urncjp

Jupyter extension for urnc

This extension is composed of a Python package named urncjp for the server extension and a NPM package named urncjp for the frontend extension.

Requirements

• JupyterLab >= 4.0.0

Install

To install the extension, execute:

pip install urncjp

Uninstall

To remove the extension, execute:

pip uninstall urncjp

Troubleshoot

If you are seeing the frontend extension, but it is not working, check that the server extension is enabled:

jupyter server extension list

If the server extension is installed and enabled, but you are not seeing the frontend extension, check the frontend extension is installed:

jupyter labextension list

Contributing

Development install

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

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

# Clone the repo to your local environment
# Change directory to the urncjp directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable urncjp
# Rebuild extension Typescript source after making changes
npm 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
npm 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 npm 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

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

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 urncjp within that folder.

Packaging the extension

The extension can be published to PyPI and npm manually or using the Jupyter Releaser.

Manual release

Python package

This extension can be distributed as Python packages. All of the Python packaging instructions are in the pyproject.toml file to wrap your extension in a Python package. Before generating a package, you first need to install some tools:

pip install build twine hatch

Bump the version using hatch. By default this will create a tag. See the docs on hatch-nodejs-version for details.

hatch version <new-version>

Make sure to clean up all the development files before building the package:

npm run clean:all

You could also clean up the local git repository:

git clean -dfX

To create a Python source package (.tar.gz) and the binary package (.whl) in the dist/ directory, do:

python -m build

python setup.py sdist bdist_wheel is deprecated and will not work for this package.

Then to upload the package to PyPI, do:

twine upload dist/*

NPM package

To publish the frontend part of the extension as a NPM package, do:

npm login
npm publish --access public

Automated releases with the Jupyter Releaser

The extension repository should already be compatible with the Jupyter Releaser. But the GitHub repository and the package managers need to be properly set up. Please follow the instructions of the Jupyter Releaser checklist.

Here is a summary of the steps to cut a new release:

• Go to the Actions panel
• Run the "Step 1: Prep Release" workflow
• Check the draft changelog
• Run the "Step 2: Publish Release" workflow

[!NOTE] Check out the workflow documentation for more information.

Publishing to conda-forge

If the package is not on conda forge yet, check the documentation to learn how to add it: https://conda-forge.org/docs/maintainer/adding_pkgs.html

Otherwise a bot should pick up the new version publish to PyPI, and open a new PR on the feedstock repository automatically.