Getting Started with GSoC and SciPy

I'm trying to resist making the obligatory "hello world" post here. The best I can do is only mentioning the urge.

First, a little bit about myself. My name is Skipper Seabold. I am finishing my first year as a PhD student in economics at American University in Washington, DC, and I have recently been accepted to the Google Summer of Code 2009 to work on the SciPy project. I have been a computer hardware and programming hobbyist since my middle school days. I have built my computers my whole life and back in high school tinkered around with Visual Basic (Apps for AOL 3.0 on Windows 3.x and Windows 95 anyone?), Turbo Pascal, C++, and Java mostly in the context of coursework. Two years ago I was introduced to the Python programming language, and I haven't looked back. Needless to say I'm very happy to have two of my interests, economics and programming, overlap.

This is where SciPy comes in. For those who are unfamiliar with SciPy, I direct you to the homepage here. In short, SciPy is an open source library of algorithms for numerical analysis for those working in engineering or the sciences more broadly defined. The SciPy library depends on NumPy. The Tentative NumPy Tutorial is a good place to start learning about the capabilities of NumPy. And likewise, the Getting Started page has plenty of resources to introduce you to the power of SciPy. In particular the tutorials, documentation, and cookbook are good to look at.

What I will be working on this summer is providing a consistent user interface for statistical models and appropriate statistical tests in SciPy similar to those found in other statistics/econometric software packages. I will also provide a unified development framework for those who would like to add to this effort in the future. Updates may be less regular over the next few weeks, but check here for at least weekly updates on the work over the summer.