koxudaxi/datamodel-code-generator
Grade a repo

92

/ 100

GradeB

A well-known project done right. Strong docs and solid engineering throughout.

Top 14% of 5,156 graded repos

Generate Pydantic v2 models, dataclasses, TypedDict, and msgspec.Struct from OpenAPI, JSON Schema, GraphQL, Avro, Protobuf, and raw JSON/YAML/CSV.

Documentation82
Engineering90
Health98
Python3,960MIT1mo ago

Top fixes

Highest-impact changes first, ranked by point weight

6 to address
  1. 1
    Tests18pt

    Wire your tests to a documented command (e.g. a test script in your build config) so the suite is reproducible.

  2. 2
    CI/CD14pt

    Add a lint step to catch style issues automatically.

  3. 3
    CI/CD14pt

    Add `tsc --noEmit`, `mypy`, or `cargo check` to catch type errors before they merge.

  4. 4
    Install and run instructions9pt

    Add a .env.example listing all required environment variables so contributors know what to set up.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

82

Contributing guide5pt5

No CONTRIBUTING.md found (−47 pts base + up to −53 pts more for content).

→ Add a CONTRIBUTING.md telling newcomers how to get involved. Include setup, code style, test, and PR instructions.

Install and run instructions9pt90

README documents how to install the project.

README12pt100

README is present.

License6pt100

Licensed under MIT.

Engineering

90

Tests18pt85

Test files detected (tests).

CI/CD14pt85

CI is configured (.github/workflows/lint.yaml).

Linting and formatting5pt100

Linter or formatter configured ([tool.ruff] / [tool.black] in pyproject.toml).

Reproducibility6pt100

Lockfile present (uv.lock). Installs are reproducible.

Issue and PR templates6pt100

Issue or PR templates present.

Project health

98

Dependency manifest6pt93

Dependency manifest found (pyproject.toml).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Housekeeping3pt100

.gitignore present.

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • 144 / 390
    Commits (30d / 90d)
  • 449
    Forks
  • 262
    Releaseslatest 6y ago

Community

  • 85% - Good
    Community health
  • 1 bus factorlow
    author own >50% of commits
  • 3,960
    Watchers

Responsiveness

  • 9h
    Median issue response
  • <1h
    Median PR merge time
  • 23
    Open issues
Repository files23 root entries
  • .github
    Good: CI is configured (.github/workflows/lint.yaml).
    Good: Dependabot covers 3 ecosystems (pip, github-actions, docker). Dependencies stay current.
    Good: Issue or PR templates present.
  • docs
  • overrides
  • scripts
  • skills
  • src
  • tests
    Good: Test files detected (tests).
  • .coderabbit.yaml
  • .gitignore
    Good: .gitignore present.
  • .pre-commit-config.yaml
  • .pre-commit-hooks.yaml
  • action.yml
  • CHANGELOG.md
  • CODE_OF_CONDUCT.md
    Good: Code of conduct present.
  • Dockerfile
    Good: Environment pinned via Dockerfile.
  • LICENSE
    Good: Licensed under MIT.
  • MANIFEST.in
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • README.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • SECURITY.md
    Good: Security policy present.
  • tox.ini
  • uv.lock
    Good: Lockfile present (uv.lock). Installs are reproducible.
  • zensical.toml
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