The power switch is crucial in advanced power electronics due to high switching speeds and low losses. Accurate analytical models for MOSFETs and IGBTs facilitate dynamic characteristic evaluation, but manually setting parasitic parameters is time-consuming and error-prone. Diverse datasheets further complicate parameter extraction. This paper introduces a Python-based data reading program that automates parameter extraction from digital datasheets and a plot extraction technology that extracts data from parametric curve figures. The program’s output is repeatable across multiple datasheets. Verification with a SiC MOSFETs analysis model shows identical output waveforms to manual methods. Such tools enhance scalability, efficiency, and comprehensive data analysis, supporting cost-effective and timely simulation research, and enabling large-scale comparative studies of power devices.