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Ad hoc polymorphism for Python classes!

Project description

Installation

pip install polymorphism

polymorphism support python 3.4+

Usage

To use the polymorphism simply inherit from the Polymorphism class:

from polymorphism import Polymorphism


class Simple(Polymorphism):
    def calc(self, x: int, y: int) -> None:
        pass

    def calc(self, x: float, y: float) -> None:
        pass

Or use it as metaclass:

from polymorphism import PolymorphismMeta

class Simple(metaclass=PolymorphismMeta):
    ...

Sometimes adding another class to the inheritance is undesirable, then you can use the overload decorator:

from polymorphism import overload


class Simple(Polymorphism):
    @overload
    def calc(self, x: int, y: int) -> None:
        pass

    @calc.overload
    def calc(self, x: float, y: float) -> None:
        pass

The only difference between using a decorator and inheriting it is checking for method shading. With overload the next example will not raise exception:

from polymorphism import overload


class Simple(Polymorphism):
    @overload
    def calc(self, x: int, y: int) -> None:
        pass

    calc = 5

And calc would be only the attribute.

Why?

The idea to implement polymorphism is not new. Many libraries implement this idea. Even the standard library has an implementation.

But they do not support use with classes or standard type annotation.

The basic idea of the implementation was inspired by the great book Python Cookbook 3rd Edition by David Beazley and Brian K. Jones. But the implementation in the book did not support usage of keyword arguments!

Advantages

In addition to named arguments the library allows:

  • Use standard and custom descriptors

  • Use naming (keyword) arguments

  • Checks for:

    • Arguments for variable length

    • Missed argument annotation

    • Name of wrapped function of descriptor

    • Shading method by attribute or data descriptor (like property)

    • Redefining the method with the same types

  • Using any name for instance, not only self

For all checks is raised TypeError exception.

Limitations

  • Simple types for dispatching

  • overload should be top of decorators

  • Custom descriptor should save wrapped function under “__wrapped__” name

  • Obvious, method argument can’t be variable length (* and **)

Examples

There are no restrictions on the use of the number of decorators, you only need to comply the naming convention.

For example:

class Simple(Polymorphism):
    def calc(self, x: int, y: int) -> None:
        pass

    @classmethod
    def calc(cls, x: float, y: float) -> None:
        pass

    @staticmethod
    def calc(x: str, y: str) -> None:
        pass

Simple().calc(1.0, y=2.0)

While use overload decorator place it on top:

class Simple:
    @overload
    def calc(self, x: int, y: int) -> None:
        pass

    @calc.overload
    @classmethod
    def calc_float(cls, x: float, y: float) -> None:
        pass

    @calc.overload
    @staticmethod
    def calc_str(x: str, y: str) -> None:
        pass

With overload only first method name matter. Other methods can have any other names.

polymorphism checks the class at the time of creation:

class Simple(Polymorphism):
    def calc(self, x: int, y: int) -> None:
        pass

    def calc(self, x: int, y: int, z: int = 3) -> None:
        pass

The below example will raise TypeError exception because calc method overloaded with z parameter with default value and it is impossible distinct last method from first.

polymorphism will raise TypeError exception on any wrong overloading, so you don’t need worry about correctness of it.

See more examples in tests.py.

To-do

  • Complex types for dispatching like List[int]

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