PANCAKE (Python bAsed Numerical Color-magnitude-diagram Analysis pacKagE) analyzes stellar populations in nearby galaxies or star clusters by fitting observed color–magnitude diagrams (CMDs) with synthetic models using numerical methods. The package reads photometric observations, constructs template CMDs from theoretical isochrones, grids the CMD data, and executes model-free fitting to infer parameters such as star formation history and stellar population characteristics. It includes routines to preprocess input data, handle gridding and fitting workflows, and assess results such as residual maps and parameter estimates. PANCAKE supports multiple gridding strategies, integrates with Python scientific libraries for array handling and optimization, and can be applied to a variety of stellar population CMD datasets.

Spectuner identifies spectral lines of interstellar molecules automatically. The code uses XCLASS (ascl:1810.016) for the spectral line model and SciPy for the peak finder. Spectral fitting is performed using article swarm optimization and the peak matching loss function. From frequency in a unit of MHz and temperature in a unit of K, Spectuner returns the combined spectrum, identification of the combined spectrum, and the identification of all candidates.