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37 lines
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ReStructuredText
37 lines
1.6 KiB
ReStructuredText
Introduction
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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. It
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always helps, but there is another problem on the horizon.
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It sounds like "I have so many classes and functions! They are great, now I can
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understand each of them, but it is so hard to see the whole picture! How are
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they linked with each other? What dependencies does this class have?". And
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this is a key question: "What dependencies do certain class / function have?".
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To resolve this issues developers have to go inside with IoC_ principles and
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implementation patterns.
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One of such IoC_ implementation patterns is called `dependency injection`_.
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*Objects* is a dependency injection framework for Python projects.
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It was designed to be developer's friendly tool for managing any kind of
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Python objects and their dependencies in formal, pretty way.
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Main idea of *Objects* is to keep dependencies under control.
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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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