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    <p>
      <h1>
        <a href="https://docs.scipy.org/doc/scipy/reference/"><img valign="middle" src="doc/source/_static/scipyshiny_small.png" height="50" height="50" alt="SciPy logo"/></a>
        SciPy
      </h1>
    </p>

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  :target: https://circleci.com/gh/scipy/scipy

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  :target: https://dev.azure.com/scipy-org/SciPy/_build/latest?definitionId=1?branchName=master

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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://codecov.io/gh/scipy/scipy

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  :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://docs.scipy.org/doc/scipy/reference/
- **Documentation:** https://docs.scipy.org/
- **Mailing list:** https://scipy.org/scipylib/mailing-lists.html
- **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://scipy.github.io/devdocs/dev/conduct/code_of_conduct.html
- **Report a security vulnerability:** https://tidelift.com/docs/security
- **Citing in your work:** https://www.scipy.org/citing.html

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.github.io/devdocs/getting_started.html#installation>`__.


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 <http://scipy.github.io/devdocs/dev/hacking.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.

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  :target: https://numfocus.org