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140 lines
5.2 KiB
ReStructuredText
140 lines
5.2 KiB
ReStructuredText
=================================================================
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Dependency Injector --- Dependency injection framework for Python
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=================================================================
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.. meta::
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:google-site-verification: V1hlKfpgL3AARAElwFcqP4qW1Smsx5bKSRU8O86i20Y
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:keywords: Python,Dependency injection,DI,Inversion of Control,IoC,
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IoC Container,Factory, Singleton, Design Patterns
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:description: Dependency Injector is a dependency injection framework
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for Python. It helps to maintain you application structure.
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It was designed to be unified, developer-friendly
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tool that helps to implement dependency injection design
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pattern in formal, pretty, Pythonic way. Dependency Injector
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provides implementations of such popular design patterns
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like IoC container, Factory and Singleton. Dependency
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Injector providers are implemented as C extension types
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using Cython.
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.. _index:
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.. image:: https://img.shields.io/pypi/v/dependency_injector.svg
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:target: https://pypi.org/project/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.org/project/dependency-injector/
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:alt: License
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.. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg
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:target: https://pypi.org/project/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.org/project/dependency-injector/
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:alt: Supported Python implementations
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.. image:: https://pepy.tech/badge/dependency-injector
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:target: https://pepy.tech/project/dependency-injector
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:alt: Downloads
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.. image:: https://pepy.tech/badge/dependency-injector/month
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:target: https://pepy.tech/project/dependency-injector
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:alt: Downloads
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.. image:: https://pepy.tech/badge/dependency-injector/week
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:target: https://pepy.tech/project/dependency-injector
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:alt: Downloads
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.. image:: https://img.shields.io/pypi/wheel/dependency-injector.svg
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:target: https://pypi.org/project/dependency-injector/
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:alt: Wheel
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.. 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:: http://readthedocs.org/projects/python-dependency-injector/badge/?version=latest
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:target: http://python-dependency-injector.ets-labs.org/
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:alt: Docs Status
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.. image:: https://coveralls.io/repos/github/ets-labs/python-dependency-injector/badge.svg?branch=master
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:target: https://coveralls.io/github/ets-labs/python-dependency-injector?branch=master
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:alt: Coverage Status
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``Dependency Injector`` is a dependency injection framework for Python.
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It helps implementing the dependency injection principle.
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Key features of the ``Dependency Injector``:
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- **Providers**. Provides ``Factory``, ``Singleton``, ``Callable``, ``Coroutine``, ``Object``,
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``List``, ``Configuration``, ``Dependency`` and ``Selector`` providers that help assembling your
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objects. See :ref:`providers`.
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- **Overriding**. Can override any provider by another provider on the fly. This helps in testing
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and configuring dev / stage environment to replace API clients with stubs etc. See
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:ref:`provider-overriding`.
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- **Configuration**. Read configuration from ``yaml`` & ``ini`` files, environment variables
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and dictionaries. See :ref:`configuration-provider`.
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- **Containers**. Provides declarative and dynamic containers. See :ref:`containers`.
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- **Performance**. Written in ``Cython``.
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- **Maturity**. Mature and ready for production.
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.. code-block:: python
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from dependency_injector import containers, providers
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class Container(containers.DeclarativeContainer):
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config = providers.Configuration()
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api_client = providers.Singleton(
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ApiClient,
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api_key=config.api_key,
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timeout=config.timeout.as_int(),
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)
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service = providers.Factory(
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Service,
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api_client=api_client,
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)
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if __name__ == '__main__':
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container = Container()
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container.config.api_key.from_env('API_KEY')
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container.config.timeout.from_env('TIMEOUT')
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service = container.service()
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With the ``Dependency Injector`` you keep **application structure in one place**.
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This place is called **the container**. You use the container to manage all the components of the
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application. All the component dependencies are defined explicitly. This provides the control on
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the application structure. It is **easy to understand and change** it.
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.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/di-map.svg
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:target: https://github.com/ets-labs/python-dependency-injector
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*The container is like a map of your application. You always know what depends on what.*
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Explore the documentation to know more about the ``Dependency Injector``.
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.. _contents:
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Contents
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--------
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.. toctree::
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:maxdepth: 2
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introduction/index
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main/installation
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tutorials/index
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providers/index
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containers/index
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examples/index
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api/index
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main/feedback
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main/changelog
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