Common Features

Except for jupyter/docker-stacks-foundation, a container launched from any Jupyter Docker Stacks image runs a Jupyter Server with the JupyterLab frontend. The container does so by executing a start-notebook.py script. This script configures the internal container environment and then runs jupyter lab, passing any command-line arguments received.

This page describes the options supported by the startup script and how to bypass it to run alternative commands.

Jupyter Server Options

You can pass Jupyter Server options to the start-notebook.py script when launching the container.

For example, to secure the Jupyter Server with a custom password hashed using jupyter_server.auth.passwd() instead of the default token, you can run the following (this hash was generated for the my-password password):

docker run -it --rm -p 8888:8888 quay.io/jupyter/base-notebook \
    start-notebook.py --PasswordIdentityProvider.hashed_password='argon2:$argon2id$v=19$m=10240,t=10,p=8$JdAN3fe9J45NvK/EPuGCvA$O/tbxglbwRpOFuBNTYrymAEH6370Q2z+eS1eF4GM6Do'

To set the base URL of the Jupyter Server, you can run the following:

docker run -it --rm -p 8888:8888 quay.io/jupyter/base-notebook \
    start-notebook.py --ServerApp.base_url=/customized/url/prefix/

Docker Options

You may instruct the start-notebook.py script to customize the container environment before launching the Server. You do so by passing arguments to the docker run command.

User-related configurations

-e NB_USER=<username> - The desired username and associated home folder. The default value is jovyan. Setting NB_USER redefines the jovyan default user and ensures that the desired user has the correct file permissions for the new home directory created at /home/<username>. For this option to take effect, you must run the container with --user root, set the working directory -w "/home/<username>" and set the environment variable -e CHOWN_HOME=yes.

Example usage:
```
docker run -it --rm \
    -p 8888:8888 \
    --user root \
    -e NB_USER="my-username" \
    -e CHOWN_HOME=yes \
    -w "/home/my-username" \
    quay.io/jupyter/base-notebook
```
```
If you set `NB_USER` to `root`, the `root` home dir will be set to `/home/root`.
See discussion [here](https://github.com/jupyter/docker-stacks/issues/2042).
```
-e NB_UID=<numeric uid> - Instructs the startup script to switch the numeric user ID of ${NB_USER} to the given value. The default value is 1000. This feature is useful when mounting host volumes with specific owner permissions. You must run the container with --user root for this option to take effect. (The startup script will su ${NB_USER} after adjusting the user ID.) Instead, you might consider using the modern Docker-native options --user and --group-add - see the last bullet in this section for more details. See bullet points regarding --user and --group-add.
-e NB_GID=<numeric gid> - Instructs the startup script to change the primary group of ${NB_USER} to ${NB_GID} (the new group is added with a name of ${NB_GROUP} if it is defined. Otherwise, the group is named ${NB_USER}). This feature is useful when mounting host volumes with specific group permissions. You must run the container with --user root for this option to take effect. (The startup script will su ${NB_USER} after adjusting the group ID.) Instead, you might consider using modern Docker options --user and --group-add. See bullet points regarding --user and --group-add. The user is added to the supplemental group users (gid 100) to grant write access to the home directory and /opt/conda. If you override the user/group logic, ensure the user stays in the group users if you want them to be able to modify files in the image.
-e NB_GROUP=<name> - The name used for ${NB_GID}, which defaults to ${NB_USER}. This group name is only used if ${NB_GID} is specified and completely optional: there is only a cosmetic effect.
--user 5000 --group-add users - Launches the container with a specific user ID and adds that user to the users group so that it can modify files in the default home directory and /opt/conda. You can use these arguments as alternatives to setting ${NB_UID} and ${NB_GID}.

Permission-specific configurations

-e NB_UMASK=<umask> - Configures Jupyter to use a different umask value from default, i.e. 022. For example, if setting umask to 002, new files will be readable and writable by group members instead of the owner only. Check this Wikipedia article for an in-depth description of umask and suitable values for multiple needs. While the default umask value should be sufficient for most use cases, you can set the NB_UMASK value to fit your requirements.
```
When `NB_UMASK` is set, it only applies to the Jupyter process itself -
you cannot use it to set a `umask` for additional files created during `run-hooks.sh`.
For example, via `pip` or `conda`.
If you need to set a `umask` for these, you **must** set the `umask` value for each command.
```
-e CHOWN_HOME=yes - Instructs the startup script to change the ${NB_USER} home directory owner and group to the current value of ${NB_UID} and ${NB_GID}. This change will take effect even if the user home directory is mounted from the host using -v as described below. The change is not applied recursively by default. You can modify the chown behavior by setting CHOWN_HOME_OPTS (e.g., -e CHOWN_HOME_OPTS='-R').
-e CHOWN_EXTRA="<some dir>,<some other dir>" - Instructs the startup script to change the owner and group of each comma-separated container directory to the current value of ${NB_UID} and ${NB_GID}. The change is not applied recursively by default. You can modify the chown behavior by setting CHOWN_EXTRA_OPTS (e.g., -e CHOWN_EXTRA_OPTS='-R').
-e GRANT_SUDO=yes - Instructs the startup script to grant the NB_USER user passwordless sudo capability. You do not need this option to allow the user to conda or pip install additional packages. This option is helpful for cases when you wish to give ${NB_USER} the ability to install OS packages with apt or modify other root-owned files in the container. You must run the container with --user root for this option to take effect. (The start-notebook.py script will su ${NB_USER} after adding ${NB_USER} to sudoers.) You should only enable sudo if you trust the user or if the container runs on an isolated host.

Additional runtime configurations

-e GEN_CERT=yes - Instructs the startup script to generate a self-signed SSL certificate. Configures Jupyter Server to use it to accept encrypted HTTPS connections.
-e DOCKER_STACKS_JUPYTER_CMD=<jupyter command> - Instructs the startup script to run jupyter ${DOCKER_STACKS_JUPYTER_CMD} instead of the default jupyter lab command. See Switching back to the classic notebook or using a different startup command for available options. This setting is helpful in container orchestration environments where setting environment variables is more straightforward than changing command line parameters.
-e RESTARTABLE=yes - Runs Jupyter in a loop so that quitting Jupyter does not cause the container to exit. This may be useful when installing extensions that require restarting Jupyter.
-v /some/host/folder/for/work:/home/jovyan/work - Mounts a host machine directory as a folder in the container. This configuration is useful for preserving notebooks and other work even after the container has been destroyed. You must grant the within-container notebook user or group (NB_UID or NB_GID) write access to the host directory (e.g., sudo chown 1000 /some/host/folder/for/work).
-e JUPYTER_ENV_VARS_TO_UNSET=ADMIN_SECRET_1,ADMIN_SECRET_2 - Unsets specified environment variables in the default startup script. The variables are unset after the hooks have been executed but before the command provided to the startup script runs.
-e NOTEBOOK_ARGS="--log-level='DEBUG' --dev-mode" - Adds custom options to add to jupyter commands. This way, the user could use any option supported by the jupyter subcommand.
-e JUPYTER_PORT=8117 - Changes the port in the container that Jupyter is using to the value of the ${JUPYTER_PORT} environment variable. This may be useful if you run multiple instances of Jupyter in swarm mode and want to use a different port for each instance.

Startup Hooks

You can further customize the container environment by adding shell scripts (*.sh) to be sourced or executables (chmod +x) to be run to the paths below:

/usr/local/bin/start-notebook.d/ - handled before any of the standard options noted above is applied
/usr/local/bin/before-notebook.d/ - handled after all the standard options noted above are applied and ran right before the Server launches

See the run-hooks.sh script here and how it's used in the start.sh script for execution details.

SSL Certificates

You may mount an SSL key and certificate file into a container and configure the Jupyter Server to use them to accept HTTPS connections. For example, to mount a host folder containing a notebook.key and notebook.crt and use them, you might run the following:

docker run -it --rm -p 8888:8888 \
    -v /some/host/folder:/etc/ssl/notebook \
    quay.io/jupyter/base-notebook \
    start-notebook.py \
    --ServerApp.keyfile=/etc/ssl/notebook/notebook.key \
    --ServerApp.certfile=/etc/ssl/notebook/notebook.crt

Alternatively, you may mount a single PEM file containing both the key and certificate. For example:

docker run -it --rm -p 8888:8888 \
    -v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
    quay.io/jupyter/base-notebook \
    start-notebook.py \
    --ServerApp.certfile=/etc/ssl/notebook.pem

In either case, Jupyter Server expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).

For additional information about using SSL, see the following:

The docker-stacks/examples for information about how to use Let's Encrypt certificates when you run these stacks on a publicly visible domain.
The jupyter_server_config.py file for how this Docker image generates a self-signed certificate.
The Jupyter Server documentation for best practices about securing a public Server in general.

Alternative Commands

Switching back to the classic notebook or using a different startup command

JupyterLab, built on top of Jupyter Server, is now the default for all the images of the stack. However, switching back to the classic notebook or using a different startup command is still possible. You can achieve this by setting the environment variable DOCKER_STACKS_JUPYTER_CMD at container startup. The table below shows some options. Since Jupyter Notebook v7 jupyter-server is used as a backend.

`DOCKER_STACKS_JUPYTER_CMD`	Frontend
`lab` (default)	JupyterLab
`notebook`	Jupyter Notebook
`nbclassic`	NbClassic
`server`	None
`retro`*	RetroLab

- Changing frontend for **JupyterHub singleuser image** is described in [JupyterHub docs](https://jupyterhub.readthedocs.io/en/latest/howto/configuration/config-user-env.html#switching-back-to-the-classic-notebook).
- \* `retro` is not installed at this time, but it could be the case in the future or in a community stack.
- Any other valid `jupyter` subcommand that starts the Jupyter Application can be used.

Example:

# Run Jupyter Server with the Jupyter Notebook frontend
docker run -it --rm \
    -p 8888:8888 \
    -e DOCKER_STACKS_JUPYTER_CMD=notebook \
    quay.io/jupyter/base-notebook

# Executing the command: start-notebook.py
# Executing: jupyter notebook
# ...

# Use Jupyter NBClassic frontend
docker run -it --rm \
    -p 8888:8888 \
    -e DOCKER_STACKS_JUPYTER_CMD=nbclassic \
    quay.io/jupyter/base-notebook

# Executing the command: start-notebook.py
# Executing: jupyter nbclassic
# ...

`start.sh`

Most of the configuration options in the start-notebook.py script are handled by an internal start.sh script that automatically runs before the command provided to the container (it's set as the container entrypoint). This allows you to specify an arbitrary command that takes advantage of all these features. For example, to run the text-based ipython console in a container, do the following:

docker run -it --rm quay.io/jupyter/base-notebook ipython

This script is handy when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like jupyter console, jupyter kernelgateway, etc.

Conda Environments

The default Python 3.x Conda environment resides in /opt/conda. The /opt/conda/bin directory is part of the default jovyan user's ${PATH}. That directory is also searched for binaries when run using sudo (sudo my_binary will search for my_binary in /opt/conda/bin/).

The jovyan user has full read/write access to the /opt/conda directory. You can use either mamba, pip, or conda (mamba is recommended) to install new packages without any additional permissions.

# install a package into the default (python 3.x) environment and cleanup it after
# the installation
mamba install --yes some-package && \
    mamba clean --all -f -y && \
    fix-permissions "${CONDA_DIR}" && \
    fix-permissions "/home/${NB_USER}"

pip install --no-cache-dir some-package && \
    fix-permissions "${CONDA_DIR}" && \
    fix-permissions "/home/${NB_USER}"

conda install --yes some-package && \
    conda clean --all -f -y && \
    fix-permissions "${CONDA_DIR}" && \
    fix-permissions "/home/${NB_USER}"

Using Alternative Channels

Conda is configured by default to use only the conda-forge channel. However, you can use alternative channels, either one-shot by overwriting the default channel in the installation command or by configuring mamba to use different channels. The examples below show how to use the anaconda default channels instead of conda-forge to install packages.

# using defaults channels to install a package
mamba install --channel defaults humanize

# configure conda to add default channels at the top of the list
conda config --system --prepend channels defaults

# install a package
mamba install --yes humanize && \
    mamba clean --all -f -y && \
    fix-permissions "${CONDA_DIR}" && \
    fix-permissions "/home/${NB_USER}"

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common.md

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Common Features

Jupyter Server Options

Docker Options

User-related configurations

Permission-specific configurations

Additional runtime configurations

Startup Hooks

SSL Certificates

Alternative Commands

Switching back to the classic notebook or using a different startup command

`start.sh`

Conda Environments

Using Alternative Channels

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Common Features

Jupyter Server Options

Docker Options

User-related configurations

Permission-specific configurations

Additional runtime configurations

Startup Hooks

SSL Certificates

Alternative Commands

Switching back to the classic notebook or using a different startup command

start.sh

Conda Environments

Using Alternative Channels

`start.sh`