Abstract The paper introduces PyPBEE, an open-source Python library for performance-based earthquake engineering (PBEE). This computational tool is designed to enable researchers and engineers to conduct complex PBEE analyses with enhanced efficiency, flexibility, and accessibility. The library encapsulates a broad range of state-of-the-art computational models and methods required for each phase of PBEE, from seismic hazard analysis to damage prediction and decision-making. PyPBEE aims to streamline the PBEE workflow by offering a user-friendly, programmable interface that currently accommodates probabilistic seismic hazard analysis, ground motion selection, nonlinear time-history analysis, probabilistic seismic demand hazard analysis, and probabilistic seismic damage hazard analysis. One of its key features is the integration of finite element models with randomized parameters, which effectively introduces a crucial probabilistic dimension to PBEE analysis that is often overlooked. It integrates data management functionalities, enabling seamless manipulation and processing of massive, high-dimensional data sets common in earthquake engineering. The paper presents an extensive exploration of the library’s architecture, functionalities, and capabilities. Real-world case studies demonstrate how PyPBEE can facilitate comprehensive, accurate earthquake risk assessments, thus aiding in the design of more resilient infrastructure. The modular design of the library facilitates and encourages community contributions, enabling its ongoing enhancement to reflect emerging trends and advancements in earthquake engineering. By providing a consolidated, intuitive, and extensible platform, PyPBEE empowers researchers, engineers, and decision-makers to perform sophisticated PBEE analyses, enhancing our ability to understand, predict, and mitigate the impact of seismic hazards.
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