Django Settings: Best Practices

Django Settings: Best Practices

Managing Django Settings: Issues

  • Different environments. Usually, you have several environments: local, dev, ci, qa, staging, production, etc. Each environment can have its own specific settings (for example: DEBUG = True, more verbose logging, additional apps, some mocked data, etc). You need an approach that allows you to keep all these Django setting configurations.

  • Sensitive data. You have SECRET_KEY in each Django project. On top of this there can be DB passwords and tokens for third-party APIs like Amazon or Twitter. This data cannot be stored in VCS.

  • Sharing settings between team members. You need a general approach to eliminate human error when working with the settings. For example, a developer may add a third-party app or some API integration and fail to add specific settings. On large (or even mid-size) projects, this can cause real issues.

  • Django settings are a Python code. This is a curse and a blessing at the same time. It gives you a lot of flexibility, but can also be a problem – instead of key-value pairs, settings.py can have a very tricky logic.

Setting Configuration: Different Approaches

There is no built-in universal way to configure Django settings without hardcoding them. But books, open-source and work projects provide a lot of recommendations and approaches on how to do it best. Let’s take a brief look at the most popular ones to examine their weaknesses and strengths.

settings_local.py

The basic idea of this method is to extend all environment-specific settings in the settings_local.py file, which is ignored by VCS.

Separate settings file for each environment

This is an extension of the previous approach. It allows you to keep all configurations in VCS and to share default settings between developers.

In this case, you make a settings package with the following file structure:

settings/
   ├── __init__.py
   ├── base.py
   ├── ci.py
   ├── local.py
   ├── staging.py
   ├── production.py
   └── qa.py

Environment variables

To solve the issue with sensitive data, you can use environment variables. This is the simplest example using Python os.environ and it has several issues:

  1. You need to handle KeyError exceptions.
  2. You need to convert types manually (see DATABASE_PORT usage).

django-environ

environment variables are the perfect place to store settings

This app gives a well-functioning API for reading values from environment variables or text files, handful type conversion, etc.