Python 3- Deep Dive -part 4 - Oop- Page

import smtplib # Concrete low-level class NotificationService: # High-level def alert(self, message): # Direct dependency on SMTP implementation server = smtplib.SMTP("smtp.gmail.com") server.sendmail(...)

class VIPDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.8 Python 3- Deep Dive -Part 4 - OOP-

This is an excellent topic. is the cornerstone of maintainable, scalable Object-Oriented Programming. In the context of Python 3: Deep Dive (Part 4) , we move beyond basic syntax into how these principles interact with Python’s dynamic nature, descriptors, metaclasses, and Abstract Base Classes (ABCs). class Fax(Protocol): def fax(self, doc: str) -> None:

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. def fax(self, doc):

from abc import ABC, abstractmethod class Bird(ABC): @abstractmethod def move(self): pass

class EmailSender(MessageSender): # Low-level def send(self, message: str) -> None: # SMTP logic here pass