A REST API should spend almost all of its descriptive effort in defining the media type(s) used for representing resources and driving application state.
— Roy Fielding, REST APIs must be hypertext driven
There are a variety of approaches to API documentation. This document introduces a few of the various tools and options you might choose from. The approaches should not be considered exclusive - you may want to provide more than one documentation style for you API, such as a self describing API that also includes static documentation of the various API endpoints.
The most common way to document Web APIs today is to produce documentation that lists the API endpoints verbatim, and describes the allowable operations on each. There are various tools that allow you to do this in an automated or semi-automated way.
DRF Docs allows you to document Web APIs made with Django REST Framework and it is authored by Emmanouil Konstantinidis. It's made to work out of the box and its setup should not take more than a couple of minutes. Complete documentation can be found on the website while there is also a demo available for people to see what it looks like. Live API Endpoints allow you to utilize the endpoints from within the documentation in a neat way.
Features include customizing the template with your branding, settings for hiding the docs depending on the environment and more.
Both this package and Django REST Swagger are fully documented, well supported, and come highly recommended.
Marc Gibbons' Django REST Swagger integrates REST framework with the Swagger API documentation tool. The package produces well presented API documentation, and includes interactive tools for testing API endpoints.
Django REST Swagger supports REST framework versions 2.3 and above.
Mark is also the author of the REST Framework Docs package which offers clean, simple autogenerated documentation for your API but is deprecated and has moved to Django REST Swagger.
Both this package and DRF docs are fully documented, well supported, and come highly recommended.
Oleksander Mashianovs' DRF Auto Docs automated api renderer.
Collects almost all the code you written into documentation effortlessly.
- functional view docs
- tree-like structure
- preserve space & newlines
- formatting with nice syntax
- choices rendering
- help_text (to specify SerializerMethodField output, etc)
- smart read_only/required rendering
- Endpoint properties:
- extra url params(GET params)
There are various other online tools and services for providing API documentation. One notable service is Apiary. With Apiary, you describe your API using a simple markdown-like syntax. The generated documentation includes API interaction, a mock server for testing & prototyping, and various other tools.
The browsable API that REST framework provides makes it possible for your API to be entirely self describing. The documentation for each API endpoint can be provided simply by visiting the URL in your browser.
The title that is used in the browsable API is generated from the view class name or function name. Any trailing
ViewSet suffix is stripped, and the string is whitespace separated on uppercase/lowercase boundaries or underscores.
For example, the view
UserListView, will be named
User List when presented in the browsable API.
When working with viewsets, an appropriate suffix is appended to each generated view. For example, the view set
UserViewSet will generate views named
User List and
The description in the browsable API is generated from the docstring of the view or viewset.
If the python
markdown library is installed, then markdown syntax may be used in the docstring, and will be converted to HTML in the browsable API. For example:
class AccountListView(views.APIView): """ Returns a list of all **active** accounts in the system. For more details on how accounts are activated please [see here][ref]. [ref]: http://example.com/activating-accounts """
Note that one constraint of using viewsets is that any documentation be used for all generated views, so for example, you cannot have differing documentation for the generated list view and detail view.
REST framework APIs also support programmatically accessible descriptions, using the
OPTIONS HTTP method. A view will respond to an
OPTIONS request with metadata including the name, description, and the various media types it accepts and responds with.
When using the generic views, any
OPTIONS requests will additionally respond with metadata regarding any
PUT actions available, describing which fields are on the serializer.
You can modify the response behavior to
OPTIONS requests by overriding the
metadata view method. For example:
def metadata(self, request): """ Don't include the view description in OPTIONS responses. """ data = super(ExampleView, self).metadata(request) data.pop('description') return data
To be fully RESTful an API should present its available actions as hypermedia controls in the responses that it sends.
In this approach, rather than documenting the available API endpoints up front, the description instead concentrates on the media types that are used. The available actions that may be taken on any given URL are not strictly fixed, but are instead made available by the presence of link and form controls in the returned document.
To implement a hypermedia API you'll need to decide on an appropriate media type for the API, and implement a custom renderer and parser for that media type. The REST, Hypermedia & HATEOAS section of the documentation includes pointers to background reading, as well as links to various hypermedia formats.