ensemble implements the Honeycutt (1992) inhomogeneous ensemble photometry method as an interactive Jupyter Lab widget to correct for atmospheric variations in differential light-curve photometry. It ingests background-subtracted photometry and uncertainties for a fixed set of stars across multiple exposures, solves for an ensemble solution, and lets users interactively mask stars, exposures, and individual star–exposure combinations via linked plots before recomputing the solution. The object-oriented design exposes attributes such as atmospheric-corrected instrumental magnitudes and masking matrices, enabling further analysis after the interactive session.

PyHammer performs rapid and automatic spectral classification of stars according to the Morgan-Keenan classification system; it is a Python revision of the IDL code The Hammer (ascl:1405.003) and offers additional capabilities. Working in the range of 3,650-10,200 Angstroms, the automatic spectral typing algorithm compares important spectral lines to template spectra and determines the best matching spectral type, ranging from O to L type stars. The code can also determine a star's metallicity ([Fe/H]) and radial velocity shifts. Once the automatic classification algorithm has run, PyHammer provides the user an interface for determining spectral types visually by comparing their spectra to provided templates.