SALib is an open-source Python library for global sensitivity analysis. It provides implementations of commonly used methods, including Sobol, Morris, FAST, Delta Moment-Independent Measure, Derivative-based Global Sensitivity Measure (DGSM), and Fractional Factorial Sensitivity Analysis. The library is useful in simulation, optimization, and systems modeling to determine the influence of model inputs or exogenous factors on outputs of interest. SALib makes it easy for scientists, researchers, and modellers to implement these techniques into typical modeling workflows. The library facilitates the generation of samples associated with a model's inputs and provides functions to analyze model outputs and visualize the results. SALib is released under a Creative Commons Attribution 4.0 International License. The authors of JOSS papers retain copyright. The library is developed by the University of California, Davis and the University of Oxford. References to various studies and authors are provided, detailing the origins and development of the methods included in SALib.SALib is an open-source Python library for global sensitivity analysis. It provides implementations of commonly used methods, including Sobol, Morris, FAST, Delta Moment-Independent Measure, Derivative-based Global Sensitivity Measure (DGSM), and Fractional Factorial Sensitivity Analysis. The library is useful in simulation, optimization, and systems modeling to determine the influence of model inputs or exogenous factors on outputs of interest. SALib makes it easy for scientists, researchers, and modellers to implement these techniques into typical modeling workflows. The library facilitates the generation of samples associated with a model's inputs and provides functions to analyze model outputs and visualize the results. SALib is released under a Creative Commons Attribution 4.0 International License. The authors of JOSS papers retain copyright. The library is developed by the University of California, Davis and the University of Oxford. References to various studies and authors are provided, detailing the origins and development of the methods included in SALib.