mllint is compiled for Linux, MacOS and Windows, both 64 and 32 bit x86 (MacOS 64-bit only), as well as 64-bit ARM on Linux and MacOS (Apple M1).
mllint is published to PyPI, so it can be installed globally or in your current environment using pip:
pip install --upgrade mllint
Alternatively, to add mllint to an existing project, if your project uses Poetry for its dependencies:
poetry add --dev mllint
Or if your project uses Pipenv:
pipenv install --dev mllint
Tools
mllint has a soft dependency on several Python tools that it uses for its analysis. While mllint will recommend that you place these tools in your project’s development dependencies, these tools are listed as optional dependencies of mllint and can be installed along with mllint using:
pip install --upgrade mllint[tools]
Docker
There are also mllint Docker containers available on Docker Hub at bvobart/mllint for Python 3.6, 3.7, 3.8 and 3.9. These may particularly be helpful when running mllint in CI environments, such as Gitlab CI or Github Actions. See the Docker Hub for a full list of available tags that can be used.
The Docker containers require that you mount the folder with your project onto the container as a volume on /app. Here is an example of how to use this Docker container, assuming that your project is in the current folder. Replace $(pwd) with the full path to your project folder if it is somewhere else.
docker run -it --rm -v $(pwd):/app bvobart/mllint:latest