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API Reference: Data Models

The core logic of envars is built around a set of simple, Pydantic-like data models that represent the different components of your configuration.

This section of the documentation is best generated automatically from the source code's docstrings. To do this, you can use a tool like mkdocstrings.

  1. Install mkdocstrings: bash pip install mkdocstrings mkdocstrings-python

  2. Configure mkdocs.yml: Add the mkdocstrings plugin to your mkdocs.yml file.

    ```yaml

    In mkdocs.yml

    plugins: - search - mkdocstrings: handlers: python: options: show_root_heading: yes ```

  3. Add Auto-Generated Content: You can then replace the content of this file with the following to automatically pull in the documentation for your models:

    ```markdown

    Data Models

    ::: envars.models.Variable

    ::: envars.models.Environment

    ::: envars.models.Location

    ::: envars.models.VariableValue

    ::: envars.models.VariableManager ```

This setup will read the docstrings from your Python classes in src/envars/models.py and render them as clean, readable documentation whenever you build your site with mkdocs build.