edgardeng / design-patterns-in-python

Design Patterns implemented in Python

Design Patterns implemented in Python

reference from DESIGN PATTERNS in Refactoring.Guru

中文版

Creational Patterns

	Creational Patterns
	Abstract Factory	Lets you produce families of related objects without specifying their concrete classes.	code
	Builder	Lets you construct complex objects step by step. The pattern allows you to produce different types and representations of an object using the same construction code.	code
	Factory Method	Provides an interface for creating objects in a superclass, but allows subclasses to alter the type of objects that will be created	code
	Prototype	Lets you copy existing objects without making your code dependent on their classes.	code
	Singleton	Lets you ensure that a class has only one instance, while providing a global access point to this instance.	code

Structural Patterns

	Structural Patterns
	Adapter	Allows objects with incompatible interfaces to collaborate.	code
	Bridge	Lets you split a large class or a set of closely related classes into two separate hierarchies—abstraction and implementation—which can be developed independently of each other.	code
	Composite	Lets you compose objects into tree structures and then work with these structures as if they were individual objects.	code
	Decorator	Lets you attach new behaviors to objects by placing these objects inside special wrapper objects that contain the behaviors.	code
	Facade	Provides a simplified interface to a library, a framework, or any other complex set of classes.	code
	Flyweight	Lets you fit more objects into the available amount of RAM by sharing common parts of state between multiple objects instead of keeping all of the data in each object.	code
	Proxy	Lets you provide a substitute or placeholder for another object. A proxy controls access to the original object, allowing you to perform something either before or after the request gets through to the original object.	code

Behavioral Patterns

	Behavioral Patterns
	Chain of Responsibility	Lets you pass requests along a chain of handlers. Upon receiving a request, each handler decides either to process the request or to pass it to the next handler in the chain.	code
	Command	Turns a request into a stand-alone object that contains all information about the request. This transformation lets you parameterize methods with different requests, delay or queue a request's execution, and support undoable operations.	code
	Iterator	Lets you traverse elements of a collection without exposing its underlying representation (list, stack, tree, etc.).	code
	Mediator	Lets you reduce chaotic dependencies between objects. The pattern restricts direct communications between the objects and forces them to collaborate only via a mediator object.	code
	Memento	Lets you save and restore the previous state of an object without revealing the details of its implementation.	code
	Observer	Lets you define a subscription mechanism to notify multiple objects about any events that happen to the object they're observing.	code
	State	Lets an object alter its behavior when its internal state changes. It appears as if the object changed its class.	code
	Strategy	Lets you define a family of algorithms, put each of them into a separate class, and make their objects interchangeable.	code
	Template Method	Defines the skeleton of an algorithm in the superclass but lets subclasses override specific steps of the algorithm without changing its structure.	[code](./Template_Method /index.py)
	Visitor	Lets you separate algorithms from the objects on which they operate.	code