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Get Started

Although using JupyterFlow does not require Kubernetes knowledge, setting up JupyterFlow requires Kubernetes understandings(YAML, helm, Service). If you're familiar with Kubernetes, it will not be too hard.

This project only works on JupyterHub for Kubernetes and Kubeflow.

Options for setting up JupyterFlow

There are two ways to set up jupyterflow

After the setup, you can run your workflow with jupyterflow on Kubernetes. Launch your jupyter notebook and follow the example.

Run my first workflow

Refer to examples/get-started to get the example scripts.

By command

Write your own code in notebook server.

import sys
print('world %s!' % sys.argv[1])

Run following command for sequence workflow.

jupyterflow run -c "python >> python foo"

Go to Argo Web UI and check out the output of launched workflow.

By workflow.yaml file

If you want to run more sophisticated workflow, such as DAG (Directed Acyclic Graph), write your own workflow file (for example, workflow.yaml, the name doesn't matter)

For more information, check out Configuring workflow

# workflow.yaml
- python 
- python foo
- python bar
- python

# Job index starts at 1.
- 1 >> 2
- 1 >> 3
- 2 >> 4
- 3 >> 4

Run jupyteflow with -f option.

jupyterflow run -f workflow.yaml

Check out the result.