python-dependency-injector/docs/index.rst

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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:
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:alt: Supported Python versions
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:alt: Supported Python implementations
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``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. See :ref:`provider-typing`.
- **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