Skip to main content

Dependency injection microframework for Python

Project description

https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/logo.svg

Latest Version License Supported Python versions Supported Python implementations Downloads Downloads Downloads Wheel Build Status Docs Status Coverage Status

What is Dependency Injector?

Dependency Injector is a dependency injection framework for Python.

It helps implementing the dependency injection principle.

Key features of the Dependency Injector:

  • Providers. Provides Factory, Singleton, Callable, Coroutine, Object, List, Configuration, 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. Read configuration from yaml & ini files, environment variables and dictionaries. See Configuration provider.

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

  • Performance. Fast. Written in Cython.

  • Typing. Provides typing stubs, mypy-friendly. See Typing and mypy.

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

from dependency_injector import containers, providers


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,
    )


if __name__ == '__main__':
    container = Container()
    container.config.api_key.from_env('API_KEY')
    container.config.timeout.from_env('TIMEOUT')

    service = container.service()

With the Dependency Injector you keep application structure in one place. This place is called the container. You use the container to manage all the components of the application. All the component dependencies are defined explicitly. This provides the control on the application structure. It is easy to understand and change it.

https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/di-map.svg

The container is like a map of your application. You always know what depends on what.

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 on the Read The Docs

Examples

Choose one of the following:

Tutorials

Choose one of the following:

Concept

Dependency Injector stands on two principles:

  • Explicit is better than implicit (PEP20).

  • Do no magic to your code.

How is it different from the other frameworks?

  • No autowiring. The framework does NOT do any autowiring / autoresolving of the dependencies. You need to specify everything explicitly. Because “Explicit is better than implicit” (PEP20).

  • Does not pollute your code. Your application does NOT know and does NOT depend on the framework. No @inject decorators, annotations, patching or any other magic tricks.

Dependency Injector makes a simple contract with you:

  • You tell the framework how to assemble your objects

  • The framework does it for you

The power of the Dependency Injector is in its simplicity and straightforwardness. It is a simple tool for the powerful concept.

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

  • you have no problems when you need to understand how it works or change it 😎

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 get it from the container

Why do I need a framework for this?
  • you need the framework for this to not create it by your own

  • this framework gives you the container and the providers

  • the container is like a dictionary with the batteries 🔋

  • the providers manage the lifetime of your components, you will need factories, singletons, smart config object etc

What price do I pay and what do I get?
  • you need to explicitly specify the dependencies in the container

  • it will be extra work in the beginning

  • it will payoff when project grows or in two weeks 😊 (when you forget what project was about)

What features does the framework have?
  • building objects graph

  • smart configuration object

  • providers: factory, singleton, thread locals registers, etc

  • positional and keyword context injections

  • overriding of the objects in any part of the graph

What features the framework does NOT have?
  • autowiring / autoresolving of the dependencies

  • the annotations and @inject-like decorators

Have a question?
Found a bug?
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


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dependency-injector-4.0.0a1.tar.gz (473.9 kB view hashes)

Uploaded Source

Built Distributions

dependency_injector-4.0.0a1-pp36-pypy36_pp73-win32.whl (217.6 kB view hashes)

Uploaded PyPy Windows x86

dependency_injector-4.0.0a1-pp36-pypy36_pp73-manylinux2010_x86_64.whl (335.0 kB view hashes)

Uploaded PyPy manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-pp36-pypy36_pp73-macosx_10_9_x86_64.whl (307.1 kB view hashes)

Uploaded PyPy macOS 10.9+ x86-64

dependency_injector-4.0.0a1-pp27-pypy_73-manylinux2010_x86_64.whl (333.6 kB view hashes)

Uploaded PyPy manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-pp27-pypy_73-macosx_10_9_x86_64.whl (309.2 kB view hashes)

Uploaded PyPy macOS 10.9+ x86-64

dependency_injector-4.0.0a1-cp38-cp38-win_amd64.whl (293.8 kB view hashes)

Uploaded CPython 3.8 Windows x86-64

dependency_injector-4.0.0a1-cp38-cp38-win32.whl (234.6 kB view hashes)

Uploaded CPython 3.8 Windows x86

dependency_injector-4.0.0a1-cp38-cp38-manylinux2010_x86_64.whl (2.5 MB view hashes)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp38-cp38-manylinux2010_i686.whl (2.4 MB view hashes)

Uploaded CPython 3.8 manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp38-cp38-macosx_10_9_x86_64.whl (441.9 kB view hashes)

Uploaded CPython 3.8 macOS 10.9+ x86-64

dependency_injector-4.0.0a1-cp37-cp37m-win_amd64.whl (274.5 kB view hashes)

Uploaded CPython 3.7m Windows x86-64

dependency_injector-4.0.0a1-cp37-cp37m-win32.whl (223.8 kB view hashes)

Uploaded CPython 3.7m Windows x86

dependency_injector-4.0.0a1-cp37-cp37m-manylinux2010_x86_64.whl (2.0 MB view hashes)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp37-cp37m-manylinux2010_i686.whl (1.8 MB view hashes)

Uploaded CPython 3.7m manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp37-cp37m-macosx_10_9_x86_64.whl (425.4 kB view hashes)

Uploaded CPython 3.7m macOS 10.9+ x86-64

dependency_injector-4.0.0a1-cp36-cp36m-win_amd64.whl (273.6 kB view hashes)

Uploaded CPython 3.6m Windows x86-64

dependency_injector-4.0.0a1-cp36-cp36m-win32.whl (224.0 kB view hashes)

Uploaded CPython 3.6m Windows x86

dependency_injector-4.0.0a1-cp36-cp36m-manylinux2010_x86_64.whl (2.0 MB view hashes)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp36-cp36m-manylinux2010_i686.whl (1.9 MB view hashes)

Uploaded CPython 3.6m manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp36-cp36m-macosx_10_9_x86_64.whl (460.0 kB view hashes)

Uploaded CPython 3.6m macOS 10.9+ x86-64

dependency_injector-4.0.0a1-cp35-cp35m-win_amd64.whl (258.1 kB view hashes)

Uploaded CPython 3.5m Windows x86-64

dependency_injector-4.0.0a1-cp35-cp35m-win32.whl (211.0 kB view hashes)

Uploaded CPython 3.5m Windows x86

dependency_injector-4.0.0a1-cp35-cp35m-manylinux2010_x86_64.whl (1.9 MB view hashes)

Uploaded CPython 3.5m manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp35-cp35m-manylinux2010_i686.whl (1.8 MB view hashes)

Uploaded CPython 3.5m manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp35-cp35m-macosx_10_9_x86_64.whl (421.3 kB view hashes)

Uploaded CPython 3.5m macOS 10.9+ x86-64

dependency_injector-4.0.0a1-cp27-cp27mu-manylinux2010_x86_64.whl (1.6 MB view hashes)

Uploaded CPython 2.7mu manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp27-cp27mu-manylinux2010_i686.whl (1.5 MB view hashes)

Uploaded CPython 2.7mu manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp27-cp27m-manylinux2010_x86_64.whl (1.6 MB view hashes)

Uploaded CPython 2.7m manylinux: glibc 2.12+ x86-64

dependency_injector-4.0.0a1-cp27-cp27m-manylinux2010_i686.whl (1.5 MB view hashes)

Uploaded CPython 2.7m manylinux: glibc 2.12+ i686

dependency_injector-4.0.0a1-cp27-cp27m-macosx_10_9_x86_64.whl (411.7 kB view hashes)

Uploaded CPython 2.7m macOS 10.9+ x86-64

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page