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Dependency injection framework for Python
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| dependency_injector | ||
| docs | ||
| examples | ||
| tests | ||
| .coveragerc | ||
| .gitignore | ||
| .pylintrc | ||
| .travis.yml | ||
| CONTRIBUTORS.rst | ||
| LICENSE.rst | ||
| MANIFEST.in | ||
| README.rst | ||
| requirements-dev.txt | ||
| requirements.txt | ||
| setup.py | ||
| tox.ini | ||
===========================================================
Dependency Injector - Python dependency injection framework
===========================================================
*Dependency Injector* is a Python dependency injection framework. 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.
+ Memory efficiency.
+ Thread safety.
+ Documentation.
+ Semantic versioning.
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 |
+---------------------------------------+----------------------------------------------------------------------------------------+
Installation
------------
*Dependency Injector* library is available on `PyPi`_::
pip install dependency_injector
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**,
but provide a way for injecting object **B** (object **B** could be injected
into object **A** in several ways: by passing it as ``__init__`` argument, by
setting it as attribute's value or by passing it as method's argument).
Dependency injection pattern has few strict rules that should be followed:
+ Object **A** (the client) delegates to external code (the dependency
injector) the responsibility of providing its dependencies - object **B**
(the service).
+ The client doesn't know how to create the service, it knows only interface
of service.
+ The service doesn't know that it is used by the client.
+ The dependency injector knows how to create the client.
+ The dependency injector knows how to create the service.
+ The dependency injector knows that the client depends on the service.
+ The dependency injector knows how to inject the service into the client.
+ The client knows nothing about the dependency injector.
+ The service knows nothing about the dependency injector.
Next two examples demonstrate refactoring of a small piece of code to
dependency injection pattern:
.. code-block:: python
"""Car & Engine example."""
class Engine(object):
"""Example engine."""
class Car(object):
"""Example car."""
def __init__(self):
"""Initializer."""
self.engine = Engine() # Engine is a "hardcoded" dependency
if __name__ == '__main__':
car = Car() # Application creates Car's instance
``Car`` **creates** an ``Engine`` during its creation. Really? Does it make
more sense than creating an ``Engine`` separately and then
**inject it into** ``Car`` when ``Car`` is being created? Looks more
realistic, right?
.. code-block:: python
"""Refactored Car & Engine example that demonstrates dependency injection."""
class Engine(object):
"""Example engine."""
class Car(object):
"""Example car."""
def __init__(self, engine):
"""Initializer."""
self.engine = engine # Engine is an "injected" dependency
if __name__ == '__main__':
engine = Engine() # Application creates Engine's instance
car = Car(engine) # and inject it into the Car's instance
Advantages of dependency injection
----------------------------------
Dependency injection pattern provides next 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 microservice system:
.. 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."""
logger = providers.Singleton(logging.Logger, name='example')
database = providers.Singleton(sqlite3.connect, ':memory:')
s3 = providers.Singleton(boto.s3.connection.S3Connection,
aws_access_key_id='KEY',
aws_secret_access_key='SECRET')
class Services(containers.DeclarativeContainer):
"""IoC container of business service providers."""
users = providers.Factory(example.services.Users,
logger=Platform.logger,
db=Platform.database)
auth = providers.Factory(example.services.Auth,
logger=Platform.logger,
db=Platform.database,
token_ttl=3600)
photos = providers.Factory(example.services.Photos,
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 dependency injection example application
defined above:
.. code-block:: python
"""Run dependency injection example application.
Instructions for running:
python run.py 1 secret photo.jpg
"""
import sys
import logging
from containers import Platform, Application
if __name__ == '__main__':
# Configure platform logger:
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.Users(logger=logger,
# db=database),
# auth_service=example.services.Auth(logger=logger,
# db=database,
# token_ttl=3600),
# photos_service=example.services.Photos(logger=logger,
# db=database,
# s3=s3))
#
# Output:
#
# User 1 has been found in database
# User 1 has been successfully authenticated
# Photo photo.jpg has been successfully uploaded by user 1
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
Documentation
-------------
*Dependency Injector* documentation is hosted on ReadTheDocs:
- `User's guide`_
- `API docs`_
Feedback
--------
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/