduct:** https://docs.scipy.org/doc/scipy/dev/conduct/code_of_conduct.html
- - **Report a security vulnerability:** https://tidelift.com/docs/security
- - **Citing in your work:** https://www.scipy.org/citing-scipy/
- SciPy is built to work with
- NumPy arrays, and provides many user-friendly and efficient numerical routines,
- such as routines for numerical integration and optimization. Together, they
- run on all popular operating systems, are quick to install, and are free of
- charge. NumPy and SciPy are easy to use, but powerful enough to be depended
- upon by some of the world's leading scientists and engineers. If you need to
- manipulate numbers on a computer and display or publish the results, give
- SciPy a try!
- For the installation instructions, see `our install
- guide <https://scipy.org/install/>`__.
- Call for Contributions
- ----------------------
- We appreciate and welcome contributions. Small improvements or fixes are always appreciated; issues labeled as "good
- first issue" may be a good starting point. Have a look at `our contributing
- guide <https://scipy.github.io/devdocs/dev/index.html>`__.
- Writing code isn’t the only way to contribute to SciPy. You can also:
- - review pull requests
- - triage issues
- - develop tutorials, presentations, and other educational materials
- - maintain and improve `our website <https://github.com/scipy/scipy.org>`__
- - develop graphic design for our brand assets and promotional materials
- - help with outreach and onboard new contributors
- - write grant proposals and help with other fundraising efforts
- If you’re unsure where to start or how your skills fit in, reach out! You can
- ask on the mailing list or here, on GitHub, by leaving a
- comment on a relevant issue that is already open.
- If you are new to contributing to open source, `this
- guide <https://opensource.guide/how-to-contribute/>`__ helps explain why, what,
- and how to get involved.
|