Scientific computing with python']python

Scripting languages have become a powerful tool for the construction of flexible scientific software because they provide scientists with an interpreted programming environment, can be easily interfaced with existing software written in C, C++, and Fortran, and can serve as a framework for modular software construction. In this paper, I describe the process of adding a scripting language to a scientific computing project by focusing on the use of Python with a large-scale molecular dynamics code developed for materials science research at Los Alamos National Laboratory. Although this application is not related to astronomical data analysis, the problems, solutions, and lessons learned may be of interest to researchers who are considering the use of scripting languages with their own projects.