Ray Distributed Debugger#
The Ray Distributed Debugger is a VS Code extension that streamlines the debugging process with an interactive debugging experience. The Ray Debugger enables you to:
Break into remote tasks: Set a breakpoint in any remote task. A breakpoint pauses execution and allows you to connect with VS Code for debugging.
Post-mortem debugging: When Ray tasks fail with unhandled exceptions, Ray automatically freezes the failing task and waits for the Ray Debugger to attach, allowing you to inspect the state of the program at the time of the error.
Ray Distributed Debugger abstracts the complexities of debugging distributed systems for you to debug Ray applications more efficiently, saving time and effort in the development workflow.
Download the Ray Debugger extension.
Set up the environment#
Create a new virtual environment and install dependencies.
conda create -n myenv python=3.9
conda activate myenv
pip install "ray[default]" debugpy
Start a Ray cluster#
Run ray start --head
to start a Ray cluster.
Register the cluster#
Find and click the Ray extension in the VS Code left side nav. Add the Ray cluster IP:PORT
to the cluster list. The default IP:PORT
is 127.0.0.1:8265
. You can change it when you start the cluster. Make sure your current machine can access the IP and port.
![../_images/register-cluster.gif](../_images/register-cluster.gif)
Create a Ray task#
Create a file job.py
with the following snippet. Add the RAY_DEBUG
environment variable to enable Ray Debugger and add breakpoint()
in the Ray task.
import ray
import sys
# Add RAY_DEBUG environment variable to enable Ray Debugger.
ray.init(
runtime_env={
"env_vars": {"RAY_DEBUG": "1"},
}
)
@ray.remote
def my_task(x):
y = x * x
breakpoint() # Add a breakpoint in the Ray task.
return y
@ray.remote
def post_mortem(x):
x += 1
raise Exception("An exception is raised.")
return x
if len(sys.argv) == 1:
ray.get(my_task.remote(10))
else:
ray.get(post_mortem.remote(10))
Run your Ray app#
Start running your Ray app.
python job.py
Attach to the paused task#
When the debugger hits a breakpoint:
The task enters a paused state.
The terminal clearly indicates when the debugger pauses a task and waits for the debugger to attach.
The paused task is listed in the Ray Debugger extension.
Click the play icon next to the name of the paused task to attach the VS Code debugger.
![../_images/attach-paused-task.gif](../_images/attach-paused-task.gif)
Start debugging#
Debug your Ray app as you would when developing locally.
Post-mortem debugging#
Use post-mortem debugging when Ray tasks encounter unhandled exceptions. In such cases, Ray automatically freezes the failing task, awaiting attachment by the Ray Debugger. This feature allows you to thoroughly investigate and inspect the program’s state at the time of the error.
Run a Ray task raised exception#
Run the same job.py
file with an additional argument to raise an exception.
python job.py raise-exception
Attach to the paused task#
When the app throws an exception:
The debugger freezes the task.
The terminal clearly indicates when the debugger pauses a task and waits for the debugger to attach.
The paused task is listed in the Ray Debugger extension.
Click the play icon next to the name of the paused task to attach the debugger and start debugging.
![../_images/post-moretem.gif](../_images/post-moretem.gif)
Start debugging#
Debug your Ray app as you would when developing locally.
Next steps#
For guidance on debugging distributed apps in Ray, see General debugging.
For tips on using the Ray debugger, see Ray debugging.