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        "author": "Sune Debel",
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        "description": "# Build Status\n\nBuild status: \n\n[![CircleCI](https://circleci.com/gh/suned/serum.svg?style=svg)](https://circleci.com/gh/suned/serum)\n\nCode quality:\n\n[![Test Coverage](https://api.codeclimate.com/v1/badges/523bc990f4ef696aa22d/test_coverage)](https://codeclimate.com/github/suned/serum/test_coverage) \n\n[![Maintainability](https://api.codeclimate.com/v1/badges/523bc990f4ef696aa22d/maintainability)](https://codeclimate.com/github/suned/serum/maintainability)\n\n\n\n\n# Description\n`serum` is a fresh take on Dependency Injection in Python 3.\n\n`serum` is pure python and has no dependencies.\n# Installation\n```\n> pip install serum\n```\n# Quickstart\n```python\nfrom serum import inject, dependency, Context\n\n\n# Classes decorated with 'dependency' are injectable types.\n@dependency \nclass Log:\n    def info(self, message: str):\n        raise NotImplementedError()\n\n\nclass SimpleLog(Log):\n    def info(self, message: str):\n        print(message)\n\n\nclass StubLog(SimpleLog):\n    def info(self, message: str):\n        pass\n\n\n@inject  # Dependencies are injected using a class decorator...\nclass NeedsLog:\n    log: Log  # ...and class level annotations...\n\n\nclass NeedsSimpleLog:\n    @inject  # ...or using a function decorator\n    def __init__(self, log: SimpleLog):\n        self.log = log \n\n\n@inject\nclass NeedsNamedDependency:\n    named_dependency: str  # class level annotations annotated with a type that is not\n                           # decorated with 'dependency' will be treated as a named\n                           # dependency\n\n\n# Contexts provide dependencies\nwith Context(SimpleLog, named_dependency='this name is injected!'):\n    assert isinstance(NeedsLog().log, SimpleLog)\n    assert NeedsNamedDependency().named_dependency == 'this name is injected!'\n\n\n# Contexts will always provide the most specific \n# subtype of the requested type. This allows you to change which\n# dependencies are injected.\nwith Context(StubLog):\n    NeedsLog().log.info('Hello serum!')  # doesn't output anything\n    NeedsSimpleLog().log.info('Hello serum!')  # doesn't output anything\n```\n# Documentation\n- [`inject`](#inject)\n- [`dependency`](#dependency)\n- [`Context`](#context)\n- [`singleton`](#singleton)\n- [`mock`](#mock)\n- [`match`](#match)\n- [IPython Integration](#ipython-integration)\n\n## `inject`\n`inject` is used to decorate functions and classes in which you want to inject\ndependencies.\n```python\nfrom serum import inject, dependency\n\n@dependency\nclass MyDependency:\n    pass\n\n@inject\ndef f(dependency: MyDependency):\n    assert isinstance(dependency, MyDependency)\n\nf()\n```\nFunctions decorated with `inject` can be called as normal functions. `serum` will\nnot attempt to inject arguments given at call time.\n```python\n@inject\ndef f(dependency: MyDependency):\n    print(dependency)\n\nf('Overridden dependency')  #  outputs: Overridden dependency \n```\n`inject` will instantiate classes decorated with [`dependency`](#dependency). In\nthis way, your entire dependency graph can be specified using just `inject` and \n`dependency`.\n\nInstances of simple types and objects you want to instantiate yourself can be\ninjected using keyword arguments to [`Context`](#context).\n```python\n@inject\ndef f(dependency: str):\n    assert dependency == 'a named dependency'\n\nwith Context(dependency='a named dependency'):\n    f()\n```\n`inject` can also be used to decorate classes. \n```python\n@inject\nclass SomeClass:\n    dependency: MyDependency \n```\nThis is roughly equivalent to:\n```python\nclass SomeClass:\n    @inject\n    def __init__(self, dependency: MyDependency):\n        self.__dependency = dependency\n\n    @property\n    def dependency(self) -> MyDependency:\n        return self.__dependency\n```\nDependencies that are specified as class level annotations can be overridden\nusing key-word arguments to `__init__`\n```python\nassert SomeClass(dependency='Overridden!').dependency == 'Overridden!'\n```\n## `dependency`\nClasses decorated with `dependency` can be instantiated and injected\nby `serum`.\n```python\nfrom serum import dependency, inject\n\n@dependency\nclass Log:\n    def info(self, message):\n        print(message)\n\n\n@inject\nclass NeedsLog:\n    log: Log\n\n\nassert isinstance(NeedsLog().log, Log)\n```\n`serum` relies on being able to inject all dependencies for `dependency` decorated classes \nrecursively. To achieve this, `serum` assumes that the `__init__` method \nof `dependency` decorated classes can be called without any arguments.\nThis means that all arguments to `__init__` of `dependency` decorated classes must be injected using `inject`.\n```python\n@dependency\nclass SomeDependency:\n    def method(self):\n        pass\n\n\n@inject\n@dependency\nclass ValidDependency:  # OK!\n    some_dependency: SomeDependency\n\n    def __init__(self):\n        ...\n\n\n@dependency\nclass AlsoValidDependency:  # Also OK!\n    @inject\n    def __init__(self, some_dependency: SomeDependency):\n        ...\n\n\n@dependency\nclass InvalidDependency:\n    def __init__(self, a):\n        ...\n\n@inject\ndef f(dependency: InvalidDependency):\n    ...\n\nf()  \n# raises:\n# TypeError: __init__() missing 1 required positional argument: 'a'\n\n# The above exception was the direct cause of the following exception:\n\n# InjectionError                            Traceback (most recent call last)\n# ...\n# InjectionError: Could not instantiate dependency <class 'InvalidDependency'> \n# when injecting argument \"dependency\" in <function f at 0x10a074ea0>.\n```\n\nNote that circular dependencies preventing instantiation of `dependency` decorated\nclasses leads to an error.\n```python\n@dependency\nclass AbstractA:\n    pass\n\n@dependency\nclass AbstractB:\n    pass\n\n\nclass A(AbstractA):\n\n    @inject\n    def __init__(self, b: AbstractB):\n        self.b = b\n\nclass B(AbstractB):\n    @inject\n    def __init__(self, a: AbstractA):\n        self.a = a\n\n@inject\nclass Dependent:\n    a: AbstractA\n\n\nwith Context(A, B):\n    Dependent().a  # raises: CircularDependency: Circular dependency encountered while injecting <class 'AbstractA'> in <B object at 0x1061e3898>\n```\n## `Context`\n`Context`s provide implementations of dependencies. A `Context` will always provide the most\nspecific subtype of the requested type (in Method Resolution Order).\n```python\n@dependency\nclass Super:\n    pass\n\n\nclass Sub(Super):\n    pass\n\n@inject\nclass NeedsSuper:\n    instance: Super\n\n\nwith Context(Sub):\n    assert isinstance(NeedsSuper().instance, Sub)\n```\nIt is an error to inject a type in an `Context` that provides two or more equally specific subtypes of that type:\n```python\nclass AlsoSub(Super):\n    pass\n\n\nwith Context(Sub, AlsoSub):\n    NeedsSuper() # raises: AmbiguousDependencies: Attempt to inject type <class 'Log'> with equally specific provided subtypes: <class 'MockLog'>, <class 'FileLog'>\n```\n`Context`s can also be used as decorators:\n```python\ncontext = Context(Sub)\n\n@context\ndef f():\n    assert isinstance(NeedsSuper().instance, Sub)\n\n``` \nYou can provide named dependencies of any type using keyword arguments.\n```python\n@inject\nclass Database:\n    connection_string: str\n\n\nconnection_string = 'mysql+pymysql://root:my_pass@127.0.0.1:3333/my_db'\ncontext = Context(\n    connection_string=connection_string\n)\nwith context:\n    assert Database().connection_string == connection_string\n```\n`Context`s are local to each thread. This means that when using multi-threading\neach thread runs in its own context\n```python\nimport threading\n\n\n@singleton\nclass SomeSingleton:\n    pass\n\ndef worker_without_environment():\n    NeedsSuper().instance\n\n@inject\ndef worker(instance: SomeSingleton):\n    print(instance)\n\nwith Context():\n    worker() # outputs: <SomeSingleton object at 0x101f75470>\n    threading.Thread(target=worker).start() # outputs: <SomeSingleton object at 0x1035fb320>\n```\n\n## `singleton`\nTo always inject the same instance of a dependency in the same `Context`, annotate your type with `singleton`.\n```python\nfrom serum import singleton\n\n\n@singleton\nclass ExpensiveObject:\n    pass\n\n\n@inject\nclass NeedsExpensiveObject:\n    expensive_instance: ExpensiveObject\n\n\ninstance1 = NeedsExpensiveObject()\ninstance2 = NeedsExpensiveObject()\nassert instance1.expensive_instance is instance2.expensive_instance\n```\nNote that `Singleton` dependencies injected in different environments \nwill not refer to the same instance.\n```python\n\nwith Context():\n    instance1 = NeedsExpensiveObject()\n\nwith Context():\n    assert instance1.expensive_instance is not NeedsExpensiveObject().expensive_instance\n```\n## `mock`\n`serum` has support for injecting `MagicMock`s from the builtin\n`unittest.mock` library in unittests using the `mock` utility\nfunction. Mocks are reset\nwhen the environment context is closed.\n```python\nfrom serum import mock\n\n@dependency\nclass SomeDependency:\n    def method(self):\n        return 'some value' \n\n@inject\nclass Dependent:\n    dependency: SomeDependency\n\n\ncontext = Context()\nwith context:\n    mock_dependency = mock(SomeDependency)\n    mock_dependency.method.return_value = 'some mocked value'\n    instance = Dependent()\n    assert instance.dependency is mock_dependency\n    assert instance.dependency.method() == 'some mocked value'\n\nwith context:\n    instance = Dependent()\n    assert instance.dependency is not mock_dependency\n    assert isinstance(instance.dependency, SomeDependency)\n```\n`mock` uses its argument to spec the injected instance of `MagicMock`. This means\nthat attempting to call methods that are not defined by the mocked `Component`\nleads to an error\n```python\nwith context:\n    mock_dependency = mock(SomeDependency)\n    mock_dependency.no_method()  # raises: AttributeError: Mock object has no attribute 'no method'\n```\nNote that `mock` will only mock requests of the\nexact type supplied as its argument, but not requests of\nmore or less specific types\n```python\nfrom unittest.mock import MagicMock\n\n@dependency\nclass Super:\n    pass\n\n\nclass Sub(Super):\n    pass\n\n\nclass SubSub(Sub):\n    pass\n\n\n@inject\nclass NeedsSuper:\n    injected: Super\n\n\n@inject\nclass NeedsSub:\n    injected: Sub\n\n\n@inject\nclass NeedsSubSub:\n    injected: SubSub\n\n\nwith Context():\n    mock(Sub)\n    needs_super = NeedsSuper()\n    needs_sub = NeedsSub()\n    needs_subsub = NeedsSubSub()\n    assert isinstance(needs_super.injected, Super)\n    assert isinstance(needs_sub.injected, MagicMock)\n    assert isinstance(needs_subsub.injected, SubSub)\n```\n## `match`\n`match` is small utility function for matching `Context` instances\nwith values of an environment variable.\n```python\n# my_script.py\nfrom serum import match, dependency, Context, inject\n\n@dependency\nclass BaseDependency:\n    def method(self):\n        raise NotImplementedError()\n\n\nclass ProductionDependency(BaseDependency):\n    def method(self):\n        print('Production!')\n\n\nclass TestDependency(BaseDependency):\n    def method(self):\n        print('Test!')\n\n\n@inject\ndef f(dependency: BaseDependency):\n    dependency.method()\n\n\ncontext = match(\n    environment_variable='MY_SCRIPT_ENV', \n    default=Context(ProductionDependency),\n    PROD=Context(ProductionDependency),\n    TEST=Context(TestDependency)\n)\n\nwith context:\n    f()\n```\n```\n> python my_script.py\nProduction!\n```\n```\n> MY_SCRIPT_ENV=PROD python my_script.py\nProduction!\n```\n```\n> MY_SCRIPT_ENV=TEST python my_script.py\nTest!\n```\n## IPython Integration\nIt can be slightly annoying to import some `Context` and start it as a\ncontext manager in the beginning of every IPython session. \nMoreover, you quite often want to run an IPython REPL in a special context,\ne.g to provide configuration that is normally supplied through command line\narguments in some other way.\n\nTo this end `serum` can act as an IPython extension. To activate it,\nadd the following lines to your `ipython_config.py`:\n```python\nc.InteractiveShellApp.extensions = ['serum']\n```\nFinally, create a file named `ipython_context.py` in the root of your project. In it,\nassign the `Context` instance you would like automatically started to a global\nvariable named `context`:\n```python\n# ipython_context.py\nfrom serum import Context\n\n\ncontext = Context()\n```\nIPython will now enter this context automatically in the beginning of\nevery REPL session started in the root of your project.\n# Why?\nIf you've been researching Dependency Injection frameworks for python,\nyou've no doubt come across this opinion:\n\n>You dont need Dependency Injection in python. \n>You can just use duck typing and monkey patching!\n\nThe position behind this statement is often that you only need Dependency \nInjection in statically typed languages.\n\nIn truth, you don't really _need_ Dependency Injection in any language, \nstatically typed or otherwise. \nWhen building large applications that need to run in multiple environments however,\nDependency Injection can make your life a lot easier. In my experience,\nexcessive use of monkey patching for managing environments leads to a jumbled\nmess of implicit initialisation steps and `if value is None` type code.\n\nIn addition to being a framework, I've attempted to design `serum` to encourage\ndesigning classes that follow the Dependency Inversion Principle:\n\n> one should \u201cdepend upon abstractions, _not_ concretions.\"\n\nThis is achieved by letting inheritance being the principle way of providing\ndependencies and allowing dependencies to be abstract.\n\n\n",
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