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``, ``Configuration``, ``Dependency`` and ``Selector`` providers that help assembling your
  objects. See `Providers <http://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 <http://python-dependency-injector.ets-labs.org/providers/overriding.html>`_.
- **Configuration**. Read configuration from ``yaml`` & ``ini`` files, environment variables
  and dictionaries.
  See `Configuration provider <http://python-dependency-injector.ets-labs.org/providers/configuration.html>`_.
- **Containers**. Provides declarative and dynamic containers.
  See `Containers <http://python-dependency-injector.ets-labs.org/containers/index.html>`_.
- **Performance**. Fast. Written in ``Cython``.
- **Typing**. Provides typing stubs, ``mypy``-friendly.
  See `Typing and mypy <http://python-dependency-injector.ets-labs.org/providers/typing_mypy.html>`_.
- **Maturity**. Mature and production-ready. Well-tested, documented and supported.

.. code-block:: python

   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.

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*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 <http://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 on the `Read The Docs <http://python-dependency-injector.ets-labs.org/>`_

Examples
--------

Choose one of the following:

- `Application example (single container) <http://python-dependency-injector.ets-labs.org/examples/application-single-container.html>`_
- `Application example (multiple containers) <http://python-dependency-injector.ets-labs.org/examples/application-multiple-containers.html>`_
- `Decoupled packages example (multiple containers) <http://python-dependency-injector.ets-labs.org/examples/decoupled-packages.html>`_

Tutorials
---------

Choose one of the following:

- `Flask web application tutorial <http://python-dependency-injector.ets-labs.org/tutorials/flask.html>`_
- `Aiohttp REST API tutorial <http://python-dependency-injector.ets-labs.org/tutorials/aiohttp.html>`_
- `Asyncio monitoring daemon tutorial <http://python-dependency-injector.ets-labs.org/tutorials/asyncio-daemon.html>`_
- `CLI application tutorial <http://python-dependency-injector.ets-labs.org/tutorials/cli.html>`_

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?
 - 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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