Metadata-Version: 2.1
Name: implements
Version: 0.3.0
Summary: Pythonic interfaces using decorators
Home-page: http://implements.readthedocs.io
Author: Kamil Sindi <ksindi@ksindi.com>
Maintainer: Kamil Sindi
Maintainer-email: ksindi@ksindi.com
License: Apache License, Version 2.0
Keywords: implements,interfaces
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: setuptools-scm (>=1.15.0)

Implements
==========

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    :alt: Build Status
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*Pythonic interfaces using decorators*

Decorate your implementation class with `@implements(<InterfaceClass>)`.
That's it!. `implements` will ensure that your implementation satisfies
attributes, methods and their signatures as defined in your interface.

Moreover, interfaces are enforced via composition. Implementations
don't inherit interfaces. Your MROs remain untouched and interfaces
are evaluated early during import instead of class instantiation.

Install
-------

Implements is available on PyPI and can be installed with `pip <https://pip.pypa.io>`_::

    pip install implements

Note Python 3.6+ is required as it relies on new features of `inspect` module.

Advantages
----------

1. `Favor composition over inheritance <https://en.wikipedia.org/wiki/Composition_over_inheritance>`_.

2. Inheriting from multiple classes can be problematic, especially when the superclasses have the same method name but different signatures. Implements will throw a descriptive error if that happens to ensure integrity of contracts.

3. The decorators are evaluated at import time. Any errors will be raised then and not when an object is instantiated or a method is called.

4. It's cleaner. Using decorators makes it clear we want shared behavior. Also, arguments are not allowed to be renamed.

Usage
-----

With _implements_, implementation classes and interface classes must have their own independent class hierarchies. Unlike common patterns, the implementation class must not inherit from an interface class. From version ``0.3.0`` and onwards, this condition is checked automatically and an error is raised on a violation.


.. code-block:: python

    from implements import Interface, implements


    class Duck:
        def __init__(self, age):
            self.age = age


    class Flyable(Interface):
        @staticmethod
        def migrate(direction):
            pass

        def fly(self) -> str:
            pass


    class Quackable(Interface):
        def fly(self) -> bool:
            pass

        def quack(self):
            pass


    @implements(Flyable)
    @implements(Quackable)
    class MallardDuck(Duck):
        def __init__(self, age):
            super(MallardDuck, self).__init__(age)

        def migrate(self, dir):
            return True

        def fly(self):
            pass


The above would throw the following errors:

.. code-block:: python

    NotImplementedError: 'MallardDuck' must implement method 'fly((self) -> bool)' defined in interface 'Quackable'
    NotImplementedError: 'MallardDuck' must implement method 'quack((self))' defined in interface 'Quackable'
    NotImplementedError: 'MallardDuck' must implement method 'migrate((direction))' defined in interface 'Flyable'

You can find a more detailed example in ``example.py`` and by looking at ``tests.py``.

Justification
-------------

There are currently two idiomatic ways to rewrite the above example.

The first way is to write base classes with mixins raising ``NotImplementedError`` in each method.

.. code-block:: python

    class Duck:
        def __init__(self, age):
            self.age = age


    class Flyable:
        @staticmethod
        def migrate(direction):
            raise NotImplementedError("Flyable is an abstract class")

        def fly(self) -> str:
            raise NotImplementedError("Flyable is an abstract class")


    class Quackable:
        def fly(self) -> bool:
            raise NotImplementedError("Quackable is an abstract class")

        def quack(self):
            raise NotImplementedError("Quackable is an abstract class")


    class MallardDuck(Duck, Quackable, Flyable):

        def __init__(self, age):
            super(MallardDuck, self).__init__(age)

        def migrate(self, dir):
            return True

        def fly(self):
            pass

But there are a couple drawbacks implementing it this way:

1. We would only get a ``NotImplementedError`` when calling ``quack`` which can happen much later during runtime. Also, raising ``NotImplementedError`` everywhere looks clunky.

2. It's unclear without checking each parent class where super is being called.

3. Similarly the return types of ``fly`` in ``Flyable`` and ``Quackable`` are different. Someone unfamiliar with Python would have to read up on `Method Resolution Order <https://www.python.org/download/releases/2.3/mro/>`_.

4. The writer of ``MallardDuck`` made method ``migrate`` an instance method and renamed the argument to ``dir`` which is confusing.

5. We really want to be differentiating between behavior and inheritance.

The advantage of using implements is it looks cleaner and you would get errors at import time instead of when the method is actually called.

Another way is to use abstract base classes from the built-in ``abc`` module:

.. code-block:: python

    from abc import ABCMeta, abstractmethod, abstractstaticmethod


    class Duck(metaclass=ABCMeta):
        def __init__(self, age):
            self.age = age


    class Flyable(metaclass=ABCMeta):
        @abstractstaticmethod
        def migrate(direction):
            pass

        @abstractmethod
        def fly(self) -> str:
            pass


    class Quackable(metaclass=ABCMeta):
        @abstractmethod
        def fly(self) -> bool:
            pass

        @abstractmethod
        def quack(self):
            pass


    class MallardDuck(Duck, Quackable, Flyable):
        def __init__(self, age):
            super(MallardDuck, self).__init__(age)

        def migrate(self, dir):
            return True

        def fly(self):
            pass


Using abstract base classes has the advantage of throwing an error earlier
on instantiation if a method is not implemented; also, there are static analysis
tools that warn if two methods have different signatures. But it doesn't solve
issues 2-4 and implements will throw an error even earlier in import.
It also in my opinion doesn't look pythonic.

Credit
------

Implementation was inspired by a `PR <https://github.com/pmatiello/python-interface/pull/1/files>`_ of @elifiner.

Test
----

Running unit tests::

    make test

Running linter::

    make lint

Running tox::

    make test-all

License
-------

Apache License v2


