Metadata-Version: 2.1
Name: wirinj
Version: 0.7.2
Summary: A comfy dependency injection library.
Home-page: https://github.com/davidcim/wirinj
Author: David Cimadevilla
Author-email: dev.davidcim@gmail.com
License: UNKNOWN
Description: Wirinj
        ======
        A comfy dependency injection library for Python 3.
        
        Why choose wirinj
        -----------------------------------------
        
        - Minimal boiler plate code.
        - Injection via `__init__` or via _attributes_.
        - Dependencies automatically detected through [reflection](https://en.wikipedia.org/wiki/Reflection_(computer_programming)#Python).
        - No naming conventions required.
        - [No factories needed](#factories) to create new instances.
        - Friendly with [IDE](https://en.wikipedia.org/wiki/Integrated_development_environment) 's [code completion](https://www.jetbrains.com/help/pycharm/auto-completing-code.html#) (e.g. with [PyCharm](https://www.jetbrains.com/pycharm/)).
        - [Autowiring](#autowiring) option.
        - [Injection reports](#injection-reports) to easily debug dependency problems.
        - Simple but powerful wiring configuration.
        - Open and extendable architecture.
        
        Installation
        ------------
        
        Python >= `3.6`
        
        Tested with Python `3.6`, `3.7` and `3.8`.
        
        ```shell
        $ pip install wirinj
        ```
        
        Table of Contents
        =================
        
          * [How to use it](#how-to-use-it)
          * [Code completion on the IDE](#code-completion-on-the-ide)
          * [Injection types](#injection-types)
             * [Into attributes](#into-attributes)
             * [Into __init__ arguments](#into-__init__-arguments)
          * [Factories](#factories)
          * [Dependency definitions](#dependency-definitions)
             * [Definition format](#definition-format)
             * [dict keys](#dict-keys)
             * [dict values](#dict-values)
             * [Custom dependency builders](#custom-dependency-builders)
             * [Configuring injection for specific classes](#configuring-injection-for-specific-classes)
             * [Custom-built dependencies](#custom-built-dependencies)
             * [Custom-built dependencies with arguments](#custom-built-dependencies-with-arguments)
             * [Split definitions](#split-definitions)
          * [Autowiring](#autowiring)
             * [Heuristic rules](#heuristic-rules)
             * [Autowiring for production](#autowiring-for-production)
             * [Autowiring report](#autowiring-report)
             * [<em>No singletons</em> option](#no-singletons-option)
          * [Injection reports](#injection-reports)
             * [Debugging the injection](#debugging-the-injection)
             * [Missing dependencies](#missing-dependencies)
             * [Instance error](#instance-error)
          * [A complete injection example](#a-complete-injection-example)
        
        
        How to use it
        -------------
        
        Example ([autowiring.py](examples/basic/autowiring.py)):
        
        ```python
        ...
        
        class MyService:
            ...
        
        class MyObject:
            my_service: MyService = INJECTED
            my_config: str = INJECTED
        
            def __init__(self, param):
                ...
        
        
        config = {
            'my_config': 'some conf',
        }
        
        
        # Use a function to get access to the root dependencies
        @inject(Definitions(config), Autowiring())
        def do(
                my_service: MyService,
                my_object_factory: Type[MyObject]
        ):
            print(my_service)
        
            my_object1 = my_object_factory(10)
            print(my_object1)
        
        
        # Inject and run it
        do()
        ```
        Output:
        ```
        my_service = <MyService>
        my_object1 = <MyObject> -> my_config: "some conf", param: 10, my_service: <MyService>
        ```
        ### Explanation of the example above
        `MyService` and `MyObject` are the two user classes.
        
        Attributes `my_service` and `my_config` are set with the constant `INJECTED` to indicate that they must be injected.
        
        The function named `do`, or any other name you choose, will contain the code inside the injection context with access to any required dependency. This function is decorated with `@inject` which will inject the dependencies into the function parameters. `@inject` takes as arguments one or more dependency sources. In this case, a `Definition` for the static config values and an `Autowiring` to automatically instantiate the required objects. `wirinj` will use this ordered list of sources to locate any required dependency.
        
        As the first parameter in the function `do` (`my_service`) is not defined in the first source (`config`), the dependency will be requested to the second one (`Autowiring`) which will lazily instantiate a `MyService` object. The class is inferred from the type annotation of the parameter. By default `Autowiring` will make the object a singleton and therefore any subsequent request for this class will get the same unique instance. 
        
        The second parameter (`my_object_factory`) is annotated as `Type[MyObject]`. `Type[]` is part of the standard  [typing](https://docs.python.org/3/library/typing.html#typing.Type) library. It indicates that the parameter is not expected to contain an object of class `MyObject` but the class `MyObject` itself or a subclass of it. Therefore you may use `my_object_factory` variable the same way you would use `MyObject` class. In the body of the function `do`, this parameter is called to instantiate a new `MyObject`. By calling `my_object_factory` instead of `MyObject` you make `wirinj` to inject all its required dependencies during the instantiation:
         ```python
        # This instantiate a MyObject but, as expected, nothing is injected.
        obj = MyObject(10)
        
        # This is the same but its dependencies are automatically injected BEFORE running __init__ 
        obj = my_object_factory(10)
        ```
        
        The last line runs the function `do` with no parameters. The `@inject` decorator will inject them from the dependency sources.
        
        Code completion on the IDE
        --------------------------
        
        If you are using an [IDE](https://en.wikipedia.org/wiki/Integrated_development_environment) such as [PyCharm](https://www.jetbrains.com/pycharm/), you will notice that [code completion](https://www.jetbrains.com/help/pycharm/auto-completing-code.html#) will work as expected in the previous example even for the factory.
        
        ![](img/code_inspect.png)
        
        
        Injection types
        ---------------
        
        ### Into attributes
        
        Example ([attribute_injection.py](examples/injection_types/attribute_injection.py)):
        
        ```python
        class Cat:
            feeder: Feeder = INJECTED
        
            def __init__(self, color, weight):
                ...
        
        @inject(...)
        def fn(factory: Type[Cat]):
            cat = factory('blue', 12)
        ```
        
        When you call the factory:
         0. The attributes set to `INJECTED` are located and injected.
         0. The `__init__` method is called.
        
        
        ### Into `__init__` arguments
        
        Example ([init_injection.py](examples/injection_types/init_injection.py)):
        
        ```python
        class Cat:
            def __init__(self, color, weight, feeder: Feeder = INJECTED):
                ...
        
        @inject(...)
        def fn(factory: Type[Cat]):
            cat = factory('blue', 12)
        ...
        ```
        
        - `color` and `weight` are passed to `__init__`.
        - `feeder` is injected.
        
        For `__init__` injections, it is not required to set `INJECTED` as a default value. Any missing argument not passed to the constructor will be injected too. This way you can inject into third party classes whose code is not under your control. However, if you can assign `INJECTED` as a default value, the IDE won't complain about a missing argument and at the same time you will get a `MissingDependenciesError` if the dependency is missing which is helpful to early detect dependency issues.
        
        Factories
        ---------
        I have already explained in the [first example](#how-to-use-it) of this README how to use factories. Now, I'm going to elaborate on that a little more.
        
        Pay attention to the function `func` and its argument `cat_class` in this example:
        
        ```python
        from typing import Type
        
        class Cat:
            pass
        
        class BlackCat(Cat):
            pass
        
        def func(cat_class: Type[Cat]):
            return cat_class()
        
        print('Cat: ', func(Cat))
        print('BlackCat: ', func(BlackCat))
        ```
        
        Output:
        ```
        Cat:  <__main__.Cat object at 0x7fc458bc7588>
        BlackCat:  <__main__.BlackCat object at 0x7fc458bc7588>
        ```
        
        Note that you pass a class and not an object as an argument.
        
        `Type[Cat]`, as described in the [typing](https://docs.python.org/3/library/typing.html#typing.Type) library docs, represents the class `Cat` or a subclass of it. A parameter annotated with `Type[]` expects to receive a class and not an object. In the body of the function, the parameter can be used the same way as its subscribed class would be used.
        
        Example ([factory.py](examples/basic/factory.py)):
        
        ```python
        from typing import Type
        
        class Cat:
            def __init__(self, sound):
                ...
        
        @inject(...)
        def fn(cat_factory: Type[Cat]):
            cat = cat_factory('Meow')
            print('cat:', cat)
        
        fn()
        ```
        By using the `Type[]` annotation, the IDE recognizes the parameter as it was the original class but with the difference that any newly created object will be automatically injected.
        
         ```python
        # This instantiate a Cat object but, as expected, nothing is injected.
        cat = Cat('Meow')
        
        # This is the same but its dependencies are automatically injected BEFORE running __init__ 
        cat = cat_factory('Meow')
        ```
        
        You have both things: the injection is enabled and the IDE completion is fully functional:
        
        ![](img/code_inspect_cat.png)
        
        
        Dependency definitions
        ----------------------
        
        In previous examples, the wiring configuration has been relegated to the automatic `Autowiring` class. However you will gain control by explicity defining how your dependencies have to be met. The general way to do this would be something like this:
        
        ```python
        defs = {
            Cat: Instance(),
            'dog': Singleton(Dog),
        }
        
        @inject(Definitions(defs))
        ```
        
        The `Definitions` class allows you to configure the wiring of your classes according to one or more definition `dict` parameters (`defs` in the example). The first definitions take precedence.
        
        ### Definition format
        
        One or several `dict` arguments passed to the `Definition` class define your dependency configuration. 
        Each _key_ represents an argument being injected.
        The _value_ represents how is it injected:
        
        ### dict keys
        
        - If the _key_ is a `class`, it will match the argument's __type__ annotation.
        E.g.: the first key in the example above causes any argument of type `Cat`, no matter its name, to be injected with a new _instance_ of `Cat`.
        
        - If the _key_ is a `string` it will match the argument __name__.
        E.g.: the second key causes any argument with name `'dog'` to be injected with a unique `Dog` instance.
        Here, as the class can't be inferred from the key, you need to explicitly provide the class as an argument: `'dog': Singleton(Dog)`.  
        
        ### dict values
        
        Each _value_ in the `dict` can be:
        
        - A _literal_ value you want to be injected. E.g. `'db_name': 'my-db'`.
        - `Instance`: inject a new instance each time.
        - `Singleton`: inject the same unique instance every time.
        - `Factory`: inject a factory object that can be called to create new injected objects dynamically.
        - `CustomInstance`: similar to `Instance` but you provide a custom function to have full control over instantiation.
        - `CustomSingleton`: similar to `Singleton` but you provide a custom function which will create the object.
        - Any other user defined subclasses of `DependencyBuilder` or `Dependency`.
        
        Example ([definition_types.py](examples/basic/definition_types.py)):
        
        ```python
        class House:
            pass
        
        
        class Cat:
            pass
        
        
        class Dog:
            pass
        
        
        def dog_builder():
            """ Custom instantiation """
            dog = Dog()
            dog.random = randint(50, 100)
            return dog
        
        
        defs = {
            House: Singleton(),
            Cat: Instance(),
            Type[Cat]: Factory(),
            Dog: CustomInstance(dog_builder),
            Type[Dog]: Factory(),
        }
        
        
        @inject(Definitions(defs))
        def fn(house: House, cat_factory: Type[Cat], dog_factory: Type[Dog]):
            cat = cat_factory()
            dog = dog_factory()
        
            print('house:', house)
            print('cat:', cat)
            print('dog:', dog)
        
        
        fn()
        ```
        
        ### Custom dependency builders 
        
        `Instance`, `Singleton` and `Factory` accept an optional class argument to indicate the class of the object to be created.
        There are two use cases where you need to pass the class:
        - The _key_ is a `string` and therefore the dependency class is undefined.
        - The attribute or argument being injected is annotated with a _base class_ but you want to provide a specific _subclass_ of it.
        
        Example of both use cases ([explicit_class.py](examples/basic/explicit_class.py)):
        
        ```python
        class Pet:
            pass
            
        class Cat(Pet):
            pass
            
        class Dog(Pet):
            pass
        
        defs = {
            'cat': Singleton(Cat),
            Pet: Singleton(Dog),
        }
        
        @inject(Definitions(defs))
        def fn(cat, pet: Pet):
            print('cat is a', cat.__class__.__name__)
            print('pet is a', pet.__class__.__name__)    
        fn()
        ```
        
        Output:
        ```
        cat is a Cat
        pet is a Dog
        ```
        
        ### Configuring injection for specific classes 
        
        ```python
        class Nail:
            pass
            
        class Leg:
            def __init__(self, nail: Nail):
                pass
            
        class Cat:
            def __init__(self, leg: Leg):
                pass
        ```
        
        Imagine `wirinj` is injecting a `Cat` which requires a `Leg` which requires a `Nail`.
        The injector will gather:
         - First, the `Nail` that has no dependencies.
         - Then, the `Leg` with the `Nail` as an argument.
         - Finally, the `Cat` with the `Leg` as an argument.
        
        We can think of this process as a path: `Cat` -> nail:`Nail` -> leg:`Leg`.
        I call this the `instantiation path`. 
        
        You can explicitly specify a `instantiation path` constraint in the definition `dict`.
        
        Example ([instantiation_path.py](examples/basic/instantiation_path.py)):
        
        ```python
        class Animal:
            def __init__(self, sound):
                self.sound = sound
        
        class Dog(Animal):
            pass
            
        class Cat(Animal):
            pass
        
        class Cow(Animal):
            pass
        
        defs = {
            Dog: Instance(),
            Cat: Instance(),
            Cow: Instance(),
        
            (Dog, 'sound'): 'woof',
            (Cat, 'sound'): 'meow',
            'sound': '?',
        }
        
        @inject(Definitions(defs))
        def fn(cat: Cat, dog: Dog, cow: Cow):
            print('Cat:', cat.sound)
            print('Dog:', dog.sound)
            print('Cow:', cow.sound)
        
        fn()
        ```
        
        Output:
        
        ```
        Cat: meow
        Dog: woof
        Cow: ?
        ```
        
        To restrict a definition entry to a particular `instantiation path` we use a `tuple` in the __key__ part.
        This `tuple` must match the last entries in the `instantiation path`.
        
        For each `tuple` entry, a `string` refers to the argument __name__ and a `class` refers to the argument __type__ annotation. 
        
        If two entries match the required dependency, the more specific one will be chosen.
        
        ### Custom-built dependencies
        
        `Instance` and `Singleton` are used for simple class instantiation.
        When a custom process is required to create or locate the dependency, use `CustomInstance` or `CustomSingleton`.
        Both take a `function` as an argument.
        
        Example ([custom_build.py](examples/basic/custom_build.py)):
        
        ```python
        from random import randint
        
        from wirinj import CustomInstance, inject, Definitions
        
        
        class Cat:
            def __init__(self, color, weight):
                self.color = color
                self.weight = weight
        
            def __str__(self):
                return f'A {self.color} pounds {self.weight} cat.'
        
        
        def create_cat(color):
            return Cat(color, randint(4, 20))
        
        
        defs = {
            'color': 'blue',
            Cat: CustomInstance(create_cat),
        }
        
        
        @inject(Definitions(defs))
        def fn(cat1: Cat, cat2: Cat, cat3: Cat):
            print(cat1)
            print(cat2)
            print(cat3)
        
        
        fn()
        ```
        
        Output:
        
        ```
        A 11 pounds blue cat.
        A 5 pounds blue cat.
        A 14 pounds blue cat.
        ```
        
        
        ### Custom-built dependencies with arguments
        
        In the previous example, the object is instantiated without arguments,
        so all of its `__init__` arguments are injected from dependencies.
        
        If your constructor requires some arguments to be passed (__explicit arguments__) and others to be injected (__injection arguments__),
        I recommend to follow these rules:
        
        0. In the `__init__` method, put the _explicit arguments_ first and then the _injection arguments_.
        This allow you to use positional arguments when you create the object.
        
        0. Set the default value of the _injection arguments_ to `INJECTED`.
        This way the IDE [code completion](https://www.jetbrains.com/help/pycharm/auto-completing-code.html#) will not complain about missing arguments.
        Also, this is the only way you can have defaults in your _explicit arguments_ when they are followed by _injection arguments_. 
        
        0. About the builder function that you pass to `CustomInstance`, use the same name and position for the _explicit arguments_ as you use in the `__init__` method. 
        The rest of the arguments don't have to be related at all to the `__init__` arguments.
        Indeed, you can specify as many dependency arguments as you need to create the object.
        The injection process will inspect the function signature and will provide them.
        
        Example ([custom_build_with_args.py](examples/basic/custom_build_with_args.py)):
        
        ```python
        from random import randint
        from typing import Type
        
        from wirinj import CustomInstance, Factory, inject, Definitions
        
        
        class Cat:
            def __init__(self, name, color=None, weight=None):
                self.name = name
                self.color = color
                self.weight = weight
        
            def __str__(self):
                return f'{self.name} is a {self.color} pounds {self.weight} cat.'
        
        
        def create_cat(name, color):
            return Cat(name, color, randint(4, 20))
        
        
        defs = {
            'color': 'black',
            Cat: CustomInstance(create_cat),
            Type[Cat]: Factory(),
        }
        
        
        @inject(Definitions(defs))
        def fn(factory: Type[Cat]):
            cat = factory('Tom')
            print(cat)
            cat2 = factory('Sam')
            print(cat2)
        
        
        fn()
        ```
        
        Output:
        ```
        Tom is a 8 pounds black cat.
        Sam is a 14 pounds black cat.
        ```
        
        About the 3 arguments of `Cat`.`__init__`:
        - One comes from calling the factory.
        - Another one from the dependency configuration.
        - The third is generated by the custom creation function.
        
        
        ### Split definitions
        
        You can split the dependency configuration in several `dict` definitions.
        
        Example ([split_definitions.py](examples/basic/split_definitions.py)):
        
        ```python
        class Cat:
            sound: str = INJECTED
            weight: float = INJECTED
        
        config = {
            'sound': 'meow',
            'weight': 5,
        }
        
        wiring = {
            Cat: Instance(),
            Type[Cat]: Factory()
        }
        
        @inject(Definitions(config, wiring))
        def fn(...):
            ...
        ```
        
        `Definitions` accepts any number of definition `dict`s.
        
        
        Autowiring
        ----------
        
        You can add an `Autowiring` instance as a last resort to provide a dependency when it is undefined.
        The automatically created dependency will be of type `Instance`, `Singleton` or `Factory` dependening on the context.
        
        Example ([autowiring.py](examples/basic/autowiring.py)):
        
        ```python
        class MyService:
            def __str__(self):
                return '<MyService>'
        
        
        class MyObject:
            my_service: MyService = INJECTED
            my_config: str = INJECTED
            ...    
            
            def __init__(self, param):
                self.param = param
        
        
        config = {
            'my_config': 'some conf',
        }
        
        
        # Use a function to get access to the root dependencies
        @inject(Definitions(config), Autowiring())
        def do(
                my_service: MyService,
                my_object_factory: Type[MyObject]
        ):
            print(my_service)
        
            my_object1 = my_object_factory(10)
            print(my_object1)
        
        
        # Inject and run it
        do()
        ```
        
        Output:
        
        ```
        <MyService>
        <MyObject> -> my_config: "some conf", param: 10, my_service: <MyService>
        ```
        
        `my_config` is the only dependency explicitly defined. The 3 others fall back to `Autowiring` which will automatically create:
        - A `MyService` singleton.
        - A `Type[MyObject]` factory.
        - A `MyObject` instance when the factory is called.
        
        ### Heuristic rules
        
        `Autowiring` works only for arguments that have a _type annotation_:
        - If the annotation is a `class`, as with `dog: Dog` in the previous example, a _singleton_ will be generated.
        - If it is `Type[class]`, as with `horse_factory: Type[Horse]`, a _factory_ will be provided.
        - If the injection comes from a factory, as when `horse_factory()` is called, an _instance_ will be created.
        
        ### Autowiring for production
        
        In my opinion, this kind of _magic_ should not be used in production environments;
        you should not take the risk of leaving such important wiring decisions in the hands of an heuristic algorithm.
        
        Fortunately, you can use `AutowiringReport` class to easily convert the autowiring configuration into a regular dependency definition:
        
        ### Autowiring report
        
        It's quite simple to use; just pass an `AutowiringReport` instance to `Autowiring`:
        
        Example ([autowiring_report.py](examples/report/autowiring_report.py)):
        
        ```python
        report = AutowiringReport()
        
        @inject(Definitions(deps), Autowiring(report))
        def fn(cat: Cat, dog: Dog, horse_factory: Type[Horse]):
            ...    
        
        fn()
        
        print(report.get())
        ```
        
        Output:
        ```
        ...
        --------------- wirinj ---------------
        Autowiring report:
        
        Definitions({
            Dog: Singleton(),
            Type[Horse]: Factory(),
            Horse: Instance(),
        }),
        --------------------------------------
        ```
        
        Call `report.get()` to get the report.
        Review and copy the definitions to your configuration file, remove `Autowiring`, and you will be production ready.
          
        ### _No singletons_ option
        
        You may set `use_singletons` to `False` to force all dependencies to be injected as an `Instance`.
        
        ```python
        Autowiring(use_singletons=False)
        ```
          
        
        Injection reports
        -------------------
        
        During each injection process, a _dependency tree_ is built with all the dependencies that are being gathered.
        
        As you change your code, your dependency configuration can get out of sync.
        `wirinj` include reporting features that can help you to solve this dependency issues:
        
        ### Debugging the injection
        
        The injection process can be debugged to expose the creation order and the _dependency tree_.
        
        Take this composition of classes ([cat_example_classes.py](examples/report/cat_example_classes.py)) :
        
        ```python
        class Nail:
            pass
        
        class Leg:
            def __init__(self, nail1: Nail, nail2: Nail, nail3: Nail, nail4: Nail, nail5: Nail):
                pass
        
        class Mouth:
            pass
        
        class Ear:
            pass
        
        class Eye:
            pass
        
        class Head:
            def __init__(self, mouth: Mouth, ear1: Ear, ear2: Ear, eye1: Eye, eye2: Eye):
                pass
        
        class Body:
            pass
        
        class Tail:
            pass
        
        class Cat:
            def __init__(self, head: Head, body: Body, tail: Tail, leg1: Leg, leg2: Leg, leg3: Leg, leg4: Leg):
                pass
        ```
        
        We can debug the injection process just by setting the logging level to `DEBUG` and then, requesting a `Cat` from the `Injector`:
        
        Example ([injection_debug_report.py](examples/report/injection_debug_report.py)):
        
        ```python
        import logging
        
        logging.basicConfig(level=logging.DEBUG, format='%(message)s')
        
        inj = Injector(Autowiring(use_singletons=False))
        
        cat = inj.get(Cat)
        ```
        Note that we are replacing all the dependency definitions by a simple `Autowiring()`.
        We pass the argument `use_singletons=False` to force all dependencies to be injected as an `Instance`.
        By default `Autowiring` generates `Singleton` dependencies and, in this case, we don't want all the legs of the `Cat` to be the same.
        
        The code above returns this:
        ```
        --------------- wirinj ---------------
                mouth:Mouth
                ear1:Ear
                ear2:Ear
                eye1:Eye
                eye2:Eye
            head:Head
            body:Body
            tail:Tail
                nail1:Nail
                nail2:Nail
                nail3:Nail
                nail4:Nail
                nail5:Nail
            leg1:Leg
                nail1:Nail
                nail2:Nail
                nail3:Nail
                nail4:Nail
                nail5:Nail
            leg2:Leg
                nail1:Nail
                nail2:Nail
                nail3:Nail
                nail4:Nail
                nail5:Nail
            leg3:Leg
                nail1:Nail
                nail2:Nail
                nail3:Nail
                nail4:Nail
                nail5:Nail
            leg4:Leg
        :Cat
        --------------------------------------
        ```
        You can see how all the dependencies are gathered, and in which order.
        The final object is the requested `Cat` object.
        
        ### Missing dependencies
        
        Injection doesn't stop when a dependency is missing.
        It continues building the _dependency tree_ as far as it can.
        This makes it possible to fix several dependency issues in one shot.
        
        If one ore more dependencies are missing, an `ERROR` level report will be logged.
        Therefore, you don't need to change the `logging` level to get it; just look above the _error traceback_ after a dependency exception.
        
        Example ([missing_dependencies_report.py](examples/report/missing_dependencies_report.py)):
        
        ```python
            from examples.report.cat_example_classes import Cat, Head
            from wirinj import Injector, Definitions, Instance
            
            inj = Injector(Definitions({
                Cat: Instance(),
                Head: Instance(),
            }))
            cat2 = inj.get(Cat)
        ```
        
        In the example above, we only define the wiring for `Cat` and `Head`.
        All the other dependencies, such as `Mouth`, `Ear`, `Eye`, etc, are undefined.
        
        After running the example, we get:
        ```
        --------------- wirinj ---------------
        Missing dependencies:
                mouth:Mouth *** NotFound ***
                ear1:Ear *** NotFound ***
                ear2:Ear *** NotFound ***
                eye1:Eye *** NotFound ***
                eye2:Eye *** NotFound ***
            head:Head
            body:Body *** NotFound ***
            tail:Tail *** NotFound ***
            leg1:Leg *** NotFound ***
            leg2:Leg *** NotFound ***
            leg3:Leg *** NotFound ***
            leg4:Leg *** NotFound ***
        :Cat
        --------------------------------------
        Traceback (most recent call last):
        ...
        wirinj.errors.MissingDependenciesError: Missing dependencies.
        ```
        
        Notice that, although the first dependency, `Mouth`, failed to be satisfied, the injection process continues in order to gather as much information as possible about the missing dependencies.
        
        With this report, it becomes clear which classes are undefined, and what needs to be added in the injection configuration.
        
        ### Instance error
        
        If an exception is raised during the instantiation of any of the dependencies,
        you will not get the `dependency tree` logs as it happens when a dependency is missing.
        
        You'll need to track the stack trace to fix the problem.
        However, there is a task planned in the [TO-DO](TODO.md) list to log the `dependency tree` in these cases too.
        
        
        
        
        ### A complete example
        
        This silly example aims to illustrate several aspects of the `wirinj` library.
        
        The two main classes, `Bob` and `Mike`, extend `PetDeliveryPerson`.
        They are used to deliver pets to the client using one or more vehicles.
        Whenever a `Vehicle` is needed, it is built in advance.
        
        While `Bob` uses his only vehicle by repeating the route several times, `Mike` builds a fleet of autonomous vehicles to deliver all the pets in one trip.
        
        The classes ([pet_delivery/classes.py](examples/pet_delivery/classes.py)):
        
        ```python
        class Pet:
            def __deps__(self, sound: str, weight):
                self.sound = sound
                self.weight = weight
        
            @deps
            def __init__(self, gift_wrapped):
                self.gift_wrapped = gift_wrapped
        
            def cry(self):
                return self.sound.lower() if self.gift_wrapped else self.sound.upper()
        
        
        class Cat(Pet):
            pass
        
        
        class Dog(Pet):
            pass
        
        
        class Bird(Pet):
            pass
        
        
        class Part:
            def __deps__(self, mount_sound):
                self.mount_sound = mount_sound
        
            @deps
            def __init__(self):
                pass
        
            def mount(self):
                return self.mount_sound
        
        
        class Engine(Part):
            pass
        
        
        class Plate(Part):
            pass
        
        
        class Wheel(Part):
            pass
        
        
        class Container(Part):
            pass
        
        
        class VehicleBuilder:
        
            def __deps__(self,
                         engine_factory: Type[Engine],
                         plate_factory: Type[Plate],
                         wheel_factory: Type[Wheel],
                         container_factory: Type[Container],
                         ):
                self.engine_factory = engine_factory
                self.plate_factory = plate_factory
                self.wheel_factory = wheel_factory
                self.container_factory = container_factory
        
            @deps
            def __init__(self):
                pass
        
            def build(self, recipe: Dict):
                parts = []  # type: List[Part]
                parts += [self.engine_factory() for _ in range(recipe.get('engines', 0))]
                parts += [self.plate_factory() for _ in range(recipe.get('plates', 0))]
                parts += [self.wheel_factory() for _ in range(recipe.get('wheels', 0))]
                parts += [self.container_factory() for _ in range(recipe.get('containers', 0))]
        
                mounting = ''
                for part in parts:
                    mounting += ' ' + part.mount()
        
                return mounting
        
        
        class Vehicle:
            def __deps__(self, builder: VehicleBuilder, recipe: Dict, max_load_weight):
                self.builder = builder
                self.recipe = recipe
                self.max_load_weight = max_load_weight
        
            @deps
            def __init__(self):
                self.pets = []
                self.build()
        
            def go(self, miles):
                logger.info('{} goes {} miles'.format(self.__class__.__name__, miles))
        
            def come_back(self):
                logger.info('{} commes back'.format(self.__class__.__name__))
        
            def build(self):
                logger.info('{} is built: {}'.format(
                    self.__class__.__name__,
                    self.builder.build(self.recipe)
                ))
        
            def get_available_load(self):
                return self.max_load_weight - sum(pet.weight for pet in self.pets)
        
        
        class Car(Vehicle):
            pass
        
        
        class Van(Vehicle):
            pass
        
        
        class Truck(Vehicle):
            pass
        
        
        class PetLoader:
        
            def upload(self, pets: List[Pet], vehicle: Vehicle):
                info = 'Uploading to the {}:'.format(vehicle.__class__.__name__.lower())
                while pets:
                    pet = pets.pop()
                    if vehicle.get_available_load() >= pet.weight:
                        vehicle.pets.append(pet)
                        info += ' ' + pet.__class__.__name__
                    else:
                        pets.append(pet)
                        break
                logger.info(info)
        
            def download(self, vehicle):
                logger.info('{} pets delivered'.format(len(vehicle.pets)))
                vehicle.pets = []
        
        
        class PetPicker:
        
            def __deps__(self, pet_store: Type[Pet]):
                self.pet_store = pet_store
        
            @deps
            def __init__(self):
                # raise Exception('HORROR!!!!')
                pass
        
            def pick(self, qty, gift_wrapped):
                info = 'Picking pets up: '
                pets = []
                for _ in range(qty):
                    pet = self.pet_store(gift_wrapped)
                    info += ' ' + pet.cry()
                    pets.append(pet)
                logger.info(info)
                return pets
        
        
        class PetDeliveryPerson:
        
            @deps
            def __init__(self):
                pass
        
            def deliver(self, pet_qty, miles, gift_wrapped):
                pass
        
        
        class Bob(PetDeliveryPerson):
            """Bob builds a car and deliver pets in his vehicle repeating the route several times."""
        
            def __deps__(self, vehicle: Vehicle, pet_picker: PetPicker, pet_loader: PetLoader):
                self.vehicle = vehicle
                self.pet_picker = pet_picker
                self.pet_loader = pet_loader
        
            def deliver(self, pet_qty, miles, gift_wrapped):
                # Pick up pets
                pets = self.pet_picker.pick(pet_qty, gift_wrapped)
        
                # Bob owns one vehicle only
                while pets:
                    self.pet_loader.upload(pets, self.vehicle)
                    self.vehicle.go(miles)
                    self.pet_loader.download(self.vehicle)
                    self.vehicle.come_back()
        
        
        class Mike(PetDeliveryPerson):
            """Mike builds several autonomous vehicles and use them to deliver the pets all together"""
        
            def __deps__(self, vehicle_factory: Type[Vehicle], pet_picker: PetPicker, pet_loader: PetLoader):
                self.vehicle_factory = vehicle_factory
                self.pet_picker = pet_picker
                self.pet_loader = pet_loader
        
            @deps
            def __init__(self):
                super().__init__()
                self.vehicles = []  # type: List[Vehicle]
        
            def get_vehicle(self):
                if self.vehicles:
                    return self.vehicles.pop()
                else:
                    return self.vehicle_factory()
        
            def park_vehicles(self, vehicles):
                self.vehicles += vehicles
        
            def deliver(self, pet_qty, miles, gift_wrapped):
        
                # Pick up pets
                pets = self.pet_picker.pick(pet_qty, gift_wrapped)
        
                # Get vehicles and upload them
                vehicles = []
                while pets:
                    vehicle = self.get_vehicle()
                    vehicles.append(vehicle)
                    self.pet_loader.upload(pets, vehicle)
        
                # Go
                for vehicle in vehicles:
                    vehicle.go(miles)
        
                # Deliver pets
                for vehicle in vehicles:
                    self.pet_loader.download(vehicle)
        
                # Come back
                for vehicle in vehicles:
                    vehicle.come_back()
        
                # Park
                self.park_vehicles(vehicles)
        ```
        
        Injection definitions ([pet_delivery/defs.py](examples/pet_delivery/defs.py)):
        
        ```python
        pet_defs = {
            Dog: Instance(),
            Cat: Instance(),
            Bird: Instance(),
        
            (Dog, 'sound'): 'Woof',
            (Dog, 'weight'): 10,
        
            (Cat, 'sound'): 'Meow',
            (Cat, 'weight'): 5,
        
            (Bird, 'sound'): 'Chirp',
            (Bird, 'weight'): 0.1,
        }
        
        
        vehicle_defs = {
            Engine: Instance(),
            Plate: Instance(),
            Wheel: Instance(),
            Container: Instance(),
        
            Type[Engine]: Factory(),
            Type[Plate]: Factory(),
            Type[Wheel]: Factory(),
            Type[Container]: Factory(),
        
            VehicleBuilder: Singleton(),
        
            (Engine, 'mount_sound'): 'RRRRoarrr',
            (Plate, 'mount_sound'): 'plaf',
            (Wheel, 'mount_sound'): 'pffff',
            (Container, 'mount_sound'): 'BLOOOOM',
        
            Car: Instance(),
            (Car, 'max_load_weight'): 10,
            (Car, 'recipe'): {
                'engines': 1,
                'plates': 6,
                'wheels': 4,
            },
        
            Van: Instance(),
            (Van, 'max_load_weight'): 50,
            (Van, 'recipe'): {
                'engines': 1,
                'plates': 8,
                'wheels': 4,
            },
        
            Truck: Instance(),
            (Truck, 'max_load_weight'): 200,
            (Truck, 'recipe'): {
                'engines': 1,
                'plates': 20,
                'wheels': 12,
                'container': 1,
            },
        }
        
        common_defs = {
            PetPicker: Singleton(),
            PetLoader: Singleton(),
        
            Bob: Singleton(),
            Mike: Singleton(),
        }
        ```
               
        Running the app ([pet_delivery/example_1.py](examples/pet_delivery/example_1.py)):
        
        ```python
        world_one_defs = {
            (Bob, Vehicle): Singleton(Car),
            (Bob, PetPicker, Type[Pet]): Factory(Bird),
        
            (Mike, Type[Vehicle]): Factory(Van),
            (Mike, PetPicker, Type[Pet]): Factory(Cat),
        }
        
        world_one = Definitions(
            pet_defs,
            vehicle_defs,
            common_defs,
            world_one_defs,
        )
        
        logging.basicConfig(format='%(message)s', level=logging.INFO)
        
        @inject(world_one)
        def do(bob: Bob, mike: Mike):
            bob.deliver(100, 5, False)
            bob.deliver(50, 200, True)
        
            mike.deliver(20, 1000, True)
        
        do()
        ```
        
        Running the same app with another wiring configuration ([pet_delivery/example_2.py](examples/pet_delivery/example_2.py)):
        
        ```python
        world_two_defs = {
            (Bob, Vehicle): Singleton(Van),
            (Bob, PetPicker, Type[Pet]): Factory(Cat),
        
            (Mike, Type[Vehicle]): Factory(Truck),
            (Mike, PetPicker, Type[Pet]): Factory(Dog),
        }
        
        world_two = Definitions(
            pet_defs,
            vehicle_defs,
            common_defs,
            world_two_defs,
        )
        
        logging.basicConfig(format='%(message)s', level=logging.INFO)
        
        @inject(world_two)
        def do(bob: Bob, mike: Mike):
            bob.deliver(100, 5, False)
            bob.deliver(50, 200, True)
        
            mike.deliver(20, 1000, True)
        
        do()
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
