widget-svelte-cookiecutter

A cookiecutter template for a custom Jupyter widget project using Svelte. With widget-svelte-cookiecutter you can create a custom Jupyter interactive widget project that uses Svelte for the frontend. This was adapted from the fantastic widget-ts-cookiecutter.

Usage

Install cookiecutter:

$ pip install cookiecutter

After installing cookiecutter, use widget-svelte-cookiecutter:

$ cookiecutter https://github.com/cabreraalex/widget-svelte-cookiecutter

As widget-svelte-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.

Code Overview

The cookiecutter creates the following files:

TypeScript and Svelte frontend code

src
├── App.svelte
├── extension.ts
├── index.ts
├── plugin.ts
├── stores.ts
├── version.ts
└── widget.ts

The primary files in this directory are widget.ts and App.svelte. widget.ts defines the frontend widget and instantiates the svelte App.svelte.

Python backend kernel

{{package-name}}
├── __init__.py
├── _frontend.py
├── _version.py
├── example.py

example.py is the main file for the backend. It defines the Traitlets, and can dynamically update and react to state changes.

Example - Adding a Traitlet

To add a new Traitlet, essentially a synced variable:

Add a definition to example.py
Define a store by the same name using createValue() in App.svelte

Any updates to the store will update the kernel Traitlet and vice-versa.

Example - Development server

Since compiling Jupyter Notebook/Lab can be slow, you can run a mock development server for the frontend widget using npm run dev

You can mock the backend functionality by editing the MockModel class in mock.ts.

Installation

When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:

jupyter labextension install @jupyter-widgets/
jlpm --no-build
jupyter labextension install .

For classic notebook, you can run:

jupyter nbextension install --sys-prefix --symlink --overwrite --py <your python package name>
jupyter nbextension enable --sys-prefix --py <your python package name>

Note that the --symlink flag doesn't work on Windows, so you will here have to run the install command every time that you rebuild your extension. For certain installations you might also need another flag instead of --sys-prefix, but we won't cover the meaning of those flags here.

Releasing your initial packages:

Make a release commit, where you remove the , 'dev' entry in _version.py.
Update the version in package.json
Release the npm packages:
```
npm login
npm publish
```
Bundle the python package: python setup.py sdist bdist_wheel

Publish the package to PyPI:

pip install twine
twine upload dist/<python package name>*

Tag the release commit (git tag <python package version identifier>)
Update the version in _version.py, and put it back to dev (e.g. 0.1.0 -> 0.2.0.dev). Update the versions of the npm packages (without publishing).
Commit the changes.
git push and git push --tags.