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 Notebook server in a local Docker container
- 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, 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 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 85f615d5cafa 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 container's internal port 8888 to port 10000 of the host machine:
docker run -p 10000:8888 jupyter/scipy-notebook:85f615d5cafaYou 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:
hostnameis the name of the computer running Dockertokenis the secret token printed in the console.
The container remains intact for restart after the Jupyter Server exits.
Example 2:
This command pulls the jupyter/datascience-notebook image tagged 85f615d5cafa 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.
docker run -it --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work jupyter/datascience-notebook:85f615d5cafaThe use of the -v flag in the command mounts the current working directory on the host (${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.
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 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 at any time. We will happily grant additional permissions (e.g., ability to merge PRs) to anyone who shows an ongoing interest in working on the project.
Following Jupyter Notebook notice, JupyterLab is now the default for all the Jupyter Docker stack 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.
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
- We publish containers for both
x86_64andaarch64platforms, except fortensorflow-notebook, which only supportsx86_64for now - Single-platform images have either
aarch64orx86_64tag prefixes, for examplejupyter/base-notebook:aarch64-python-3.10.5 - Starting from
2022-09-21, we create multi-platform images
This project only builds one set of images at a time.
On 2022-10-09, we rebuilt images with old Ubuntu and python versions for users who still need them:
| Ubuntu | Python | Tag |
|---|---|---|
| 20.04 | 3.7 | 1aac87eb7fa5 |
| 20.04 | 3.8 | a374cab4fcb6 |
| 20.04 | 3.9 | 5ae537728c69 |
| 20.04 | 3.10 | f3079808ca8c |
| 22.04 | 3.7 | b86753318aa1 |
| 22.04 | 3.8 | 7285848c0a11 |
| 22.04 | 3.9 | ed2908bbb62e |
| 22.04 | 3.10 | latest (this image is rebuilt weekly) |