Python has become the de facto standard programming language for astronomical research, with many open-source packages available for accessing, manipulating, and visualizing photometric time series data from Kepler, K2, and TESS. However, specialized tools for fitting frequency solutions to these time series have been conspicuously absent, causing many researchers to rely on closed-source legacy software, such as Period04. The interactive tutorial at https://dirac.us/oil demonstrates the use of the new Pyriod package for the pre-whitening analysis of time series photometry of pulsating stars that fills this gap in the modern Python workflow for time domain stellar astrophysics. Pyriod can be used either interactively with Jupyter Notebook widgets, or through direct access to functions for automated analyses. It can also be easily extended by the user to provide additional functionality as desired.

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