How to install JupyterHub with Docker on a local machine and in a sub domain - jupyter-notebook

Question

I will run JupyterHub in a sub domain. Here is the Dockerfile, jupyterhub_config.py, .gitlab-ci.yml.
My first question is how to configure the jupyter_config.py. How can I load the jupyterhub_config.py on the build in the container?
How do I start Jupyterhub in the .gitlab-ci.yml for tests and how do I copy the application in the sub domain? I wrote a README.md. I need a little help for the JupyterHub. If all works fine, I will write a complete HOWTO Install JupyterHub on a local machine and in a sub domain by a provider.
FROM continuumio/miniconda3
# Updating packages
RUN apt-get update -y \
&& apt-get install -y --no-install-recommends \
git \
nano \
unzip \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# Install conda and Jupyter
RUN conda update -y conda
RUN conda install -c conda-forge jupyter_nbextensions_configurator \
jupyterhub \
jupyterlab \
matplotlib \
pandas \
scipy
# Setup application
EXPOSE 8000
CMD ["jupyterhub", "--ip='*'", "--port=8000", "--no-browser", "--allow-root"]
The .gitlab-ci.yml
image: docker:latest
variables:
CONTAINER_IMAGE: registry.gitlab.com/joklein
DOCKER_IMAGE: jupyterhub
TAG: 0.1.0
services:
- docker:dind
stages:
- build
- test
- release
- deploy
before_script:
- echo "$GITLAB_PASSWORD" | docker login registry.gitlab.com --username $GITLAB_USER --password-stdin
build:
stage: build
script:
- docker build -t $CONTAINER_IMAGE/$DOCKER_IMAGE .
- docker push $CONTAINER_IMAGE/$DOCKER_IMAGE
test:
stage: test
script:
- docker pull $CONTAINER_IMAGE/$DOCKER_IMAGE
# - docker run $CONTAINER_IMAGE/$DOCKER_IMAGE -dt -p 8000:8000 --name $DOCKER_IMAGE
release:
stage: release
script:
- docker pull $CONTAINER_IMAGE/$DOCKER_IMAGE
- docker tag $CONTAINER_IMAGE/$DOCKER_IMAGE:latest $CONTAINER_IMAGE/$DOCKER_IMAGE:$TAG
- docker push $CONTAINER_IMAGE/$DOCKER_IMAGE:$TAG
only:
- master
deploy:
stage: deploy
image: alpine:latest
before_script:
- apk update && apk add git openssh-client rsync
script:
- mkdir .public
- cp -r * .public
- mv .public public
- mkdir "${HOME}/.ssh"
- echo "${SSH_HOST_KEY}" > "${HOME}/.ssh/known_hosts"
- echo "${SSH_PRIVATE_KEY}" > "${HOME}/.ssh/id_rsa"
- chmod 700 "${HOME}/.ssh/id_rsa"
- rsync -hrvz --delete --exclude=_ public/ user#example.com:www/jupyter/
only:
- master
The jupyterhub_config.py
c = get_config()
# Letsencrypt (https://letsencrypt.org/) to obtain a free, trusted SSL
# certificate.
c.JupyterHub.ssl_key = '/etc/letsencrypt/live/example.com/privkey.pem'
c.JupyterHub.ssl_cert = '/etc/letsencrypt/live/example.com/fullchain.pem'
c.JupyterHub.port = 443
#
# Change from JupyterHub to JupyterLab
c.Spawner.default_url = '/lab'
c.Spawner.debug = True
#
# # Specify users and admin
c.Authenticator.whitelist = {"systemuser"}
c.Authenticator.admin_users = {"systemuser"}
Docker base image of JupyterHub and JupyterLab
JupyterHub is a multi-user server for Jupyter notebooks. JupyterLab is the
next-generation web-based user interface for the Jupyter Project. This
JupyterHub is a Docker base image for JupyterHub and JupyterLab
that works as a stand-alone application and in a (sub) domain.
Images derived from this image can either run as a stand-alone server, or
function as a volume image for your server. You can also use them in a CI/CD
system such as GitLab CI to build your content prior to bundling it into a
standalone server container.
Building your JupyterHub image
Based on this structure, you can easily build an image for your needs. There are two options for using the image you generated:
as a stand-alone image
as a volume image for your webserver
The simplest way to build your own image is to use a Dockerfile. This is only an example. If you need more software packages you can install them with this
Dockerfile and conda.
Build the container
docker build -t juypterhub .
Your JupyterHub with JupyterLab is automatically generated during this build.
Run the container
docker run -p 8000:8000 -d --name jupyterhub jupyterhub jupyterhub
-p is used to map your local port 8000 to the container port 8000
-d is used to run the container in background. JupyterHub will just write
logs so no need to output them in your terminal unless you want to troubleshoot a server error.
-- name jupyterhub names your container jupyterhub
jupyterhub the image
jupyterhub is the last command used to start the jupyterhub server
and your JupyterHub with Jupyterlab is now available of http://localhost:8000.
Start / Stop JupyterHub
docker start / stop juyterhub
Configure JupyterHub
Let's encrypt certificates for JupyterHub
To enable HTTPS on your website, you need to get a certificate (a type of file) from a Certificate Authority (CA). Let’s Encrypt is a CA. In order to get a certificate for your website’s domain from Let’s Encrypt, you have to
demonstrate control over the domain. With Let’s Encrypt, you do this using
software that uses the ACME protocol, which typically runs on your web host.
Change to zerossl.com and generate a certificate for your domain. As the
result you get four files, domain-key.txt, domain-crt.txt, domain-csr.txt, account-key.txt. This files uses base 64, which is readable in
ASCII, not binary format. The certificates are already in PEM format. Just
change the extension to *.pem.
For JupyterHub only the files domain-key.txt and domain-crt are needed.
cp domain-crt.txt fullchain.pem
cp domain-key.txt privkey.pem
Add a System user in the container
By default JupyterHub searches for users on the server. In order to be able to
log in to our new JupyterHub server we need to connect to the JupyterHub docker
container and create a new system user with a password.
docker exec -it jupyterhub bash
useradd --create-home systemuser
passwd systemuser
exit
The command docker exec -it jupyterhub bash will spawn a root shell in your
docker container. You can use the root shell to create system users in the
container. These accounts will be used for authentication in JupyterHub's
default configuration.
The first command useradd creates a new user named systemuser. The second will
ask you for a password.

Answer 1

The all process might be simpler with GitLab 12.0 (June 2019), and its
Git integration for JupyterHub
Deploying JupyterHub via GitLab’s Kubernetes integration provides an easy way to get started with Jupyter notebooks, which can be used to create and share documents that contain live code, visualizations, and even runbooks.
Starting with GitLab 12.0, JupyterLab’s Git extension is automatically provisioned and configured when installing JupyterHub onto your Kubernetes cluster.
This integration enables full version control of your notebooks as well as issuance of Git commands within Jupyter. Git commands can be issued via the Git tab on the left panel or via Jupyter’s command line prompt.
See documentation and gitlab-ce issue 47138.

Answer 2

jupyterhub --generate-config
This is what on the documentation
It created a config.py file in /srv/jupyterhub