David Mertz at IBM DeveloperWorks covers SimPy, a Python simulation package:
The stochastic behavior of real-world systems is often difficult to understand or predict. Sometimes it is possible rigorously to demonstrate statistical properties of systems, such as average, worst-case, and best-case performance features. But at other times, pitfalls of concrete designs only become evident when you actually run (or simulate) a system. In this article, David takes a look at SimPy, a Python package that allows you to very easily create models of discrete event systems.
[via NewsForge]