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Implementation of design patterns in Python

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🧩 Demystifying Design Patterns 🧩

Ever wondered how top-notch software engineers consistently create elegant, efficient, and maintainable code? Enter design patterns – the secret sauce that simplifies complex software design challenges.

Design patterns are like tried-and-true blueprints, offering reusable solutions to common problems. They empower us to craft code that's not just functional, but also flexible and scalable.

There are three main categories of design patterns:

  1. Creational Patterns 🏗️: These focus on object creation mechanisms.

    • Singleton: Guarantees only one instance of a class exists.
    • Factory Method: Creates objects without locking them into a specific class.
    • Abstract Factory: Produces families of related or dependent objects.
    • Builder: Separates complex object construction from its representation.
    • Prototype: Clones objects for efficient instance creation.
  2. Structural Patterns 🏗️: These deal with object composition and relationships.

    • Adapter: Makes different interfaces work together harmoniously.
    • Bridge: Separates abstraction from implementation.
    • Composite: Composes objects into tree structures for part-whole hierarchies.
    • Decorator: Dynamically adds responsibilities to objects.
    • Facade: Offers a simplified interface to a subsystem.
    • Flyweight: Efficiently shares and reuses objects to minimize resource usage.
    • Proxy: Acts as a placeholder for another object to control access.
  3. Behavioral Patterns 🏗️: These dictate object interactions and communications.

    • Chain of Responsibility: Passes a request along a chain of handlers.
    • Command: Encapsulates requests as objects for flexible execution.
    • Interpreter: Evaluates language grammar or expressions.
    • Iterator: Provides sequential access to elements in an aggregate object.
    • Mediator: Encapsulates object interaction logic.
    • Memento: Captures and externalizes an object's internal state.
    • Observer: Notifies objects of changes in state.
    • State: Allows objects to change behavior when their internal state changes.
    • Strategy: Defines interchangeable algorithms for flexible usage.
    • Template Method: Establishes a skeleton algorithm with customizable steps.
    • Visitor: Performs operations on elements of an object structure.

Harness the power of design patterns to level up your software craftsmanship! 💡💻

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Implementation of design patterns in Python


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