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93 lines
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93 lines
3.9 KiB
ReStructuredText
Introduction
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============
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Before you have started with *Dependency Injector* framework and dependecy
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injection, there are a couple of introduction notes that might be useful.
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What is DI and why is it needed?
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--------------------------------
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Python ecosystem consists of a big amount of various libraries that contain
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different classes and functions that could be used for applications
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development. Each of them has its own role.
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Modern Python applications are mostly the composition of well-known open
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source systems / frameworks / libraries and some turnkey functionality.
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When application goes bigger, its complexity and SLOC_ are also increased.
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Being driven by SOLID_ (for example), developers often start to split
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application's sources into not so big classes, functions and modules, that are
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less complex, could be reused several times and so on... It always helps, but
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there is another problem on the horizon.
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The name of this problem is - "Dependency hell!". It sounds like "I have so
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many classes and functions! They are great, now I can understand each of them,
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but it is so hard to see the whole picture! How are they linked with each
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other? What dependencies does this class have?". And this is a key question:
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"What dependencies does certain class / function have?". To resolve this issues
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developers have to go inside with IoC_ principles and implementation patterns.
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One of such IoC_ implementation patterns is called `dependency injection`_.
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Dependency injection in Python
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------------------------------
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Interesting but, dependency injection is not very popular topic in Python.
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The things are so because Python is an awesome language. Your eyes are opened
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and your hands are free while you are using Python. In practice this means that
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you can do dependency injection in Python in quite an easy way because language
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itself helps you to do this. At the same time, even the thins are so, you still
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have to do some work. Another one 'minor' problem is that there are several
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ways to do dependency injection container.
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Key features
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------------
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*Dependency Injector* is a dependency injection framework for Python projects.
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It was designed to be unified, developer's friendly tool for managing any kind
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of Python objects and their dependencies in formal, pretty way.
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Below is a list of some key features and points of *Dependency Injector*
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framework:
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- Easy, smart, pythonic style.
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- Obvious, clear structure.
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- Memory efficiency.
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- Semantic versioning.
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Main idea of *Dependency Injector* is to keep dependencies under control.
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Main entities
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-------------
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Current section describes *Dependency Injector* main entities and their
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interaction with each other.
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.. image:: /images/internals.png
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:width: 100%
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:align: center
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There are 3 main entities:
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- Providers. Providers are strategies of accesing objects. For example,
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``dependency_injector.providers.Factory`` creates new instance of provided
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class every time it is called. ``dependency_injector.providers.Singleton``
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creates provided instance once and returns it on every next call. Providers
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could be overridden by another providers. Base class is -
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``dependency_injector.providers.Provider``.
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- Injections. Injections are instructions for making dependency injections
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(there are several ways how they could be done). Injections are used mostly
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by ``dependency_injector.providers.Factory`` and
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``dependency_injector.providers.Singleton`` providers, but these are not only
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cases. Base class is -
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``dependency_injector.injections.Injection``.
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- Catalogs. Catalogs are collections of providers. They are used for grouping
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of providers by some principles. Base class is -
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``dependency_injector.catalog.AbstractCatalog``.
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.. _SLOC: http://en.wikipedia.org/wiki/Source_lines_of_code
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.. _SOLID: http://en.wikipedia.org/wiki/SOLID_%28object-oriented_design%29
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.. _IoC: http://en.wikipedia.org/wiki/Inversion_of_control
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.. _dependency injection: http://en.wikipedia.org/wiki/Dependency_injection
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