The “Share” button for Jupyter Notebooks - A generic service for publishing and sharing notebook files
Zach Sailer, Sathish kumar Thangaraj, Shravan Achar
Reminder - The date and time of this sessions are placeholder due to the limitation of the conference software.
All Poster will be presented during the Poster Session from 6:30 to 8:00 on Thus 11th,
https://cfp.jupytercon.com/2023/talk/AKPRE8/
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A key innovation of Jupyter Notebooks is that they are both computational AND narrative documents—i.e. they are meant to be read by an audience. However, “sharing” a notebook is no easy task. JupyterLab (and other Jupyter applications) does not provide a generic service for sharing notebooks between notebook servers.
Introducing the Notebook Sharing service—an open-source, generic, configurable service and set of JupyterLab extension that make notebook sharing easy and intuitive. Users see a “Share” button in the top right corner of every Jupyter Notebook and a new “Sharing” side panel in JupyterLab to browse shared files. This service offers a generic interface for talking to any storage backend (e.g. DropBox, Amazon S3, Box, local file system, etc.) and works seamlessly with JupyterHub to enable notebook sharing between all hub users
In this talk, we will give a live demo of this service and highlight the strengths and value it brings to Jupyter community, such as:
- generic authentication module, extensible collaborator model and optional remote storage backend APIs
- Jupyter server- and JupyterLab-extensions that provide a complete Notebook sharing experience
- Bonus user-experience features, like preview a shared notebook inside JupyterLab, preview a shared notebook on a web browser with a URL, download a copy and filter all shared files
- customization extension points for searching collaborators and storing with different backends
Finally, we would like to invite audience to collaborate on this project and solicit feedback on how to improve this software. We would also like to invite members to submit implementations for their favorite storage systems
Prerequisistes
- The talk will be fairly technical. Basic familiarity with JupyterLab concepts such as server extension, kernels, REST APIs, front-end technologies like React
- Familiarity with JupyterLab’s content API is a plus.
