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Version:0.5.0
Source:https://github.com/maykinmedia/django-setup-configuration
Keywords:Configuration
PythonVersion:3.10

Build status Code quality checks black Coverage status Documentation Status

python-versions django-versions pypi-version

Manage your configuration via django command.

This library will allow you to define one or more "configuration steps" which declare a set of expected configuration values and hooks which can be used to configure some part of your project based on those settings. The steps can be run programmatically or via an included Django management command.

It's intended usage is larger Django projects that require a significant amount of configuration to be provisioned, as well as a way to store configuration in an agnostic format (such as yaml) that is not tightly coupled to your Django models.

  • Python 3.10 or above
  • Django 3.2 or above
  • Pydantic 2 or above
  • Pydantic-settings 2.2 or above
  1. Install from PyPI
pip install django-setup-configuration
  1. Add django_setup_configuration to the INSTALLED_APPS setting.
  • Configuration Model: A Pydantic model defining the structure and validation rules for your configuration.
  • Configuration Step: A class that implements the actual configuration logic using the validated configuration model.
from pydantic import Field
from django_setup_configuration import ConfigurationModel, DjangoModelRef

class UserConfigurationModel(ConfigurationModel):
    # A regular Pydantic field
    add_to_groups: list[str] = Field(
        default_factory=list,
        description="Groups to add the user to"
    )

    # Reference Django model fields with automatic type inference
    username = DjangoModelRef("auth.User", "username", default="admin")

    # You can optionally override the inferred type (overriding the type is
    # required for fields that can not be unambiguously mapped to a Python type,
    # such as relational fields or third-party fields).
    is_staff: Optional[int] = DjangoModelRef("auth.User", "username", default=0)

    # If you have no need for overriding any of the inferred attributes, you can reference model fields in a Meta class
    class Meta:
        django_model_refs = {
            User: ["password"]
        }

For regular Pydantic fields, you must explicitly configure defaults using Field (default=...) or Field(default_factory=lambda: ...) as specified in the Pydantic documentation.

NOTE: Marking a field as Optional or using ... | None does not automatically set the field's default to None. You must set this explicitly if you want the field to be optional:

from pydantic import Field

class ConfigModel(ConfigurationModel):
    optional_field: int | None = DjangoModelRef(SomeModel, "some_field", default=None)

For DjangoModelRef, the default value handling follows these rules:

You can provide explicit defaults using the default or default_factory kwargs, similar to regular Pydantic fields:

class ConfigModel(ConfigurationModel):
    # Explicit string default
    field_with_explicit_default = DjangoModelRef(SomeModel, "some_field", default="foobar")

    # Explicit default factory for a list
    field_with_explicit_default_factory: list[str] = DjangoModelRef(
        SomeModel, "some_other_field", default_factory=list
    )

When no explicit default is provided, the default is derived from the referenced Django field:

  1. If the Django field has an explicit default, that default will be used.

  2. If no explicit default is set but the field has null=True set:

    1. The default will be set to None
    2. The field will be optional
  3. If no explicit default is provided and the field is not nullable, but has blank=True and it is a string-type field:

    1. The default will be an empty string
    2. The field will be optional
from django_setup_configuration import BaseConfigurationStep
from django.contrib.auth.models import Group, User

class UserConfigurationStep(BaseConfigurationStep[UserConfigurationModel]):
    """Configure initial user accounts"""

    config_model = UserConfigurationModel
    enable_setting = "user_configuration_enabled"
    namespace = "user_configuration"
    verbose_name = "User Configuration"

    def execute(self, model: UserConfigurationModel) -> None:
        # Idempotent user creation and configuration
        user_qs = User.objects.filter(username=model.username)
        if user_qs.exists():
            user = user_qs.get()
            if not user.check_password(model.password):
                user.set_password(model.password)
                user.save()
        else:
            user = User.objects.create_user(
                username=model.username,
                password=model.password,
                is_superuser=True,
            )

        for group_name in model.add_to_groups:
            group = Group.objects.get(name=group_name)
            group.user_set.add(user)

Create a YAML configuration file with your settings:

user_configuration_enabled: true
user_configuration:
    username: alice
    password: supersecret
    add_to_groups:
        - moderators
        - editors

some_other_step_enabled_flag: true
some_other_step:
    foo: bar
    bar: baz

Note that you can combine settings for multiple steps in a single file. The root level keys are exclusively used for the steps' enable_setting key, and the namespace key which encapsulates the configuration model's attributes.

Register your configuration steps in Django settings:

SETUP_CONFIGURATION_STEPS = [
    "myapp.configuration_steps.user_configuration.UserConfigurationStep",
]

Note that steps will be executed in the order in which they are defined.

python manage.py setup_configuration --yaml-file /path/to/config.yaml

You can also validate that the configuration source can be successfully loaded, without actually running the steps, by adding the validate-only flag:

python manage.py setup_configuration --yaml-file /path/to/config.yaml --validate-only

The command will either return 0 and a success message if the configuration file can be loaded without issues, otherwise it will return a non-zero exit code and print any validation errors. This can be useful e.g. in CI to confirm that your sources are valid without actually running any steps.

from django_setup_configuration.runner import SetupConfigurationRunner

runner = SetupConfigurationRunner(
    steps=["myapp.configuration_steps.user_configuration.UserConfigurationStep"],
    yaml_source="/path/to/config.yaml"
)
# Validate that the configuration settings can be loaded from the source
runner.validate_all_requirements()

# Execute all steps
runner.execute_all()

Note that regardless of the execution method, only enabled steps will be executed. By default, steps are not enabled, so you will have to explicitly set the enable_setting flag to true for each step you intend to run.

def test_execute_step():
    config_model = UserConfigurationModel(
        username="alice",
        password="supersecret",
        add_to_groups=["moderators", "editors"]
    )
    step = UserConfigurationStep()
    step.execute(config_model)

    # Add assertions
from django_setup_configuration.test_utils import build_step_config_from_sources

def test_execute_step():
    config =  {
        'user_configuration_enabled': True,
        'user_configuration': {
            'username': 'alice',
            'password': 'supersecret',
            'groups': ['moderators', 'editors']
        }
    }
    config_model = build_step_config_from_sources(UserConfigurationStep,
        object_source=config,
        # or yaml_source="/path/to/file.yaml"
        )
    step = UserConfigurationStep()
    step.execute(config_model_instance)

    # Add assertions
from django_setup_configuration.test_utils import execute_single_step

def test_execute_step():
    execute_single_step(
        UserConfigurationStep,
        yaml_source="/path/to/test_config.yaml"
    )

    # Add assertions

Note that when using execute_single_step, the enabled flag in your setting source will be ignored and the step will be executed regardless of its presence or value.

  • Idempotency: Design steps that can be run multiple times without unintended side effects.
  • Validation: You can use the full range of Pydantic's validation capabilities.
  • Modularity: Break complex configurations into focused, manageable steps based on your domain in a way that will make sense to your users.

To install and develop the library locally, use:

pip install -e .[tests,coverage,docs,release]

When running management commands via django-admin, make sure to add the root directory to the python path (or use python -m django <command>):

export PYTHONPATH=. DJANGO_SETTINGS_MODULE=testapp.settings
django-admin check
# or other commands like:
# django-admin makemessages -l nl

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