codebase-inspection

To count lines of code and analyze language breakdown, scan the repository using pygount to summarize file counts, code versus comment ratios, and language composition. This returns a summary of the codebase size and its distribution across different programming languages.

The best way to measure codebase size for a monorepo audit is applying pygount-based scanning with folder exclusions. This profiles the monorepo to reveal its total lines of code, file counts, and language mix without manually counting files.

Yes, you can get JSON output for repository metrics when scanning a source tree. The scanning process supports summary, JSON, or suffix-filtered output formats to capture repository metrics including lines of code and comment ratios.

Codebase analysis handles comment ratios by calculating code lines versus comment lines per language using pygount. It applies folder exclusions during the scan to skip irrelevant directories, ensuring the repository metrics accurately reflect the source tree.

Yes, you need pygount for analyzing lines of code in your project, as the scanning relies on pygount-based logic to count code and comment lines. This dependency is required to perform the codebase analysis and generate the language breakdown.