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https://github.com/scipy/scipy

SciPy library main repository
https://github.com/scipy/scipy

algorithms closember python scientific-computing scipy

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SciPy library main repository

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README 

        
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  :target: https://scipy.org

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.. image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A

  :target: https://numfocus.org



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  :target: https://pypi.org/project/scipy/



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  :target: https://anaconda.org/conda-forge/scipy



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  :target: https://stackoverflow.com/questions/tagged/scipy



.. image:: https://img.shields.io/badge/DOI-10.1038%2Fs41592--019--0686--2-blue.svg

  :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

- **SciPy development forum:** https://discuss.scientific-python.org/c/contributor/scipy 

- **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 `__.



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 `__.



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 `__

- 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 `__ helps explain why, what,

and how to get involved.