Neural Networks and Deep Learning

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

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

class StandardDiscount(DiscountStrategy): def apply(self, amount: float) -> float: return amount * 0.9

class EmailSender(MessageSender): # Low-level def send(self, message: str) -> None: # SMTP logic here pass Python 3- Deep Dive -Part 4 - OOP-

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

from abc import ABC, abstractmethod class DiscountStrategy(ABC): @abstractmethod def apply(self, amount: float) -> float: pass from abc import ABC

class NotificationService: # High-level def (self, sender: MessageSender): # Injected dependency self._sender = sender

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

def save_to_db(self): print(f"Saving self.name to DB") # Persistence

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

def generate_pdf_report(self): print(f"PDF: self.name") # Presentation