Automation of common building energy simulation workflows using Python

A valuable skillset for building industry professionals is proficiency in high-level, scripting languages that can automate and perform many common repetitive or technically intensive tasks. This application-focused paper emphasizes the use of the Python program-ming language in various workflows common to the building performance modeling and simulation pro-cess. Python is an open, powerful, and easy-to-learn scripting language with an emphasis on programmer productivity. While the highlighted applications them-selves are notably ordinary amongst building simu-lation practitioners, the novelty of this discussion is in the speed and usefulness of new Python libraries and data analysis techniques. Four short examples are illustrated: simulation input file templating, data exchange and interoperability, performance curve re-gression, and time-series output data postprocessing. An overview is presented of the growing current and planned Python libraries, extensions, and projects that are especially applicable and, in some cases, explicitly designed for the building industry.