Pyage

Pyage is an open‑source Python library that provides utilities for manipulating and analyzing age data. It was introduced in 2018 by Michael Smith and is released under the MIT license. The project is hosted on GitHub, where it receives active maintenance, issue tracking, and community contributions.

The core functionality centers on age calculation from birth dates, age‑group classification for demographic studies, and statistical summaries of age distributions. Users can create Age objects from timestamps or calendar dates and query numeric age in years, months, or days. The age_group function assigns individuals to predefined categories such as “child,” “adult,” and “senior,” based on configurable cutoffs. Pyage also includes a statistics module that computes mean, median, standard deviation, and percentile values over a collection of ages, and it supports integration with pandas DataFrames to enable large‑scale analysis.

Pyage supports Python 3.8+ and depends on NumPy for underlying time‑delta calculations. In addition to the main API functions, the library ships with a command‑line interface that can read CSV files, compute age statistics, and output the results in JSON or CSV format. The codebase follows PEP‑8 guidelines, and documentation is automatically generated with Sphinx and hosted on ReadTheDocs.

Typical use cases for Pyage include demographic research for public health, market segmentation in business analytics, and age‑based filtering in educational software. The community around the project provides plugins for additional age‑group frameworks and supports backward compatibility across major releases.