# Annotated Doc Document parameters, class attributes, return types, and variables inline, with `Annotated`. Test Coverage Package version Supported Python versions ## Installation ```bash pip install annotated-doc ``` Or with `uv`: ```Python uv add annotated-doc ``` ## Usage Import `Doc` and pass a single literal string with the documentation for the specific parameter, class attribute, return type, or variable. For example, to document a parameter `name` in a function `hi` you could do: ```Python from typing import Annotated from annotated_doc import Doc def hi(name: Annotated[str, Doc("Who to say hi to")]) -> None: print(f"Hi, {name}!") ``` You can also use it to document class attributes: ```Python from typing import Annotated from annotated_doc import Doc class User: name: Annotated[str, Doc("The user's name")] age: Annotated[int, Doc("The user's age")] ``` The same way, you could document return types and variables, or anything that could have a type annotation with `Annotated`. ## Who Uses This `annotated-doc` was made for: * [FastAPI](https://fastapi.tiangolo.com/) * [Typer](https://typer.tiangolo.com/) * [SQLModel](https://sqlmodel.tiangolo.com/) * [Asyncer](https://asyncer.tiangolo.com/) `annotated-doc` is supported by [griffe-typingdoc](https://github.com/mkdocstrings/griffe-typingdoc), which powers reference documentation like the one in the [FastAPI Reference](https://fastapi.tiangolo.com/reference/). ## Reasons not to use `annotated-doc` You are already comfortable with one of the existing docstring formats, like: * Sphinx * numpydoc * Google * Keras Your team is already comfortable using them. You prefer having the documentation about parameters all together in a docstring, separated from the code defining them. You care about a specific set of users, using one specific editor, and that editor already has support for the specific docstring format you use. ## Reasons to use `annotated-doc` * No micro-syntax to learn for newcomers, it’s **just Python** syntax. * **Editing** would be already fully supported by default by any editor (current or future) supporting Python syntax, including syntax errors, syntax highlighting, etc. * **Rendering** would be relatively straightforward to implement by static tools (tools that don't need runtime execution), as the information can be extracted from the AST they normally already create. * **Deduplication of information**: the name of a parameter would be defined in a single place, not duplicated inside of a docstring. * **Elimination** of the possibility of having **inconsistencies** when removing a parameter or class variable and **forgetting to remove** its documentation. * **Minimization** of the probability of adding a new parameter or class variable and **forgetting to add its documentation**. * **Elimination** of the possibility of having **inconsistencies** between the **name** of a parameter in the **signature** and the name in the docstring when it is renamed. * **Access** to the documentation string for each symbol at **runtime**, including existing (older) Python versions. * A more formalized way to document other symbols, like type aliases, that could use Annotated. * **Support** for apps using FastAPI, Typer and others. * **AI Accessibility**: AI tools will have an easier way understanding each parameter as the distance from documentation to parameter is much closer. ## History I ([@tiangolo](https://github.com/tiangolo)) originally wanted for this to be part of the Python standard library (in [PEP 727](https://peps.python.org/pep-0727/)), but the proposal was withdrawn as there was a fair amount of negative feedback and opposition. The conclusion was that this was better done as an external effort, in a third-party library. So, here it is, with a simpler approach, as a third-party library, in a way that can be used by others, starting with FastAPI and friends. ## License This project is licensed under the terms of the MIT license.