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Strategy in Python
Strategy is a behavioral design pattern that turns a set of behaviors into objects and makes them interchangeable inside original context object.
The original object, called context, holds a reference to a strategy object. The context delegates executing the behavior to the linked strategy object. In order to change the way the context performs its work, other objects may replace the currently linked strategy object with another one.
Complexity:
Popularity:
Usage examples: The Strategy pattern is very common in Python code. It’s often used in various frameworks to provide users a way to change the behavior of a class without extending it.
Identification: Strategy pattern can be recognized by a method that lets a nested object do the actual work, as well as a setter that allows replacing that object with a different one.
Conceptual Example
This example illustrates the structure of the Strategy design pattern. It focuses on answering these questions:
- What classes does it consist of?
- What roles do these classes play?
- In what way the elements of the pattern are related?
main.py: Conceptual example
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()
Output.txt: Execution result
Client: Strategy is set to normal sorting.
Context: Sorting data using the strategy (not sure how it'll do it)
a,b,c,d,e
Client: Strategy is set to reverse sorting.
Context: Sorting data using the strategy (not sure how it'll do it)
e,d,c,b,a
