.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/logo.svg :target: https://github.com/ets-labs/python-dependency-injector | .. 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://img.shields.io/github/actions/workflow/status/ets-labs/python-dependency-injector/tests-and-linters.yml?branch=master :target: https://github.com/ets-labs/python-dependency-injector/actions :alt: Build 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 What is ``Dependency Injector``? ================================ ``Dependency Injector`` is a dependency injection framework for Python. It helps implement 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 assemble 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``, and ``json`` files, ``pydantic`` settings, environment variables, and dictionaries. See `Configuration provider `_. - **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 `_. - **Containers**. Provides declarative and dynamic containers. See `Containers `_. - **Wiring**. Injects dependencies into functions and methods. Helps integrate 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 dependency_injector import containers, providers from dependency_injector.wiring import Provide, inject class Container(containers.DeclarativeContainer): config = providers.Configuration() api_client = providers.Singleton( ApiClient, api_key=config.api_key, timeout=config.timeout, ) service = providers.Factory( Service, api_client=api_client, ) @inject def main(service: Service = Provide[Container.service]) -> None: ... if __name__ == "__main__": container = Container() container.config.api_key.from_env("API_KEY", required=True) container.config.timeout.from_env("TIMEOUT", as_=int, default=5) container.wire(modules=[__name__]) main() # <-- dependency is injected automatically with container.api_client.override(mock.Mock()): main() # <-- overridden dependency is injected automatically When you call the ``main()`` function the ``Service`` dependency is assembled and injected automatically. When you do testing, you call the ``container.api_client.override()`` method 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 a re-configuring project for different environments: replace an API client with a stub on the dev or stage. With the ``Dependency Injector``, object assembling is consolidated in a container. Dependency injections are defined explicitly. This makes it easier to understand and change how an 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) `_ principle: .. 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 its simplicity. ``Dependency Injector`` is a simple tool for the powerful concept. Frequently asked questions -------------------------- What is 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 applying 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 project grows Have a question? - Open a `Github Issue `_ Found a bug? - Open a `Github Issue `_ Want to help? - |star| Star the ``Dependency Injector`` on the `Github `_ - |new| Start a new project with the ``Dependency Injector`` - |tell| Tell your friend about the ``Dependency Injector`` Want to contribute? - |fork| Fork the project - |pull| Open a pull request to the ``develop`` branch .. _PyPi: https://pypi.org/project/dependency-injector/ .. |star| unicode:: U+2B50 U+FE0F .. star sign1 .. |new| unicode:: U+1F195 .. new sign .. |tell| unicode:: U+1F4AC .. tell sign .. |fork| unicode:: U+1F500 .. fork sign .. |pull| unicode:: U+2B05 U+FE0F .. pull sign