Scientific Tools for Python

SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. 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!

SciPy 2008 Conferences

Yes, you read that heading right. There will be two SciPy Conferences in 2008.

SciPy 2008

The Conference at Caltech is scheduled on the following dates:

• Tutorials: August 19-20
• Conference: August 21-22
• Sprints: August 23-24

The Call for Papers and Talks has been issued, and registration is now open. Early registration ends on July 11, 2008, so create an account on the conference site, to upload an abstract or register for the conference.

EuroSciPy 2008

We're also meeting for the first ever EuroScipy in Leipzig, Germany on Saturday and Sunday July 26-27, 2008. The conference schedule has been issued and registration is open, so check out the EuroSciPy page. Early registration ends on June 15, so sign up now to take advantage of the lower rate.

Python and Scientific Computing

NumPy and SciPy are two of many open-source packages for scientific computing that use the Python programming language. This website, together with other subdomains of the scipy.org domain, serves as a portal for all scientific computing with Python, not just NumPy and SciPy. The index under Topical Software in the navigation bar lists these domains and other destinations for scientific software using Python.

Good places to start to learn more about SciPy:

• More about NumPy / SciPy

• Index of Python packages for scientific computing

• Projects using NumPy / SciPy

• Download NumPy / SciPy

• Install SciPy

• Documentation

• Cookbook

This is a community effort. We seek volunteers at all levels of ability to work on the project, from coding and packaging to documentation, tutorials, recipes, and the web site. Visit the Developer Zone if you are interested in helping out (or if you have bug reports).

SciPy is sponsored by Enthought, Inc.

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