Python3面向对象——案例-01

经典的策略模式案例

问题描述

使用“策略”设计模式处理订单折扣的 UML 类图

定义一系列算法，把它们一一封装起来，并且使它们可以相互替换。本模式使得算法可以独立于使用它的客户而变化。

电商领域有个功能明显可以使用“策略”模式，即根据客户的属性或订单中的商品计算折扣。

假如一个网店制定了下述折扣规则，每个订单只能享用一个折扣：

1. Customers with 1,000 or more fidelity points get a global 5% discount per order.
2. A 10% discount is applied to each line item with 20 or more units in the same order.
3. Orders with at least 10 distinct items get a 7% global discount.

content

把一些计算委托给实现不同算法的可互换组件，它提供服务。在这个电商示例中，上下文是 Order，它会根据不同的算法计算促销折扣。

strategy

实现不同算法的组件共同的接口。在这个示例中，名为 Promotion 的抽象类扮演这个角色。

concrete strategy

“策略”的具体子类。fidelityPromo、BulkPromo 和 LargeOrderPromo 是这里实现的三个具体策略。

问题解决代码

from abc import ABC, abstractmethod
from collections import namedtuple
#--------------------------------------------------------
Customer = namedtuple('Customer', 'name fidelity') #类：(顾客, 积分)
#--------------------------------------------------------
class LineItem:
    def __init__(self, product, quantity, price):
        self.product = product
        self.quantity = quantity
        self.price = price
    def total(self):
        return self.price * self.quantity
#--------------------------------------------------------
class Order:
    def __init__(self, customer, cart, promotion=None):
        self.customer = customer
        self.cart = list(cart)
        self.promotion = promotion
    def total(self):
        if not hasattr(self, '__total'):
            self.__total = sum(item.total() for item in self.cart)
        return self.__total
    def due(self):
        if self.promotion is None:
            discount = 0
        else:
            discount = self.promotion.discount(self)
        return self.total() - discount
    def __repr__(self):
        fmt = '<Order total: {:.2f} due: {:.2f}>'
        return fmt.format(self.total(), self.due())
#--------------------------------------------------------
class Promotion(ABC): # the Strategy: an abstract base class
    @abstractmethod
    def discount(self, order):
        """Return discount as a positive dollar amount"""
#--------------------------------------------------------
class FidelityPromo(Promotion): # first Concrete Strategy
    """5% discount for customers with 1000 or more fidelity points"""
    def discount(self, order):
        return order.total() * .05 if order.customer.fidelity >= 1000 else 0
#--------------------------------------------------------
class BulkItemPromo(Promotion): # second Concrete Strategy
    """10% discount for each LineItem with 20 or more units"""
    def discount(self, order):
        discount = 0
        for item in order.cart:
            if item.quantity >= 20:
                discount += item.total() * .1
        return discount
#--------------------------------------------------------
class LargeOrderPromo(Promotion): # third Concrete Strategy
    """7% discount for orders with 10 or more distinct items"""
    def discount(self, order):
        distinct_items = {item.product for item in order.cart}
        if len(distinct_items) >= 10:
            return order.total() * .07
        return 0

# 两个顾客：joe 的积分是 0，ann 的积分是 1100。
joe = Customer('John Doe', 0)
ann = Customer('Ann Smith', 1100)

# 有三个商品的购物车
cart = [LineItem('banana', 4, .5),
       LineItem('apple', 10, 1.5),
       LineItem('watermellon', 5, 5.0)]

# fidelityPromo 没给 joe 提供折扣
Order(joe, cart, FidelityPromo())

<Order total: 42.00 due: 42.00>

# ann 得到了 5% 折扣，因为她的积分超过 1000
Order(ann, cart, FidelityPromo())

<Order total: 42.00 due: 39.90>

# banana_cart 中有 30 把香蕉和 10 个苹果
banana_cart = [LineItem('banana', 30, .5),
              LineItem('apple', 10, 1.5)]

# BulkItemPromo 为 joe 购买的香蕉优惠了 1.50 美元
Order(joe, banana_cart, BulkItemPromo())

<Order total: 30.00 due: 28.50>

# long_order 中有 10 个不同的商品，每个商品的价格为 1.00 美元
long_order = [LineItem(str(item_code), 1, 1.0) for item_code in range(10)]

# LargerOrderPromo 为 joe 的整个订单提供了 7% 折扣
Order(joe, long_order, LargeOrderPromo())

<Order total: 10.00 due: 9.30>

Order(joe, cart, LargeOrderPromo())

<Order total: 42.00 due: 42.00>

案例来自《Fluent Python》Luciano Ramalho著