Marrying Encapsulation and Design Patterns in Python: Build Scalable Systems

Applying encapsulation alongside proven design patterns for robust, extensible applications

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Design patterns represent timeless blueprints guiding engineers toward elegant problem resolution. Often rooted in experience, wisdom, and empirical evidence, these tested strategies foster order amid chaos. Coupling design patterns with encapsulation propels Python practitioners forward, empowering them to devise scalable, adaptive systems. Delving into this fruitful marriage, let’s examine prominent combinations and bolster our expertise along the way.

Factory Pattern Meets Encapsulation

Factories generate objects according to specified criteria, centralizing creation logic. Commonly employed factory variations comprise Simple Factory, Abstract Factory, and Factory Method. Regardless of choice, factories benefit immensely from encapsulation.

Below lies an exemplar Simple Factory pattern, manufacturing distinct shapes:

from abc import ABCMeta, abstractmethod

class Shape(metaclass=ABCMeta):
    @abstractmethod
    def draw(self):
        pass

class Rectangle(Shape):
    def draw(self):
        print("Drawing rectangle...")

class…