python-dependency-injector/README.rst
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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``, ``Dict``, ``Configuration``, ``Resource``, ``Dependency`` and ``Selector`` providers
that help assembling your objects.
See `Providers <https://python-dependency-injector.ets-labs.org/providers/index.html>`_.
- **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 <https://python-dependency-injector.ets-labs.org/providers/overriding.html>`_.
- **Configuration**. Reads configuration from ``yaml`` & ``ini`` files, environment variables
and dictionaries.
See `Configuration provider <https://python-dependency-injector.ets-labs.org/providers/configuration.html>`_.
- **Containers**. Provides declarative and dynamic containers.
See `Containers <https://python-dependency-injector.ets-labs.org/containers/index.html>`_.
- **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 <https://python-dependency-injector.ets-labs.org/providers/resource.html>`_.
- **Wiring**. Injects dependencies into functions and methods. Helps integrating with
other frameworks: Django, Flask, Aiohttp, Sanic, FastAPI, etc.
See `Wiring <https://python-dependency-injector.ets-labs.org/wiring.html>`_.
- **Asynchronous**. Supports asynchronous injections.
See `Asynchronous injections <https://python-dependency-injector.ets-labs.org/providers/async.html>`_.
- **Typing**. Provides typing stubs, ``mypy``-friendly.
See `Typing and mypy <https://python-dependency-injector.ets-labs.org/providers/typing_mypy.html>`_.
- **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 inject, Provide
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,
)
@inject
def main(service: Service = Provide[Container.service]):
...
if __name__ == '__main__':
container = Container()
container.config.api_key.from_env('API_KEY')
container.config.timeout.from_env('TIMEOUT')
container.wire(modules=[sys.modules[__name__]])
main() # <-- dependency is injected automatically
with container.api_client.override(mock.Mock()):
main() # <-- overridden dependency is injected automatically
When you call ``main()`` function the ``Service`` dependency is assembled and injected automatically.
When doing a testing you call the ``container.api_client.override()`` 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 configuring project for the different environments: replace an API client
with a stub on the dev or stage.
With the ``Dependency Injector`` objects assembling is consolidated in the container.
Dependency injections are defined explicitly.
This makes easier to understand and change how application works.
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Visit the docs to know more about the
`Dependency injection and inversion of control in Python <https://python-dependency-injector.ets-labs.org/introduction/di_in_python.html>`_.
Installation
------------
The package is available on the `PyPi`_::
pip install dependency-injector
Documentation
-------------
The documentation is available `here <https://python-dependency-injector.ets-labs.org/>`_.
Examples
--------
Choose one of the following:
- `Application example (single container) <https://python-dependency-injector.ets-labs.org/examples/application-single-container.html>`_
- `Application example (multiple containers) <https://python-dependency-injector.ets-labs.org/examples/application-multiple-containers.html>`_
- `Decoupled packages example (multiple containers) <https://python-dependency-injector.ets-labs.org/examples/decoupled-packages.html>`_
- `Django example <https://python-dependency-injector.ets-labs.org/examples/django.html>`_
- `Flask example <https://python-dependency-injector.ets-labs.org/examples/flask.html>`_
- `Aiohttp example <https://python-dependency-injector.ets-labs.org/examples/aiohttp.html>`_
- `Sanic example <https://python-dependency-injector.ets-labs.org/examples/sanic.html>`_
- `FastAPI example <https://python-dependency-injector.ets-labs.org/examples/fastapi.html>`_
- `FastAPI + Redis example <https://python-dependency-injector.ets-labs.org/examples/fastapi-redis.html>`_
Tutorials
---------
Choose one of the following:
- `Flask web application tutorial <https://python-dependency-injector.ets-labs.org/tutorials/flask.html>`_
- `Aiohttp REST API tutorial <https://python-dependency-injector.ets-labs.org/tutorials/aiohttp.html>`_
- `Asyncio monitoring daemon tutorial <https://python-dependency-injector.ets-labs.org/tutorials/asyncio-daemon.html>`_
- `CLI application tutorial <https://python-dependency-injector.ets-labs.org/tutorials/cli.html>`_
Concept
-------
The framework stands on the `PEP20 (The Zen of Python) <https://www.python.org/dev/peps/pep-0020/>`_ 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 a simplicity.
``Dependency Injector`` 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 😎
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 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 the project grows
Have a question?
- Open a `Github Issue <https://github.com/ets-labs/python-dependency-injector/issues>`_
Found a bug?
- Open a `Github Issue <https://github.com/ets-labs/python-dependency-injector/issues>`_
Want to help?
- |star| Star the ``Dependency Injector`` on the `Github <https://github.com/ets-labs/python-dependency-injector/>`_
- |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/
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