Use our JupyterLab extension (“JupyterLab-Pachyderm”) to:

• Connect your Notebook to a Pachyderm cluster
• Browse, open, and analyze data stored in Pachyderm directly from your Notebook
• Run and test out your pipeline code before creating a Docker image

Try it Out #

To try JupyterLab-Pachyderm right away, run our JupyterLab Docker image, which contains JupyterLab and JupyterLab-Pachyderm pre-installed. If you have a running Pachyderm cluster, you can run the image, connect it to your cluster and explore your Pachyderm data in a notebook.

Install the Extension #

If you have your own Jupyter notebook runner (such as JupyterHub or Kubeflow), or you’re simply running JupyterLab on your local machine, check out our JupyterLab-Pachyderm walkthrough to learn about the components of JupyterLab-Pachyderm and how to get the pieces installed, running, and connected.

Examples #

Make sure to check our data science notebook examples running on Pachyderm, from a market sentiment NLP implementation using a FinBERT model to pipelines training a regression model on the Boston Housing Dataset. You will also find integration examples with open-source products, such as labeling or model serving applications.