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README.rst
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README.rst
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@ -32,97 +32,10 @@ What is ``Dependency Injector``?
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``Dependency Injector`` is a Python dependency injection framework for Python.
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It was designed to be a unified and developer-friendly tool that helps
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implement a dependency injection design pattern in a formal, pretty, and
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Pythonic way.
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The key features of the *Dependency Injector* framework are:
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+ Easy, smart, and pythonic style.
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+ Obvious and 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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+ Documented.
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+ Semantically versioned.
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*Dependency Injector* containers and providers are implemented as C extension
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types using Cython.
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Installation
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------------
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The *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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Documentation is on `Read The Docs <http://python-dependency-injector.ets-labs.org/>`_
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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`_ to resolve 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 to *inject*
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object **B**. The responsibilities of objects creation and dependency
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injection are delegated to external code - the *dependency injector*.
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Popular terminology of the dependency injection pattern:
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+ Object **A**, which depends on object **B**, is often called -
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the *client*.
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+ Object **B**, which is depended on, 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 to inject a *service* into a *client*:
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+ by passing it as an ``__init__`` argument (constructor / initializer
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injection)
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+ by setting it as an attribute's value (attribute injection)
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+ by passing it as a method's argument (method injection)
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The 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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the 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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The dependency injection pattern provides the following advantages:
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+ Control of application structure.
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+ Decreased coupling of 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 a system without rebuilding.
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Dependency Injector in action
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-----------------------------
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The brief example below is a simplified version of inversion of control
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containers from a real-life application. The example demonstrates the usage
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of *Dependency Injector* inversion of control container and providers for
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specifying application components and their dependencies on each other in one
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module. Besides other previously mentioned advantages, it shows a great
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opportunity to control and manage application's structure in one place.
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Example:
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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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@ -132,11 +45,10 @@ opportunity to control and manage application's structure in one place.
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from example import services, main
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class IocContainer(containers.DeclarativeContainer):
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"""Application IoC container."""
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class Application(containers.DeclarativeContainer):
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"""Application container."""
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config = providers.Configuration('config')
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logger = providers.Singleton(logging.Logger, name='example')
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# Gateways
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@ -153,33 +65,22 @@ opportunity to control and manage application's structure in one place.
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users_service = providers.Factory(
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services.UsersService,
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db=database_client,
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logger=logger,
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)
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auth_service = providers.Factory(
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services.AuthService,
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token_ttl=config.auth.token_ttl,
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db=database_client,
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logger=logger,
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)
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photos_service = providers.Factory(
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services.PhotosService,
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db=database_client,
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s3=s3_client,
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logger=logger,
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)
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# Misc
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main = providers.Callable(
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main.main,
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users_service=users_service,
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auth_service=auth_service,
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photos_service=photos_service,
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)
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The next example demonstrates a run of the example application defined above:
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Run the application:
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.. code-block:: python
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@ -188,12 +89,12 @@ The next example demonstrates a run of the example application defined above:
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import sys
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import logging
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from container import IocContainer
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from container import Application
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if __name__ == '__main__':
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# Configure container:
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container = IocContainer(
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container = Application(
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config={
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'database': {
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'dsn': ':memory:',
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@ -218,6 +119,19 @@ on our 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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The *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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Documentation is on `Read The Docs <http://python-dependency-injector.ets-labs.org/>`_
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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.org/project/dependency-injector/
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