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SciPy (pronounced "Sigh Pie") is 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. It is also the name of a very popular conference on scientific programming with Python.
The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library 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 installation instructions, see INSTALL.rst.txt.
Scipy documentation is available on the web:
https://docs.scipy.org
How to generate the HTML documentation, see doc/README.txt.
The user's site is:
https://www.scipy.org/
The addresses and archives for the developer and user mailing lists can be found here:
http://scipy.org/scipylib/mailing-lists.html
The latest development version of Scipy's sources are always available at:
https://github.com/scipy/scipy
They can be downloaded as a zip file or using the Git client.
To search for bugs or report them, please use the Scipy Bug Tracker at:
https://github.com/scipy/scipy/issues
If you would like to take part in SciPy development, take a look
at the file CONTRIBUTING.
See the file LICENSE.txt for information on the history of this
software, terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.