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Dependency Injector - Dependency injection microframework for Python
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*Dependency Injector* is a dependency injection microframework for Python. 
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
------

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| *PyPi*                                | .. image:: https://img.shields.io/pypi/v/dependency_injector.svg                                                   |
|                                       |    :target: https://pypi.python.org/pypi/dependency_injector/                                                      |
|                                       |    :alt: Latest Version                                                                                            |
|                                       | .. image:: https://img.shields.io/pypi/l/dependency_injector.svg                                                   |
|                                       |    :target: https://pypi.python.org/pypi/dependency_injector/                                                      |
|                                       |    :alt: License                                                                                                   |
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| *Python versions and implementations* | .. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg                                          |
|                                       |    :target: https://pypi.python.org/pypi/dependency_injector/                                                      |
|                                       |    :alt: Supported Python versions                                                                                 |
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|                                       |    :target: https://pypi.python.org/pypi/dependency_injector/                                                      |
|                                       |    :alt: Supported Python implementations                                                                          |
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|                                       |    :alt: Build Status                                                                                              |
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|                                       |    :alt: Github watchers                                                                                           |
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|                                       |    :alt: Github forks                                                                                              |
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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** 
directly. Instead of this object **A** must provide a way for *injecting* 
object **B**. The responsibilities of objects creation and dependencies 
injection are delegated to external code - the *dependency injector*. 

Popular terminology of dependency injection pattern:

+ Object **A**, that is dependant on object **B**, is often called - 
  the *client*.
+ Object **B**, that is a dependency, 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 of how *service* can be injected into the *client*: 

+ by passing it as ``__init__`` argument (constructor / initializer injection)
+ by setting it as attribute's value (attribute injection)
+ by passing it as method's argument (method injection)

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 
  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*.

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 example application:

.. code-block:: python

    """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.UsersService,
                                  logger=Platform.logger,
                                  db=Platform.database)

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

        photos = providers.Factory(example.services.PhotosService,
                                   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 example application defined above:

.. code-block:: python

    """Run example application."""

    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.UsersService(logger=logger,
        #                                                 db=database),
        #     auth_service=example.services.AuthService(logger=logger,
        #                                               db=database,
        #                                               token_ttl=3600),
        #     photos_service=example.services.PhotosService(logger=logger,
        #                                                   db=database,
        #                                                   s3=s3))
   
Alternative definition styles of providers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

*Dependecy Injector* supports few other styles of dependency injections 
definition.

IoC containers from previous example could look like these:

.. code-block:: python

    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:

.. code-block:: python

    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

Installation
------------

*Dependency Injector* library is available on `PyPi`_::

    pip install dependency_injector

Documentation
-------------

*Dependency Injector* documentation is hosted on ReadTheDocs:

- `User's guide`_ 
- `API docs`_

Feedback & Support
------------------

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!


.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
.. _PyPi: https://pypi.python.org/pypi/dependency_injector
.. _User's guide: http://python-dependency-injector.ets-labs.org/en/stable/
.. _API docs: http://python-dependency-injector.ets-labs.org/en/stable/api/