mehen

mehen is a Rust-powered CLI for detecting heuristic source code metrics at scale: complexity, maintainability, lines of code, documentation health, and more.

It is designed for fast, deterministic analysis over large codebases, helping both human and AI engineers track how complexity evolves over time.

📚 Documentation: https://mehen.ophi.dev

What is Mehen?

In Ophidiarium projects, names matter. Mehen is a mythical ancient Egyptian serpent associated with guarding Ra. In the same spirit, mehen helps guard your codebase from slowly collapsing under complexity.

Why teams use mehen

  • Polyglot by design — per-file language detection across eleven source languages plus Markdown and SQL. Useful for monorepos.
  • Real language parsers — Ruff for Python, Oxc for TS/JS/JSX/TSX, Mago for PHP, Prism for Ruby, ra_ap_syntax for Rust, ANTLR (Kotlin spec grammar for Kotlin, grammars-v4 for Java and C#), pulldown-cmark for Markdown, sqruff for SQL, tree-sitter for Go, C, PowerShell.
  • Code, documentation, and SQL in one tool — source-code complexity, Markdown documentation health, and a dedicated relational metric family for .sql files.
  • Deterministic, no network — pure static analysis. Same input → same output. Safe for air-gapped CI.
  • Pull-request native — built-in mehen diff plus a sticky comment GitHub Action.

Install

# npm
npm install -g mehen

# PyPI / uv
uv tool install mehen
# or: pip install mehen

# cargo binstall
cargo binstall --git https://github.com/ophi-dev/mehen mehen

Full installation guide: https://mehen.ophi.dev/installation.

Quick start

# Analyze a single file
mehen metrics src/main.py --pretty

# Rank the worst offenders in a tree
mehen top-offenders src --metric cognitive

# Diff metrics against main
mehen diff --from main --to HEAD --paths src --output-format markdown

Quickstart: https://mehen.ophi.dev/quickstart.

Configuration

Drop a mehen.toml (or .mehen.toml) anywhere between the directory you run mehen from and the git repository root — discovery walks upward and stops at the repository boundary — or pin an explicit file with --config <PATH>:

[thresholds]
cognitive = 15         # higher-is-worse metrics: the limit is a maximum
"loc.lloc" = 500
mi.visual_studio = 40  # higher-is-better metrics (mi.*): the limit is a minimum

[languages.python.thresholds]
cognitive = 10         # overrides the global limit for Python files only

Every command that reports a configured metric enforces it: mehen metrics checks the full metric set of the analyzed file, while mehen diff (head side) and mehen top-offenders check the metrics selected for output — across all analyzed files, not just the displayed rows. Any crossed limit prints a grouped report on stderr and fails the command with exit code 1:

  × 2 metric threshold violations (config: /repo/mehen.toml)
  │
  │ src/app/core.py
  │   cognitive = 23 — exceeds max 10  (set by languages.python.thresholds)
  │   loc.lloc = 640 — exceeds max 500  (set by thresholds)
  help: adjust or remove the limit at the configuration path shown, or bring the file back within it.

Configuration mistakes fail fast with a caret into the TOML source and a suggestion ("unknown metric cognitve … did you mean cognitive?"): every metric name is validated against the keys the analyzers actually publish — including the sql.* and markdown.* namespaces — so a typo can never silently disable a gate. Full reference: https://mehen.ophi.dev/configuration.

GitHub Action

Drop the action into a workflow to publish per-PR metric trends:

permissions:
  contents: read
  pull-requests: write
  issues: write

steps:
  - uses: actions/checkout@v6
    with:
      fetch-depth: 0
  - uses: ophi-dev/mehen@v1
    with:
      paths: src

Full reference: https://mehen.ophi.dev/guides/github-action.

Documentation

Everything else lives in the docs site:

  • Code metrics — cyclomatic, cognitive, Halstead, MI, ABC, LOC family, NOM, NPA, NPM, WMC.
  • Markdown metrics — DMI, MRPC, MCC, link debt, filler/lazy risk, English/Japanese prose layer.
  • SQL metrics — CTE graphs, join/subquery structure, object-touch risk, SQL Halstead, and composite scores via mehen-sql (sqruff-backed).
  • Commands — mehen metrics, mehen diff, mehen top-offenders.
  • Configuration — mehen.toml thresholds and per-language overrides.
  • Developers guide — build, test, contribute, add a language.

Contributing

Issues and pull requests welcome at https://github.com/ophi-dev/mehen/issues.

License

mehen is released under the GNU Affero General Public License v3.0.

Project links

Data verified by PyPI on Aug 17, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.10.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for tinovyatkin from gravatar.com tinovyatkin

Credits

Author: Konstantin Vyatkin

GitHub Statistics

Data verified by PyPI on Aug 17, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

AGPL-3.0-only
View SPDX License List

Requires

Python >=3.8

Tags

metrics code-analysis complexity cyclomatic halstead

Classifiers

Report project as malware

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