Skip to main content

Jupyterlab Scicap Verdant

This project is an adaptation of the Verdant project for Science Capsule. Events from Verdant are intercepted and sent to an API so that jupyter events can be stored with other Science Capsule events.

Verdant

🌱🌿🌱 Verdant is a JupyterLab extension that automatically records history of all experiments you run in a Jupyter notebook, and stores them in a tidy .ipyhistory JSON file designed to be work alongside and compliment any other version control you use, like SVN or Git. Verdant also visualizes history of individual cells, code snippets, markdown, and outputs for you, for quick checks and references as you work.

For design discussion and the research behind this check out the paper:

Mary Beth Kery, Bonnie E. John, Patrick O’Flaherty, Amber Horvath, and Brad A. Myers. 2019. Towards Effective Foraging by Data Scientists to Find Past Analysis Choices. In Proceedings of ACM SIGCHI, Glasgow, UK, May 2019 (CHI’19), 11 pages. DOI: 10.475/123 4

Install for Local Development

If developing and making changes to the package locally, run the following commands after making changes:

# Install package in development mode
pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Enable the server extension
jupyter server extension enable jupyterlab_scicap_verdant
# Rebuild extension Typescript source after making changes
jlpm run build

Check that the extension is installed and enabled:

jupyter labextension list

Run jupyterlab:

jupyter lab

Build and Publish

First rebuild the labextension and commit changes.

jlpm run build
pip install -e .
git commit add .
git commit -m "My updates"

Then upgrade the package version using npm.

npm version patch

Then build the python distribution.

jlpm run build:dist

Then publish the .whl file to pypi.

jlpm run publish

In order to publish, you will have to authenticate with pypi and your account must have permission to administer the jupyterlab-scicap-verdant package on pypi.

Acknowledgements

The original Verdant library was authored by Mary Beth Kery. Research has been funded by Bloomberg L.P. and has been conducted at the Bloomberg L.P. and at the Natural Programming Group at the Human-Computer Interaction Institute at Carnegie Mellon University. Thank you to the JupyterLab project and also to all our awesome study participants for volunteering early design feedback!

Release files for jupyterlab-scicap-verdant 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for jupyterlab-scicap-verdant 0.1.1
File Interpreter ABI Platform
jupyterlab_scicap_verdant-0.1.1-py3-none-any.whl Python 3 none any Details

Release files / jupyterlab_scicap_verdant-0.1.1-py3-none-any.whl

Download URL jupyterlab_scicap_verdant-0.1.1-py3-none-any.whl
Size 430.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
c19a2dc551bb5554382ec4bf00b7db646b8c083b7eef710f21a8acfddeba695a
BLAKE2b-256 checksum
How to use checksums
0f3beb64492f4d16dc7274825d0f2d6fd92e69d319bf5927b7c10ff16fc4924a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.6

Release history Release notifications | RSS feed

This release

0.1.1 This release

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page