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Community Stacks
We love to see the community create and share new Jupyter Docker images. We've created a cookiecutter project and the documentation below as one way to get started defining, building, and sharing your Jupyter environments in Docker. If you choose to follow these steps, you will:
- Setup a project on GitHub containing a Dockerfile based on either the
jupyter/base-notebookorjupyter/minimal-notebookimage. - Configure Travis CI to build and test your image when users submit pull requests to your repository.
- Configure Docker Cloud to build and host your images for others to use.
- Update the list of community stacks in this documentation to include your image.
This approach mirrors how we build and share the core stack images. Again, it just one of many approaches you might choose to take to share your creations.
Creating a Project
First, install cookiecutter using pip or conda:
pip install cookiecutter # or conda install cookiecutter
Run the cookiecutter command pointing to the jupyter/cookiecutter-docker-stacks project on GitHub.
cookiecutter https://github.com/jupyter/cookiecutter-docker-stacks.git
Enter a name for your new stack image. This will serve as both the git repository name and the part of the Docker image name after the slash.
stack_name [my-jupyter-stack]:
Enter the user or organization name under which this stack will reside on Docker Cloud / Hub. You must have access to manage this Docker Cloud org in order to push images here and setup automated builds.
stack_org [my-project]:
Select an image from the jupyter/docker-stacks project that will serve as the base for your new image.
stack_base_image [jupyter/base-notebook]:
Enter a longer description of the stack for your README.
stack_description [my-jupyter-stack is a community maintained Jupyter Docker Stack image]:
Initialize your project as a Git repository and push it to GitHub.
cd <stack_name you chose>
git init
git add .
git commit -m 'Seed repo'
git remote add origin <url from github>
git push -u origin master