Playing around with cookie cutter docker template

A project cut from cookiecutter-ds-docker consists of a docker-compose stack with the services below:

1. A customized Jupyter service with a starter Python package installed. It runs on Python 3.7.
2. An mlflow tracking server to log experiments.
3. A postgresql database, which stores mlflow tracking information.

We mount several folders from our host to these services:

• The project base folder, ./, is mounted on the Jupyter docker container so that all modifications are synchronized immediately.
• The folder, ./data/artifacts, where the artifacts logged by mlflow are stored by default, is mounted on the Jupyter and mlflow services.
• The postgresql data folder, /var/lib/postgresql/data inside the container, is mounted locally on ./data/db/ to keep the database intact, after stopping the stack.