Docdantic is a Python library that enables the automatic generation of Markdown documentation from Pydantic models. It works as an extension of the Markdown package, extracting model details and creating neat tables with model fields and their properties.
- Supports both Pydantic V1 and V2 models.
- Automatically generate tables of Pydantic model fields with their details (name, type, required, default).
- Supports nested Pydantic models.
- Configurable exclusion of specific fields from the documentation.
pip install docdanticTo generate documentation directly from Markdown files, you can use the Docdantic extension. Simply include the !docdantic: import.path.to.Model directive in your Markdown text:
# MyModel Reference
!docdantic: my_module.MyModelDocdantic will replace the !docdantic directive with a table of model field details.
If you want to programmatically generate Markdown documentation from Pydantic v2 models, you can use Docdantic in your Python code. Here's an example:
import markdown
from docdantic import Docdantic
markdown_text = "Here are the details of my model:\n\n!docdantic: your.model.path"
converted_text = markdown.markdown(markdown_text, extensions=[Docdantic()])
# `converted_text` will contain the Markdown text with the model documentationYou can include the !docdantic: your.model.path directive in your Markdown text as before, and the markdown.markdown method will process it using the Docdantic extension.
Docdantic allows you to exclude specific fields from the generated documentation by using the exclude configuration. You can provide a JSON object in the exclude field of the configuration to specify which fields to exclude. For example:
!docdantic: my_module.MyModel
{
"exclude": {
"MyModel": ["field1", "field2"]
}
}In the example above, the fields field1 and field2 will be excluded from the documentation of the MyModel model. Notice the configuration has to be indented with 2-4 spaces or a tab.
This project is licensed under the terms of the MIT license. See LICENSE for more details.