Git Product home page Git Product logo

python-dependency-injector's Introduction

Latest Version

License

Supported Python versions

Supported Python implementations

Downloads

Downloads

Downloads

Wheel

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.
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.

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:

Tutorials

Choose one of the following:

Concept

The framework stands on the PEP20 (The Zen of Python) principle:

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 ๐Ÿ˜Ž
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?
Found a bug?
Want to help?
  • โญ ๏ธ Star the Dependency Injector on the Github
  • ๐Ÿ†• Start a new project with the Dependency Injector
  • ๐Ÿ’ฌ Tell your friend about the Dependency Injector
Want to contribute?
  • ๐Ÿ”€ Fork the project
  • โฌ… ๏ธ Open a pull request to the develop branch

python-dependency-injector's People

Contributors

rmk135 avatar sonthonaxrk avatar withshubh avatar metaperl avatar kinow avatar xotonic avatar rda-dev avatar ebr avatar piperubio avatar kootoopas avatar illia-v avatar jameslafa avatar stummej avatar jeroenrietveld avatar kirill-shershen avatar sirkonst avatar loingo95 avatar rajanjha786 avatar robinsonma avatar jarnorfb avatar thiromi avatar gerschtli avatar vkfisher avatar smirnovskoe avatar supakeen avatar whysage avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.