A cookiecutter template for a custom Jupyter widget project using Vue 3 and Pinia. This cookiecutter is based on the great widget-ts-cookiecutter and widget-svelte-cookiecutter.

In addition this custom Jupyter widget cookiecutter uses Docker as a dev environment for a better DX.

This cookiecutter is part of a larger research project trying to bring AI into design education: KITeGG / gestaltung.ai.

Install cookiecutter:

pip install cookiecutter

After installing cookiecutter, use the widget-vue-cookiecutter:

cookiecutter https://github.com/ki-tegg/widget-vue-cookiecutter.git

As widget-vue-cookiecutter runs, you will be asked for basic information about your custom Jupyter widget project. You will be prompted for the following information:

• author_name: your name or the name of your organization,
• author_email: your project's contact email,
• github_project_name: name of your custom Jupyter widget's GitHub repository,
• github_organization_name: name of your custom Jupyter widget's GitHub user or organization,
• python_package_name: name of the Python "back-end" package used in your custom widget.
• npm_package_name: name for the npm "front-end" package holding the JavaScript implementation used in your custom widget.
• npm_package_version: initial version of the npm package.
• project_short_description : a short description for your project that will be used for both the "back-end" and "front-end" packages.

After this, you will have a directory containing files used for creating a custom Jupyter widget.

Navigate in your freshly created folder and execute the following command:

docker compose up

This will start the docker container used for developing the widgets.

The first time running this command it could take some time, because the container needs to be downloaded and build. The second time starting the container it should be significantly faster.

Sometimes it could be necessary to rebuild the container. For example if the image was updated or the current container is broken. Run the following command to rebuild the container:

docker compose up --build

The container will start in an idle mode. It will do nothing but will keep on running until you close your terminal window.

After starting the container you are prompted with instructions on how to continue. Alternatively you can follow these steps:

Open a new terminal window and hook into the container.

docker exec -it <python package name> /bin/bash

Execute the setup.sh. This bash script contains multiple commands which will install all the needed dependencies as well as building and installing the widget. In the end it will start a watch command to automatically rebuild the widget on code changes.

bash setup.sh

Now you can start Jupyter Lab inside the container. Open another terminal window and execute the following command to start Jupyter Lab.

jupyter lab --ip=0.0.0.0 --port=8888 --no-browser --allow-root --notebook-dir=/home --ServerApp.token=''

Open the link displayed in the terminal. By default is is localhost:8888.

If you make a change to the JavaScript or TypeScript code you need to reload the browser window to see the changes.

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.

This widget can also be released as a PyPI package which can then be installed via pip.

For that follow the instructions of the widget-ts-cookiecutter here.

In the /examples folder is a Jupyter notebook, which executes an example widget.

KITeGG is founded by BMBF and the states of RLP, NRW, BW, HE.

• https://gestaltung.ai/
• https://twitter.com/gestaltungai
• https://www.instagram.com/gestaltungai/