This is how I built a docker container to run a jupyter server. The reason why I did it was that I wanted to isolate any non-python dependencies I needed to install, but so far I haven't done any, so this could actually be done more easily using virtualenv, but this is a starting point.

The Dockerfile

This is the configuration for building the docker image.

FROM ubuntu:latest
WORKDIR /code
RUN apt-get update && apt-get -y upgrade
RUN apt-get install -y build-essential python-dev
RUN apt-get install -y python python-distribute python-pip
RUN pip install pip --upgrade
ADD requirements.txt /code
RUN pip install -r requirements.txt
RUN mkdir /notebooks
CMD jupyter notebook --no-browser --ip 0.0.0.0 --port 8888 /notebooks

The FROM line shows that I'm building my container using an ubuntu image (the latest image). The WORKDIR sets the current working directory so commands that are run will look there for files. The next set of RUN lines just say to update apt-get and install some basic python packages. The ADD line takes the requirements.txt file in the directory where I'm going to run this and put it in /CODE which I pointed to with the WORKDIR line. The next RUN commands install my python dependencies and make a folder called /notebooks to put the jupyter notebooks in. The last line (CMD) is what will be executed when the container is run.

Building the Image

If the docker-file is stored in a file named jupyter.dockerfile next to the requirements.txt file, both of which are in the directory where I run the build command. To build it (and name the image jupyter) I'd run the command:

docker -f jupyter.dockerfile -t jupyter:latest .

Running the Server

To run the server in the same directory where the notebooks should be stored and using the default port of 8888:

docker --name jupyter -p 8888:8888 -v $PWD:/notebooks -d jupyter

Now the server should be reachable at http://localhost:8888.