compehndly¶

compehndly is a cross-language collection of derived-variable functions for Personal Exposure Health data.

The project currently centers on a Polars-first Python implementation, with an R implementation kept aligned through shared conformance vectors.

Documentation Map¶

• Python overview: current implementation, public APIs, and function behavior.
• Python integration patterns: how external callers use stable entrypoint paths and Polars map_batches.
• R overview: placeholder structure for the R implementation.
• Shared conformance: how Python and R stay aligned.

Repository Layout¶

• python/: Python package, Polars kernels, adapters, and tests.
• R/: R package scaffold and implementation.
• shared/conformance/: shared JSON test vectors.
• docs/: this documentation site.