Ray Documentation

Repository for documentation of the Ray project, hosted at docs.ray.io.

Installation

To build the documentation, make sure you have ray installed first. For building the documentation locally install the following dependencies:

pip install -r requirements-doc.txt

Building the documentation

To compile the documentation and open it locally, run the following command from this directory.

make develop && open _build/html/index.html

Building just one subproject

Often your changes in documentation just concern one subproject, such as Tune or Train. To build just this one subproject, and ignore the rest (leading to build warnings due to broken references etc.), run the following command:

DOC_LIB=<project> sphinx-build -b html -d _build/doctrees  source _build/html

where <project> is the name of the subproject and can be any of the docs projects in the source/ directory either called tune, rllib, train, cluster, serve, data or the ones starting with ray-, e.g. ray-observability.

Announcements and includes

To add new announcements and other messaging to the top or bottom of a documentation page, check the _includes folder first to see if the message you want is already there (like "get help" or "we're hiring" etc.) If not, add the template you want and include it accordingly, i.e. with

.. include:: /_includes/<my-announcement>

This ensures consistent messaging across documentation pages.

Checking for broken links

To check if there are broken links, run the following (we are currently not running this in the CI since there are false positives).

make linkcheck

Running doctests

To run tests for examples shipping with docstrings in Python files, run the following command:

make doctest

Adding examples as MyST Markdown Notebooks

You can now add executable notebooks to this project, which will get built into the documentation.

By default, building the docs with make develop will not run those notebooks. If you set the RUN_NOTEBOOKS environment variable to "cache", each notebook cell will be run when you build the documentation, and outputs will be cached into _build/.jupyter_cache.

RUN_NOTEBOOKS="cache" make develop

To force re-running the notebooks, use RUN_NOTEBOOKS="force".

Using caching, this means the first time you build the documentation, it might take a while to run the notebooks. After that, notebook execution is only triggered when you change the notebook source file.

The benefits of working with notebooks for examples are that you don't separate the code from the documentation, but can still easily smoke-test the code.

Adding Markdown docs from external (ecosystem) repositories

In order to avoid a situation where duplicate documentation files live in both the docs folder in this repository and in external repositories of ecosystem libraries (eg. xgboost-ray), you can specify Markdown files that will be downloaded from other GitHub repositories during the build process.

In order to do that, simply edit the EXTERNAL_MARKDOWN_FILES list in source/custom_directives.py using the format in the comment. Before build process, the specified files will be downloaded, preprocessed and saved to given paths. The build process will then proceed as normal.

While both GitHub Markdown and MyST are supersets of Common Markdown, there are differences in syntax. Furthermore, some contents such as Sphinx headers are not desirable to be displayed on GitHub. In order to deal with this, simple preprocessing is performed to allow for differences in rendering on GitHub and in docs. You can use two commands ($UNCOMMENT and $REMOVE/$END_REMOVE) in the Markdown file, specified in the following way:

$UNCOMMENT

GitHub:

<!--$UNCOMMENTthis will be uncommented--> More text

In docs, this will become:

this will be uncommented More text

$REMOVE/$END_REMOVE

GitHub:

<!--$REMOVE-->This will be removed<!--$END_REMOVE--> More text

In docs, this will become:

More text

Please note that the parsing is extremely simple (regex replace) and will not support nesting.

Testing changes locally

If you want to run the preprocessing locally on a specific file (to eg. see how it will render after docs have been built), run source/preprocess_github_markdown.py PATH_TO_MARKDOWN_FILE PATH_TO_PREPROCESSED_MARKDOWN_FILE. Make sure to also edit EXTERNAL_MARKDOWN_FILES in source/custom_directives.py so that your file does not get overwritten by one downloaded from GitHub.