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tao.chenandClaude cd1aba6698 dev: initial implementation of notebook-snapshot extension

Manual-commit notebook snapshot extension (JupyterLab 4):

Backend
- Storage adapter layer (Local + S3 via boto3, pip extra)
  - Dumb put/get/list/delete contract; key validation
  - S3Storage: lazy boto3 import, S3ConnectionError with friendly
    messages + connectivity check at startup
- SnapshotStore
  - Strip code outputs/execution_count, MD5 on cleaned JSON
  - Gzipped envelope (id/timestamp/name/description/hash/size/notebook)
  - Append-only manifest.json (rebuildable from version files)
  - SnapshotUnchangedError when new hash matches most recent version
- REST API (commit / list / content) under /snapshot/ namespace
- traitlets config (storage_type, local_root, s3_* + S3_* env fallback)

Frontend
- snapshot:commit command (toolbar button + command palette)
- Dialog for name + description
- SnapshotPanel (left sidebar timeline) + DiffWidget (main area)
- Cell diff: id-match first, LCS fallback; jsdiff for line diff
- Restore via model.fromJSON() + context.save() (no refresh)
- All AGENTS.md hard conventions enforced

Tests: 33 backend pytest passing (storage + store + routes)

Docs: AGENTS.md, design.md, README.md synced with implementation.

Co-Authored-By: Claude <noreply@anthropic.com>

2026-07-21 17:33:55 +08:00

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Contributing

Development install

Note: You will need Node.js to build the extension package. You may install it from nodejs.org. We recommend using the latest LTS version of Node.js.

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the snapshot directory

# Set up a virtual environment and install package in development mode
python -m venv .venv
source .venv/bin/activate
pip install --editable ".[dev,test]"

# Link your development version of the extension with JupyterLab
jupyter-builder develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable snapshot

# Rebuild extension Typescript source after making changes
# IMPORTANT: Unlike the steps above which are performed only once, do this step
# every time you make a change.
jlpm build

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

# Server extension must be manually disabled in develop mode
jupyter server extension disable snapshot
pip uninstall snapshot

In development mode, you will also need to remove the symlink created by jupyter-builder develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named snapshot within that folder.

Testing the extension

Server tests

This extension is using Pytest for Python code testing.

Install test dependencies (needed only once):

pip install -e ".[test]"
# Each time you install the Python package, you need to restore the front-end extension link
jupyter-builder develop . --overwrite

To execute them, run:

pytest -vv -r ap --cov snapshot

Frontend tests

This extension is using Jest for JavaScript code testing.

To execute them, execute:

jlpm
jlpm test

Integration tests

This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.

More information is provided within the ui-tests README.

Packaging the extension

See RELEASE

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