xcube-jl-ext 0.1.0

xcube JupyterLab integration

xcube_jl_ext

xcube JupyterLab integration

This extension is composed of a Python package named xcube_jl_ext for the JupyterLab server extension and a NPM package named xcube-jl-ext for the JupyterLab frontend extension.

The extension adds the following features to JupyterLab:

1. Allows running a configurable xcube Viewer as widget in the JupyterLab.
2. Allows using xcube Server and Viewer from within Jupyter Notebooks, even if JupyterLab is running remotely, i.e., spawned by JupyterHub.

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NOTE

This extension is still experimental and has neither been packaged nor deployed. Refer to the section Development below for dev installs.

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Requirements

• JupyterLab >= 3.0
• xcube >= 0.13

Install

To install the extension, execute:

pip install xcube_jl_ext

Uninstall

To remove the extension, execute:

pip uninstall xcube_jl_ext

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

Development

Setup environment

Build xcube Viewer resources from sources. Note you'll need yarn to be installed on your system.

cd ${projects}
git clone https://github.com/dcs4cop/xcube-viewer.git
cd xcube-viewer
yarn install
yarn build

Now set environment variable XCUBE_VIEWER_PATH to point to the xcube Viewer build directory:

export XCUBE_VIEWER_PATH=${projects}/xcube-viewer/build

Make sure to have a source installation of xcube in a dedicated xcube Python environment.

cd ${projects}
git clone https://github.com/dcs4cop/xcube.git
cd xcube
mamba env create

Activate xcube environment and install xcube in editable (development) mode:

conda activate xcube
pip install -ve .

Update environment with required packages for building and running the JupyterLab extension.

Note, the version of the jupyterlab in our development environment should match the version of the target system. We also install jupyter-server-proxy.

mamba install -c conda-forge -c nodefaults jupyterlab=3.4.0 jupyter-server-proxy

Also install some packaging and build tools:

mamba install -c conda-forge -c nodefaults nodejs jupyter-packaging
pip install build

Refer also to the JupyterLab Extension Tutorial for the use these tools.

Install extension from sources

Make sure, xcube environment is active:

conda activate xcube

Clone xcube JupyterLab extension repository next to the xcube source folder:

cd ${projects}
git clone https://github.com/dcs4cop/xcube-jl-ext.git
cd xcube-jl-ext

Install the initial project dependencies and install the extension into the JupyterLab environment. Copy the frontend part of the extension into JupyterLab. We can run this pip install command again every time we make a change to copy the change into JupyterLab.

pip install -ve .

Create a symbolic link from JupyterLab to our source directory. This means our changes are automatically available in JupyterLab:

jupyter labextension develop --overwrite .

If successful, we can run JupyterLab and check if the extension works as expected:

jupyter lab

Build after changes

Run the following to rebuild the extension. This will be required after any changes of package.json or changes of frontend TypeScript files and other resources.

jlpm run build

If you wish to avoid building after each change, you can run the

jlpm run watch

from your extension directory in another terminal. This will automatically compile the TypeScript files as they are changed and saved.

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 xcube_jl_ext directory
# Install package in development mode
pip install -e ".[test]"
# 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 xcube_jl_ext
# 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

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

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 xcube-jl-ext within that folder.

Testing the extension

Server tests

This extension is using Pytest for Python code testing.

Install test dependencies (needed only once):

pip install -e ".[test]"
# Each time you install the Python package, you need to restore the front-end extension link
jupyter labextension develop . --overwrite

To execute them, run:

pytest -vv -r ap --cov xcube_jl_ext

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