ClassiPyGRB downloads, processes, visualizes, and classifies GRBs in the Swift/BAT database. Users can query light curves for any GRB and use tools to preprocess the data, including noise/duration reduction and interpolation. The package provides a set of facilities and tutorials for classifying GRBs based on their light curves using a method based on a dimensionality reduction of the data using t-Distributed Stochastic Neighbour Embedding (TSNE); results are visualized using a Graphical User Interface (GUI). ClassiPyGRB also plots and animates the results of the TSNE analysis for a deeper hyperparameter grid search.