aolney-jupyterlab-blockly-python-extension 0.2.1

A JupyterLab extension that creates a Blockly palette for Python.

aolney_jupyterlab_blockly_python_extension

A JupyterLab extension implementing a Blockly palette for the Python language. For data science training materials using this extension, see here. For an R extension with the same Blockly functionality, see here.

The following query string parameters enable functionality:

• 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

[!WARNING]

1. Currently there appears to be a conflict between the Python and R extensions, so we recommend that only one be installed at a time.
2. See environment.yml for required versions of other packages

Requirements

• JupyterLab >= 4.0.0

An earlier version targets JupyterLab 1.2x. You can find that version on npm and in the commit history of this repository (final tag)

Install

To install the extension, execute:

pip install aolney_jupyterlab_blockly_python_extension

Uninstall

To remove the extension, execute:

pip uninstall aolney_jupyterlab_blockly_python_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

    mamba create -n dev jupyterlab=4 nodejs=18 git copier=7 jinja2-time

    /home/ubuntu/miniforge3/bin/mamba init

    mamba activate dev

    mamba install -c conda-forge jupyterlab

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 aolney_jupyterlab_blockly_python_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 aolney_jupyterlab_blockly_python_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 @aolney/jupyterlab-blockly-python-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