Skip to main content

A JupyterLab extension to render expressions given in Markdown.

Project description

jupyterlab_imarkdown

binder-badge pypi-badge

A JupyterLab extension to embed rich output in Markdown cells, e.g.

The current value of x is {{ x }}

preview

Technical Details

jupyterlab-imarkdown has to do some pretty unpleasant things in order to provide interactive Markdown. In particular, we implement our own NotebookPanel.ContentFactory in order to inject our own IMarkdownCell. This custom class implements routines to detect when the Markdown cell has been rendered, keep track of special eval-expr DOM nodes, and update these DOM nodes with the result of kernel execution.

Requirements

  • JupyterLab >= 3.0

Install

To install the extension, execute:

pip install jupyterlab_imarkdown

Uninstall

To remove the extension, execute:

pip uninstall jupyterlab_imarkdown

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_imarkdown 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 run 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 run 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 run 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_imarkdown

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-imarkdown within that folder.

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_imarkdown-0.2.0.tar.gz (135.3 kB view details)

Uploaded Source

Built Distribution

jupyterlab_imarkdown-0.2.0-py3-none-any.whl (667.2 kB view details)

Uploaded Python 3

File details

Details for the file jupyterlab_imarkdown-0.2.0.tar.gz.

File metadata

  • Download URL: jupyterlab_imarkdown-0.2.0.tar.gz
  • Upload date:
  • Size: 135.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for jupyterlab_imarkdown-0.2.0.tar.gz
Algorithm Hash digest
SHA256 4b0eda1885b09881413d6295b8ca0dab6cee48b17e12c72b905d29e6a815cc41
MD5 af63a11a5b83117003826cc3bfe826b9
BLAKE2b-256 8ac5979a469d6d9e93e0e2c812e2889126d6b7cf1df8f265ff19ea2b58aa7a97

See more details on using hashes here.

File details

Details for the file jupyterlab_imarkdown-0.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlab_imarkdown-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 df40894839a54b17fe6a29b0da6ab69e4ac9f66a17cf3b86694ca4095f0be325
MD5 b0adc7b35216501c793287a3335c6540
BLAKE2b-256 76deb8c0d2411059e3bde5fbebedeae849551fd55cf947ce7baacb837c810e17

See more details on using hashes here.

Supported by

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