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README.md

Design Patterns with Python

Design patterns are the best-formalized practices a programmer can use to solve common problems when designing an application or system.

Types of design patterns

  • Creational - designed for object creation to increase flexibility and reuse of existing code. Polymorphism is used.
  • Structural - establishes a relationship between classes making larger structures. Inheritance is used.
    • Whenever you think of designing architecture for your system, structural design patterns help you to plan for the future, and arrange classes in neat hierarchies.
  • Behavioral - effective communications and interactions between objects/classes. Methods are used.

Using common design patterns, you can:

  • Speed up the development process;
  • Reduce the number of lines of code;
  • Make sure your code is well-designed;
  • Anticipate future problems arising from small issues.

Notes

  1. Creational
    • *Singleton, restricts a class from having more than one instance and ensures a global access point to this instance.
    • *Factory, the method that helps to create other objects.
    • *Factory abstract, like factory but object that provides a way to encapsulate a group of individual factories.
    • *Builder, separating class from building complex object.
    • Borg, allows all instances of one class to share common data.
    • Prototype, registers object and clones objects (if instantiation is costly).
    • Pool, like flyweight but for mutable objects.
  2. Structural
    • *Facade, hides the complexity of implementations. New API on top of other APIs.
    • *Bridge, separates the implementation from abstraction. Ex: DrawingAPIOne, DrawingAPITwo
    • *Adapter, makes incompatible objects adaptable to each other. Ex: speak=english.hello(), speak=korean.anyong()
    • *Proxy, like decorator, adds functionality to a class without changing its interface.
    • Decorator, attach new behaviors to the objects without modifying their structure.
    • Composite, describes a group of objects the same way as a single instance, using a Tree data structure.
    • Flyweight, cache, reuses existing instances of objects with similar/identical state.
  3. Behavioural
    • *Strategy, enables our application to select algorithms (method) at runtime.
    • *Observer, lets subscribed entities know about changes in an observable. Ex: Elon & Twitter.
    • *Iterator, helps to iterate through the elements of the collection.
    • *Mediator, objects in a system communicate through a Mediator instead of directly with each other.
    • Publish & Subscribe, a source syndicates events/data to 0+ registered listeners.
    • Visitor, adds new features to an existing hierarchy without changing its structure. Ex: electricity, hvac.
    • Chain of responsibility, allows a request to pass down a chain of receivers until it is handled.
    • Template, defines the skeleton of a base algorithm, deferring the definition of exact steps to subclasses.
    • Momento, generates an opaque token that can be used to go back to a previous state.
    • State, logic is organized into a discrete number of potential states and the next state that can be transitioned to

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