Python 3- Deep Dive -part 4 - Oop- 〈99% Popular〉

Here is a deep technical breakdown of applying principles in advanced Python OOP. 1. S: Single Responsibility Principle (SRP) A class should have only one reason to change. Deep Dive Issue: In Python, it's tempting to add save() , load() , or generate_report() methods directly into a data class because of how easy dynamic attributes are.

from abc import ABC, abstractmethod class MessageSender(ABC): # Abstraction @abstractmethod def send(self, message: str) -> None: pass Python 3- Deep Dive -Part 4 - OOP-

class Sparrow(FlyingBird): def move(self): return self.fly(100) def fly(self, altitude: int): return f"Flying at altitude" Here is a deep technical breakdown of applying

class Fax(Protocol): def fax(self, doc: str) -> None: ... class SimplePrinter: def print(self, doc: str) -> None: print(f"Printing doc") Multi-function device can compose multiple protocols class MultiFunctionDevice(Printer, Scanner, Fax): def print(self, doc): ... def scan(self, doc): ... def fax(self, doc): ... 5. D: Dependency Inversion Principle (DIP) Depend on abstractions, not concretions. High-level modules should not depend on low-level modules. Deep Dive Issue: Python's dynamic imports and global singletons (e.g., requests.get , open ) often hard-code dependencies, making unit testing impossible. Deep Dive Issue: In Python, it's tempting to

class SmsSender(MessageSender): # Another low-level def send(self, message: str) -> None: # Twilio logic here pass

from typing import Protocol class Printer(Protocol): def print(self, doc: str) -> None: ...