docker-stacks/docs/using/common.md

Common Features

By default, a container launched from any Jupyter Docker Stacks image runs a Jupyter Server with JupyterLab frontend. The container does so by executing a start-notebook.sh 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.sh script when launching the container.

1. For example, to secure the Notebook server with a custom password hashed using IPython.lib.passwd() instead of the default token, you can run the following (this hash was generated for my-password password):

   docker run -it --rm -p 8888:8888 jupyter/base-notebook \
       start-notebook.sh --NotebookApp.password='sha1:7cca89c48283:e3c1f9fbc06d1d2aa59555dfd5beed925e30dd2c'
   

2. To set the base URL of the notebook server, you can run the following:

   docker run  -it --rm -p 8888:8888 jupyter/base-notebook \
       start-notebook.sh --NotebookApp.base_url=/customized/url/prefix/
   

Docker Options

You may instruct the start-notebook.sh script to customize the container environment before launching the notebook 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 refits 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/${NB_USER}" 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/${NB_USER}" \
      jupyter/base-notebook
  

• -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. For this option to take effect, you must run the container with --user root. (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. For this option to take effect, you must run the container with --user root. (The startup script will su ${NB_USER} after adjusting the group ID.) You might consider using modern Docker options --user and --group-add instead. See bullet points regarding --user and --group-add. The user is added to 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 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.

  `NB_UMASK` when set only applies to the Jupyter process itself -
  you cannot use it to set a `umask` for additional files created during run-hooks.
  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 useful, however, when you wish to give ${NB_USER} the ability to install OS packages with apt or modify other root-owned files in the container. For this option to take effect, you must run the container with --user root. (The start-notebook.sh 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 is running 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 is 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 jupyter subcommand.

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

See the run-hooks function in the jupyter/base-notebook 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 \
    jupyter/base-notebook \
    start-notebook.sh \
    --NotebookApp.keyfile=/etc/ssl/notebook/notebook.key \
    --NotebookApp.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 \
    jupyter/base-notebook \
    start-notebook.sh \
    --NotebookApp.certfile=/etc/ssl/notebook.pem

In either case, Jupyter Notebook 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_notebook_config.py file for how this Docker image generates a self-signed certificate.
• The Jupyter Notebook documentation for best practices about securing a public notebook 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, it is still possible to switch back to the classic notebook or use a different startup command. You can achieve this by setting the environment variable DOCKER_STACKS_JUPYTER_CMD at container startup. The table below shows some options.

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

Notes:

• *Not installed at this time, but it could be the case in the future or in a community stack.
• Any other valid jupyter command that starts the Jupyter server can be used.

Example:

# Run Jupyter Notebook on Jupyter Server
docker run -it --rm \
    -p 8888:8888 \
    -e DOCKER_STACKS_JUPYTER_CMD=notebook \
    jupyter/base-notebook
# Executing the command: jupyter notebook ...

# Run Jupyter Notebook classic
docker run -it --rm \
    -p 8888:8888 \
    -e DOCKER_STACKS_JUPYTER_CMD=nbclassic \
    jupyter/base-notebook
# Executing the command: jupyter nbclassic ...

start.sh

The start-notebook.sh script inherits most of its option handling capability from a more generic start.sh script. The start.sh script supports all of the features described above but allows you to specify an arbitrary command to execute. For example, to run the text-based ipython console in a container, do the following:

docker run -it --rm jupyter/base-notebook start.sh 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.

Others

You can bypass the provided scripts and specify an arbitrary start command. If you do, keep in mind that features supported by the start.sh script and its kin will not function (e.g., GRANT_SUDO).

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 after
# the installation
mamba install --quiet --yes some-package && \
    mamba clean --all -f -y && \
    fix-permissions "${CONDA_DIR}" && \
    fix-permissions "/home/${NB_USER}"

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

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