# Jupyter Docker Stacks

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Jupyter Docker Stacks are a set of ready-to-run [Docker images](https://quay.io/organization/jupyter) 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 quay.io/jupyter/base-notebook image on mybinder.org](https://mybinder.org/v2/gh/jupyter/docker-stacks/main?urlpath=lab/tree/README.ipynb).
Otherwise, the examples below may help you get started if you [have Docker installed](https://docs.docker.com/get-started/get-docker/),
know [which Docker image](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html) you want to use, and want to launch a single Jupyter Application in a container.

The [User Guide on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/) describes additional uses and features in detail.

```{note}
Since `2023-10-20` our images are only pushed to `Quay.io` registry.
Older images are available on Docker Hub, but they will no longer be updated.
```

### Example 1

This command pulls the `jupyter/scipy-notebook` image tagged `2025-03-14` from Quay.io 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:

```bash
docker run -p 10000:8888 quay.io/jupyter/scipy-notebook:2025-03-14
```

You can modify the port on which the container's port is exposed by [changing the value of the `-p` option](https://docs.docker.com/engine/containers/run/#exposed-ports) to `-p 8888:8888`.

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

- The `hostname` is the name of the computer running Docker
- The `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 `2025-03-14` from Quay.io 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.

```bash
docker run -it --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work quay.io/jupyter/datascience-notebook:2025-03-14
```

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 `--rm` flag](https://docs.docker.com/reference/cli/docker/container/run/#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 `-i` flag](https://docs.docker.com/reference/cli/docker/container/run/#interactive) keeps the container's `STDIN` open, and lets you send input to the container through standard input.
[The `-t` flag](https://docs.docker.com/reference/cli/docker/container/run/#tty) attaches a pseudo-TTY to the container.

```{note}
By default, [jupyter's root_dir](https://jupyter-server.readthedocs.io/en/latest/other/full-config.html) is `/home/jovyan`.
So, new notebooks will be saved there, unless you change the directory in the file browser.

To change the default directory, you must specify `ServerApp.root_dir` by adding this line to the previous command: `start-notebook.py --ServerApp.root_dir=/home/jovyan/work`.
```

## 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](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html#alternative-commands).

## Resources

- [Documentation on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/)
- [Issue Tracker on GitHub](https://github.com/jupyter/docker-stacks/issues)
- [Jupyter Discourse Forum](https://discourse.jupyter.org/)
- [Jupyter Website](https://jupyter.org)
- [Images on Quay.io](https://quay.io/organization/jupyter)

## Acknowledgments

- Starting from `2022-07-05`, `aarch64` self-hosted runners were sponsored by [`@mathbunnyru`](https://github.com/mathbunnyru/).
  Please, consider [sponsoring his work](https://github.com/sponsors/mathbunnyru) on GitHub
- Starting from `2023-10-31`, `aarch64` self-hosted runners are sponsored by an amazing [`2i2c non-profit organization`](https://2i2c.org)
- Starting from `2025-02-11`, we use GitHub-hosted `aarch64` runners

## 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, `quay.io/jupyter/base-notebook:aarch64-python-3.11.6`
- Starting from `2022-09-21`, we create multi-platform images (except `tensorflow-notebook`)
- Starting from `2023-06-01`, we create a multi-platform `tensorflow-notebook` image as well
- Starting from `2024-02-24`, we create CUDA enabled variants of `pytorch-notebook` image for `x86_64` platform
- Starting from `2024-03-26`, we create CUDA enabled variant of `tensorflow-notebook` image for `x86_64` platform

## Using old images

[![Python versions badge](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue.svg)](https://www.python.org/downloads/ "Python versions supported")

This project only builds one set of images at a time.
If you want to use the older `Ubuntu` and/or `Python` version, you can use the 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` |
| 2024-08-26   | 22.04  | 3.11   | `00987883e58d` |
| 2024-10-22   | 24.04  | 3.11   | `b74418220768` |
| weekly build | 24.04  | 3.12   | `latest`       |

## Contributing

Please see the [Contributor Guide on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/)
for information about how to contribute recipes, features, tests, and community-maintained stacks.

## Alternatives

- [rocker/binder](https://rocker-project.org/images/versioned/binder.html) -
  From the R focused [rocker-project](https://rocker-project.org),
  lets you run both RStudio and Jupyter either standalone or in a JupyterHub
- [jupyter/repo2docker](https://github.com/jupyterhub/repo2docker) -
  Turn git repositories into Jupyter-enabled Docker Images
- [openshift/source-to-image](https://github.com/openshift/source-to-image) -
  A tool for building artifacts from source code and injecting them into docker images
- [jupyter-on-openshift/jupyter-notebooks](https://github.com/jupyter-on-openshift/jupyter-notebooks) -
  OpenShift compatible S2I builder for basic notebook images