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Update conclusion of asyncio daemon tutorial
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@ -1018,54 +1018,16 @@ In this tutorial we've built an ``asyncio`` monitoring daemon following the dep
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injection principle.
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We've used the ``Dependency Injector`` as a dependency injection framework.
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The benefit you get with the ``Dependency Injector`` is the container. It starts to payoff
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when you need to understand or change your application structure. It's easy with the container,
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cause you have everything defined explicitly in one place:
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With a help of :ref:`containers` and :ref:`providers` we have defined how to assemble application components.
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.. code-block:: python
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``List`` provider helped to inject a list of monitors into dispatcher.
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:ref:`configuration-provider` helped to deal with reading YAML file.
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"""Containers module."""
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We used :ref:`wiring` feature to inject dispatcher into the ``main()`` function.
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:ref:`provider-overriding` feature helped in testing.
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import logging
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import sys
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from dependency_injector import containers, providers
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from . import http, monitors, dispatcher
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class Container(containers.DeclarativeContainer):
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config = providers.Configuration()
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configure_logging = providers.Callable(
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logging.basicConfig,
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stream=sys.stdout,
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level=config.log.level,
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format=config.log.format,
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)
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http_client = providers.Factory(http.HttpClient)
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example_monitor = providers.Factory(
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monitors.HttpMonitor,
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http_client=http_client,
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options=config.monitors.example,
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)
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httpbin_monitor = providers.Factory(
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monitors.HttpMonitor,
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http_client=http_client,
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options=config.monitors.httpbin,
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)
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dispatcher = providers.Factory(
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dispatcher.Dispatcher,
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monitors=providers.List(
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example_monitor,
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httpbin_monitor,
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),
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)
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We kept all the dependencies injected explicitly. This will help when we need to add or
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change something in future.
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You can find complete project on the
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`Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/asyncio-daemon>`_.
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