Python, with its clear and readable syntax, has always been a preferred language for developers across various domains. As software complexity grows, understanding and utilizing design patterns becomes imperative. These patterns offer tried and tested solutions, helping developers avoid pitfalls and ensure efficient and scalable designs.
Design patterns represent reusable solutions to commonly encountered programming challenges. They aren't directly transformable into code but serve as templates or guidelines. Patterns encapsulate the software design experience of expert developers and provide a shared lexicon for design-centric discussions.
Design patterns are conventionally classified into three categories: Creational, Structural, and Behavioral.
1. Creational Patterns
These focus on object creation mechanisms, aiming to create objects in a manner suitable to the situation.
Python Factory Method Design Pattern
Python Abstract Factory Design Pattern
Python Builder Design Pattern
Python Prototype Design Pattern
2. Structural Patterns
These concern class and object composition. They provide different ways to form a class structure, ensuring that when one part changes, the entire structure doesn't need alteration.
Python Adapter Design Pattern
Python Bridge Design Pattern
Python Composite Design Pattern
Python Decorator Design Pattern
Python Facade Design Pattern
Python Flyweight Design Pattern
Python Proxy Design Pattern
3. Behavioral Patterns
These are centered on object responsibilities and how they communicate. They address the responsibilities of objects and the communication between them.
Python Chain of Responsibility Design Pattern
Python Command Design Pattern
Python Interpreter Design Pattern
Python Iterator Design Pattern
Python Mediator Design Pattern
Python Memento Design Pattern
Python Observer Design Pattern
Python State Design Pattern
Python Strategy Design Pattern
Python Template Method Design Pattern
Python Visitor Design Pattern
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