python-dependency-injector/docs/introduction/what_is_di.rst
2016-04-20 14:19:54 +03:00

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What is dependency injection and inversion of control?
------------------------------------------------------
.. meta::
:description: This article provides definition of dependency injection,
inversion of control and dependency inversion. It contains
example code in Python that is refactored to be following
inversion of control principle and then enhanced by
inversion of control container based on "Dependency Injector"
declarative catalog.
Definition
~~~~~~~~~~
Wikipedia provides quite good definitions of dependency injection pattern
and related principles:
.. glossary::
`Dependency injection`_
In software engineering, dependency injection is a software design
pattern that implements inversion of control for resolving
dependencies. A dependency is an object that can be used (a service).
An injection is the passing of a dependency to a dependent object (a
client) that would use it. The service is made part of the client's
state. Passing the service to the client, rather than allowing a
client to build or find the service, is the fundamental requirement of
the pattern.
Dependency injection allows a program design to follow the dependency
inversion principle. The client delegates to external code (the
injector) the responsibility of providing its dependencies. The client
is not allowed to call the injector code. It is the injecting code
that constructs the services and calls the client to inject them. This
means the client code does not need to know about the injecting code.
The client does not need to know how to construct the services. The
client does not need to know which actual services it is using. The
client only needs to know about the intrinsic interfaces of the
services because these define how the client may use the services.
This separates the responsibilities of use and construction.
`Inversion of control`_
In software engineering, inversion of control (IoC) describes a design
in which custom-written portions of a computer program receive the
flow of control from a generic, reusable library. A software
architecture with this design inverts control as compared to
traditional procedural programming: in traditional programming, the
custom code that expresses the purpose of the program calls into
reusable libraries to take care of generic tasks, but with inversion
of control, it is the reusable code that calls into the custom, or
task-specific, code.
Inversion of control is used to increase modularity of the program and
make it extensible, and has applications in object-oriented
programming and other programming paradigms. The term was popularized
by Robert C. Martin and Martin Fowler.
The term is related to, but different from, the dependency inversion
principle, which concerns itself with decoupling dependencies between
high-level and low-level layers through shared abstractions.
`Dependency inversion`_
In object-oriented programming, the dependency inversion principle
refers to a specific form of decoupling software modules. When
following this principle, the conventional dependency relationships
established from high-level, policy-setting modules to low-level,
dependency modules are reversed, thus rendering high-level modules
independent of the low-level module implementation details. The
principle states:
+ High-level modules should not depend on low-level modules.
Both should depend on abstractions.
+ Abstractions should not depend on details.
Details should depend on abstractions.
The principle inverts the way some people may think about
object-oriented design, dictating that both high- and low-level
objects must depend on the same abstraction.
Example
~~~~~~~
Let's go through the code of ``example.py``:
.. literalinclude:: ../../examples/ioc_di_demos/example.py
:language: python
:linenos:
At some point, things defined above mean, that the code from ``example.py``,
could look different, like in ``ioc_example.py``:
.. literalinclude:: ../../examples/ioc_di_demos/ioc_example.py
:language: python
:linenos:
Also the code from ``ioc_example.py`` could be upgraded with inversion of
control container, like in ``ioc_container_example.py``:
.. literalinclude:: ../../examples/ioc_di_demos/ioc_container_example.py
:language: python
:linenos:
.. note::
``Components`` from ``ioc_container_example.py`` is an IoC container. It
contains a collection of component providers that could be injected into
each other.
Assuming this, ``Components`` could be one and the only place, where
application's structure is being managed on the high level.
Best explanation, ever
~~~~~~~~~~~~~~~~~~~~~~
Some times ago `user198313`_ posted awesome `question`_ about dependency
injection on `StackOverflow`_:
.. note::
How to explain dependency injection to a 5-year-old?
And `John Munsch`_ provided absolutely Great answer:
.. note::
When you go and get things out of the refrigerator for yourself, you can
cause problems. You might leave the door open, you might get something
Mommy or Daddy doesn't want you to have. You might even be looking for
something we don't even have or which has expired.
What you should be doing is stating a need, "I need something to drink
with lunch," and then we will make sure you have something when you sit
down to eat.
.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
.. _Dependency inversion: https://en.wikipedia.org/wiki/Dependency_inversion_principle
.. _StackOverflow: http://stackoverflow.com/
.. _question: http://stackoverflow.com/questions/1638919/how-to-explain-dependency-injection-to-a-5-year-old/1639186
.. _user198313: http://stackoverflow.com/users/198313/user198313
.. _John Munsch: http://stackoverflow.com/users/31899/john-munsch