Python 3- Deep Dive -part 4 - Oop- <360p — 720p>

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() .

class VIPDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.8

from abc import ABC, abstractmethod class MessageSender(ABC): # Abstraction @abstractmethod def send(self, message: str) -> None: pass

from abc import ABC, abstractmethod class Bird(ABC): @abstractmethod def move(self): pass Python 3- Deep Dive -Part 4 - OOP-

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.

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.

class Employee: def __init__(self, name, salary): self.name = name self.salary = salary def calculate_pay(self): return self.salary * 0.8 # Business rule Deep Dive Issue: Python is not statically typed

class FlyingBird(Bird): @abstractmethod def fly(self, altitude: int): pass

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 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. class Bird: def fly(self

class Bird: def fly(self, altitude: int) -> None: return f"Flying at altitude" class Penguin(Bird): def fly(self, altitude: int) -> None: # Violation: Changes pre-condition (cannot fly) raise NotImplementedError("Penguins can't fly")

class Scanner(Protocol): def scan(self, doc: str) -> None: ...

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