bayesian-optimization/BayesianOptimizationNew scan
91/ 100 · A

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

A Python implementation of global optimization with gaussian processes.

Python8,644 starsMITupdated 17d ago
DocumentationREADME, setup, examples, license
82
EngineeringTests, CI, linting, lockfiles
94
Project healthDescription, activity, stars, deps
98

What to fix first

The highest-impact improvements for this repo.

  1. 1
    Tests
    EngineeringWarning

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

  2. 2
    CI/CD
    EngineeringInfo

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

  3. 3
    Install and run instructions
    DocumentationInfo

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

Detailed breakdown

Documentation

82
  • README100
    • README is present.
    • README is well structured with multiple sections.
    • README includes screenshots or visuals. Great for first impressions.
    • README has code examples.
    • README links to a live demo or deployed app.
    • README includes status badges.
  • Install and run instructions90
    • README documents how to install the project.
    • README documents how to run the project.
    • If your project uses environment variables, add a .env.example listing them (+10 pts).Add a .env.example listing all required environment variables so contributors know what to set up.
  • License100
    • Licensed under MIT.
  • Contributing guide0
    • 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.
    • Optional: add a Code of Conduct.A CODE_OF_CONDUCT.md signals that your project is welcoming. GitHub has a template you can add in one click.

Engineering

94
  • Tests95
    • Test files detected (tests).
    • Pytest referenced in pyproject.toml and test files present.
    • Coverage reporting is configured in pyproject.toml.
    • Test files detected (95/100) but no test runner configured (−5 pts). Without a documented test command the suite cannot be verified by contributors.Wire your tests to a documented command (e.g. a test script in your build config) so the suite is reproducible.
  • CI/CD100

    Not applicable?

    • CI is configured (.github/workflows/build_docs.yml).
    • CI workflow runs tests.
    • CI runs on pull requests, not just on pushes to main.
    • CI workflow runs a lint or format check.
    • Optional: add type checking to CI.Add `tsc --noEmit`, `mypy`, or `cargo check` to catch type errors before they merge.
    • CI reports or uploads test coverage.
    • CI tests across multiple environments or versions.
  • Linting and formatting100
    • Linter or formatter configured (ruff.toml).
  • Reproducibility70
    • Lockfile present (docsrc/requirements.txt). Installs are reproducible.
    • No Dockerfile or runtime version pin found. Adding one earns +10 pts.Add a Dockerfile, .nvmrc, or .python-version to pin the runtime version and make the environment reproducible.
    • No Dependabot config (adding it earns up to +20 pts).Add .github/dependabot.yml with at least one package-ecosystem entry so dependencies are updated automatically.
  • Issue and PR templates100
    • Issue or PR templates present.
    • Optional: add a SECURITY.md.A SECURITY.md explains how to responsibly disclose vulnerabilities. Worth adding once the project has real users.

Project health

98
  • Dependency manifest93
    • Dependency manifest found (pyproject.toml).
    • pyproject.toml has a [project] table with package metadata.
    • pyproject.toml includes a description.
    • pyproject.toml specifies requires-python, preventing installs on incompatible versions.
    • pyproject.toml has no project URLs (−7 pts).Add a [project.urls] table (Homepage, Repository) so PyPI links back to your project.
    • pyproject.toml has a [build-system] table. The package can be built and published.
  • Repository metadata100
    • Repository has a description.
    • Primary language detected: Python.
  • Activity100
    • Actively maintained (pushed within the last month).
    • 8,644 stars.
  • Housekeeping100
    • .gitignore present.
Repository files12 root entries
  • .github
    Good: CI is configured (.github/workflows/build_docs.yml).
    Good: Issue or PR templates present.
  • bayes_opt
  • docsrc
    Good: Lockfile present (docsrc/requirements.txt). Installs are reproducible.
  • examples
  • scripts
  • tests
    Good: Test files detected (tests).
  • .gitignore
    Good: .gitignore present.
  • .pre-commit-config.yaml
  • LICENSE
    Good: Licensed under MIT.
  • 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.
  • ruff.toml
    Good: Linter or formatter configured (ruff.toml).