# Objects Dependency management tool for Python projects. [![Latest Version](https://pypip.in/version/Objects/badge.svg)](https://pypi.python.org/pypi/Objects/) [![Downloads](https://pypip.in/download/Objects/badge.svg)](https://pypi.python.org/pypi/Objects/) [![Build Status](https://travis-ci.org/rmk135/objects.svg?branch=master)](https://travis-ci.org/rmk135/objects) [![Coverage Status](https://coveralls.io/repos/rmk135/objects/badge.svg)](https://coveralls.io/r/rmk135/objects) [![License](https://pypip.in/license/Objects/badge.svg)](https://pypi.python.org/pypi/Objects/) [![Supported Python versions](https://pypip.in/py_versions/Objects/badge.svg)](https://pypi.python.org/pypi/Objects/) [![Supported Python implementations](https://pypip.in/implementation/Objects/badge.svg)](https://pypi.python.org/pypi/Objects/) ## Introduction Python ecosystem consists of a big amount of various classes, functions and objects that could be used for applications development. Each of them has its own role. Modern Python applications are mostly the composition of well-known open source systems, frameworks, libraries and some turnkey functionality. When application goes bigger, its amount of objects and their dependencies also increased extremely fast and became hard to maintain. `Objects` is designed to be developer's friendly tool for managing objects and their dependencies in formal, pretty way. Main idea of `Objects` is to keep dependencies under control. ## Entities Current section describes main `Objects` entities and their interaction. ### Providers Providers are strategies of accessing objects. They describe how particular object need to be provided. For example: ```python from objects.providers import NewInstance from objects.providers import Singleton # NewInstance provider will create new instance of specified class on every call. new_object = NewInstance(object) object_1 = new_object() object_2 = new_object() assert object_1 is not object_2 # Singleton provider will create new instance of specified class on first call, and return same instance on every next call. single_object = Singleton(object) single_object_1 = single_object() single_object_2 = single_object() assert single_object_1 is single_object_2 ``` ### Injections Injections are additional instructions, that are used for determining dependencies of objects. ### Catalogs Catalogs are named set of providers. ## Example ```python """Concept example of `Objects`.""" from objects.catalog import AbstractCatalog from objects.providers import Singleton from objects.providers import NewInstance from objects.injections import KwArg from objects.injections import Attribute from objects.injections import inject import sqlite3 class ObjectA(object): """Example class ObjectA, that has dependency on database.""" def __init__(self, db): """Initializer.""" self.db = db class ObjectB(object): """Example class ObjectB, that has dependencies on ObjectA and database.""" def __init__(self, a, db): """Initializer.""" self.a = a self.db = db class Catalog(AbstractCatalog): """Catalog of objects providers.""" database = Singleton(sqlite3.Connection, KwArg('database', ':memory:'), Attribute('row_factory', sqlite3.Row)) """:type: (objects.Provider) -> sqlite3.Connection""" object_a = NewInstance(ObjectA, KwArg('db', database)) """:type: (objects.Provider) -> ObjectA""" object_b = NewInstance(ObjectB, KwArg('a', object_a), KwArg('db', database)) """:type: (objects.Provider) -> ObjectB""" # Catalog static provides. a1, a2 = Catalog.object_a(), Catalog.object_a() b1, b2 = Catalog.object_b(), Catalog.object_b() assert a1 is not a2 assert b1 is not b2 assert a1.db is a2.db is b1.db is b2.db is Catalog.database() # Example of inline injections. @inject(KwArg('a', Catalog.object_a)) @inject(KwArg('b', Catalog.object_b)) @inject(KwArg('database', Catalog.database)) def example(a, b, database): assert a.db is b.db is database is Catalog.database() example() ```