Object-Oriented Programming: Classes and Objects

Object-Oriented Programming: Classes and Objects

Master the fundamentals of object-oriented programming including classes, objects, __init__, methods, attributes, and encapsulation. Model real-world systems like Indian Railway booking.

Understanding Classes and Objects

Classes are blueprints for objects. They define attributes (data) and methods (behavior).

# Basic class definition
class Student:
    # Class attribute (shared by all instances)
    school_name = 'Delhi Public School'
    
    # Constructor method
    def __init__(self, name, roll_no, marks):
        # Instance attributes
        self.name = name
        self.roll_no = roll_no
        self.marks = marks
    
    # Instance methods
    def display_info(self):
        print(f'Name: {self.name}')
        print(f'Roll No: {self.roll_no}')
        print(f'Marks: {self.marks}')
    
    def get_grade(self):
        if self.marks >= 90:
            return 'A'
        elif self.marks >= 80:
            return 'B'
        elif self.marks >= 70:
            return 'C'
        else:
            return 'F'

# Creating objects
student1 = Student('Aditya Singh', 101, 92)
student2 = Student('Priya Sharma', 102, 88)

# Accessing attributes
print(student1.name)  # Aditya Singh
print(student1.roll_no)  # 101

# Calling methods
student1.display_info()
print(f'Grade: {student1.get_grade()}')

# Accessing class attribute
print(Student.school_name)  # Delhi Public School
print(student1.school_name)  # Delhi Public School
      

The __init__ and __str__ Methods

Special methods (dunder methods) have specific purposes in Python classes.

class Book:
    def __init__(self, title, author, isbn, pages):
        '''Constructor: called when object is created'''
        self.title = title
        self.author = author
        self.isbn = isbn
        self.pages = pages
    
    def __str__(self):
        '''String representation: used by print()'''
        return f'{self.title} by {self.author}'
    
    def __repr__(self):
        '''Developer representation: unambiguous string'''
        return f'Book({self.title!r}, {self.author!r}, {self.isbn!r}, {self.pages!r})'
    
    def __len__(self):
        '''Called by len()'''
        return self.pages
    
    def __eq__(self, other):
        '''Equality comparison'''
        if isinstance(other, Book):
            return self.isbn == other.isbn
        return False

# Using the class
book1 = Book('The Great Gatsby', 'F. Scott Fitzgerald', '123-456', 180)
book2 = Book('1984', 'George Orwell', '789-012', 328)

# __str__ is used by print()
print(book1)  # The Great Gatsby by F. Scott Fitzgerald

# __repr__
print(repr(book1))
# Book('The Great Gatsby', 'F. Scott Fitzgerald', '123-456', 180)

# __len__
print(len(book1))  # 180

# __eq__
book3 = Book('Different', 'Author', '123-456', 100)
print(book1 == book3)  # True (same ISBN)
      

Real-World Example: Indian Railway Booking System

Model a railway reservation system using OOP principles.

class Train:
    def __init__(self, train_id, name, source, destination, total_seats):
        self.train_id = train_id
        self.name = name
        self.source = source
        self.destination = destination
        self.total_seats = total_seats
        self.booked_seats = 0
    
    def available_seats(self):
        return self.total_seats - self.booked_seats
    
    def book_ticket(self, num_tickets):
        if num_tickets > self.available_seats():
            return False
        self.booked_seats += num_tickets
        return True
    
    def cancel_ticket(self, num_tickets):
        if num_tickets > self.booked_seats:
            return False
        self.booked_seats -= num_tickets
        return True
    
    def display_info(self):
        print(f'Train: {self.name} ({self.train_id})')
        print(f'Route: {self.source} -> {self.destination}')
        print(f'Available: {self.available_seats()}/{self.total_seats}')

class Passenger:
    def __init__(self, passenger_id, name, pnr=None):
        self.passenger_id = passenger_id
        self.name = name
        self.pnr = pnr  # Passenger Name Record
        self.bookings = []
    
    def book_train(self, train, num_tickets, pnr):
        if train.book_ticket(num_tickets):
            self.pnr = pnr
            self.bookings.append({
                'train': train.name,
                'tickets': num_tickets,
                'pnr': pnr
            })
            return True
        return False
    
    def display_bookings(self):
        print(f'Passenger: {self.name}')
        for booking in self.bookings:
            print(f'  - {booking["train"]}: {booking["tickets"]} tickets (PNR: {booking["pnr"]})')

# Using the system
train1 = Train('12345', 'Rajdhani Express', 'Delhi', 'Mumbai', 500)
train2 = Train('12346', 'Shatabdi Express', 'Delhi', 'Jaipur', 300)

passenger1 = Passenger(1, 'Aditya Singh')
passenger2 = Passenger(2, 'Priya Sharma')

# Booking trains
if passenger1.book_train(train1, 2, 'PNR123456'):
    print('Booking successful!')
    
train1.display_info()
passenger1.display_bookings()
      

Encapsulation: Protecting Data

Encapsulation hides internal details and controls access to object attributes.

class BankAccount:
    def __init__(self, account_holder, initial_balance):
        self.account_holder = account_holder
        self.__balance = initial_balance  # Private attribute (name mangling)
    
    def deposit(self, amount):
        '''Public method to deposit money'''
        if amount <= 0:
            raise ValueError('Deposit amount must be positive')
        self.__balance += amount
        return self.__balance
    
    def withdraw(self, amount):
        '''Public method to withdraw money'''
        if amount <= 0:
            raise ValueError('Withdrawal amount must be positive')
        if amount > self.__balance:
            raise ValueError('Insufficient funds')
        self.__balance -= amount
        return self.__balance
    
    def get_balance(self):
        '''Public method to check balance'''
        return self.__balance
    
    def __str__(self):
        return f'Account: {self.account_holder}, Balance: ${self.__balance:.2f}'

# Using the account
account = BankAccount('Aditya Singh', 10000)
print(account)  # Account: Aditya Singh, Balance: $10000.00

account.deposit(5000)
print(account.get_balance())  # 15000

account.withdraw(3000)
print(account.get_balance())  # 12000

# Cannot directly access __balance (name mangling)
# print(account.__balance)  # AttributeError
# Can access as: print(account._BankAccount__balance)  # Not recommended
      

Static Methods and Class Methods

Static methods and class methods are different from instance methods.

class MathUtils:
    pi = 3.14159
    
    # Instance method (has self)
    def __init__(self, radius):
        self.radius = radius
    
    def area(self):
        return self.pi * self.radius ** 2
    
    # Static method (no self or cls)
    @staticmethod
    def add(a, b):
        return a + b
    
    @staticmethod
    def is_positive(num):
        return num > 0
    
    # Class method (has cls)
    @classmethod
    def from_diameter(cls, diameter):
        return cls(diameter / 2)

# Using static methods
print(MathUtils.add(10, 20))  # 30
print(MathUtils.is_positive(-5))  # False

# Using class method
circle = MathUtils.from_diameter(10)
print(circle.area())  # 78.53975

# Using instance method
circle2 = MathUtils(5)
print(circle2.area())  # 78.53975
      

Practice Problems

1. Create a Student class with attributes (name, roll_no, marks) and methods (get_grade, is_passed)
2. Create a BankAccount class with deposit and withdraw methods with proper validation
3. Create a Rectangle class with methods to calculate area and perimeter
4. Create a library management system with Book and Library classes
5. Implement a shopping cart class with add_item, remove_item, and calculate_total methods

Key Takeaways

• Classes are blueprints for creating objects with attributes and methods
• The __init__ method initializes object attributes when an object is created
• Methods are functions defined in classes that operate on instance data
• Encapsulation protects data by restricting direct access to attributes
• Special methods like __str__ and __repr__ customize object behavior

Under the Hood: Object-Oriented Programming: Classes and Objects

Here is what separates someone who merely USES technology from someone who UNDERSTANDS it: knowing what happens behind the screen. When you tap "Send" on a WhatsApp message, do you know what journey that message takes? When you search something on Google, do you know how it finds the answer among billions of web pages in less than a second? When UPI processes a payment, what makes sure the money goes to the right person?

Understanding Object-Oriented Programming: Classes and Objects gives you the ability to answer these questions. More importantly, it gives you the foundation to BUILD things, not just use things other people built. India's tech industry employs over 5 million people, and companies like Infosys, TCS, Wipro, and thousands of startups are all built on the concepts we are about to explore.

This is not just theory for exams. This is how the real world works. Let us get into it.

Object-Oriented Programming: Modelling the Real World

OOP lets you model real-world entities as code "objects." Each object has properties (data) and methods (behaviour). Here is a practical example:

class BankAccount:
    """A simple bank account — like what SBI or HDFC uses internally"""

    def __init__(self, holder_name, initial_balance=0):
        self.holder = holder_name
        self.balance = initial_balance    # Private in practice
        self.transactions = []            # History log

    def deposit(self, amount):
        if amount <= 0:
            raise ValueError("Deposit must be positive")
        self.balance += amount
        self.transactions.append(f"+₹{amount}")
        return self.balance

    def withdraw(self, amount):
        if amount > self.balance:
            raise ValueError("Insufficient funds!")
        self.balance -= amount
        self.transactions.append(f"-₹{amount}")
        return self.balance

    def statement(self):
        print(f"
--- Account Statement: {self.holder} ---")
        for t in self.transactions:
            print(f"  {t}")
        print(f"  Balance: ₹{self.balance}")

# Usage
acc = BankAccount("Rahul Sharma", 5000)
acc.deposit(15000)      # Salary credited
acc.withdraw(2000)      # UPI payment to Swiggy
acc.withdraw(500)       # Metro card recharge
acc.statement()

This is encapsulation — bundling data and behaviour together. The user of BankAccount does not need to know HOW deposit works internally; they just call it. Inheritance lets you extend this: a SavingsAccount could inherit from BankAccount and add interest calculation. Polymorphism means different account types can respond to the same .withdraw() method differently (savings accounts might check minimum balance, current accounts might allow overdraft).

Real-World System Design: Swiggy's Architecture

When you order food on Swiggy, here is what happens behind the scenes in about 2 seconds: your location is geocoded (algorithms), nearby restaurants are queried from a spatial index (data structures), menu prices are pulled from a database (SQL), delivery time is estimated using ML models trained on historical data (AI), the order is placed in a distributed message queue (Kafka), a delivery partner is assigned using a matching algorithm (optimization), and real-time tracking begins using WebSocket connections (networking). EVERY concept in your CS curriculum is being used simultaneously to deliver your biryani.

How the Web Request Cycle Works

Every time you visit a website, a precise sequence of events occurs. Here is the flow:

    You (Browser)          DNS Server          Web Server
        |                      |                    |
        |---[1] bharath.ai --->|                    |
        |                      |                    |
        |<--[2] IP: 76.76.21.9|                    |
        |                      |                    |
        |---[3] GET /index.html ----------------->  |
        |                      |                    |
        |                      |    [4] Server finds file,
        |                      |        runs server code,
        |                      |        prepares response
        |                      |                    |
        |<---[5] HTTP 200 OK + HTML + CSS + JS --- |
        |                      |                    |
   [6] Browser parses HTML                          |
       Loads CSS (styling)                          |
       Executes JS (interactivity)                  |
       Renders final page                           |

Step 1-2 is DNS resolution — converting a human-readable domain name to a machine-readable IP address. Step 3 is the HTTP request. Step 4 is server-side processing (this is where frameworks like Node.js, Django, or Flask operate). Step 5 is the HTTP response. Step 6 is client-side rendering (this is where React, Angular, or Vue operate).

In a real-world scenario, this cycle also involves CDNs (Content Delivery Networks), load balancers, caching layers, and potentially microservices. Indian companies like Jio use this exact architecture to serve 400+ million subscribers.

Production Engineering: Object-Oriented Programming: Classes and Objects at Scale

Understanding object-oriented programming: classes and objects at an academic level is necessary but not sufficient. Let us examine how these concepts manifest in production environments where failure has real consequences.

Consider India's UPI system processing 10+ billion transactions monthly. The architecture must guarantee: atomicity (a transfer either completes fully or not at all — no half-transfers), consistency (balances always add up correctly across all banks), isolation (concurrent transactions on the same account do not interfere), and durability (once confirmed, a transaction survives any failure). These are the ACID properties, and violating any one of them in a payment system would cause financial chaos for millions of people.

At scale, you also face the thundering herd problem: what happens when a million users check their exam results at the same time? (CBSE result day, anyone?) Without rate limiting, connection pooling, caching, and graceful degradation, the system crashes. Good engineering means designing for the worst case while optimising for the common case. Companies like NPCI (the organisation behind UPI) invest heavily in load testing — simulating peak traffic to identify bottlenecks before they affect real users.

Monitoring and observability become critical at scale. You need metrics (how many requests per second? what is the 99th percentile latency?), logs (what happened when something went wrong?), and traces (how did a single request flow through 15 different microservices?). Tools like Prometheus, Grafana, ELK Stack, and Jaeger are standard in Indian tech companies. When Hotstar streams IPL to 50 million concurrent users, their engineering team watches these dashboards in real-time, ready to intervene if any metric goes anomalous.

The career implications are clear: engineers who understand both the theory (from chapters like this one) AND the practice (from building real systems) command the highest salaries and most interesting roles. India's top engineering talent earns ₹50-100+ LPA at companies like Google, Microsoft, and Goldman Sachs, or builds their own startups. The foundation starts here.

Key Vocabulary

Here are important terms from this chapter that you should know:

💡 Interview-Style Problem

Here is a problem that frequently appears in technical interviews at companies like Google, Amazon, and Flipkart: "Design a URL shortener like bit.ly. How would you generate unique short codes? How would you handle millions of redirects per second? What database would you use and why? How would you track click analytics?"

Think about: hash functions for generating short codes, read-heavy workload (99% redirects, 1% creates) suggesting caching, database choice (Redis for cache, PostgreSQL for persistence), and horizontal scaling with consistent hashing. Try sketching the system architecture on paper before looking up solutions. The ability to think through system design problems is the single most valuable skill for senior engineering roles.

Where This Takes You

The knowledge you have gained about object-oriented programming: classes and objects is directly applicable to: competitive programming (Codeforces, CodeChef — India has the 2nd largest competitive programming community globally), open-source contribution (India is the 2nd largest contributor on GitHub), placement preparation (these concepts form 60% of technical interview questions), and building real products (every startup needs engineers who understand these fundamentals).

India's tech ecosystem offers incredible opportunities. Freshers at top companies earn ₹15-50 LPA; experienced engineers at FAANG companies in India earn ₹50-1 Cr+. But more importantly, the problems being solved in India — digital payments for 1.4 billion people, healthcare AI for rural areas, agricultural tech for 150 million farmers — are some of the most impactful engineering challenges in the world. The fundamentals you are building will be the tools you use to tackle them.

Crafted for Class 8–9 • Python Mastery • Aligned with NEP 2020 & CBSE Curriculum