Skip to main content

JupyterLab extension adding context menu 'Refresh View' command to reload file content from disk while preserving scroll position

Project description

JupyterLab Refresh View Extension

GitHub Actions npm version PyPI version Total PyPI downloads JL4 Ready

JupyterLab extension that adds a "Refresh View" context menu command to reload file content from disk while preserving scroll position.

Refresh View Context Menu

Features

The extension provides intelligent content refresh while preserving your exact position in the document. For notebooks, it identifies the visible cell in your viewport and automatically scrolls back to that cell after refresh, restoring both the cell position and viewport offset even when JupyterLab's windowed rendering progressively loads cells. For markdown and text files, it maintains precise scroll coordinates. The extension works seamlessly with jupyterlab_tabular_data_viewer_extension to refresh CSV and tabular data files in their custom viewer.

  • Automatic Cell Scrolling - Identifies visible notebook cell before refresh and automatically scrolls back to it afterward, preserving exact viewport position
  • Hybrid Position Tracking - Cell-based anchoring for notebooks with scroll coordinate fallback, ensuring position preservation regardless of content loading order
  • Intelligent Stabilization - Monitors content loading and adaptively restores position as cells render, stabilizing within 300ms typically
  • Tabular Data Viewer Compatibility - Works with jupyterlab_tabular_data_viewer_extension to refresh CSV files in custom tabular view
  • Context Menu Integration - Right-click access for markdown files, notebooks, text editors, and tabular data viewers
  • Command Palette Access - Available under "File Operations" category
  • Smart Enable/Disable - Only active when a document with reloadable context is open

Use Cases

  • Iterative Editing - Refresh files edited externally without losing your place
  • Live Documentation - Keep markdown files in sync with external updates
  • Collaborative Work - View changes from teammates without manual reload
  • Build System Integration - Refresh generated files after build processes

Requirements

  • JupyterLab >= 4.0.0

Installation

From PyPI

pip install jupyterlab-refresh-view-extension

From npm

jupyter labextension install jupyterlab_refresh_view_extension

Usage

  1. Open a markdown file, notebook, or text file in JupyterLab
  2. Right-click anywhere in the document content
  3. Select "Refresh View" from the context menu
  4. The file reloads from disk while maintaining your scroll position

Alternatively, open the command palette (Ctrl+Shift+C or Cmd+Shift+C) and search for "Refresh View".

Uninstall

pip uninstall jupyterlab-refresh-view-extension

Contributing

Development install

Note: You will need NodeJS to build the extension package.

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 jupyterlab_refresh_view_extension directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
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

pip uninstall jupyterlab_refresh_view_extension

In development mode, you will also need to remove the symlink created by jupyter labextension 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 jupyterlab_refresh_view_extension within that folder.

Testing the extension

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 are provided within the ui-tests README.

Packaging the extension

See RELEASE

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterlab_refresh_view_extension-1.2.17.tar.gz (574.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file jupyterlab_refresh_view_extension-1.2.17.tar.gz.

File metadata

File hashes

Hashes for jupyterlab_refresh_view_extension-1.2.17.tar.gz
Algorithm Hash digest
SHA256 9437e8793f908366704442fef496fc7dcb6a5e5d4bcdcde8eeaf5996c6d45afb
MD5 a8acc4d36ddf4e194a2682e45ea96b71
BLAKE2b-256 996b0251b7e9f09e5247a2288fa9ba1e88c229ede8a7bf1458f6e750a55e5eac

See more details on using hashes here.

File details

Details for the file jupyterlab_refresh_view_extension-1.2.17-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlab_refresh_view_extension-1.2.17-py3-none-any.whl
Algorithm Hash digest
SHA256 8a922b9182c7de93d808e51db283fe240a6d73c6eff6d23d80db29e774c4f767
MD5 3e641ec68c5231d0333e7fa7c8ac2236
BLAKE2b-256 9a60f01634f840f790a19857bc11cb612f84bd59c9d6bd2fbe4703c97d084b38

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page