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Semantic chunking utilities for scientific code and documentation corpora.

Project description

Chunky

Chunky is a python package for intelligently chunking scientific and technical repositories. It provides a modular pipeline that powers the Nancy Brain knowledge base and MCP services, while remaining useful as a standalone library for retrieval systems that need deterministic, metadata-rich chunks.

Documentation lives on Read the Docs: https://chunky.readthedocs.io

Installation

Install from source using the pyproject.toml metadata:

# clone the repo (if you haven't already)
git clone https://github.com/AmberLee2427/chunky.git
cd chunky

# install the library
pip install .

For development and documentation builds, install the optional extras:

pip install -e ".[dev,docs]"

-e performs an editable install so local changes reflect immediately. .[dev,docs] installs the tooling declared under the dev and docs extras in pyproject.toml.

Tooling

  • Code style: Ruff (ruff check src tests or ruff check src tests --fix)
  • Tests: Pytest (pytest --cov=chunky)
  • Docs: Sphinx + MyST + Furo (sphinx-build -b html docs docs/_build/html)
  • Packaging: Hatchling build backend
  • Versioning: bump-my-version (driven by tags and the release workflow)

Workflows

  • CI tests run on Linux, macOS, and Windows for Python 3.8 through 3.12.
  • Pushing a tag that matches the form vX.Y.Z triggers the release workflow. It validates that the tag matches the version in pyproject.toml, builds the distribution, and publishes to PyPI using the PYPI_API_TOKEN secret.
  • Read the Docs builds the documentation automatically for pushes to the default branch. Local builds use sphinx-build -b html docs docs/_build/html.

Release checklist:

  1. Review and update CHANGELOG.md, keeping the [Unreleased] section accurate.
  2. Run bump-my-version bump <part> to update version metadata and append a dated entry in the changelog.
  3. Build distributions locally (rm -rf dist && python -m build) and verify metadata with python -m twine check dist/*.
  4. Commit the changes and push to main.
  5. Tag the commit (git tag vX.Y.Z && git push origin vX.Y.Z) to trigger the Release workflow.
  6. Verify the PyPI publish job and Read the Docs build succeed.

Contributing

  • Know your audience: most contributors will be scientific coders. Write docs assuming limited familiarity with packaging internals.
  • Use Ruff for style checks and keep numpy-style docstrings on all non-test functions.
  • Target test coverage above 70% and ensure existing CI jobs pass before opening a PR.
  • In pull requests, summarise code changes, testing/validation, doc updates, and provide a brief TL;DR when the description runs long.

License

Chunky is released under the MIT License.

Glossary

Term Meaning
PR GitHub pull request – a request to merge one branch or fork with another
Release Publishing a tagged version of the project to PyPI
ChangeLog A document describing changes between releases
PyPI Python Package Index – where published distributions live
Ruff A fast Python linter/formatter used for style enforcement
origin The upstream GitHub repository
fork A downstream copy of the origin repo used for contributing
master/main The default branch
CI Continuous Integration – automated checks that run on every push/PR
GitHub Workflows GitHub’s automation runner configured via YAML files
pyproject.toml Core metadata and build configuration for the package
bump-my-version CLI used to bump version numbers consistently
Read the Docs Hosted documentation service that builds from the repo

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