dependency-injector 2.2.2

Python dependency injection framework

Dependency Injector is a Python dependency injection framework. It was designed to be unified, developer-friendly tool that helps to implement dependency injection pattern in formal, pretty, Pythonic way.

Dependency Injector framework key features are:

• Easy, smart, pythonic style.

• Obvious, clear structure.

• Extensibility and flexibility.

• Memory efficiency.

• Thread safety.

• Documentation.

• Semantic versioning.

Status

PyPi
Python versions and implementations
Builds and tests coverage

Installation

Dependency Injector library is available on PyPi:

pip install dependency_injector

Dependency Injection

Dependency injection is a software design pattern that implements Inversion of control for resolving dependencies. Formally, if object A depends on object B, object A must not create or import object B, but provide a way for injecting object B (object B could be injected into object A in several ways: by passing it as __init__ argument, by setting it as attribute’s value or by passing it as method’s argument).

Dependency injection pattern has few strict rules that should be followed:

• Object A (the client) delegates to external code (the dependency injector) the responsibility of providing its dependencies - object B (the service).

• The client doesn’t know how to create the service, it knows only interface of service.

• The service doesn’t know that it is used by the client.

• The dependency injector knows how to create the client.

• The dependency injector knows how to create the service.

• The dependency injector knows that the client depends on the service.

• The dependency injector knows how to inject the service into the client.

• The client knows nothing about the dependency injector.

• The service knows nothing about the dependency injector.

Next two examples demonstrate refactoring of a small piece of code to dependency injection pattern:

"""Car & Engine example."""


class Engine(object):
    """Example engine."""


class Car(object):
    """Example car."""

    def __init__(self):
        """Initializer."""
        self.engine = Engine()  # Engine is a "hardcoded" dependency


if __name__ == '__main__':
    car = Car()  # Application creates Car's instance

Car creates an Engine during its creation. Really? Does it make more sense than creating an Engine separately and then inject it into Car when Car is being created? Looks more realistic, right?

"""Refactored Car & Engine example that demonstrates dependency injection."""


class Engine(object):
    """Example engine."""


class Car(object):
    """Example car."""

    def __init__(self, engine):
        """Initializer."""
        self.engine = engine  # Engine is an "injected" dependency


if __name__ == '__main__':
    engine = Engine()  # Application creates Engine's instance
    car = Car(engine)  # and inject it into the Car's instance

Advantages of dependency injection

Dependency injection pattern provides next advantages:

• Control on application structure.

• Decreased coupling between application components.

• Increased code reusability.

• Increased testability.

• Increased maintainability.

• Reconfiguration of system without rebuilding.

Example of dependency injection

Brief example below demonstrates usage of Dependency Injector for creating several IoC containers for some microservice system:

"""Example of dependency injection in Python."""

import logging
import sqlite3

import boto.s3.connection

import example.main
import example.services

import dependency_injector.containers as containers
import dependency_injector.providers as providers


class Platform(containers.DeclarativeContainer):
    """IoC container of platform service providers."""

    logger = providers.Singleton(logging.Logger, name='example')

    database = providers.Singleton(sqlite3.connect, ':memory:')

    s3 = providers.Singleton(boto.s3.connection.S3Connection,
                             aws_access_key_id='KEY',
                             aws_secret_access_key='SECRET')


class Services(containers.DeclarativeContainer):
    """IoC container of business service providers."""

    users = providers.Factory(example.services.Users,
                              logger=Platform.logger,
                              db=Platform.database)

    auth = providers.Factory(example.services.Auth,
                             logger=Platform.logger,
                             db=Platform.database,
                             token_ttl=3600)

    photos = providers.Factory(example.services.Photos,
                               logger=Platform.logger,
                               db=Platform.database,
                               s3=Platform.s3)


class Application(containers.DeclarativeContainer):
    """IoC container of application component providers."""

    main = providers.Callable(example.main.main,
                              users_service=Services.users,
                              auth_service=Services.auth,
                              photos_service=Services.photos)

Next example demonstrates run of dependency injection example application defined above:

"""Run dependency injection example application.

Instructions for running:

    python run.py 1 secret photo.jpg
"""

import sys
import logging

from containers import Platform, Application


if __name__ == '__main__':
    # Configure platform logger:
    Platform.logger().addHandler(logging.StreamHandler(sys.stdout))

    # Run application:
    Application.main(uid=sys.argv[1],
                     password=sys.argv[2],
                     photo=sys.argv[3])

    # Previous call is an equivalent of next operations:
    #
    # logger = logging.Logger(name='example')
    # database = sqlite3.connect(':memory:')
    # s3 = boto.s3.connection.S3Connection(aws_access_key_id='KEY',
    #                                      aws_secret_access_key='SECRET')
    #
    # example.main.main(uid=sys.argv[1],
    #                   password=sys.argv[2],
    #                   photo=sys.argv[3],
    #                   users_service=example.services.Users(logger=logger,
    #                                                        db=database),
    #                   auth_service=example.services.Auth(logger=logger,
    #                                                      db=database,
    #                                                      token_ttl=3600),
    #                   photos_service=example.services.Photos(logger=logger,
    #                                                          db=database,
    #                                                          s3=s3))
    #
    # Output:
    #
    # User 1 has been found in database
    # User 1 has been successfully authenticated
    # Photo photo.jpg has been successfully uploaded by user 1

Alternative definition styles of providers

Dependecy Injector supports few other styles of dependency injections definition.

IoC containers from previous example could look like these:

class Platform(containers.DeclarativeContainer):
    """IoC container of platform service providers."""

    logger = providers.Singleton(logging.Logger) \
        .add_kwargs(name='example')

    database = providers.Singleton(sqlite3.connect) \
        .add_args(':memory:')

    s3 = providers.Singleton(boto.s3.connection.S3Connection) \
        .add_kwargs(aws_access_key_id='KEY',
                    aws_secret_access_key='SECRET')

or like this these:

class Platform(containers.DeclarativeContainer):
    """IoC container of platform service providers."""

    logger = providers.Singleton(logging.Logger)
    logger.add_kwargs(name='example')

    database = providers.Singleton(sqlite3.connect)
    database.add_args(':memory:')

    s3 = providers.Singleton(boto.s3.connection.S3Connection)
    s3.add_kwargs(aws_access_key_id='KEY',
                  aws_secret_access_key='SECRET')

You can get more Dependency Injector examples in /examples directory on GitHub:

https://github.com/ets-labs/python-dependency-injector

Documentation

Dependency Injector documentation is hosted on ReadTheDocs:

• User’s guide

• API docs

Feedback

Feel free to post questions, bugs, feature requests, proposals etc. on Dependency Injector GitHub Issues:

https://github.com/ets-labs/python-dependency-injector/issues

Your feedback is quite important!