We present Transient Absorption Processing and Analysis Software (TAPAS), an open-source, Python-based graphical platform that covers the entire transient absorption (TA) workflow, from raw data import and preprocessing to visualization, global and target fitting, and statistical evaluation. Users operate TAPAS through an intuitive, seven-tab GUI, yet all underlying modules remain accessible for inspection and extension, merging GUI convenience with script-level flexibility. The fitting engine employs just-in-time compilation via an open-source machine learning compiler ecosystem, delivering two-20-fold speed gains over established packages. Automatic differentiation and residual-based effective-sample-size calculations yield reliable confidence intervals and correlation matrices, while an integrated sampling routine provides full Bayesian posterior exploration-diagnostics which are rarely available in other TA tools. All raw, processed, and fitted data are written to standardized Hierarchical Data Format 5 containers and automatically annotated with rich metadata, ensuring complete provenance. An extended case study on Rose Bengal shows how TAPAS first reveals hidden lifetime correlations, then employs broadband global and target analysis to merge TA traces with complementary steady-state and literature data, yielding a single, self-consistent kinetic model. By uniting advanced uncertainty quantification and transparent data management within a user-friendly interface, TAPAS closes the gap between accessibility and rigorous statistical treatment in TA spectroscopy.
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