Jupyter Docker Stacks

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 Server with the JupyterLab frontend (default)
• Run JupyterLab for a team using JupyterHub
• Start a personal Jupyter Server with the Jupyter Notebook frontend in a local Docker container
• Write your own project Dockerfile

Quick Start

You can try a relatively recent build of the jupyter/base-notebook image on mybinder.org by simply clicking the preceding link. Otherwise, the 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 Application 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 2023-07-31 from Docker Hub if it is not already present on the local host. It then starts a container running a Jupyter Server with the JupyterLab frontend and exposes the container's internal port 8888 to port 10000 of the host machine:

docker run -p 10000:8888 jupyter/scipy-notebook:2023-07-31

You can modify the port on which the container's port is exposed by changing the value of the -p option to -p 8888:8888.

Visiting http://<hostname>:10000/?token=<token> in a browser loads JupyterLab, where:

• hostname is the name of the computer running Docker
• token is the secret token printed in the console.

The container remains intact for restart after the Server exits.

Example 2:

This command pulls the jupyter/datascience-notebook image tagged 2023-07-31 from Docker Hub if it is not already present on the local host. It then starts an ephemeral container running a Jupyter Server with the JupyterLab frontend and exposes the server on host port 10000.

docker run -it --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work jupyter/datascience-notebook:2023-07-31

The use of the -v flag in the command mounts the current working directory on the host (${PWD} in the example command) 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.

Due to the usage of the flag --rm Docker automatically cleans up the container and removes the file system when the container exits, but any changes made to the ~/work directory and its files in the container will remain intact on the host. The -it flag allocates pseudo-TTY.

Contributing

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

Maintainer Help Wanted

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

• Issue triaging: 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 anytime. We will happily grant additional permissions (e.g., the ability to merge PRs) to anyone who shows an ongoing interest in working on the project.

Choosing Jupyter frontend

JupyterLab is the default for all the Jupyter Docker Stacks images. It is still possible to switch back to Jupyter Notebook (or to launch a different startup command). You can achieve this by passing the environment variable DOCKER_STACKS_JUPYTER_CMD=notebook (or any other valid jupyter subcommand) at container startup; more information is available in the documentation.

Alternatives

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

Resources

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

CPU Architectures

• We publish containers for both x86_64 and aarch64 platforms
• Single-platform images have either aarch64- or x86_64- tag prefixes, for example, jupyter/base-notebook:aarch64-python-3.10.5
• Starting from 2022-09-21, we create multi-platform images (except tensorflow-notebook)
• Starting from 2023-07-31, we create multi-platform tensorflow-notebook image as well

Using old images

This project only builds one set of images at a time. If you want to use older Ubuntu and/or python version, you can use following images:

Build Date	Ubuntu	Python	Tag
2022-10-09	20.04	3.7	1aac87eb7fa5
2022-10-09	20.04	3.8	a374cab4fcb6
2022-10-09	20.04	3.9	5ae537728c69
2022-10-09	20.04	3.10	f3079808ca8c
2022-10-09	22.04	3.7	b86753318aa1
2022-10-09	22.04	3.8	7285848c0a11
2022-10-09	22.04	3.9	ed2908bbb62e
2023-05-30	22.04	3.10	4d70cf8da953
weekly build	22.04	3.11	latest