Dependency injection framework for Python
Project description
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 😎
- 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 the Dependency Injector on the Github
🆕 Start a new project with the Dependency Injector
💬 Tell your friend about the Dependency Injector
- Want to contribute?
🔀 Fork the project
⬅️ Open a pull request to the develop branch
Project details
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