Table of Contents
Design patterns are proven solutions to common programming problems. In Python, these patterns help engineers write efficient, maintainable, and scalable code. Understanding these patterns can improve software design and development processes.
Creational Patterns
Creational patterns focus on object creation mechanisms, aiming to create objects in a manner suitable to the situation. They help in reducing complexity and increasing flexibility in code.
- Singleton: Ensures a class has only one instance and provides a global point of access to it.
- Factory Method: Defines an interface for creating an object but allows subclasses to alter the type of objects that will be created.
- Abstract Factory: Provides an interface for creating families of related or dependent objects without specifying their concrete classes.
Structural Patterns
Structural patterns deal with object composition, helping to organize code and make it more flexible and easier to extend.
- Adapter: Allows incompatible interfaces to work together by converting the interface of one class into another expected by clients.
- Decorator: Adds new functionalities to objects dynamically without altering their structure.
- Facade: Provides a simplified interface to a complex subsystem.
Behavioral Patterns
Behavioral patterns focus on communication between objects, defining how they interact and distribute responsibilities.
- Observer: Defines a one-to-many dependency between objects so that when one object changes state, all its dependents are notified.
- Strategy: Enables selecting an algorithm’s behavior at runtime by defining a family of algorithms.
- Command: Encapsulates a request as an object, allowing parameterization of clients with queues, requests, and operations.