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Documenting REST API endpoints

This document briefly explains how to document Zulip's REST API endpoints.

Our API documentation files live under templates/zerver/api/*. To begin, we recommend using an existing doc file (render-message.md is a good example) as a template. Make sure you link to your new Markdown file in templates/zerver/help/include/rest-endpoints.md , so that it appears in the index in the left sidebar on the /api page.

The markdown framework is the same one used by the user docs, which supports macros and various other features, though we don't use them heavily here.

If you look at the documentation for existing endpoints (see a live example here), you'll notice that a typical endpoint's documentation is roughly divided into three sections: Usage examples, Arguments, and Response. The rest of this guide describes how to write each of these sections.

There's also a small section at the top, where you'll want to explain what the endpoint does in clear English, and any important notes on how to use it correctly or what it's good or bad for.

Usage examples

We display usage examples in three languages: Python, JavaScript and curl. For JavaScript and curl we simply recommend copying and pasting the examples directly into the Markdown file. JavaScript examples should conform to the coding style and structure of Zulip's existing JavaScript examples. However, since Zulip's Python bindings are used most frequently, the process of adding Python examples for an endpoint have a more involved process that includes automated tests for your documentation(!).

We recommend skimming zerver/lib/api_test_helpers.py before proceeding with the steps below.

Start adding a function for the endpoint you'd like to document to zerver/lib/api_test_helpers.py. render_message is a good example to follow. There are generally two key pieces to your test: (1) doing an API query and (2) verifying its result is as expected using test_against_fixture.
Make the desired API call inside the function. If our Python bindings don't have a dedicated method for a specific API call, you may either use client.call_endpoint or add a dedicated function to the zulip PyPI package. Ultimately, the goal is for every endpoint to be documented the latter way, but it's nice to be able to write your docs before you have to finish writing dedicated functions.
Add the function to the TEST_FUNCTIONS dict and one of the test_* functions at the end of zerver/lib/api_test_helpers.py; these will ensure your function will be called when running test-api.
Capture the JSON response returned by the API call (the test "fixture"). The easiest way to do this is add an appropriate print statement, and then run tools/test-api (see Formatting JSON for how to get in it the right JSON format). Add the fixture to templates/zerver/api/fixtures.json, where the key is the name of the Markdown file documenting the endpoint (without the .md extension), and the value is the fixture JSON object.
Run ./tools/test-api to make sure your new test function is being run and the tests pass.
Now, inside the function, isolate the lines of code that call the API and could be displayed as a code example. Wrap the relevant lines in # {code_example|start} ... relevant lines go here ... # {code_example|end} comments. The lines inside these comments are what will be displayed as the code example on our /api page.
You may now use the following Markdown directive to render the lines inside the # {code_example|start} and # {code_example|end} blocks in your Markdown file, like so:
```
{generate_code_example(python)|KEY_IN_TEST_FUNCTIONS|example}
```
KEY_IN_TEST_FUNCTIONS is the key in the TEST_FUNCTIONS dict (added in step 2) that points to your test function.

This Markdown-based framework allows us to extract code examples from within tests, which makes sure that code examples never get out of date, since if they do, ./tools/test-api will fail in our continuous integration. To learn more about how this Markdown extension works, see zerver/lib/bugdown/api_code_examples.py.

Documenting arguments

We have a separate Markdown extension to document the arguments that an API endpoint expects.

Essentially, you document the arguments for a specific endpoint in templates/zerver/api/arguments.json, where the key is the name of the Markdown file documenting the endpoint, and the value is the JSON object describing the arguments.

You can use the following Markdown directive to render the arguments' documentation as a neatly organized table:

{generate_api_arguments_table|arguments.json|KEY_IN_ARGUMENTS_FILE}

KEY_IN_ARGUMENTS_FILE refers to the key in arguments.json, usually the name of the Markdown file where it will be used. To learn more about how this Markdown extension works, see zerver/lib/bugdown/api_arguments_table_generator.py.

The best way to find out what arguments an API endpoint takes is to find the corresponding URL pattern in zprojects/urls.py and examining the backend function that the URL pattern points to.

To understand how arguments are specified in Zulip backend endpoints, read our REST API tutorial, paying special attention to the details of how REQ works.

Be careful here! There's no currently automated testing verifying that the arguments match the code, so you need to be sure that you understand precisely how each argument is formatted.

Displaying example payloads/responses

If you've already followed the steps in the Usage examples section, this part should be fairly trivial.

You can use the following Markdown directive to render the fixtures stored in templates/zerver/api/fixtures.json:

{generate_code_example|KEY_IN_FIXTURES_FILE|fixture}

KEY_IN_FIXTURES_FILE refers to the key in fixtures.json, which is usually the name of the Markdown file (without the .md extension) where it will be used. You may add more fixtures to fixtures.json, if necessary. To learn more about how this Markdown extension works, see zerver/lib/bugdown/api_code_examples.py.

Formatting JSON

A quick way to format JSON is to use the Python json module and use the command json.dumps(json_dict, indent=4, sort_keys=True), where json_dict is the JSON object (which is a Python dict) to be formatted.

You can also use http://jsonformatter.curiousconcept.com/ to format the JSON fixtures.

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