Building Ray from Source

For a majority of Ray users, installing Ray via the latest wheels or pip package is usually enough. However, you may want to build the latest master branch.

Tip

If you are only editing Python files, follow instructions for Building Ray (Python Only) to avoid long build times.

Clone the repository

To build Ray locally you will need to have the Git repository, so first, fork it on GitHub. Then you can clone it to your machine:

To clone the repository using Git with SSH (the default) run:

git clone git@github.com:[your username]/ray.git

To clone the repository using Git with HTTPS run:

git clone https://github.com/[your username]/ray.git

Then you can enter into the Ray git repository directory:

cd ray

Next make sure you connect your repository to the upstream (main project) Ray repository. This will allow you to push your code to your repository when proposing changes (in pull requests) while also pulling updates from the main project.

To connect your repository using SSH (the default) run the command:

git remote add upstream git@github.com:ray-project/ray.git

To connect your repository using HTTPS run the command:

git remote add upstream https://github.com/ray-project/ray.git

Every time you want to update your local version you can pull the changes from the main repository:

# Checkout the local master branch
git checkout master
# Pull the latest changes from the main repository
git pull upstream master

Prepare the Python environment

Tip

To setup an isolated Anaconda environment, see Installing Ray with Anaconda.

You will probably want to have some type of Python virtual environment. For example you could use Python’s integrated venv module to create one:

python -m venv env

That will create a virtual environment called env in the current directory, it will contain a directory with all the packages used by the local Python of your project. You only need to do this step once.

Next, you need to activate the environment to tell your shell/terminal to use this particular Python. This will also depend on the system you use to set up your virtual environment (conda, venv, or other methods).

If you are using the example from above using venv, you would activate your virtual environment with:

source env/bin/activate

You will need to activate the virtual environment every time you start a new shell/terminal to work on Ray.

After that, it’s always good to make sure you have the latest version of pip and wheel. When you create a new virtual environment it can come with an older version, and many strange-looking problems while installing packages are simply solved by upgrading pip to the latest version:

python -m pip install --upgrade pip wheel

That command tells Python to use the module pip to install the latest version of pip (itself) and wheel.

Building Ray (Python Only)

Note

Unless otherwise stated, directory and file paths are relative to the project root directory.

RLlib, Tune, Autoscaler, and most Python files do not require you to build and compile Ray. Follow these instructions to develop Ray’s Python files locally without building Ray.

  1. Make sure you have a clone of Ray’s git repository as explained above.

  2. Make sure you activate the Python (virtual) environment as described above.

  3. Pip install the latest Ray wheels. See Daily Releases (Nightlies) for instructions.

# For example, for Python 3.8:
pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
  1. Replace Python files in the installed package with your local editable copy. We provide a simple script to help you do this: python python/ray/setup-dev.py. Running the script will remove the ray/tune, ray/rllib, ray/autoscaler dir (among other directories) bundled with the ray pip package, and replace them with links to your local code. This way, changing files in your git clone will directly affect the behavior of your installed Ray.

# This replaces `<package path>/site-packages/ray/<package>`
# with your local `ray/python/ray/<package>`.
python python/ray/setup-dev.py

Warning

Do not run pip uninstall ray or pip install -U (for Ray or Ray wheels) if setting up your environment this way. To uninstall or upgrade, you must first rm -rf the pip-installation site (usually a directory at the site-packages/ray location), then do a pip reinstall (see the command above), and finally run the above setup-dev.py script again.

# To uninstall, delete the symlinks first.
rm -rf <package path>/site-packages/ray # Path will be in the output of `setup-dev.py`.
pip uninstall ray # or `pip install -U <wheel>`

Preparing to build Ray on Linux

Tip

If you are only editing Tune/RLlib/Autoscaler files, follow instructions for Building Ray (Python Only) to avoid long build times.

To build Ray on Ubuntu, run the following commands:

sudo apt-get update
sudo apt-get install -y build-essential curl unzip psmisc

# Install Bazel.
ci/env/install-bazel.sh

For RHELv8 (Redhat EL 8.0-64 Minimal), run the following commands:

sudo yum groupinstall 'Development Tools'
sudo yum install psmisc

In RedHat, install Bazel manually from this link: https://docs.bazel.build/versions/main/install-redhat.html

Preparing to build Ray on MacOS

Tip

Assuming you already have Brew and Bazel installed on your mac and you also have grpc and protobuf installed on your mac consider removing those (grpc and protobuf) for smooth build through the commands brew uninstall grpc, brew uninstall protobuf. If you have built the source code earlier and it still fails with errors like No such file or directory:, try cleaning previous builds on your host by running the commands brew uninstall binutils and bazel clean --expunge.

To build Ray on MacOS, first install these dependencies:

brew update
brew install wget

# Install Bazel.
ray/ci/env/install-bazel.sh

Building Ray on Linux & MacOS (full)

Make sure you have a local clone of Ray’s git repository as explained above. You will also need to install NodeJS to build the dashboard.

Enter into the project directory, for example:

cd ray

Now you can build the dashboard. From inside of your local Ray project directory enter into the dashboard client directory:

cd dashboard/client

Then you can install the dependencies and build the dashboard:

npm install
npm run build

After that, you can now move back to the top level Ray directory:

cd ../..

Now let’s build Ray for Python. Make sure you activate any Python virtual (or conda) environment you could be using as described above.

Enter into the python/ directory inside of the Ray project directory and install the project with pip:

# Install Ray.
cd python/
pip install -e . --verbose  # Add --user if you see a permission denied error.

The -e means “editable”, so changes you make to files in the Ray directory will take effect without reinstalling the package.

Warning

if you run python setup.py install, files will be copied from the Ray directory to a directory of Python packages (/lib/python3.6/site-packages/ray). This means that changes you make to files in the Ray directory will not have any effect.

Tip

If your machine is running out of memory during the build or the build is causing other programs to crash, try adding the following line to ~/.bazelrc:

build --local_ram_resources=HOST_RAM*.5 --local_cpu_resources=4

The build --disk_cache=~/bazel-cache option can be useful to speed up repeated builds too.

Building Ray on Windows (full)

Requirements

The following links were correct during the writing of this section. In case the URLs changed, search at the organizations’ sites.

You can also use the included script to install Bazel:

# Install Bazel.
ray/ci/env/install-bazel.sh
# (Windows users: please manually place Bazel in your PATH, and point
# BAZEL_SH to MSYS2's Bash: ``set BAZEL_SH=C:\Program Files\Git\bin\bash.exe``)

Steps

  1. Enable Developer mode on Windows 10 systems. This is necessary so git can create symlinks.

    1. Open Settings app;

    2. Go to “Update & Security”;

    3. Go to “For Developers” on the left pane;

    4. Turn on “Developer mode”.

  2. Add the following Miniconda subdirectories to PATH. If Miniconda was installed for all users, the following paths are correct. If Miniconda is installed for a single user, adjust the paths accordingly.

    • C:\ProgramData\Miniconda3

    • C:\ProgramData\Miniconda3\Scripts

    • C:\ProgramData\Miniconda3\Library\bin

  3. Define an environment variable BAZEL_SH to point to bash.exe. If git for Windows was installed for all users, bash’s path should be C:\Program Files\Git\bin\bash.exe. If git was installed for a single user, adjust the path accordingly.

4. Bazel 4.2 installation. Go to Bazel 4.2 release web page and download bazel-4.2.1-windows-x86_64.exe. Copy the exe into the directory of your choice. Define an environment variable BAZEL_PATH to full exe path (example: set BAZEL_PATH=C:\bazel\bazel.exe). Also add the Bazel directory to the PATH (example: set PATH=%PATH%;C:\bazel)

  1. Download ray source code and build it.

# cd to the directory under which the ray source tree will be downloaded.
git clone -c core.symlinks=true https://github.com/ray-project/ray.git
cd ray\python
pip install -e . --verbose

Environment variables that influence builds

You can tweak the build with the following environment variables (when running pip install -e . or python setup.py install):

  • BUILD_JAVA: If set and equal to 1, extra build steps will be executed to build java portions of the codebase

  • RAY_INSTALL_CPP: If set and equal to 1, ray-cpp will be installed

  • RAY_DISABLE_EXTRA_CPP: If set and equal to 1, a regular (non - cpp) build will not provide some cpp interfaces

  • SKIP_BAZEL_BUILD: If set and equal to 1, no Bazel build steps will be executed

  • SKIP_THIRDPARTY_INSTALL: If set will skip installation of third-party python packages

  • RAY_DEBUG_BUILD: Can be set to debug, asan, or tsan. Any other value will be ignored

  • BAZEL_LIMIT_CPUS: If set, it must be an integers. This will be fed to the --local_cpu_resources argument for the call to Bazel, which will limit the number of CPUs used during Bazel steps.

  • IS_AUTOMATED_BUILD: Used in CI to tweak the build for the CI machines

  • SRC_DIR: Can be set to the root of the source checkout, defaults to None which is cwd()

  • BAZEL_SH: used on Windows to find a bash.exe, see below

  • BAZEL_PATH: used on Windows to find bazel.exe, see below

  • MINGW_DIR: used on Windows to find bazel.exe if not found in BAZEL_PATH

Installing additional dependencies for development

Dependencies for the linter (scripts/format.sh) can be installed with:

pip install -r python/requirements_linters.txt

Dependencies for running Ray unit tests under python/ray/tests can be installed with:

pip install -r python/requirements.txt

Requirement files for running Ray Data / ML library tests are under python/requirements/.

Fast, Debug, and Optimized Builds

Currently, Ray is built with optimizations, which can take a long time and interfere with debugging. To perform fast, debug, or optimized builds, you can run the following (via -c fastbuild/dbg/opt, respectively):

bazel build -c fastbuild //:ray_pkg

This will rebuild Ray with the appropriate options (which may take a while). If you need to build all targets, you can use "//:*" instead of //:ray_pkg.

To make this change permanent, you can add an option such as the following line to your user-level ~/.bazelrc file (not to be confused with the workspace-level .bazelrc file):

build --compilation_mode=fastbuild

If you do so, remember to revert this change, unless you want it to affect all of your development in the future.

Using dbg instead of fastbuild generates more debug information, which can make it easier to debug with a debugger like gdb.

Building the Docs

To learn more about building the docs refer to Contributing to the Ray Documentation.

Using a local repository for dependencies

If you’d like to build Ray with custom dependencies (for example, with a different version of Cython), you can modify your .bzl file as follows:

http_archive(
  name = "cython",
  ...,
) if False else native.new_local_repository(
  name = "cython",
  build_file = "bazel/BUILD.cython",
  path = "../cython",
)

This replaces the existing http_archive rule with one that references a sibling of your Ray directory (named cython) using the build file provided in the Ray repository (bazel/BUILD.cython). If the dependency already has a Bazel build file in it, you can use native.local_repository instead, and omit build_file.

To test switching back to the original rule, change False to True.