A cookiecutter template for a custom Jupyter widget project.
With widget-cookiecutter you can create a custom Jupyter interactive widget project with sensible defaults. widget-cookiecutter helps custom widget authors get started with best practices for the packaging and distribution of a custom Jupyter interactive widget library.
Popular widget libraries such as: bqplot, pythreejs and ipyleaflet follow exactly the same template and directory structure as widget-cookiecutter provides. These libraries can serve as advanced examples of usage of the Jupyter widget infrastructure.
Install cookiecutter:
$ pip install cookiecutter
After installing cookiecutter, use the widget-cookiecutter:
$ cookiecutter https://github.com/jupyter/widget-cookiecutter.git
As widget-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.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. You will now be able to easily package and distribute your custom Jupyter widget.
- Documentation of Jupyter widgets
- Ask questions about using widget-cookiecutter on the Gitter channel
- If you find an issue with widget-cookiecutter or would like to contribute an enhancement, file an issue at the widget-cookiecutter GitHub repo.