lintquarto 0.10.0

Package for running linters, static type checkers and code analysis tools on python code in quarto (.qmd) files.

lintquarto

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Package for running linters, static type checkers and code analysis tools on python code in quarto (.qmd) files.

By default, python code validation tools can't check embedded python code in Quarto files. This package fills that gap, enabling analysts and researchers to run python quality checks within Quarto documents.

Currently supported:

• Linters: pylint, flake8, pydoclint, pyflakes, ruff, vulture, and pycodestyle.
• Static type checkers: mypy, pyright, pyrefly, and pytype.
• Code analysis tools: radon.

Installation

You can install lintquarto with pip (from PyPI or GitHub) or conda (from conda-forge).

Install with pip

pip install lintquarto

To include your selection of linters, install them as needed.

For a one-step installation that includes lintquarto and all supported linters and type checkers, use:

pip install lintquarto[all]

Install with conda

conda install conda-forge::lintquarto

With conda, only the main lintquarto tool is installed. If you want to use any linters or type checkers, you must install them separately (either with conda or pip, depending on availability).

Development version

To install the latest development version of lintquarto directly from this repository:

pip install git+https://github.com/lintquarto/lintquarto

If you also want all supported linters and type checkers in one step, install from a local clone in editable mode with the all extra:

git clone https://github.com/lintquarto/lintquarto.git
cd lintquarto
pip install -e ".[all]"

Getting started using lintquarto

Usage

Usage:

lintquarto -l LINTER [LINTER ...] -p PATH [PATH ...] [-e EXCLUDE [EXCLUDE ...]] [-k]

Options:

• -l, --linters LINTER [LINTER ...] - linters to run.
• -p, --paths PATH [PATH ...] - quarto files and/or directories to include.
• -e, --exclude EXCLUDE [EXCLUDE ...] - optional, files and/or directories to exclude.
• -k, --keep-temp - optional, keep temporary .py files created during linting (for debugging).

Passing extra arguments directly to linters is not supported. Only .qmd files are processed.

Examples

The linter used is interchangeable in these examples.

Lint all .qmd files in the current directory (using pylint):

lintquarto -l pylint -p .

Lint several specific files (using pylint and flake8):

lintquarto -l pylint flake8 -p file1.qmd file2.qmd

Keep temporary .py files after linting (with pylint)

lintquarto -l pylint -p . -k

Lint all files in current directory (using ruff):

• Excluding folders examples/ and ignore/, or-
• Excluding a specific file analysis/test.qmd.

lintquarto -l ruff -p . -e examples ignore

lintquarto -l ruff -p . -e analysis/test.qmd

Find out more

Visit our website to find out more and see examples from running with each code validation tool.

PyOpenSci

This package has been submit to PyOpenSci for review. This includes an article for consideration by the Journal of Open Source Software (JOSS) which is in the inst/ folder of this repository.

Community

Curious about contributing? Check out the contributing guidelines to learn how you can help. Every bit of help counts, and your contribution - no matter how minor - is highly valued.

How to cite lintquarto

Please cite the repository on GitHub, PyPI, conda and/or Zenodo:

Heather, A. (2026). lintquarto (v0.10.0). https://github.com/lintquarto/lintquarto.

Heather, A. (2026). lintquarto (v0.10.0). https://pypi.org/project/lintquarto/.

Heather, A. (2026). lintquarto (v0.10.0). https://anaconda.org/conda-forge/lintquarto.

Heather, A. (2026). lintquarto (v0.10.0). https://doi.org/10.5281/zenodo.15731161.

Citation instructions are also provided in CITATION.cff.

Acknowledgements

This project was written and maintained by hand, with occasional use of Perplexity AI during development (specific models and versions varied over time).

AI assistance was used for small, targeted tasks (e.g. help when troubleshooting, identifying issues, refining docstrings, improving code structure), rather than to generate complete functions or substantial content.

All code and design decisions were reviewed and finalised by a human. For transparency, the use of AI is acknowledged, but the project should not be considered AI‑generated.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Amy Heather 🎨 📖 🤔 🚇 🚧 ⚠️

Isabel Zimmerman 📖 🤔

This project follows the all-contributors specification. Contributions of any kind welcome!