In this section, a walkthrough example of installing and using ULaMDyn is provided. The entire clustering or dimensionality reduction analysis workflow is automated by ULaMDyn, starting with data collection and the conversion of molecular geometries into descriptors. The selected unsupervised learning algorithms are then applied to the descriptor space. Additionally, various postprocessing statistical analyses are conducted by grouping the data according to the cluster labels generated by the clustering process. All these steps can be executed via a command-line interface (CLI) or by customized Python scripts by importing the ULaMDyn modules. In the following subsections, this pipeline will be broken down, demonstrating how each step can be carried out within a Python framework using ULaMDyn. A Python notebook of this example can be found at .