docker-stacks: Ready-to-run Docker images containing Jupyter applications

# Jupyter Docker Stacks

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Jupyter Docker Stacks are a set of ready-to-run [Docker images](https://hub.docker.com/u/jupyter)
containing Jupyter applications and interactive computing tools.

## Quick Start

You can try a [relatively recent build of the jupyter/base-notebook image on mybinder.org](https://mybinder.org/v2/gh/jupyter/docker-stacks/master?filepath=README.ipynb)
by simply clicking the preceding link.
The image used in binder was last updated on 22 May 2021.
Otherwise, three examples below may help you get started if you [have Docker installed](https://docs.docker.com/install/),
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 Notebook server in a container.

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

**Example 1:** This command pulls the `jupyter/scipy-notebook` image tagged `33add21fab64` from Docker Hub if it is not already present on the local host.
It then starts a container running a Jupyter Notebook 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 the Jupyter Notebook dashboard page,
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 notebook server exits.

```bash
docker run -p 8888:8888 jupyter/scipy-notebook:33add21fab64
```

**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 Jupyter Notebook server,
where `hostname` is the name of the computer running docker and `token` is the secret token printed in the console.

```bash
docker run -p 10000:8888 jupyter/scipy-notebook:33add21fab64
```

**Example 3:** This command pulls the `jupyter/datascience-notebook` image tagged `33add21fab64` from Docker Hub if it is not already present on the local host.
It then starts an _ephemeral_ container running a Jupyter Notebook 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 notebook server exit, but any files written to `~/work` in the container remain intact on the host.

```bash
docker run --rm -p 10000:8888 -e JUPYTER_ENABLE_LAB=yes -v "${PWD}":/home/jovyan/work jupyter/datascience-notebook:33add21fab64
```

## Contributing

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

## Maintainer Help Wanted

We value all positive contributions to the Docker stacks project,
from [bug reports](https://jupyter-docker-stacks.readthedocs.io/en/latest/contributing/issues.html)
to [pull requests](https://jupyter-docker-stacks.readthedocs.io/en/latest/contributing/packages.html)
to [translations](https://jupyter-docker-stacks.readthedocs.io/en/latest/contributing/translations.html)
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.

## Jupyter Notebook Deprecation Notice

Following [Jupyter Notebook notice](https://github.com/jupyter/notebook#notice), we encourage users to transition to JupyterLab.
This can be done by passing the environment variable `JUPYTER_ENABLE_LAB=yes` at container startup,
more information is available in the [documentation](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html#docker-options).

At some point, JupyterLab will become the default for all of the Jupyter Docker stack images, however a new environment variable will be introduced to switch back to Jupyter Notebook if needed.

After the change of default, and 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](https://github.com/jupyter/docker-stacks/issues/1217), please check its content for more information.

## Alternatives

- [jupyter/repo2docker](https://github.com/jupyter/repo2docker) - Turn git repositories into
  Jupyter-enabled Docker Images
- [openshift/source-to-image](https://github.com/openshift/source-to-image) - A tool for
  building/building artifacts from source and injecting into docker images
- [jupyter-on-openshift/jupyter-notebooks](https://github.com/jupyter-on-openshift/jupyter-notebooks) -
  OpenShift compatible S2I builder for basic notebook images

## Resources

- [Documentation on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/)
- [Issue Tracker on GitHub](https://github.com/jupyter/docker-stacks)
- [Jupyter Discourse Forum](https://discourse.jupyter.org/)
- [Jupyter Website](https://jupyter.org)
- [Images on DockerHub](https://hub.docker.com/u/jupyter)

## CPU Architectures

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

### Caveats for arm64 images

- 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](https://github.com/jupyter/docker-stacks/issues/1401).
- Only the amd64 images are actively tested currently. For the status about
  this, see [#1402](https://github.com/jupyter/docker-stacks/issues/1402).

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