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Opinionated Markdown formatter and linter

Project description

mdlint — Python package

This directory contains the Python distribution for mdlint, an opinionated Markdown formatter and linter written in Rust.

The package wraps the pre-built mdlint binary. No Rust toolchain is required to install or use it.

Installation

pip install mdlint

Or with uv:

uv tool install mdlint

Usage

# Format Markdown files
mdlint format

# Check for issues
mdlint check

# Check and auto-fix
mdlint check --fix

See the full documentation for all options, configuration, and CI integration examples.

How it works

pip install mdlint downloads a platform-specific wheel that bundles the correct pre-built mdlint binary for your OS and architecture. The mdlint command is a thin Python wrapper that locates and execs that binary.

Supported platforms:

Platform Architecture
Linux x86_64 (glibc)
Linux aarch64 (glibc)
macOS x86_64
macOS arm64 (Apple Silicon)
Windows x86_64

Development

Prerequisites

Build a wheel locally

cd python

# Pure-Python wheel (no binary bundled — for metadata validation only)
uv build --wheel

# Platform-specific wheel with a binary
cp /path/to/mdlint-binary mdlint/mdlint
MDLINT_PLATFORM_TAG=macosx_11_0_arm64 uv build --wheel

MDLINT_PLATFORM_TAG is read by hatch_build.py to stamp the correct platform tag onto the wheel. Without it, the wheel is tagged py3-none-any and contains no binary — useful for metadata validation in CI but not for distribution.

Validate package metadata

cd python
uv build --wheel
uvx twine check dist/*.whl

Platform tags

Asset MDLINT_PLATFORM_TAG
mdlint-linux-x86_64 manylinux_2_17_x86_64.manylinux2014_x86_64
mdlint-linux-aarch64 manylinux_2_17_aarch64.manylinux2014_aarch64
mdlint-macos-x86_64 macosx_10_12_x86_64
mdlint-macos-aarch64 macosx_11_0_arm64
mdlint-windows-x86_64.exe win_amd64

Release

Releases are automated via .github/workflows/build-python.yml. On a version tag push, the workflow downloads each pre-built binary from the GitHub release, builds a platform-specific wheel, uploads it to the GitHub release, and publishes it to PyPI.

A PYPI_TOKEN secret must be configured in the repository settings.

Project details


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