# Running a Container

Using one of the Jupyter Docker Stacks requires two choices:

1. Which Docker image you wish to use
2. How you wish to start Docker containers from that image

This section provides details about the second.

## Using the Docker CLI

You can launch a local Docker container from the Jupyter Docker Stacks using the [Docker command line interface](https://docs.docker.com/engine/reference/commandline/cli/).
There are numerous ways to configure containers using the CLI.
The following are some common patterns.

**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 Notebook server and exposes the server on host port 8888.
The server logs appear in the terminal and include a URL to the notebook server.

```bash
docker run -it -p 8888:8888 jupyter/scipy-notebook:b418b67c225b

# Entered start.sh with args: jupyter lab

# ...

#     To access the server, open this file in a browser:
#         file:///home/jovyan/.local/share/jupyter/runtime/jpserver-7-open.html
#     Or copy and paste one of these URLs:
#         http://042fc8ac2b0c:8888/lab?token=f31f2625f13d131f578fced0fc76b81d10f6c629e92c7099
#      or http://127.0.0.1:8888/lab?token=f31f2625f13d131f578fced0fc76b81d10f6c629e92c7099
```

Pressing `Ctrl-C` twice shuts down the notebook server but leaves the container intact on disk for later restart or permanent deletion using commands like the following:

```bash
# list containers
docker ps -a
# CONTAINER ID   IMAGE                                                 COMMAND                  CREATED          STATUS                     PORTS     NAMES
# 221331c047c4   jupyter/scipy-notebook:b418b67c225b                   "tini -g -- start-no…"   11 seconds ago   Exited (0) 8 seconds ago             cranky_benz

# start the stopped container
docker start -a 221331c047c4
# Entered start.sh with args: jupyter lab
# ...

# remove the stopped container
docker rm 221331c047c4
# 221331c047c4
```

**Example 2** This command pulls the `jupyter/r-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 Notebook server and exposes the server on host port 10000.
The server logs appear in the terminal and include a URL to the notebook server, but with the internal container port (8888) instead of the the correct host port (10000).

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

Pressing `Ctrl-C` twice shuts down the notebook server and immediately destroys the Docker container.
Files written to `~/work` in the container remain touched.
Any other changes made in the container are lost.

**Example 3** This command pulls the `jupyter/all-spark-notebook` image currently tagged `latest` from Docker Hub if an image tagged `latest` is not already present on the local host.
It then starts a container named `notebook` running a JupyterLab server and exposes the server on a randomly selected port.
The `-d` flag mean to run the container in detached mode.

```bash
docker run -d -P --name notebook jupyter/all-spark-notebook
```

The assigned port and notebook server token are visible using other Docker commands.

```bash
# get the random host port assigned to the container port 8888
docker port notebook 8888
# 0.0.0.0:49153
# :::49153

# get the notebook token from the logs
docker logs --tail 3 notebook
    # Or copy and paste one of these URLs:
    #     http://878f1a9b4dfa:8888/lab?token=d336fa63c03f064ff15ce7b269cab95b2095786cf9ab2ba3
    #  or http://127.0.0.1:8888/lab?token=d336fa63c03f064ff15ce7b269cab95b2095786cf9ab2ba3
```

Together, the URL to visit on the host machine to access the server in this case is <http://127.0.0.1:49153/lab?token=d336fa63c03f064ff15ce7b269cab95b2095786cf9ab2ba3>.

The container runs in the background until stopped and/or removed by additional Docker commands.

```bash
# stop the container
docker stop notebook
# notebook

# remove the container permanently
docker rm notebook
# notebook
```

## Using Binder

[Binder](https://mybinder.org/) is a service that allows you to create and share custom computing environments for projects in version control.
You can use any of the Jupyter Docker Stacks images as a basis for a Binder-compatible Dockerfile.
See the
[docker-stacks example](https://mybinder.readthedocs.io/en/latest/sample_repos.html#using-a-docker-image-from-the-jupyter-docker-stacks-repository) and
[Using a Dockerfile](https://mybinder.readthedocs.io/en/latest/tutorials/dockerfile.html) sections in the
[Binder documentation](https://mybinder.readthedocs.io/en/latest/index.html) for instructions.

## Using JupyterHub

You can configure JupyterHub to launcher Docker containers from the Jupyter Docker Stacks images.
If you've been following the [Zero to JupyterHub with Kubernetes](https://zero-to-jupyterhub.readthedocs.io/en/latest/) guide,
see the [Use an existing Docker image](https://zero-to-jupyterhub.readthedocs.io/en/latest/jupyterhub/customizing/user-environment.html#choose-and-use-an-existing-docker-image) section for details.
If you have a custom JupyterHub deployment, see the [Picking or building a Docker image](https://github.com/jupyterhub/dockerspawner#picking-or-building-a-docker-image)
instructions for the [dockerspawner](https://github.com/jupyterhub/dockerspawner) instead.

## Using Other Tools and Services

You can use the Jupyter Docker Stacks with any Docker-compatible technology
(e.g., [Docker Compose](https://docs.docker.com/compose/), [docker-py](https://github.com/docker/docker-py), your favorite cloud container service).
See the documentation of the tool, library, or service for details about how to reference, configure, and launch containers from these images.