codebase-inspection

To get a language breakdown and lines of code count for a repository, run a codebase inspection to extract file counts, language distribution, and code-to-comment ratios using pygount. It quickly quantifies project size and composition for mixed-language codebases.

Measuring code-to-comment ratios across a monorepo requires analyzing code lines versus documentation lines to estimate readability. A codebase inspection calculates these documentation density metrics using pygount to help estimate maintainability.

Yes, you can export lines of code metrics as JSON output. The codebase inspection supports machine-friendly JSON output formats alongside human-readable summaries, allowing you to easily integrate repository metrics into downstream analysis pipelines.

Yes, pygount supports skipping specific folders when analyzing repository size. The codebase inspection execution requires configuring appropriate folders-to-skip parameters to ensure accurate lines of code and language distribution metrics.

You need to quantify repo size and composition for a legacy codebase when evaluating modernization, refactoring, or auditing tasks. Extracting lines of code and language breakdown helps assess project scope and documentation density before committing time.