pozalabs-dependeny-injector 4.42.0

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.

pip install dependency-injector

Explicit is better than implicit