from abc import ABC, abstractmethod class DiscountStrategy(ABC): @abstractmethod def apply(self, amount: float) -> float: pass
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
class SmsSender(MessageSender): # Another low-level def send(self, message: str) -> None: # Twilio logic here pass Python 3- Deep Dive -Part 4 - OOP-
class Penguin(Bird): def move(self): return "Swimming" # No fly method. Substitutable for Bird. Clients should not be forced to depend on methods they do not use. Deep Dive Issue: Python has no explicit interface keyword. We use Protocol (PEP 544) or multiple ABCs . Fat protocols lead to NotImplementedError stubs.
def save_to_db(self): print(f"Saving self.name to DB") # Persistence
class EmployeeDiscount(DiscountStrategy): # Extension: No existing code modified def apply(self, amount: float) -> float: return amount * 0.5 Deep Dive Issue: Python has no explicit interface keyword
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.
class VIPDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.8
def generate_pdf_report(self): print(f"PDF: self.name") # Presentation def save_to_db(self): print(f"Saving self
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 StandardDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.9
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.