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.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/logo.svg
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.. image:: https://img.shields.io/pypi/v/dependency_injector.svg
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:target: https://pypi.org/project/dependency-injector/
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:alt: Latest Version
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.. image:: https://img.shields.io/pypi/l/dependency_injector.svg
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:target: https://pypi.org/project/dependency-injector/
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:alt: License
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.. image:: https://pepy.tech/badge/dependency-injector
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:target: https://pepy.tech/project/dependency-injector
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:alt: Downloads
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.. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg
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:target: https://pypi.org/project/dependency-injector/
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:alt: Supported Python versions
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.. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg
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:target: https://pypi.org/project/dependency-injector/
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:alt: Supported Python implementations
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.. image:: https://travis-ci.org/ets-labs/python-dependency-injector.svg?branch=master
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:target: https://travis-ci.org/ets-labs/python-dependency-injector
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:alt: Build Status
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.. image:: http://readthedocs.org/projects/python-dependency-injector/badge/?version=latest
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:target: http://python-dependency-injector.ets-labs.org/
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:alt: Docs Status
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.. image:: https://coveralls.io/repos/github/ets-labs/python-dependency-injector/badge.svg?branch=master
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:target: https://coveralls.io/github/ets-labs/python-dependency-injector?branch=master
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:alt: Coverage Status
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What is ``Dependency Injector``?
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================================
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2020-07-07 00:20:39 +03:00
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``Dependency Injector`` is a Python dependency injection framework for Python.
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2019-08-18 03:57:10 +03:00
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It was designed to be a unified and developer-friendly tool that helps
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implement a dependency injection design pattern in a formal, pretty, and
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Pythonic way.
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2016-02-04 23:47:45 +03:00
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2019-08-18 03:57:10 +03:00
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The key features of the *Dependency Injector* framework are:
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+ Easy, smart, and pythonic style.
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+ Obvious and clear structure.
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+ Extensibility and flexibility.
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+ High performance.
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+ Memory efficiency.
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+ Thread safety.
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+ Documented.
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+ Semantically versioned.
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2017-03-26 22:45:05 +03:00
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*Dependency Injector* containers and providers are implemented as C extension
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types using Cython.
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2016-11-11 18:05:25 +03:00
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2015-08-31 16:31:38 +03:00
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2020-01-27 03:04:23 +03:00
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Installation
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------------
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The *Dependency Injector* library is available on `PyPi`_::
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2020-01-27 03:33:28 +03:00
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pip install dependency-injector
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Documentation
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-------------
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2020-07-07 00:20:39 +03:00
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Documentation is on `Read The Docs <http://python-dependency-injector.ets-labs.org/>`_
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2016-10-07 17:33:51 +03:00
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Dependency injection
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2016-10-06 23:15:41 +03:00
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--------------------
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2016-10-07 14:52:28 +03:00
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`Dependency injection`_ is a software design pattern that implements
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`Inversion of control`_ to resolve dependencies. Formally, if object **A**
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depends on object **B**, object **A** must not create or import object **B**
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directly. Instead of this object **A** must provide a way to *inject*
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object **B**. The responsibilities of objects creation and dependency
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injection are delegated to external code - the *dependency injector*.
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Popular terminology of the dependency injection pattern:
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+ Object **A**, which depends on object **B**, is often called -
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the *client*.
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+ Object **B**, which is depended on, is often called - the *service*.
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+ External code that is responsible for creation of objects and injection
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of dependencies is often called - the *dependency injector*.
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There are several ways to inject a *service* into a *client*:
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+ by passing it as an ``__init__`` argument (constructor / initializer
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injection)
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+ by setting it as an attribute's value (attribute injection)
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+ by passing it as a method's argument (method injection)
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The dependency injection pattern has few strict rules that should be followed:
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+ The *client* delegates to the *dependency injector* the responsibility
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of injecting its dependencies - the *service(s)*.
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+ The *client* doesn't know how to create the *service*, it knows only
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the interface of the *service*. The *service* doesn't know that it is used by
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the *client*.
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+ The *dependency injector* knows how to create the *client* and
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the *service*. It also knows that the *client* depends on the *service*,
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and knows how to inject the *service* into the *client*.
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+ The *client* and the *service* know nothing about the *dependency injector*.
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The dependency injection pattern provides the following advantages:
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+ Control of application structure.
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+ Decreased coupling of application components.
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+ Increased code reusability.
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+ Increased testability.
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+ Increased maintainability.
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+ Reconfiguration of a system without rebuilding.
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2017-01-30 00:30:38 +03:00
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Dependency Injector in action
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-----------------------------
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2016-12-28 00:06:40 +03:00
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2019-08-18 03:57:10 +03:00
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The brief example below is a simplified version of inversion of control
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containers from a real-life application. The example demonstrates the usage
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of *Dependency Injector* inversion of control container and providers for
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specifying application components and their dependencies on each other in one
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module. Besides other previously mentioned advantages, it shows a great
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opportunity to control and manage application's structure in one place.
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2016-05-18 23:18:29 +03:00
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2016-03-14 01:04:55 +03:00
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.. code-block:: python
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2016-10-06 22:48:43 +03:00
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"""Example of dependency injection in Python."""
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2016-10-06 22:48:43 +03:00
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import logging
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import sqlite3
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2017-03-15 18:26:59 +03:00
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import boto3
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2016-09-18 23:00:10 +03:00
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2018-07-02 16:43:23 +03:00
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from dependency_injector import containers, providers
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from example import services, main
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class IocContainer(containers.DeclarativeContainer):
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"""Application IoC container."""
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config = providers.Configuration('config')
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logger = providers.Singleton(logging.Logger, name='example')
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2018-06-27 17:37:03 +03:00
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# Gateways
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database_client = providers.Singleton(sqlite3.connect, config.database.dsn)
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s3_client = providers.Singleton(
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boto3.client, 's3',
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aws_access_key_id=config.aws.access_key_id,
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aws_secret_access_key=config.aws.secret_access_key,
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)
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2018-06-27 17:37:03 +03:00
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# Services
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users_service = providers.Factory(
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services.UsersService,
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db=database_client,
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logger=logger,
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)
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auth_service = providers.Factory(
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services.AuthService,
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token_ttl=config.auth.token_ttl,
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db=database_client,
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logger=logger,
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)
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photos_service = providers.Factory(
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services.PhotosService,
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db=database_client,
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s3=s3_client,
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logger=logger,
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)
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2018-06-27 17:37:03 +03:00
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# Misc
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main = providers.Callable(
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main.main,
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users_service=users_service,
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auth_service=auth_service,
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photos_service=photos_service,
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)
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The next example demonstrates a run of the example application defined above:
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2016-09-18 23:00:10 +03:00
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.. code-block:: python
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2018-06-27 17:37:03 +03:00
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"""Run example of dependency injection in Python."""
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2016-10-06 22:48:43 +03:00
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import sys
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import logging
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2018-06-27 17:37:03 +03:00
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from container import IocContainer
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2016-04-20 14:19:54 +03:00
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if __name__ == '__main__':
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# Configure container:
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container = IocContainer(
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config={
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'database': {
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'dsn': ':memory:',
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},
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'aws': {
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'access_key_id': 'KEY',
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'secret_access_key': 'SECRET',
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},
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'auth': {
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'token_ttl': 3600,
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},
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}
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)
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container.logger().addHandler(logging.StreamHandler(sys.stdout))
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# Run application:
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container.main(*sys.argv[1:])
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2019-08-18 03:57:10 +03:00
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You can find more *Dependency Injector* examples in the ``/examples`` directory
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on our GitHub:
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2016-04-25 11:07:47 +03:00
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https://github.com/ets-labs/python-dependency-injector
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2015-04-03 00:35:22 +03:00
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2015-04-03 00:29:00 +03:00
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2016-10-07 14:52:28 +03:00
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.. _Dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
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.. _Inversion of control: https://en.wikipedia.org/wiki/Inversion_of_control
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.. _PyPi: https://pypi.org/project/dependency-injector/
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.. _User's guide: http://python-dependency-injector.ets-labs.org/
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.. _API docs: http://python-dependency-injector.ets-labs.org/api/
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