python-dependency-injector/README.rst
2016-12-02 20:43:39 +02:00

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Dependency Injector - Dependency injection microframework for Python
====================================================================
*Dependency Injector* is a dependency injection microframework for Python.
It was designed to be unified, developer-friendly tool that helps to implement
dependency injection pattern in formal, pretty, Pythonic way.
*Dependency Injector* framework key features are:
+ Easy, smart, pythonic style.
+ Obvious, clear structure.
+ Extensibility and flexibility.
+ High performance.
+ Memory efficiency.
+ Thread safety.
+ Documentation.
+ Semantic versioning.
*Dependency Injector* providers are implemented as C extension types using
Cython.
Status
------
+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
| *PyPi* | .. image:: https://img.shields.io/pypi/v/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Latest Version |
| | .. image:: https://img.shields.io/pypi/l/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: License |
+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
| *Python versions and implementations* | .. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python versions |
| | .. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python implementations |
+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
| *Builds and tests coverage* | .. image:: https://travis-ci.org/ets-labs/python-dependency-injector.svg?branch=master |
| | :target: https://travis-ci.org/ets-labs/python-dependency-injector |
| | :alt: Build Status |
| | .. image:: https://coveralls.io/repos/ets-labs/python-dependency-injector/badge.svg |
| | :target: https://coveralls.io/r/ets-labs/python-dependency-injector |
| | :alt: Coverage Status |
+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
| *Github* | .. image:: https://img.shields.io/github/watchers/ets-labs/python-dependency-injector.svg?style=social&label=Watch |
| | :target: https://github.com/ets-labs/python-dependency-injector |
| | :alt: Github watchers |
| | .. image:: https://img.shields.io/github/stars/ets-labs/python-dependency-injector.svg?style=social&label=Star |
| | :target: https://github.com/ets-labs/python-dependency-injector |
| | :alt: Github stargazers |
| | .. image:: https://img.shields.io/github/forks/ets-labs/python-dependency-injector.svg?style=social&label=Fork |
| | :target: https://github.com/ets-labs/python-dependency-injector |
| | :alt: Github forks |
+---------------------------------------+--------------------------------------------------------------------------------------------------------------------+
Dependency injection
--------------------
`Dependency injection`_ is a software design pattern that implements
`Inversion of control`_ for resolving dependencies. Formally, if object **A**
depends on object **B**, object **A** must not create or import object **B**
directly. Instead of this object **A** must provide a way for *injecting*
object **B**. The responsibilities of objects creation and dependencies
injection are delegated to external code - the *dependency injector*.
Popular terminology of dependency injection pattern:
+ Object **A**, that is dependant on object **B**, is often called -
the *client*.
+ Object **B**, that is a dependency, is often called - the *service*.
+ External code that is responsible for creation of objects and injection
of dependencies is often called - the *dependency injector*.
There are several ways of how *service* can be injected into the *client*:
+ by passing it as ``__init__`` argument (constructor / initializer injection)
+ by setting it as attribute's value (attribute injection)
+ by passing it as method's argument (method injection)
Dependency injection pattern has few strict rules that should be followed:
+ The *client* delegates to the *dependency injector* the responsibility
of injecting its dependencies - the *service(s)*.
+ The *client* doesn't know how to create the *service*, it knows only
interface of the *service*. The *service* doesn't know that it is used by
the *client*.
+ The *dependency injector* knows how to create the *client* and
the *service*, it also knows that the *client* depends on the *service*,
and knows how to inject the *service* into the *client*.
+ The *client* and the *service* know nothing about the *dependency injector*.
Dependency injection pattern provides the following advantages:
+ Control on application structure.
+ Decreased coupling between application components.
+ Increased code reusability.
+ Increased testability.
+ Increased maintainability.
+ Reconfiguration of system without rebuilding.
Example of dependency injection
-------------------------------
Brief example below demonstrates usage of *Dependency Injector* for creating
several IoC containers for some example application:
.. code-block:: python
"""Example of dependency injection in Python."""
import logging
import sqlite3
import boto.s3.connection
import example.main
import example.services
import dependency_injector.containers as containers
import dependency_injector.providers as providers
class Platform(containers.DeclarativeContainer):
"""IoC container of platform service providers."""
configuration = providers.Configuration('config')
logger = providers.Singleton(logging.Logger, name='example')
database = providers.Singleton(sqlite3.connect, configuration.database.dsn)
s3 = providers.Singleton(boto.s3.connection.S3Connection,
configuration.aws.access_key_id,
configuration.aws.secret_access_key)
class Services(containers.DeclarativeContainer):
"""IoC container of business service providers."""
users = providers.Factory(example.services.UsersService,
logger=Platform.logger,
db=Platform.database)
auth = providers.Factory(example.services.AuthService,
logger=Platform.logger,
db=Platform.database,
token_ttl=Platform.configuration.auth.token_ttl)
photos = providers.Factory(example.services.PhotosService,
logger=Platform.logger,
db=Platform.database,
s3=Platform.s3)
class Application(containers.DeclarativeContainer):
"""IoC container of application component providers."""
main = providers.Callable(example.main.main,
users_service=Services.users,
auth_service=Services.auth,
photos_service=Services.photos)
Next example demonstrates run of example application defined above:
.. code-block:: python
"""Run example application."""
import sys
import logging
from containers import Platform, Application
if __name__ == '__main__':
# Configure platform:
Platform.configuration.update({'database': {'dsn': ':memory:'},
'aws': {'access_key_id': 'KEY',
'secret_access_key': 'SECRET'},
'auth': {'token_ttl': 3600}})
Platform.logger().addHandler(logging.StreamHandler(sys.stdout))
# Run application:
Application.main(uid=sys.argv[1],
password=sys.argv[2],
photo=sys.argv[3])
# Previous call is an equivalent of next operations:
#
# logger = logging.Logger(name='example')
# database = sqlite3.connect(':memory:')
# s3 = boto.s3.connection.S3Connection(aws_access_key_id='KEY',
# aws_secret_access_key='SECRET')
#
# example.main.main(
# uid=sys.argv[1],
# password=sys.argv[2],
# photo=sys.argv[3],
# users_service=example.services.UsersService(logger=logger,
# db=database),
# auth_service=example.services.AuthService(logger=logger,
# db=database,
# token_ttl=3600),
# photos_service=example.services.PhotosService(logger=logger,
# db=database,
# s3=s3))
Alternative definition styles of providers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*Dependecy Injector* supports few other styles of dependency injections
definition.
IoC containers from previous example could look like these:
.. code-block:: python
class Platform(containers.DeclarativeContainer):
"""IoC container of platform service providers."""
logger = providers.Singleton(logging.Logger) \
.add_kwargs(name='example')
database = providers.Singleton(sqlite3.connect) \
.add_args(':memory:')
s3 = providers.Singleton(boto.s3.connection.S3Connection) \
.add_kwargs(aws_access_key_id='KEY',
aws_secret_access_key='SECRET')
or like this these:
.. code-block:: python
class Platform(containers.DeclarativeContainer):
"""IoC container of platform service providers."""
logger = providers.Singleton(logging.Logger)
logger.add_kwargs(name='example')
database = providers.Singleton(sqlite3.connect)
database.add_args(':memory:')
s3 = providers.Singleton(boto.s3.connection.S3Connection)
s3.add_kwargs(aws_access_key_id='KEY',
aws_secret_access_key='SECRET')
You can get more *Dependency Injector* examples in ``/examples`` directory on
GitHub:
https://github.com/ets-labs/python-dependency-injector
Installation
------------
*Dependency Injector* library is available on `PyPi`_::
pip install dependency_injector
Documentation
-------------
*Dependency Injector* documentation is hosted on ReadTheDocs:
- `User's guide`_
- `API docs`_
Feedback & Support
------------------
Feel free to post questions, bugs, feature requests, proposals etc. on
*Dependency Injector* GitHub Issues:
https://github.com/ets-labs/python-dependency-injector/issues
Your feedback is quite important!
.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
.. _PyPi: https://pypi.python.org/pypi/dependency_injector
.. _User's guide: http://python-dependency-injector.ets-labs.org/en/stable/
.. _API docs: http://python-dependency-injector.ets-labs.org/en/stable/api/