Jupyter + MongoDB

Includes example Jupyter notebook to push data to MongoDB, and a mongo-express admin interface. Runs the Jupyter Data Science Notebook container with an installation of Zipline.

Instructions

1. Clone this repository and cd into the directory:

   git clone https://github.com/aeksco/docker_jupyter_mongodb.git

   cd docker_jupyter_mongodb

2. Start the docker containers:

   docker-compose up

   NOTE - there's a unique token you'll need to access the Jupyter notebook server.

   The docker-compose terminal will print out a self-authenticating URL, which looks like:

   http://localhost:8888/?token=8a78623a6eadf3433f0b1ccef1049b2ce525fef20823a12d

   Opening that URL will take you to the notebook server.

Usage

• MongoDB admin interface running at http://localhost:8081

• Jupyter server running at http://localhost:8888

• Run the MongoDB notebook to create the jupyter database and a single example restaurant record

Notes

• This configuration is not optimized for size. The jupyter/datascience-notebook has a footprint of 6.28 GB - you could substitute the jupyter/minimal-notebook (footprint of 2.74 GB) by changing the FROM statement in jupyter/Dockerfile.

• You may run a command inside the jupyter docker container as the root user with the following command:

  docker-compose run --user="root" jupyter pip install pandas

Optional NGINX Configuration

• Run the following to setup an NGINX reverse-proxy to the Jupyter Notebook server

  sudo apt-get update
  sudo apt-get install nginx
  

• Copy the contents of NGINX_EXAMPLE into /etc/nginx/sites-available/my_site

• Simlink the file from sites-available to sites-enabled

  ln -s /etc/nginx/sites-available/my_site /etc/nginx/sites-enabled/my_site

• Control NGINX with the following system commands:

  sudo systemctl start nginx
  sudo systemctl stop nginx
  sudo systemctl restart nginx