Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools. You can use a stack image to do any of the following (and more):

• Start a personal Jupyter Notebook server in a local Docker container
• Run JupyterLab servers for a team using JupyterHub
• Write your own project Dockerfile

You can try a relatively recent build of the jupyter/base-notebook image on mybinder.org by simply clicking the preceding link. Otherwise, three examples below may help you get started if you have Docker installed, know which Docker image you want to use and want to launch a single Jupyter Server in a container.

The User Guide on ReadTheDocs describes additional uses and features in detail.

Example 1: This command pulls the jupyter/scipy-notebook image tagged b418b67c225b from Docker Hub if it is not already present on the local host. It then starts a container running a Jupyter Server and exposes the server on host port 8888. The server logs appear in the terminal. Visiting http://<hostname>:8888/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console. The container remains intact for restart after the Jupyter Server exits.

docker run -p 8888:8888 jupyter/scipy-notebook:b418b67c225b

Example 2: This command performs the same operations as Example 1, but it exposes the server on host port 10000 instead of port 8888. Visiting http://<hostname>:10000/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console.

docker run -p 10000:8888 jupyter/scipy-notebook:b418b67c225b

Example 3: This command pulls the jupyter/datascience-notebook image tagged b418b67c225b from Docker Hub if it is not already present on the local host. It then starts an ephemeral container running a Jupyter Server and exposes the server on host port 10000. The command mounts the current working directory on the host as /home/jovyan/work in the container. The server logs appear in the terminal. Visiting http://<hostname>:10000/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console. Docker destroys the container after Jupyter Server exit, but any files written to ~/work in the container remain intact on the host.

docker run --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work jupyter/datascience-notebook:b418b67c225b

Please see the Contributor Guide on ReadTheDocs for information about how to contribute package updates, recipes, features, tests, and community maintained stacks.

We value all positive contributions to the Docker stacks project, from bug reports to pull requests to help answering questions. We'd also like to invite members of the community to help with two maintainer activities:

• Issue triage: Reading and providing a first response to issues, labeling issues appropriately, redirecting cross-project questions to Jupyter Discourse
• Pull request reviews: Reading proposed documentation and code changes, working with the submitter to improve the contribution, deciding if the contribution should take another form (e.g., a recipe instead of a permanent change to the images)

Anyone in the community can jump in and help with these activities at any time. We will happily grant additional permissions (e.g., ability to merge PRs) to anyone who shows an on-going interest in working on the project.

Following Jupyter Notebook notice, JupyterLab is now the default for all of the Jupyter Docker stack images. It is still possible to switch back to Jupyter Notebook (or to launch a different startup command). This can be done by passing the environment variable DOCKER_STACKS_JUPYTER_CMD=notebook (or any other valid jupyter command) at container startup, more information is available in the documentation.

According to the Jupyter Notebook project status and its compatibility with JupyterLab, these Docker images may remove the classic Jupyter Notebook interface altogether in favor of another classic-like UI built atop JupyterLab.

This change is tracked in the issue #1217, please check its content for more information.

• jupyter/repo2docker - Turn git repositories into Jupyter-enabled Docker Images
• openshift/source-to-image - A tool for building/building artifacts from source and injecting into docker images
• jupyter-on-openshift/jupyter-notebooks - OpenShift compatible S2I builder for basic notebook images

• Documentation on ReadTheDocs
• Issue Tracker on GitHub
• Jupyter Discourse Forum
• Jupyter Website
• Images on DockerHub

All published containers support amd64 (x86_64) and aarch64, except for datascience-notebook and tensorflow-notebook, which only support amd64 for now.

• The manifests we publish in this projects wiki as well as the image tags for the multi platform images that also support arm, are all based on the amd64 version even though details about the installed packages versions could differ between architectures. For the status about this, see #1401.
• Only the amd64 images are actively tested currently. For the status about this, see #1402.