Python is a powerful high-level open source programming language that is available for multiple platforms. It supports object-oriented programming and has recently become a serious alternative to low-level compiled languages such as C + +. It is easy to learn and use, and is recognized for very fast development times, which makes it suitable for rapid software prototyping as well as teaching purposes. We motivate the use of Python and its free extension modules for high performance stand-alone applications in econometrics and statistics, and as a tool for gluing different applications together. (It is in this sense that Python forms a “unified” environment for statistical research.) We give details on the core language features, which will enable a user to immediately begin work, and then provide practical examples of advanced uses of Python. Finally, we compare the run-time performance of extended Python against a number of commonly-used statistical packages and programming environments. Supplemental materials are available for this article. Go to the publisher's online edition of Econometric Reviews to view the free supplemental file.