CityDPC: A Python library for handling 3D city model datasets

Abstract This study presents CityDPC, a Python library for geometric computations on CityGML and CityJSON datasets, merging features from tools such as CityATB. It supports loading, analyzing, validating, and manipulating 3D city model datasets, aiming to enhance Python applications for urban building stock analyses. It introduces a shared building class to expedite new data formats integration and improve software development and interoperability among urban‐scope applications. A novel feature is the calculation of party or shared walls, showcased in a UBEM (Urban Building Energy Modeling) context through TEASER+ integration. This demonstrates the library's utility in urban energy modeling, calculating shared walls to advance existing tools’ functionality and foster innovative urban‐scale building analysis applications.