class FlyingBird(Bird): @abstractmethod def fly(self, altitude: int): pass
class StandardDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.9
class Employee: def __init__(self, name, salary): self.name = name self.salary = salary def calculate_pay(self): return self.salary * 0.8 # Business rule
from abc import ABC, abstractmethod class Bird(ABC): @abstractmethod def move(self): pass Python 3- Deep Dive -Part 4 - OOP-
from typing import Protocol class Printer(Protocol): def print(self, doc: str) -> None: ...
class DiscountCalculator: def calculate(self, amount: float, strategy: DiscountStrategy) -> float: return strategy.apply(amount) Subtypes must be substitutable for their base types. Deep Dive Issue: Python's duck typing hides LSP violations. A subclass might accept different argument types or raise unexpected exceptions.
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). A subclass might accept different argument types or
class DiscountCalculator: def calculate(self, customer_type, amount): if customer_type == "standard": return amount * 0.9 elif customer_type == "vip": return amount * 0.8 elif customer_type == "employee": # Modification needed here return amount * 0.5
class MultiFunctionDevice(ABC): @abstractmethod def print(self, doc): pass @abstractmethod def scan(self, doc): pass @abstractmethod def fax(self, doc): pass class SimplePrinter(MultiFunctionDevice): def print(self, doc): ... def scan(self, doc): raise NotImplementedError # Forced dependency def fax(self, doc): raise NotImplementedError
from dataclasses import dataclass @dataclass class Employee: name: str salary: float Responsibility 2: Business logic class PayCalculator: def calculate(self, emp: Employee) -> float: return emp.salary * 0.8 Responsibility 3: Persistence class EmployeeRepository: def save(self, emp: Employee) -> None: # Uses SQLAlchemy, filesystem, etc. pass 2. O: Open/Closed Principle (OCP) Classes should be open for extension, but closed for modification. Deep Dive Issue: Python is not statically typed. Without ABC or Protocol , developers often write long if/elif chains checking type() . In the context of Python 3: Deep Dive
class VIPDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.8
class Scanner(Protocol): def scan(self, doc: str) -> None: ...
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.