🧱 Python Object-Oriented Programming – Classes, Objects, Inheritance

Build Reusable and Scalable Applications with Python OOP

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🧲 Introduction – Why Learn OOP in Python?

Object-Oriented Programming (OOP) provides a powerful structure for managing complexity in large Python applications. It allows developers to bundle data (attributes) and behavior (methods) into reusable blueprints called classes, which are instantiated into objects.

Whether you’re designing real-world systems, APIs, or games—OOP makes your code modular, reusable, and easier to manage.

🎯 In this guide, you’ll learn:

• All major OOP features in Python
• Practical examples with explanation
• How to build extensible and scalable codebases

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📘 Topics Covered in This Guide

🔢 Topic Name	🔎 Description
Python OOP Concepts	Core pillars: Encapsulation, Abstraction, Inheritance, Polymorphism
Python Classes & Objects	Blueprint and instances in OOP
Python Class Attributes	Instance vs Class variables
Python Class Methods	Methods that operate on object instances
Python Static Methods	Utility methods that don’t depend on instance
Python Constructors	The __init__() initializer method
Python Access Modifiers	Public, protected, private attributes
Python Inheritance	Reuse code from parent classes
Python Polymorphism	Same method name, different behavior
Python Method Overriding	Redefine a parent method in child class
Python Method Overloading	Simulating multiple method versions
Python Abstraction	Hide implementation with abstract base classes
Python Encapsulation	Keep internal data protected
Python Packages	Organize classes into modular directories
Python Inner Classes	Classes defined inside other classes
Python Anonymous Class and Objects	On-the-fly class creation
Python Singleton Class	Ensures only one instance exists
Python Wrapper Classes	Add functionality to other classes
Python Reflection	Introspect and manipulate code at runtime
Python Enums	Create named constants

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1. 🔷 Python OOP Concepts

The four core pillars of OOP in Python are:

• Encapsulation: Keeping data safe inside objects.
• Abstraction: Hiding complex logic behind simple interfaces.
• Inheritance: Deriving new classes from existing ones.
• Polymorphism: Same interface, different behavior.

These principles allow for organized, DRY (Don’t Repeat Yourself), and maintainable code.

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2. 🧱 Python Classes & Objects

A class is a template for creating objects. An object is an instance of a class.

class Dog:
    def bark(self):
        print("Woof!")

my_dog = Dog()
my_dog.bark()

✅ Explanation:

• Dog is the class.
• my_dog is an object of class Dog.
• The method bark() prints a message when called on the object.

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3. 🏷️ Python Class Attributes

Attributes can be instance-level or class-level.

class Car:
    wheels = 4  # Class attribute
    def __init__(self, color):
        self.color = color  # Instance attribute

c1 = Car("red")
print(c1.color, Car.wheels)

✅ Explanation:

• wheels is shared across all instances.
• color is unique to each instance.

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4. ⚙️ Python Class Methods

Defined with self, they operate on instance data.

class Circle:
    def __init__(self, radius):
        self.radius = radius

    def area(self):
        return 3.14 * self.radius ** 2

✅ Explanation:

• area() uses the radius of the object to compute area.

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5. ⚡ Python Static Methods

They don’t access or modify class state.

class Math:
    @staticmethod
    def square(x):
        return x * x

print(Math.square(4))

✅ Explanation:

• Use @staticmethod when no access to self or cls is needed.

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6. 🚀 Python Constructors

Used for object initialization.

class Student:
    def __init__(self, name):
        self.name = name

s1 = Student("Alice")
print(s1.name)

✅ Explanation:

• __init__() is the constructor called on object creation.

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7. 🔐 Python Access Modifiers

Python uses naming conventions:

• public – accessible everywhere
• _protected – internal use (by convention)
• __private – name mangled to restrict access

class Bank:
    def __init__(self):
        self.balance = 1000      # public
        self._pin = "1234"       # protected
        self.__password = "abc"  # private

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8. 👪 Python Inheritance

One class derives from another.

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def bark(self):
        print("Dog barks")

d = Dog()
d.speak()
d.bark()

✅ Explanation:

• Dog inherits from Animal and gets its speak() method.

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9. 🔁 Python Polymorphism

Different classes can define the same method.

class Cat:
    def sound(self):
        print("Meow")

class Cow:
    def sound(self):
        print("Moo")

for animal in [Cat(), Cow()]:
    animal.sound()

✅ Explanation:

• sound() is polymorphic across different class instances.

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10. 🔄 Python Method Overriding

Child overrides parent method.

class Animal:
    def speak(self):
        print("Animal sound")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

d = Dog()
d.speak()

✅ Explanation:

• Dog overrides Animal‘s speak().

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11. ➕ Python Method Overloading

Python doesn’t support it natively, but can be simulated.

class Calc:
    def add(self, a=None, b=None):
        if a and b:
            return a + b
        elif a:
            return a
        return 0

✅ Explanation:

• Conditional logic allows multiple method forms.

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12. 🧼 Python Abstraction

Achieved using abc module.

from abc import ABC, abstractmethod

class Shape(ABC):
    @abstractmethod
    def area(self):
        pass

✅ Explanation:

• Shape can’t be instantiated directly; subclasses must define area().

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13. 🧊 Python Encapsulation

Hides object details and restricts direct access.

class Account:
    def __init__(self):
        self.__balance = 0

    def deposit(self, amount):
        self.__balance += amount
        return self.__balance

✅ Explanation:

• __balance is private; only accessible through deposit().

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14. 📦 Python Packages

Organizing classes into reusable modules.

project/
│
├── animals/
│   ├── __init__.py
│   └── dog.py

✅ Explanation:

• Packages help in modular development and code reuse.

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15. 🧬 Python Inner Classes

Defined within another class.

class Person:
    class Address:
        def __init__(self, city):
            self.city = city

✅ Explanation:

• Address is tightly coupled with Person.

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16. 🕵️‍♂️ Python Anonymous Class and Objects

Objects without variable binding.

print(type('Anonymous', (object,), {'value': 42})())

✅ Explanation:

• Creates a class dynamically using type().

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17. 🧍 Python Singleton Class

Only one instance allowed.

class Singleton:
    _instance = None

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance

✅ Explanation:

• Ensures a single instance using __new__().

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18. 🎁 Python Wrapper Classes

Used to add functionality to an object.

class TextWrapper:
    def __init__(self, text):
        self.text = text.upper()

print(TextWrapper("hello").text)

✅ Explanation:

• Wraps behavior around basic types like strings.

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19. 🔢 Python Enums

Symbolic constants.

from enum import Enum

class Status(Enum):
    ACTIVE = 1
    INACTIVE = 0

✅ Explanation:

• Use Status.ACTIVE for clarity over raw values.

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20. 🔍 Python Reflection

Access metadata dynamically.

class Car:
    brand = "Toyota"

c = Car()
print(getattr(c, 'brand'))

✅ Explanation:

• Use getattr(), hasattr() for runtime object inspection.

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📌 Summary – Recap & Next Steps

Python’s OOP model provides a complete toolkit for building robust, extensible applications. From basic classes to advanced features like singletons and reflection, Python OOP empowers developers to write clean, maintainable code.

🔍 Key Takeaways:

• OOP organizes code into classes and objects.
• Key concepts: encapsulation, inheritance, abstraction, and polymorphism.
• Python supports advanced OOP features like static methods, packages, and reflection.

⚙️ Real-World Relevance:
OOP is the foundation of frameworks like Django, Flask, and even machine learning libraries like TensorFlow. Mastery in OOP is essential for building scalable systems.

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❓ FAQ – Python OOP

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❓ What is the main difference between a class and an object?
✅ A class is a blueprint; an object is an instance of that blueprint.

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❓ Does Python support method overloading?
❌ Not directly. You simulate it using default or variable-length arguments.

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❓ What is the purpose of @staticmethod?
✅ To create a method that doesn’t require access to the instance or class.

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❓ What are private attributes in Python?
✅ Prefixed with __, they are not directly accessible outside the class.

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