Get Started

(Note: These instructions currently OSX specifix because of brew but does work on other OSes.)

Before you install the library there are some minimal environment setup steps.

Docker setup

Install and start Docker:

brew cask install docker
open /Applications/

Build Example Image


FROM google/cloud-sdk:slim
RUN pip install jupyterlab notebook pandas
RUN  /bin/echo -e '#!/bin/bash\njupyter notebook --notebook-dir="/" --ip= --allow-root --NotebookApp.token=""' > /usr/bin/notebook && \
    chmod +x /usr/bin/notebook && \
     /bin/echo -e '#!/bin/bash\njupyter lab --notebook-dir="/" --ip= --allow-root --NotebookApp.token=""' > /usr/bin/lab && \
    chmod +x /usr/bin/lab
WORKDIR /current
CMD notebook

This Dockerfile uses the current directory as the workspace, and will look for all files there and the build command, docker build -t notebook -f Dockerfile ., will create a local docker image called Notebook, which uses the google/cloud-sdk as a base image. The Dockerfile also then makes a couple of small scripts to make it easier to launch notebooks or jupyterlab.

Install pydocker

pip install sq-pydocker

Setup ssh for pydocker

pydocker init

This will copy your ssh keys, and create a new config based on your main square config, but modified because of running in a docker container. This only needs to be run the first time.

Using pydocker

Usage: pydocker [OPTIONS] COMMAND [ARGS]...

  -v, --verbose
  --help         Show this message and exit.


Start ssh-agent container

If you need to have the ability to ssh into machines you can start an ssh-agent in a container with:

pydocker agent

This will add keys copied with the init command without passwords automatically, or print the command you need to run to add password protected keys. This ssh-agent container will then be connected to all other containers, so you don’t need to keep entering your key password. The makes it more secure by not storing any credentials in the Image. This container can be restarted when needed, if you run pydocker agent it will delete the container, and make a new one.


    -i, --image TEXT        Docker image
    -n, --name TEXT         container name
    -d, --working-dir TEXT  host directory to mount
    -p, --port INTEGER      Host port to be connected to container port 8888
    -l, --no-logs           disable streaming of container logs
    --gcloud / --no-gcloud  include gcloud credentials
    -c, --command TEXT      command which is passed to container
    -r, --rm                enable auto-removal of the container on daemon side
                            when the container’s process exits
    --help                  Show this message and exit.

This command launches the notebook (which we built above) and forwards internal port 8888 to the laptops port 9000 and creates a container named test. In addition the host’s current folder . is mounted in the working_dir folder. This gives the container access to the host filesystem. After running the command you can go to localhost:9000 in your browser.

pydocker launch --image notebook --name test --working-dir . --port 9000 --no-gcloud

Remote images also work:

pydocker launch --image jupyter/minimal-notebook:latest --name example --working-dir . --port 9000 --no-gcloud

Will pull the remote image down first. You can still do docker pull IMAGE and pydocker will use the already downloaded image.

Google Cloud Setup (optional)

This is only required if you are going to be using Google Cloud. If you already have gcloud installed, update by running gcloud components update. If you have not setup Google Cloud already, begin by installing Google Cloud.

  1. Download the (archive)( and unpack it (only do the “Before you begin” section).

  2. Navigate to the folder containing google-cloud-sdk and run

  3. Set your gcloud account and project.

    gcloud auth login
    gcloud config set account ${USER}
    gcloud config set project YOUR_PROJECT
    gcloud auth application-default login
  4. Now generate your ssh credentials by running:

    gcloud compute ssh --zone "us-central1-a" "RUNNING_VM"

Status Server

pydocker status

This will open a status server which will show a page with information about all local containers. This includes a link to clink into any with open port forwarding.

Container Status

Container Status

Remove Containers

pydocker remove-all
pydocker remove CONTAINER_NAME

This delete all running containers, or just the one selected.

Stop Containers

pydocker stop-all
pydocker stop CONTAINER_NAME

This stop all running containers, or just the one selected.