python-dependency-injector/README.rst
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What is ``Dependency Injector``?
================================
``Dependency Injector`` is a Python dependency injection framework for Python.
It was designed to be a unified and developer-friendly tool that helps
implement a dependency injection design pattern in a formal, pretty, and
Pythonic way.
The key features of the *Dependency Injector* framework are:
+ Easy, smart, and pythonic style.
+ Obvious and clear structure.
+ Extensibility and flexibility.
+ High performance.
+ Memory efficiency.
+ Thread safety.
+ Documented.
+ Semantically versioned.
*Dependency Injector* containers and providers are implemented as C extension
types using Cython.
Installation
------------
The *Dependency Injector* library is available on `PyPi`_::
pip install dependency-injector
Documentation
-------------
Documentation is on `Read The Docs <http://python-dependency-injector.ets-labs.org/>`_
Dependency injection
--------------------
`Dependency injection`_ is a software design pattern that implements
`Inversion of control`_ to resolve dependencies. Formally, if object **A**
depends on object **B**, object **A** must not create or import object **B**
directly. Instead of this object **A** must provide a way to *inject*
object **B**. The responsibilities of objects creation and dependency
injection are delegated to external code - the *dependency injector*.
Popular terminology of the dependency injection pattern:
+ Object **A**, which depends on object **B**, is often called -
the *client*.
+ Object **B**, which is depended on, is often called - the *service*.
+ External code that is responsible for creation of objects and injection
of dependencies is often called - the *dependency injector*.
There are several ways to inject a *service* into a *client*:
+ by passing it as an ``__init__`` argument (constructor / initializer
injection)
+ by setting it as an attribute's value (attribute injection)
+ by passing it as a method's argument (method injection)
The dependency injection pattern has few strict rules that should be followed:
+ The *client* delegates to the *dependency injector* the responsibility
of injecting its dependencies - the *service(s)*.
+ The *client* doesn't know how to create the *service*, it knows only
the interface of the *service*. The *service* doesn't know that it is used by
the *client*.
+ The *dependency injector* knows how to create the *client* and
the *service*. It also knows that the *client* depends on the *service*,
and knows how to inject the *service* into the *client*.
+ The *client* and the *service* know nothing about the *dependency injector*.
The dependency injection pattern provides the following advantages:
+ Control of application structure.
+ Decreased coupling of application components.
+ Increased code reusability.
+ Increased testability.
+ Increased maintainability.
+ Reconfiguration of a system without rebuilding.
Dependency Injector in action
-----------------------------
The brief example below is a simplified version of inversion of control
containers from a real-life application. The example demonstrates the usage
of *Dependency Injector* inversion of control container and providers for
specifying application components and their dependencies on each other in one
module. Besides other previously mentioned advantages, it shows a great
opportunity to control and manage application's structure in one place.
.. code-block:: python
"""Example of dependency injection in Python."""
import logging
import sqlite3
import boto3
from dependency_injector import containers, providers
from example import services, main
class IocContainer(containers.DeclarativeContainer):
"""Application IoC container."""
config = providers.Configuration('config')
logger = providers.Singleton(logging.Logger, name='example')
# Gateways
database_client = providers.Singleton(sqlite3.connect, config.database.dsn)
s3_client = providers.Singleton(
boto3.client, 's3',
aws_access_key_id=config.aws.access_key_id,
aws_secret_access_key=config.aws.secret_access_key,
)
# Services
users_service = providers.Factory(
services.UsersService,
db=database_client,
logger=logger,
)
auth_service = providers.Factory(
services.AuthService,
token_ttl=config.auth.token_ttl,
db=database_client,
logger=logger,
)
photos_service = providers.Factory(
services.PhotosService,
db=database_client,
s3=s3_client,
logger=logger,
)
# Misc
main = providers.Callable(
main.main,
users_service=users_service,
auth_service=auth_service,
photos_service=photos_service,
)
The next example demonstrates a run of the example application defined above:
.. code-block:: python
"""Run example of dependency injection in Python."""
import sys
import logging
from container import IocContainer
if __name__ == '__main__':
# Configure container:
container = IocContainer(
config={
'database': {
'dsn': ':memory:',
},
'aws': {
'access_key_id': 'KEY',
'secret_access_key': 'SECRET',
},
'auth': {
'token_ttl': 3600,
},
}
)
container.logger().addHandler(logging.StreamHandler(sys.stdout))
# Run application:
container.main(*sys.argv[1:])
You can find more *Dependency Injector* examples in the ``/examples`` directory
on our GitHub:
https://github.com/ets-labs/python-dependency-injector
.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
.. _PyPi: https://pypi.org/project/dependency-injector/
.. _User's guide: http://python-dependency-injector.ets-labs.org/
.. _API docs: http://python-dependency-injector.ets-labs.org/api/