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288 lines
14 KiB
ReStructuredText
288 lines
14 KiB
ReStructuredText
====================================================================
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Dependency Injector - Dependency injection microframework for Python
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====================================================================
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*Dependency Injector* is a dependency injection microframework for Python.
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It was designed to be unified, developer-friendly tool that helps to implement
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dependency injection pattern in formal, pretty, Pythonic way.
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*Dependency Injector* framework key features are:
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+ Easy, smart, pythonic style.
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+ Obvious, clear structure.
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+ Extensibility and flexibility.
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+ High performance.
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+ Memory efficiency.
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+ Thread safety.
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+ Documentation.
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+ Semantic versioning.
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*Dependency Injector* providers are implemented as C extension types using
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Cython.
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Status
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------
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+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
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| *PyPi* | .. image:: https://img.shields.io/pypi/v/dependency_injector.svg |
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| | :target: https://pypi.python.org/pypi/dependency_injector/ |
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| | :alt: Latest Version |
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| | .. image:: https://img.shields.io/pypi/l/dependency_injector.svg |
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| | :target: https://pypi.python.org/pypi/dependency_injector/ |
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| | :alt: License |
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+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
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| *Python versions and implementations* | .. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg |
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| | :target: https://pypi.python.org/pypi/dependency_injector/ |
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| | :alt: Supported Python versions |
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| | .. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg |
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| | :target: https://pypi.python.org/pypi/dependency_injector/ |
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| | :alt: Supported Python implementations |
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+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
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| *Builds and tests coverage* | .. image:: https://travis-ci.org/ets-labs/python-dependency-injector.svg?branch=master |
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| | :target: https://travis-ci.org/ets-labs/python-dependency-injector |
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| | :alt: Build Status |
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| | .. image:: https://coveralls.io/repos/ets-labs/python-dependency-injector/badge.svg |
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| | :target: https://coveralls.io/r/ets-labs/python-dependency-injector |
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| | :alt: Coverage Status |
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+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
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| *Github* | .. image:: https://img.shields.io/github/watchers/ets-labs/python-dependency-injector.svg?style=social&label=Watch |
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| | :target: https://github.com/ets-labs/python-dependency-injector |
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| | :alt: Github watchers |
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| | .. image:: https://img.shields.io/github/stars/ets-labs/python-dependency-injector.svg?style=social&label=Star |
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| | :target: https://github.com/ets-labs/python-dependency-injector |
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| | :alt: Github stargazers |
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| | .. image:: https://img.shields.io/github/forks/ets-labs/python-dependency-injector.svg?style=social&label=Fork |
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| | :target: https://github.com/ets-labs/python-dependency-injector |
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| | :alt: Github forks |
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+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
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Dependency injection
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--------------------
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`Dependency injection`_ is a software design pattern that implements
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`Inversion of control`_ for resolving dependencies. Formally, if object **A**
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depends on object **B**, object **A** must not create or import object **B**
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directly. Instead of this object **A** must provide a way for *injecting*
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object **B**. The responsibilities of objects creation and dependencies
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injection are delegated to external code - the *dependency injector*.
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Popular terminology of dependency injection pattern:
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+ Object **A**, that is dependant on object **B**, is often called -
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the *client*.
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+ Object **B**, that is a dependency, is often called - the *service*.
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+ External code that is responsible for creation of objects and injection
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of dependencies is often called - the *dependency injector*.
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There are several ways of how *service* can be injected into the *client*:
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+ by passing it as ``__init__`` argument (constructor / initializer injection)
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+ by setting it as attribute's value (attribute injection)
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+ by passing it as method's argument (method injection)
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Dependency injection pattern has few strict rules that should be followed:
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+ The *client* delegates to the *dependency injector* the responsibility
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of injecting its dependencies - the *service(s)*.
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+ The *client* doesn't know how to create the *service*, it knows only
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interface of the *service*. The *service* doesn't know that it is used by
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the *client*.
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+ The *dependency injector* knows how to create the *client* and
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the *service*, it also knows that the *client* depends on the *service*,
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and knows how to inject the *service* into the *client*.
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+ The *client* and the *service* know nothing about the *dependency injector*.
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Dependency injection pattern provides the following advantages:
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+ Control on application structure.
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+ Decreased coupling between application components.
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+ Increased code reusability.
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+ Increased testability.
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+ Increased maintainability.
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+ Reconfiguration of system without rebuilding.
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Example of dependency injection
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-------------------------------
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Brief example below demonstrates usage of *Dependency Injector* for creating
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several IoC containers for some example application:
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.. code-block:: python
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"""Example of dependency injection in Python."""
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import logging
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import sqlite3
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import boto.s3.connection
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import example.main
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import example.services
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import dependency_injector.containers as containers
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import dependency_injector.providers as providers
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class Platform(containers.DeclarativeContainer):
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"""IoC container of platform service providers."""
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configuration = providers.Configuration('config')
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logger = providers.Singleton(logging.Logger, name='example')
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database = providers.Singleton(sqlite3.connect, configuration.database.dsn)
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s3 = providers.Singleton(boto.s3.connection.S3Connection,
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configuration.aws.access_key_id,
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configuration.aws.secret_access_key)
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class Services(containers.DeclarativeContainer):
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"""IoC container of business service providers."""
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users = providers.Factory(example.services.UsersService,
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logger=Platform.logger,
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db=Platform.database)
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auth = providers.Factory(example.services.AuthService,
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logger=Platform.logger,
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db=Platform.database,
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token_ttl=Platform.configuration.auth.token_ttl)
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photos = providers.Factory(example.services.PhotosService,
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logger=Platform.logger,
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db=Platform.database,
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s3=Platform.s3)
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class Application(containers.DeclarativeContainer):
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"""IoC container of application component providers."""
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main = providers.Callable(example.main.main,
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users_service=Services.users,
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auth_service=Services.auth,
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photos_service=Services.photos)
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Next example demonstrates run of example application defined above:
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.. code-block:: python
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"""Run example application."""
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import sys
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import logging
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from containers import Platform, Application
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if __name__ == '__main__':
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# Configure platform:
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Platform.configuration.update({'database': {'dsn': ':memory:'},
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'aws': {'access_key_id': 'KEY',
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'secret_access_key': 'SECRET'},
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'auth': {'token_ttl': 3600}})
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Platform.logger().addHandler(logging.StreamHandler(sys.stdout))
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# Run application:
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Application.main(uid=sys.argv[1],
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password=sys.argv[2],
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photo=sys.argv[3])
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# Previous call is an equivalent of next operations:
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#
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# logger = logging.Logger(name='example')
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# database = sqlite3.connect(':memory:')
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# s3 = boto.s3.connection.S3Connection(aws_access_key_id='KEY',
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# aws_secret_access_key='SECRET')
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#
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# example.main.main(
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# uid=sys.argv[1],
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# password=sys.argv[2],
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# photo=sys.argv[3],
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# users_service=example.services.UsersService(logger=logger,
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# db=database),
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# auth_service=example.services.AuthService(logger=logger,
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# db=database,
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# token_ttl=3600),
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# photos_service=example.services.PhotosService(logger=logger,
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# db=database,
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# s3=s3))
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Alternative definition styles of providers
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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*Dependecy Injector* supports few other styles of dependency injections
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definition.
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IoC containers from previous example could look like these:
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.. code-block:: python
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class Platform(containers.DeclarativeContainer):
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"""IoC container of platform service providers."""
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logger = providers.Singleton(logging.Logger) \
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.add_kwargs(name='example')
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database = providers.Singleton(sqlite3.connect) \
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.add_args(':memory:')
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s3 = providers.Singleton(boto.s3.connection.S3Connection) \
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.add_kwargs(aws_access_key_id='KEY',
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aws_secret_access_key='SECRET')
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or like this these:
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.. code-block:: python
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class Platform(containers.DeclarativeContainer):
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"""IoC container of platform service providers."""
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logger = providers.Singleton(logging.Logger)
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logger.add_kwargs(name='example')
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database = providers.Singleton(sqlite3.connect)
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database.add_args(':memory:')
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s3 = providers.Singleton(boto.s3.connection.S3Connection)
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s3.add_kwargs(aws_access_key_id='KEY',
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aws_secret_access_key='SECRET')
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You can get more *Dependency Injector* examples in ``/examples`` directory on
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GitHub:
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https://github.com/ets-labs/python-dependency-injector
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Installation
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------------
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*Dependency Injector* library is available on `PyPi`_::
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pip install dependency_injector
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Documentation
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-------------
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*Dependency Injector* documentation is hosted on ReadTheDocs:
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- `User's guide`_
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- `API docs`_
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Feedback & Support
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------------------
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Feel free to post questions, bugs, feature requests, proposals etc. on
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*Dependency Injector* GitHub Issues:
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https://github.com/ets-labs/python-dependency-injector/issues
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Your feedback is quite important!
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.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
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.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
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.. _PyPi: https://pypi.python.org/pypi/dependency_injector
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.. _User's guide: http://python-dependency-injector.ets-labs.org/en/stable/
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.. _API docs: http://python-dependency-injector.ets-labs.org/en/stable/api/
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