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