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python-dependency-injector/README.rst
Roman Mogylatov 6febd03646 Bump version to 3.43.1
2020-09-09 23:48:08 -04:00

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What is ``Dependency Injector``?
================================
``Dependency Injector`` is a dependency injection framework for Python.
It helps implementing the dependency injection principle.
What is dependency injection?
-----------------------------
Dependency injection is a principle that helps to decrease coupling and increase cohesion.
What is coupling and cohesion?
Coupling and cohesion are about how tough the components are tied.
- **High coupling**. If the coupling is high it's like using a superglue or welding. No easy way
to disassemble.
- **High cohesion**. High cohesion is like using the screws. Very easy to disassemble and
assemble back or assemble a different way. It is an opposite to high coupling.
When the cohesion is high the coupling is low.
Low coupling brings a flexibility. Your code becomes easier to change and test.
How to implement dependency injection?
--------------------------------------
Objects do not create each other anymore. They provide a way to inject the dependencies instead.
Before:
.. code-block:: python
import os
class ApiClient:
def __init__(self):
self.api_key = os.getenv('API_KEY') # <-- the dependency
self.timeout = os.getenv('TIMEOUT') # <-- the dependency
class Service:
def __init__(self):
self.api_client = ApiClient() # <-- the dependency
if __name__ == '__main__':
service = Service()
After:
.. code-block:: python
import os
class ApiClient:
def __init__(self, api_key: str, timeout: int):
self.api_key = api_key # <-- the dependency is injected
self.timeout = timeout # <-- the dependency is injected
class Service:
def __init__(self, api_client: ApiClient):
self.api_client = api_client # <-- the dependency is injected
if __name__ == '__main__':
service = Service(ApiClient(os.getenv('API_KEY'), os.getenv('TIMEOUT')))
``ApiClient`` is decoupled from knowing where the options come from. You can read a key and a
timeout from a configuration file or even get them from a database.
``Service`` is decoupled from the ``ApiClient``. It does not create it anymore. You can provide a
stub or other compatible object.
Flexibility comes with a price.
Now you need to assemble the objects like this::
service = Service(ApiClient(os.getenv('API_KEY'), os.getenv('TIMEOUT')))
The assembly code might get duplicated and it'll become harder to change the application structure.
Here comes the ``Dependency Injector``.
What does the Dependency Injector do?
-------------------------------------
With the dependency injection pattern objects loose the responsibility of assembling the
dependencies. The ``Dependency Injector`` absorbs that responsibility.
``Dependency Injector`` helps to assemble the objects.
It provides a container and providers that help you with the objects assembly. When you
need an object you get it from the container. The rest of the assembly work is done by the
framework:
.. 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()
Retrieving of the ``Service`` instance now is done like this::
service = container.service()
Objects assembling is consolidated in the container. When you need to make a change you do it in
one place.
When doing a testing you call the ``container.api_client.override()`` to replace the real API
client with a mock:
.. code-block:: python
from unittest import mock
with container.api_client.override(mock.Mock()):
service = container.service()
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.
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/>`_
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/
.. |star| unicode:: U+2B50 U+FE0F .. star sign1
.. |new| unicode:: U+1F195 .. new sign
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