codebase-inspection

To analyze a codebase for language distribution and LOC metrics, you can run pygount on the target repository to automatically measure lines of code, identify dominant languages, and calculate code-vs-comment ratios for a structured summary report.

The best way to get a code vs comment ratio for a software repository is to use an analysis tool like pygount, which scans standard repository structures to automatically calculate and report the density of comments relative to actual code.

Yes, you can use pygount to evaluate a monorepo by scanning its structure to surface hotspots like heavy directories or nested monorepos, providing file counts and language balance insights suitable for optimization and audits.

Codebase LOC analysis works with software repositories of varying sizes, using standard repository structures to assess language balance, compare file counts, and measure code density without requiring specific scale limitations.

To generate a codebase metrics report for onboarding or refactoring, you need a standard repository structure and the pygount dependency, which together produce a structured summary of repository sizing and language breakdown insights.