jupyterlab-blockly-polyglot-extension 1.1.0

A JupyterLab extension implementing a Blockly palette for multiple programming languages.

jupyterlab_blockly_polyglot_extension

A JupyterLab extension implementing a Blockly palette for multiple programming languages.

Data science training materials in Python using this extension are here and matched versions for R are here.

The following query string parameters enable functionality that is useful for classroom instruction and/or research:

• bl=py forces the extension to display on load (it is already active)
• log=xxx specifies a url for a logging endpoint (e.g. https://yourdomain.com/log)
• id=xxx adds an identifier for logging

Requirements

• JupyterLab >= 4.0.0

Later versions of JupyterLab changed the command UI. See here for the options to launch the extension

Install

To install the extension, execute:

pip install jupyterlab_blockly_polyglot_extension

Uninstall

To remove the extension, execute:

pip uninstall jupyterlab_blockly_polyglot_extension

Contributing

• Andrew Olney
• Luiz Barboza

Development install

Creating a virtual environment is recommended:

    curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
    bash Miniforge3-$(uname)-$(uname -m).sh

    !!! Edit the environment.yml file to change the environment name as you like !!!

    mamba env create -f environment.yml

    /home/ubuntu/miniforge3/bin/mamba init

    mamba activate <NAME>

Note: This extension is designed to use a language server. It will work without a language server, but functionality will be reduced. See here to install language servers for the languages you want to use.

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, but don't do it unless you really know what you're doing.

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

The watch.sh script runs JupyterLab in watch mode with the Chrome browser

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_blockly_polyglot_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-blockly-polyglot-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