我正在学习策略设计模式,以及Python中的属性装饰器。我遇到了这个例子:
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import List
class Context():
"""
The Context defines the interface of interest to clients.
"""
def __init__(self, strategy: Strategy) -> None:
"""
Usually, the Context accepts a strategy through the constructor, but
also provides a setter to change it at runtime.
"""
self._strategy = strategy
@property
def strategy(self) -> Strategy:
"""
The Context maintains a reference to one of the Strategy objects. The
Context does not know the concrete class of a strategy. It should work
with all strategies via the Strategy interface.
"""
return self._strategy
@strategy.setter
def strategy(self, strategy: Strategy) -> None:
"""
Usually, the Context allows replacing a Strategy object at runtime.
"""
self._strategy = strategy
def do_some_business_logic(self) -> None:
"""
The Context delegates some work to the Strategy object instead of
implementing multiple versions of the algorithm on its own.
"""
# ...
print("Context: Sorting data using the strategy (not sure how it'll do it)")
result = self._strategy.do_algorithm(["a", "b", "c", "d", "e"])
print(",".join(result))
# ...
class Strategy(ABC):
"""
The Strategy interface declares operations common to all supported versions
of some algorithm.
The Context uses this interface to call the algorithm defined by Concrete
Strategies.
"""
@abstractmethod
def do_algorithm(self, data: List):
pass
"""
Concrete Strategies implement the algorithm while following the base Strategy
interface. The interface makes them interchangeable in the Context.
"""
class ConcreteStrategyA(Strategy):
def do_algorithm(self, data: List) -> List:
return sorted(data)
class ConcreteStrategyB(Strategy):
def do_algorithm(self, data: List) -> List:
return reversed(sorted(data))
if __name__ == "__main__":
# The client code picks a concrete strategy and passes it to the context.
# The client should be aware of the differences between strategies in order
# to make the right choice.
context = Context(ConcreteStrategyA())
print("Client: Strategy is set to normal sorting.")
context.do_some_business_logic()
print()
print("Client: Strategy is set to reverse sorting.")
context.strategy = ConcreteStrategyB()
context.do_some_business_logic()我对属性方法/装饰器的理解是,在这种情况下,@property提供了一个接口来设置属性(温度)。在__init__方法中将属性命名为_strategy意味着它应该是一个私有变量。这是错误的还是多余的?我认为这个变量应该命名为strategy,但它的接口应该使用私有变量实现(即在getter/setter中)
摘自https://refactoring.guru/design-patterns/strategy/python/example
编辑:
为了澄清我的推理:是否可以在运行时更改策略,如下所示:
a = Context()
a.strategy = somestrategy发布于 2020-10-07 12:26:22
该属性没有命名为_strategy,而是命名为strategy,但是保存其值的内部变量命名为_strategy。
这一点:
def __init__(self, strategy: Strategy) -> None:
self._strategy = strategy允许:
c = Context(some_strategy)但是,当您尝试c._strategy时,将其命名为_strategy会导致警告。
还有这个:
@property
def strategy(self) -> Strategy:
return self._strategy然后允许:
my_strategy = c.strategy当访问该属性时,getter返回self._strategy的值。
最后是这个:
@strategy.setter
def strategy(self, strategy: Strategy) -> None:
self._strategy = strategy允许:
c.strategy = another_strategy使strategy不仅是一个只读属性,而且是一个读/写属性。
注意:下面的代码没有错,但它做了一些其他的事情:
class Complex:
def __init__(self, strategy: int) -> None:
self.strategy = strategy
@property
def strategy(self) -> int:
return self._strategy
@strategy.setter
def strategy(self, strategy: int) -> None:
self._strategy = strategy
c = Complex(1)
print(c.strategy)不同之处在于,构造函数(__init__)现在不直接设置隐藏属性,而是自己调用属性的设置器。
如果现在有人覆盖了这个类,它仍然会使用它,比较一下:
class MyClass:
def __init__(self, a, b: int) -> None:
self.a = a
self._b = b
@property
def a(self) -> int:
return self._a
@a.setter
def a(self, a: int) -> None:
self._a = a
@property
def b(self) -> int:
return self._b
@b.setter
def b(self, b: int) -> None:
self._b = b
class MySubClass(MyClass):
@MyClass.a.setter
def a(self, a: int) -> None:
self._a = a + 10
@MyClass.b.setter
def b(self, b: int) -> None:
self._b = b + 10
c = MyClass(1, 2)
print(c.a)
print(c.b)
s = MySubClass(1, 2)
print(s.a)
print(s.b)结果:
1
2
11
2因此,这取决于您是否希望继承您的类的人能够更改该行为。
https://stackoverflow.com/questions/64237084
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