A Beginner’s Guide to Docker

Docker is a way to isolate and run entire applications. With Docker it doesn’t matter if you are using a Mac, Windows, or Linux computer anymore. The entire development environment is isolated: programming language, software packages, databases, and more.

With Docker we now longer have to mess around with virtual environments. We can faithfully reproduce a production environment locally. And Docker can be shared among team members so everyone is working on the same setup. Wins all around.

What’s the downside? Complexity. Docker is a complex beast under the hood. However a little knowledge can take you a long way and that’s the goal of this guide!

Linux Containers

Docker is really just Linux containers which are a type of virtualization.

Virtualization has its roots at the beginning of computer science when large, expensive mainframe computers were the norm. How could multiple programmers use the same single machine? The answer was virtualization and specifically virtual machines which are complete copies of a computer system from the operating system on up.

If you rent space on a cloud provider like AWS they are typically not providing you with a dedicated piece of hardware. Instead you are probably sharing a physical server with hundreds or even thousands of other clients.

What’s the downside to a virtual machine? Size and speed. A typical guest operating system can easily take up 700MB of size. So if one physical server supports three virtual machines, that’s at least 2.1GB of disk space taken up along with separate needs for CPU and memory resources.

Most computers rely on the same Linux operating system, so what if we virtualized from that level up instead? Wouldn’t that provide a lightweight, faster way to duplicate much of the same functionality?

The answer is yes. And in recent years Linux containers, also known as “containerization,” has become increasingly popular. For most applications, a virtual machine provides far more resources than are needed and a container is more than sufficient.

This, fundamentally, is what Docker is. A way to implement Linux containers!

An analogy we can use here is that of homes and apartments. Virtual Machines are like homes: stand-alone buildings with their own infrastructure including plumbing and heating, as well as a kitchen, bathrooms, bedrooms, and so on. Docker containers are like apartments: they share common infrastructure like plumbing and heating, but come in various sizes that match the exact needs of an owner.

Containers vs Virtual Environments

If you are a Python programmer (like me) a common question at this point is, what about virtual environments? How do they differ from containers?

Virtual environments are used to isolate Python software packages locally. We can create an isolated box for individual projects so one can use Python 2.7 and Django 1.5 while another can use Python 3.5 and Django 2.1 on the same computer. Virtual environments are great.

But…virtual environments can only isolate Python packages. They still rely on a global, system-level installation of Python albeit they can refer to the proper version. So when we use Python 2.7 in a project, we’re pointing to an installation of Python 2.7 on the computer itself, not actually within the virtual environment.

Also we can’t run a production database or other services within virtual environments so compared to Docker containers they are far more limited.

Library Website and API

Django REST Framework works alongside the Django web framework to create web APIs. We cannot build a web API with only Django Rest Framework; it always must be added to a project after Django itself has been installed and configured.

In this chapter we will review the similarities and differences between traditional Django and Django REST Framework. The most important takeaway is that Django creates websites containing webpages, while Django REST Framework creates web APIs which are a collection of URL endpoints containing available HTTP verbs that return JSON.

To illustrate these concepts, we will build out a basic Library website with traditional Django and then extend it into a web API with Django REST Framework.

Django REST Framework

Django REST Framework is added just like any other third-party app. Make sure to quit the local server Control + c if it is still running. Then on the command line type the below.

(library) $ pipenv install djangorestframework~=3.11.0

Add it to the INSTALLED_APPS config in our settings.py file. I like to make a distinction between third-party apps and local apps as follows since the number of apps grows quickly in most projects.

INSTALLED_APPS = [
    'django.contrib.admin',
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.messages',
    'django.contrib.staticfiles',

    'rest_framework', # new

    'books',
]

Ultimately, our API will expose a single endpoint that lists out all books in JSON. So we will need a new URL route, a new view, and a new serializer file (more on this shortly).

There are multiple ways we can organize these files however my preferred approach is to create a dedicated api app. That way even if we add more apps in the future, each app can contain the models, views, templates, and urls needed for dedicated webpages, but all API-specific files for the entire project will live in a dedicated api app.