FlyteInteractive Jupyter Decorator

Once you have a Union account, install union:

pip install union

Export the following environment variable to build and push images to your own container registry:

# replace with your registry name
export IMAGE_SPEC_REGISTRY="<your-container-registry>"

Then run the following commands to run the workflow:

git clone https://github.com/unionai/unionai-examples
cd unionai-examples
union run --remote tutorials/sentiment_classifier/sentiment_classifier.py main --model distilbert-base-uncased

The source code for this tutorial can be found here {octicon}mark-github.
The @jupyter task decorator launches and monitors a Jupyter notebook server.

Usage

1. Add the @jupyter decorator to a task function definition

The @jupyter decorator takes the following optional parameters:

  • max_idle_seconds: Optional[int] (default 36000)
  • port: Optional[int] (default 8888)
  • enable: Optional[bool] (default True)
  • notebook_dir: Optional[str] (default “/root”)
  • pre_execute: Optional[Callable] (default None)
  • post_execute: Optional[Callable], (default None)
from flytekit import task, workflow
from flytekitplugins.flyteinteractive import jupyter


@task
@jupyter
def jupyter_task():
    print("opened notebook")


@workflow
def wf():
    jupyter_task()


if __name__ == "__main__":
    print(wf())

2. Connect to the Jupyter notebook server

You can connect in two ways:

  • (Recommended) Expose a URL on the Flyte console. Set up ingress on the Flyte backend to expose a URL on the Flyte console. Details are to be determined (TBD).

  • Use port forwarding. To use port forwarding, execute the following command:

    $ kubectl port-forward <pod name> <port>

    Then, open a browser and navigate to localhost:<port>, replacing <port> with the port number configured above. You should be presented with the Jupyter notebook interface.