jupyterlab-ds-snapshot 0.3.6

Capture data science evidence, notes, and documentation snapshots in JupyterLab.

DS Snapshot

A lightweight JupyterLab extension for capturing data science evidence, review notes, and documentation snapshots directly from notebooks.

Available for:

• JupyterLab 4.0+
• VS Code

DS Snapshot helps data scientists keep a structured record of important spot checks, intermediate outputs, review notes, and supporting evidence without turning every notebook check into a formal workflow step. It is designed for local-first analytical work, model review, reproducibility, audit trails, and handoff.

Why DS Snapshot?

Clean notebooks are useful, but real data science work often includes many small checks that are easy to lose: row-count checks, missing-value checks, outlier investigations, comparison tables, chart inspections, and review notes. DS Snapshot creates a lightweight evidence archive under a JupyterLab-root path that you choose and can export a review package that is easier to share than a long notebook.

Features

• Capture selected notebook evidence into a structured archive
• Save review notes and evidence summaries as Markdown and HTML
• Maintain a registry of captured evidence
• Generate an evidence hub for quick navigation
• Export a review package for review, audit, or handoff
• Works locally inside JupyterLab

Demo

Capture

Save important evidence from your workflow as you work.

Hub

Review captured evidence in one place.

Package

Select and export evidence for review, documentation, or handoff.

Tutorials

Panel Overview

• Panel Overview

Capture Evidence

• Python + Excel
• SQL + Excel
• Validate AI Work
• Model Comparison

Evidence Management

• Evidence Management

Installation

Public package release is planned. After release, the target installation command will be:

pip install jupyterlab-ds-snapshot

For local development:

git clone https://github.com/<your-username>/jupyterlab-ds-snapshot.git
cd jupyterlab-ds-snapshot
pip install -e .
npm install
npm run build
jupyter lab

Quick start

1. Open JupyterLab.
2. Open the DS Snapshot side panel.
3. Choose an absolute JupyterLab archive path, such as /ds-snapshot-archive or /project/ds-snapshot-archive.
4. Capture evidence from the active notebook.
5. Open the hub or export a review package.

The extension creates files under the selected archive path. If multiple notebooks use the same path, they share the same registry and hub. For example:

/ds-snapshot-archive/
  registry.json
  hub.md
  hub.html
  reviews/
  evidence/
  review_packages/

Archive path rule

The archive path must start with / and is resolved under the JupyterLab file browser root. It is not a Windows or macOS local OS path.

Use the same archive path across multiple notebooks to create one shared evidence hub. Use different archive paths when you want separate archives.

Review packages

The review package export currently collects review notes, evidence summaries, and navigation pages into a shareable folder. The archive remains complete; the exported package is intended for review or handoff:

/ds-snapshot-archive/
  review_packages/
    review_package_<timestamp>/
      index.html
      hub.html
      hub.md
      README.md
      manifest.json
      reviews/
      evidence/

This package is intended to help reviewers, future maintainers, or AI agents understand what was checked and where the supporting evidence lives.

Development

Build the TypeScript source and JupyterLab prebuilt extension:

npm run build

Run JupyterLab locally:

jupyter lab

Build the Python package:

python -m build

Status

This project is an early public preview. APIs, folder layouts, and generated documentation formats may change before a stable release.

License

Apache License 2.0. See LICENSE.