Development Tips

If you are doing development on the Ray codebase, the following tips may be helpful.

  1. Speeding up compilation: Be sure to install Ray with

    cd ray/python
    pip install -e . --verbose

    The -e means “editable”, so changes you make to files in the Ray directory will take effect without reinstalling the package. In contrast, if you do python install, files will be copied from the Ray directory to a directory of Python packages (often something like /home/ubuntu/anaconda3/lib/python3.6/site-packages/ray). This means that changes you make to files in the Ray directory will not have any effect.

    If you run into Permission Denied errors when running pip install, you can try adding --user. You may also need to run something like sudo chown -R $USER /home/ubuntu/anaconda3 (substituting in the appropriate path).

    If you make changes to the C++ files, you will need to recompile them. However, you do not need to rerun pip install -e .. Instead, you can recompile much more quickly by doing

    cd ray/python/ray/core
    make -j8
  2. Starting processes in a debugger: When processes are crashing, it is often useful to start them in a debugger (gdb on Linux or lldb on MacOS). See the latest discussion about how to do this here.

  3. Running tests locally: Suppose that one of the tests (e.g., is failing. You can run that test locally by running python test/ However, doing so will run all of the tests which can take a while. To run a specific test that is failing, you can do

    cd ray
    python test/ APITest.testKeywordArgs

    When running tests, usually only the first test failure matters. A single test failure often triggers the failure of subsequent tests in the same script.

  4. Running linter locally: To run the Python linter on a specific file, run something like flake8 ray/python/ray/ You may need to first run pip install flake8.

  5. Inspecting Redis shards by hand: To inspect the primary Redis shard by hand, you can query it with commands like the following.

    r_primary = ray.worker.global_worker.redis_client

    To inspect other Redis shards, you will need to create a new Redis client. For example (assuming the relevant IP address is and the relevant port is 1234), you can do this as follows.

    import redis
    r = redis.StrictRedis(host='', port=1234)

    You can find a list of the relevant IP addresses and ports by running

    r_primary.lrange('RedisShards', 0, -1)