Shrestha, HilsonWilburn, JackBollen, BrianMcNutt, Andrew M.Lex, AlexanderHarrison, LaneDiehl, AlexandraKucher, KostiantynMédoc, Nicolas2025-05-262025-05-262025978-3-03868-286-8https://doi.org/10.2312/evp.20251133https://diglib.eg.org/handle/10.2312/evp20251133User experiments are an important part of visualization research, yet they remain costly, time-consuming to create, and difficult to prototype and pilot. The process of prototyping a study-from initial design to data collection and analysis-often requires the use of multiple systems (e.g. webservers and databases), adding complexity. We present reVISitPy, a Python library that enables visualization researchers to design, pilot deployments, and analyze pilot data entirely within a Jupyter notebook. Re- VISitPy provides a higher-level Python interface for the reVISit Domain-Specific Language (DSL) and study framework, which traditionally relies on manually authoring complex JSON configuration files. As study configurations grow larger, editing raw JSON becomes increasingly tedious and error-prone. By streamlining the configuration, testing, and preliminary analysis workflows, reVISitPy reduces the overhead of study prototyping and helps researchers quickly iterate on study designs before full deployment through the reVISit framework.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Visualization toolkits; User studiesHuman centered computing → Visualization toolkitsUser studies10.2312/evp.202511333 pages