Strategy Pattern

1. What Is It?

The Strategy pattern defines a family of algorithms, encapsulates each one, and makes them interchangeable. It lets the algorithm vary independently from the clients that use it.

Without it, behavioral variations end up as branching logic (if/elif/switch) inside a single class. Each new variation requires modifying that class, violating Open/Closed. The class grows, tests multiply, and adding a new "strategy" risks breaking all existing ones.

2. How It Works

Participants:

• Strategy — interface declaring the algorithm method (e.g., execute(), sort(), calculate())
• ConcreteStrategy — implements a specific algorithm variant
• Context — holds a reference to a Strategy object; delegates the algorithm call to it; clients configure the Context with the desired ConcreteStrategy

Step-by-step:

1. Identify the behavior that varies (e.g., sorting algorithm, pricing rule, authentication method)
2. Extract that behavior into a Strategy interface
3. Implement each variant as a ConcreteStrategy
4. Context holds a Strategy reference and calls it — no if/else needed
5. At runtime, inject the desired strategy into the Context

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Python:

Copy
from abc import ABC, abstractmethod
from typing import List


class PricingStrategy(ABC):
    @abstractmethod
    def calculate(self, base_price: float) -> float:
        pass


class RegularPricingStrategy(PricingStrategy):
    def calculate(self, base_price: float) -> float:
        return base_price


class DiscountPricingStrategy(PricingStrategy):
    def __init__(self, discount_rate: float) -> None:
        self._discount_rate = discount_rate

    def calculate(self, base_price: float) -> float:
        return base_price * (1 - self._discount_rate)


class HolidayPricingStrategy(PricingStrategy):
    def calculate(self, base_price: float) -> float:
        return base_price * 0.8  # 20% holiday discount


class ShoppingCart:
    def __init__(self, pricing_strategy: PricingStrategy) -> None:
        self._pricing_strategy = pricing_strategy
        self._items: List[float] = []

    def set_pricing_strategy(self, pricing_strategy: PricingStrategy) -> None:
        self._pricing_strategy = pricing_strategy

    def add_item(self, price: float) -> None:
        self._items.append(price)

    def checkout(self) -> float:
        base_total = sum(self._items)
        return self._pricing_strategy.calculate(base_total)


# Usage
cart = ShoppingCart(RegularPricingStrategy())
cart.add_item(100.0)
cart.add_item(50.0)
print(cart.checkout())  # 150.0

# Swap strategy at runtime — no structural change to ShoppingCart
cart.set_pricing_strategy(DiscountPricingStrategy(0.1))
print(cart.checkout())  # 135.0

cart.set_pricing_strategy(HolidayPricingStrategy())
print(cart.checkout())  # 120.0

Java:

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import java.util.List;
import java.util.ArrayList;

// Strategy interface
public interface PricingStrategy {
    double calculate(double basePrice);
}

// ConcreteStrategy A
public class RegularPricingStrategy implements PricingStrategy {
    @Override
    public double calculate(double basePrice) {
        return basePrice;
    }
}

// ConcreteStrategy B
public class DiscountPricingStrategy implements PricingStrategy {
    private final double discountRate;

    public DiscountPricingStrategy(double discountRate) {
        this.discountRate = discountRate;
    }

    @Override
    public double calculate(double basePrice) {
        return basePrice * (1 - discountRate);
    }
}

// ConcreteStrategy C
public class HolidayPricingStrategy implements PricingStrategy {
    @Override
    public double calculate(double basePrice) {
        return basePrice * 0.8;
    }
}

// Context
public class ShoppingCart {
    private PricingStrategy pricingStrategy;
    private final List<Double> items = new ArrayList<>();

    public ShoppingCart(PricingStrategy pricingStrategy) {
        this.pricingStrategy = pricingStrategy;
    }

    public void setPricingStrategy(PricingStrategy pricingStrategy) {
        this.pricingStrategy = pricingStrategy;
    }

    public void addItem(double price) {
        items.add(price);
    }

    public double checkout() {
        double baseTotal = items.stream().mapToDouble(Double::doubleValue).sum();
        return pricingStrategy.calculate(baseTotal);
    }

    public static void main(String[] args) {
        ShoppingCart cart = new ShoppingCart(new RegularPricingStrategy());
        cart.addItem(100.0);
        cart.addItem(50.0);
        System.out.println(cart.checkout());  // 150.0

        cart.setPricingStrategy(new DiscountPricingStrategy(0.1));
        System.out.println(cart.checkout());  // 135.0

        cart.setPricingStrategy(new HolidayPricingStrategy());
        System.out.println(cart.checkout());  // 120.0
    }
}

3. Variants & Comparisons

In Python/Java 8+, a single-method Strategy interface can be replaced with a callable/lambda for simple cases. Prefer named strategy classes when the algorithm has state or complex logic.

4. When to Use It (and When NOT To)

Use when:

• You have multiple variants of an algorithm and want to swap them at runtime
• You want to eliminate a growing if/elif/switch block that changes whenever a new variant is added
• You need to isolate algorithm logic for independent testing

Don't use when:

• You only have 2 variants and they'll never change — the abstraction costs more than it saves
• The algorithm is trivial (a one-liner) — a lambda or simple parameter is sufficient

Decision triggers:

• "Every time we add a new payment method / sort algorithm / pricing rule, I have to touch this class" → Strategy
• "I need to let users choose their algorithm at runtime" → Strategy
• "All variants share the same skeleton but differ in a couple of steps" → consider Template Method instead

Anti-patterns:

• Strategy with a single ConcreteStrategy — pointless abstraction
• Putting strategy selection logic back inside the Context (if type == 'holiday': strategy = HolidayStrategy()) — defeats the purpose

5. Real-World Usage

1. Java's Comparator interface: Collections.sort(list, comparator) accepts any Comparator<T> — a classic Strategy. You swap the comparison algorithm without touching the sort code. Comparator.naturalOrder(), Comparator.reverseOrder(), and custom comparators are all ConcreteStrategies.

2. Spring Framework AuthenticationProvider: Spring Security's authentication pipeline uses Strategy — AuthenticationProvider is the interface, and DaoAuthenticationProvider, JwtAuthenticationProvider, etc., are ConcreteStrategies. The AuthenticationManager (Context) delegates without knowing which provider is active.

3. Python's sort() / sorted() key parameter: sorted(items, key=lambda x: x.price) uses a callable strategy for comparison. The sorting algorithm is fixed; the comparison logic varies — exactly the Strategy intent.

6. Interview Cheat Sheet

Key sentences:

1. "Strategy replaces conditional branching with polymorphism — instead of asking 'which algorithm?' at runtime with an if/else, you inject the right implementation up front."
2. "The Context is closed for modification but open for extension — adding a new strategy requires zero changes to the Context."
3. "Strategy and Template Method both handle algorithm variation, but Strategy uses composition and allows runtime swapping; Template Method uses inheritance and is fixed at compile time."
4. "The pattern shines when the number of variants is expected to grow — each new variant is a new class, not a modified method."

Common follow-up questions:

Q: How is Strategy different from State? A: Both delegate to an encapsulated object, but State transitions happen internally based on object state; Strategy is injected externally by the client. Context drives Strategy changes; object's own logic drives State transitions.

Q: Can you use lambdas instead of Strategy classes? A: Yes, for simple stateless algorithms. When the algorithm needs configuration (e.g., DiscountPricingStrategy(0.1)) or multiple methods, a named class is cleaner and more testable.

Q: How do you decide between Strategy and a simple map of functions? A: A map works for pure dispatch. Strategy is better when strategies have state, need injection/mocking, or when you want type safety guaranteeing the right interface.

Connections:

• Strategy + Factory → Factory creates the right ConcreteStrategy based on context
• Strategy + Dependency Inversion → Context depends on Strategy abstraction, not concrete implementations
• Strategy vs. Template Method → composition vs. inheritance trade-off for algorithm variation