Desktop GIS applications, such as ArcGIS and QGIS, provide tools essential for conducting suitability analysis, an activity that is central in formulating a land-use plan. But, when it comes to building complicated land-use suitability models, these applications have several limitations, including operating system-dependence, lack of dedicated modules, insufficient reproducibility, and difficult, if not impossible, deployment on a computing cluster. To address the challenges, this paper introduces PyLUSAT: Python for Land Use Suitability Analysis Tools. PyLUSAT is an open-source software package that provides a series of tools (functions) to conduct various tasks in a suitability modeling workflow. These tools were evaluated against comparable tools in ArcMap 10.4 with respect to both accuracy and computational efficiency. Results showed that PyLUSAT functions were two to ten times more efficient depending on the job's complexity, while generating outputs with similar accuracy compared to the ArcMap tools. PyLUSAT also features extensibility and cross-platform compatibility. It has been used to develop fourteen QGIS Processing Algorithms and implemented on a high-performance computational cluster (HiPerGator at the University of Florida) to expedite the process of suitability analysis. All these properties make PyLUSAT a competitive alternative solution for urban planners/researchers to customize and automate suitability analysis as well as integrate the technique into a larger analytical framework.