Design patterns are language-independent, but in the context of languages with first-class functions, it’s beneficial to rethink some patterns. The general idea is: you can replace instances of some participant class with simple functions, reducing a lot of boilerplate code.
In this post, I will refactor Strategy using functions objects.
Strategy is a good example of a design pattern that can be simpler in Python if you leverage functions as first-class objects.
Classic Strategy
A coarse explanation of Strategy is Strategy, and a clear example is needed.
Let’s consider an online store with three discount rules:
- 5% discount for customers with 1000 or more fidelity points
- 7% discount for orders with 10 or more distinct items
- 10% discount for each LineItem with 20 or more units
The participants in this example are:
- Context. Provides a service by delegating some computation to interchangeable components that implement alternative algorithms. The
Orderin this example is the context. - Strategy. The interface common to the components that implement different algorithms. In our example, it’s
Promotion. - Concrete Strategy. One of the concrete subclasses of Strategy.
LargeOrderPromo,BulkItemPromo, andFidelityPromo.
from abc import ABC, abstractmethod
from collections import namedtuple
Customer = namedtuple('Customer', 'name fidelity')
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: # Context
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):
discount = 0 if self.promotion is None else 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): # Concrete Strategy
def discount(self, order):
"""
5% discount for customers with 1000 or more fidelity points
"""
return order.total() * 0.05 if order.customer.fidelity >= 1000 else 0
class BulkItemPromo(Promotion): # Concrete Strategy
def discount(self, order):
"""
10% discount for each LineItem with 20 or more units
"""
discount = 0
for item in order.cart:
if item.quantity >= 20:
discount += item.total() * 0.1
return discount
class LargeOrderPromo(Promotion):
def discount(self, order):
"""
7% discount for orders with 10 or more distinct items
"""
distinctItems = {item.product for item in order.cart}
if len(distinctItems) >= 10:
return order.total() * 0.07
return 0
joe = Customer('John Doe', 0)
ann = Customer('Ann Smith', 1100)
cart = [LineItem('banana', 4, 0.5),
LineItem('apple', 10, 1.5),
LineItem('watermellon', 5, 5.0)]
print(Order(joe, cart, FidelityPromo()))
print(Order(ann, cart, FidelityPromo()))
bananaCart = [LineItem('banana', 30, 0.05), LineItem('apple', 10, 1.5)]
print(Order(joe, bananaCart, BulkItemPromo()))
longOrder = [LineItem(str(item), 1, 1.0) for item in range(10)]
print(Order(joe, longOrder, LargeOrderPromo()))
The above code works perfectly well, but same functionality can be implemented with less code in Python.
Functions-oriented Strategy
Each concrete strategy in our example is a class with a single method, which can be replaced with a simple function.
from abc import ABC, abstractmethod
from collections import namedtuple
Customer = namedtuple('Customer', 'name fidelity')
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: # Context
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):
discount = 0 if self.promotion is None else self.promotion(self)
return self.total() - discount
def __repr__(self):
fmt = '<Order total: {:.2f} due: {:.2f}>'
return fmt.format(self.total(), self.due())
def fidelityPromo(order):
"""
5% discount for customers with 1000 or more fidelity points
"""
return order.total() * 0.05 if order.customer.fidelity >= 1000 else 0
def bulkItemPromo(order):
"""
10% discount for each LineItem with 20 or more units
"""
discount = 0
for item in order.cart:
if item.quantity >= 20:
discount += item.total() * 0.1
return discount
def largeOrderPromo(order):
"""
7% discount for orders with 10 or more distinct items
"""
distinctItems = {item.product for item in order.cart}
if len(distinctItems) >= 10:
return order.total() * 0.07
return 0
joe = Customer('John Doe', 0)
ann = Customer('Ann Smith', 1100)
cart = [LineItem('banana', 4, 0.5),
LineItem('apple', 10, 1.5),
LineItem('watermellon', 5, 5.0)]
print(Order(joe, cart, fidelityPromo))
print(Order(ann, cart, fidelityPromo))
bananaCart = [LineItem('banana', 30, 0.05), LineItem('apple', 10, 1.5)]
print(Order(joe, bananaCart, bulkItemPromo))
longOrder = [LineItem(str(item), 1, 1.0) for item in range(10)]
print(Order(joe, longOrder, largeOrderPromo))
There is no need to instantiate a new promotion object with each new order: the functions are ready to use.
Reference