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What is

Dependency Injector

?

Dependency Injector

It helps implementing the dependency injection principle.

Key features of the

Dependency Injector

• Providers. Provides

  Factory

  ,

  Singleton

  ,

  Callable

  ,

  Coroutine

  ,

  Object

  ,

  List

  ,

  Dict

  ,

  Configuration

  ,

  Resource

  ,

  Dependency

  and

  Selector

  providers that help assembling your objects. See

  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

  Provider overriding 

  _.
• Configuration. Reads configuration from

  yaml

  &

  ini

  files,

  pydantic

  settings, environment variables, and dictionaries. See

  Configuration provider 

  _.
• Containers. Provides declarative and dynamic containers. See

  Containers 

  _.
• Resources. Helps with initialization and configuring of logging, event loop, thread or process pool, etc. Can be used for per-function execution scope in tandem with wiring. See

  Resource provider 

  _.
• Wiring. Injects dependencies into functions and methods. Helps integrating with other frameworks: Django, Flask, Aiohttp, Sanic, FastAPI, etc. See

  Wiring 

  _.
• Asynchronous. Supports asynchronous injections. See

  Asynchronous injections 

  _.
• Typing. Provides typing stubs,

  mypy

  -friendly. See

  Typing and mypy 

  _.
• Performance. Fast. Written in

  Cython

  .
• Maturity. Mature and production-ready. Well-tested, documented and supported.

.. code-block:: python

from dependencyinjector import containers, providers from dependencyinjector.wiring import inject, Provide

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,
   )

@inject def main(service: Service = Provide[Container.service]): ...

if name == 'main': container = Container() container.config.apikey.fromenv('APIKEY') container.config.timeout.fromenv('TIMEOUT') container.wire(modules=[sys.modules[name]])

   main()  # 
When you call 
main()
 function the 
Service
 dependency is assembled and injected automatically.

When doing a testing you call the 
container.api_client.override()
 to replace the real API
client with a mock. When you call 
main()
 the mock is injected.

You can override any provider with another provider.

It also helps you in configuring project for the different environments: replace an API client
with a stub on the dev or stage.

With the 
Dependency Injector
 objects assembling is consolidated in the container.
Dependency injections are defined explicitly.
This makes easier to understand and change how application works.

.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/di-readme.svg
   :target: https://github.com/ets-labs/python-dependency-injector

Visit the docs to know more about the
Dependency injection and inversion of control in Python 
_.

Installation

The package is available on the 
PyPi
_::
pip install dependency-injector

Documentation

The documentation is available 
here 
_.

Examples

Choose one of the following:

• Application example (single container) 

  _

• Application example (multiple containers) 

  _

• Decoupled packages example (multiple containers) 

  _

• Boto3 example 

  _

• Django example 

  _

• Flask example 

  _

• Aiohttp example 

  _

• Sanic example 

  _

• FastAPI example 

  _

• FastAPI + Redis example 

  _

• FastAPI + SQLAlchemy example 

  _

Tutorials

Choose one of the following:

• Flask web application tutorial 

  _

• Aiohttp REST API tutorial 

  _

• Asyncio monitoring daemon tutorial 

  _

• CLI application tutorial 

  _

Concept

The framework stands on the

PEP20 (The Zen of Python) 

.. code-block:: bash

Explicit is better than implicit

You need to specify how to assemble and where to inject the dependencies explicitly.

The power of the framework is in a simplicity.

Dependency Injector

Frequently asked questions

What is the dependency injection? - dependency injection is a principle that decreases coupling and increases cohesion

Why should I do the dependency injection? - your code becomes more flexible, testable and clear 😎

How do I start doing the dependency injection? - you start writing the code following the dependency injection principle - you register all of your application components and their dependencies in the container - when you need a component, you specify where to inject it or get it from the container

What price do I pay and what do I get? - you need to explicitly specify the dependencies - it will be extra work in the beginning - it will payoff as the project grows

Have a question? - Open a

Github Issue 

Found a bug? - Open a

Github Issue 

Want to help? - |star| Star the

Dependency Injector

Github 

Dependency Injector

Dependency Injector

Want to contribute? - |fork| Fork the project - |pull| Open a pull request to the

develop

.. _PyPi: https://pypi.org/project/dependency-injector/

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