Django settings are used to configure the Django framework and its applications. They can be set in a variety of ways, but the most common way is to use a settings file. This file is typically called settings.py and is located in the root directory of your Django project.
There are a few issues with managing Django settings in a single file:
- It can be difficult to keep track of all of the settings, especially if you have a large project.
- It can be difficult to share settings with other developers or to use the same settings for multiple projects.
- It can be difficult to keep sensitive data, such as database passwords, secure.
Table of Contents
Setting Django Configurations: Different Approaches
There are a few different approaches to setting Django configurations. The most common approach is to use a single settings file, but there are other options, such as using environment variables or a separate settings file for each environment.
settings_local.py
One approach to managing Django settings is to use a separate settings file for local development. This file is typically called settings_local.py and is ignored by version control systems. This allows you to store sensitive information, such as database passwords, in the local settings file without having to commit them to your repository.
Here is an example of a settings_local.py file:
Python
DEBUG = True DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'my_database', 'USER': 'my_user', 'PASSWORD': 'my_password', 'HOST': 'localhost', 'PORT': '5432', } }
How to organize Django settings into a package
One way to organize Django settings is to create a package called settings. This package would contain several different settings files, each of which would be specialized for a different purpose.
The structure of the settings package would look like this:
settings/ __init__.py base.py development.py testing.py production.py local.py
The base.py file would contain the base settings for your Django project. These settings would be used in all environments, regardless of whether you are developing, testing, or running in production.
The development.py, testing.py, and production.py files would contain settings that are specific to each environment. For example, the development.py file might contain settings for connecting to your development database, while the production.py file might contain settings for connecting to your production database.
The local.py file would contain settings that are specific to your local development environment. For example, the local.py file might contain settings for debugging your Django project.
Finally, the __init__.py file would be empty. It is required for Python to recognize the settings package.
To use the local settings file, you need to add the following line to your settings.py file:
Python
from .settings_local import *
This will import all of the settings from the settings_local.py file into the global settings object.
Pros:
- Easy to use
- Allows you to store sensitive information in a separate file that is ignored by version control systems
Cons:
- It can be difficult to keep track of which settings are coming from the local settings file and which settings are coming from the global settings file
- It can be difficult to share settings with other developers or to use the same settings for multiple projects
Separate settings file for each environment
Another approach to managing Django settings is to use a separate settings file for each environment. This means that you will have a different settings file for development, production, and any other environments that you use.
This approach has a few advantages over using a single settings file:
- It is easier to keep track of which settings are for which environment.
- It is easier to share settings with other developers or to use the same settings for multiple projects.
- It is easier to keep sensitive data secure.
To use this approach, you would create a directory called settings and then create a separate setting file for each environment. For example, you would create a file called settings/development.py for your development environment and a file called settings/production.py for your production environment.
In your settings.py file, you would then import the settings from the appropriate settings file based on the current environment. For example, if you are running in the development environment, you would import the settings from the settings/development.py file.
Here is an example of a settings.py file that uses this approach:
Python
from .settings import * if os.environ.get('DJANGO_ENV') == 'production': from .settings_production import * else: from .settings_development import *
This approach has a few disadvantages:
- It can be more difficult to set up and maintain.
- It can be more difficult to troubleshoot problems, as you need to figure out which settings file is being used.
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Environment variables
Environment variables are key-value pairs that are stored outside of your codebase. They can be set on a per-environment basis, which makes them ideal for storing sensitive information.
To use environment variables, you need to set them in your environment. For example, to set the database password environment variable, you would run the following command:
export DATABASE_PASSWORD=my_password
You can then access environment variables in your Django settings file using the os.environ object. For example, to set the database password in your Django settings file, you would add the following line:
Python
DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': 'my_database', 'USER': 'my_user', 'PASSWORD': os.environ.get('DATABASE_PASSWORD'), 'HOST': 'localhost', 'PORT': '5432', } }
Using environment variables to configure Django settings has several advantages:
- It makes it easier to keep sensitive information secure.
- It makes it easier to share settings with other developers.
- It makes it easier to use the same settings for multiple projects.
- It makes it easier to deploy your application to different environments.
However, using environment variables to configure Django settings also has some disadvantages:
- You need to handle KeyError exceptions, as environment variables may not be set.
- You need to convert types manually.
- It can be difficult to debug problems, as you need to figure out which environment variables are being used.
Django-environ
Using environment variables with Python’s os.environ object
The simplest way to use environment variables to configure Django settings is to use the os.environ object. The os.environ object is a dictionary that contains all of the environment variables that are currently set.
To access an environment variable, you can simply use the os.environ object as a dictionary. For example, to access the database password environment variable, you would use the following code:
Python:
database_password = os.environ.get(‘DATABASE_PASSWORD’)
if the environment variable is not set, the os.environ.get() method will return None.
Using environment variables with the django-environ package
The django-environ package is a third-party package that makes it easier to use environment variables to configure Django settings.
To use the django-environ package, you first need to install it:
pip install django-environ
Once the django-environ package is installed, you need to add the following line to your settings.py file:
Python
import environ env = environ.Env()
The environ.Env() object will load all of the environment variables from your environment.
To access an environment variable, you can use the env() object as a function. For example, to access the database password environment variable, you would use the following code:
Python
database_password = env('DATABASE_PASSWORD')
3
If the environment variable is not set, the env() function will raise a django_environ.ImproperlyConfigured exception.
Example
The following is an example of how to use environment variables to configure the database settings in your Django settings file:
Python
import environ env = environ.Env() DATABASES = { 'default': { 'ENGINE': os.environ.get('DATABASE_ENGINE', 'django.db.backends.postgresql_psycopg2'), 'NAME': os.environ.get('DATABASE_NAME', 'my_database'), 'USER': os.environ.get('DATABASE_USER', 'my_user'), 'PASSWORD': os.environ.get('DATABASE_PASSWORD', ''), 'HOST': os.environ.get('DATABASE_HOST', 'localhost'), 'PORT': os.environ.get('DATABASE_PORT', '5432'), } }
Naming Conventions for Django Settings
Naming conventions are important for making your code more readable and maintainable. They also help to avoid name collisions, which can lead to errors.
Here are some good practices for naming Django settings:
- Use all caps for setting names. This helps to distinguish setting names from other variables in your code.
- Use underscores to separate words in setting names. For example, DATABASE_PASSWORD instead of databasePassword.
- Avoid using abbreviations in setting names. This can make your code less readable and more difficult to understand.
- Use descriptive names for settings. For example, instead of SETTING_1, use DEBUG_MODE.
Here is an example of a poorly named Django setting:
Python
# Poorly named setting DEBUG = True
This setting is poorly named because:
- It is not in all caps.
- It does not use underscores to separate words.
- It is not descriptive.
Here is an example of a well-named Django setting:
Python
# Well-named setting DEBUG_MODE = True
This setting is well-named because:
- It is in all caps.
- It uses underscores to separate words.
- It is descriptive.
Additional tips:
- Avoid using special characters in setting names, such as hyphens, spaces, or periods.
- Avoid using keywords or reserved words in setting names.
- Avoid using the same name for a setting and a variable in your code.
By following these good practices, you can make your Django settings more readable, maintainable, and error-free.
Conclusion
Using environment variables to configure Django settings is a good way to keep sensitive information secure and to make it easier to share settings with other developers and to use the same settings for multiple projects