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Contributing to MetDataPy

Thank you for your interest in contributing! This guide explains how to set up your environment, propose changes, and follow project conventions.

Getting started

  • Fork the repo and create a feature branch from main.
  • Use recent Python (>=3.9). Install in editable mode: 
    python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
python -m pip install -U pip
python -m pip install -e .
python -m pip install pytest mkdocs mkdocs-material

Note: For regular users, MetDataPy is available on PyPI: pip install metdatapy. This development setup is only needed for contributors.

Running tests and docs

  • Tests: 
    python -m pytest -q
  • Docs (MkDocs): 
    mkdocs serve   # live preview
mkdocs build   # static site in site/

Coding standards

  • Write clear, readable, and typed Python where reasonable.
  • Prefer vectorized pandas/numpy operations; avoid unnecessary loops.
  • Keep public APIs stable; add deprecations with care.
  • Lint/formatting enabled in CI: ruff, black, isort; type checking with mypy.
  • Match existing code style and avoid unrelated reformatting.

Pull requests

  • Scope PRs narrowly; include tests and docs for new features.
  • Update README.md and relevant pages in docs/ when behavior changes.
  • Add entries/checkmarks to ROADMAP.md when features are implemented.
  • Explain motivation, approach, and any trade-offs in the PR description.

Issue reporting

  • Include minimal reproducible examples, data snippets, versions, and OS.
  • Label issues appropriately (bug, enhancement, docs, question).

Security and conduct

  • Please avoid sharing sensitive data in issues/PRs.
  • Be respectful and professional. See CODE_OF_CONDUCT.md.

Release process (outline)

  • Ensure tests/docs pass on CI; bump version in pyproject.toml.
  • Tag the release; publish wheels/sdist to PyPI; archive on Zenodo (planned).

Thanks again for contributing!