Why Are Classes Confusing in Python for Beginners? (And How to Finally Understand Them)

Feb 8, 2026

The Problem

When I started learning Python, I could understand functions, loops, and booleans without much trouble. These concepts felt natural - a function is like a recipe, a loop repeats things, and booleans are just yes/no logic.

But then I hit classes. Suddenly, everything felt weird.

I saw code like this:

class Dog:
    def __init__(self, name, breed):
        self.name = name
        self.breed = breed

    def bark(self):
        print(f"{self.name} says Woof!")

And I had so many questions:

What is self and why is it everywhere?
Why do I need __init__ with those double underscores?
What’s the difference between Dog (the class) and my_dog (the object)?
When would I actually use this instead of functions?

I wasn’t alone. Looking at Reddit threads, I see many beginners feel the same way. Classes feel like a wall after the smooth slope of learning functions and loops.

Why Classes Feel So Hard

I think classes are confusing for a few reasons.

1. It’s a Paradigm Shift

When I write functions, I think in steps: “Do this, then that, then this other thing.” This is procedural thinking.

Classes require object-oriented thinking. Instead of steps, I think about “things” that have both data (what they know) and behavior (what they can do).

This isn’t just new syntax. It’s a new way to think about problems entirely.

2. Too Many New Concepts at Once

When I learned functions, I only needed to understand one thing: a reusable block of code.

With classes, I suddenly need to understand 5+ new concepts simultaneously:

Classes vs objects
self and what it refers to
__init__ and dunder methods
Instance variables
Methods (which look like functions but behave differently)
Later: inheritance, polymorphism, encapsulation

That’s a lot of cognitive load all at once.

3. The Syntax Looks Different

Python’s class syntax introduces symbols I hadn’t seen before:

def __init__(self, name):  # Double underscores?
    self.name = name  # What is self?

Compare this to a function:

def create_user(name):  # Familiar
    return {"name": name}

The function version uses only concepts I already know. The class version introduces unfamiliar patterns.

4. I Don’t See the “Why”

When I was learning, my functions worked fine for simple scripts. I could write:

def create_user(name, email):
    return {"name": name, "email": email}

def get_user_info(user):
    return f"{user['name']} ({user['email']})"

user1 = create_user("Alice", "[email protected]")
print(get_user_info(user1))

This works perfectly. Why do I need classes?

This practical disconnect made classes feel unnecessary - just more complex syntax for problems I’d already solved.

How I Started Understanding Classes

I found that breaking the problem down helped. Let me share what worked.

Step 1: See Classes as Data Containers

First, I learned to think of classes as a way to bundle related data together.

Here’s the function version I already understood:

def create_user(name, email):
    return {"name": name, "email": email}

user1 = create_user("Alice", "[email protected]")
print(user1['name'])  # Access data

And here’s the class version:

class User:
    def __init__(self, name, email):
        self.name = name
        self.email = email

user1 = User("Alice", "[email protected]")
print(user1.name)  # Access data

I can see the parallel:

create_user() function → User class
Dictionary returned → self.name and self.email
Dictionary access user['name'] → attribute access user.name

The class is just a more structured way to hold data.

Step 2: Add Behavior to the Data

The real power of classes is bundling functions with the data they operate on.

With functions, data and behavior are separate:

def create_user(name, email):
    return {"name": name, "email": email}

def get_user_info(user):
    return f"{user['name']} ({user['email']})"

user1 = create_user("Alice", "[email protected]")
# I have to pass user1 to the function
print(get_user_info(user1))

With classes, the data knows how to describe itself:

class User:
    def __init__(self, name, email):
        self.name = name
        self.email = email

    def get_info(self):
        return f"{self.name} ({self.email})"

user1 = User("Alice", "[email protected]")
# The user object knows how to describe itself
print(user1.get_info())

I don’t need to pass user1 to get_info() - the method already has access to the data through self.

Step 3: Understanding `self`

This was my biggest confusion point. Let me show what I wished would work:

class Dog:
    def __init__(name, breed):  # No self
        self.name = name  # ERROR: What is self?
        self.breed = breed

dog1 = Dog("Buddy", "Golden Retriever")  # TypeError!

This fails because Python doesn’t know which dog we’re talking about.

Here’s why self is necessary:

class Dog:
    def __init__(self, name, breed):
        self.name = name  # "THIS dog's name is..."
        self.breed = breed  # "THIS dog's breed is..."

dog1 = Dog("Buddy", "Golden Retriever")
# Inside __init__, self refers to dog1

dog2 = Dog("Max", "Poodle")
# Inside __init__, self refers to dog2 (different object!)

When I create dog1, self becomes dog1. When I create dog2, self becomes dog2. Each object gets its own data.

The self parameter is just Python’s way of saying “this specific object I’m working with right now.”

Step 4: Real-World Analogies

I found analogies helped make things click.

Cookie Cutter (Class) vs Cookies (Objects):

class Cookie:  # This is the cookie cutter (template)
    def __init__(self, flavor):
        self.flavor = flavor  # Each cookie has a flavor
        self.bites = 0  # Each cookie tracks its own bites

    def take_bite(self):
        self.bites += 1
        print(f"Yum! This {self.flavor} cookie has been bitten {self.bites} times")

# Make cookies from the cutter
chocolate_cookie = Cookie("chocolate chip")
raisin_cookie = Cookie("oatmeal raisin")

chocolate_cookie.take_bite()  # "Yum! This chocolate chip cookie has been bitten 1 times"
chocolate_cookie.take_bite()  # Bites: 2
raisin_cookie.take_bite()     # Bites: 1 (different cookie!)

The class (Cookie) is the cutter. I can use it to make many cookies (objects). Each cookie is independent - biting one doesn’t affect the other.

When Should I Use Classes?

I don’t need classes for every script. Here’s when I use them:

Use functions when:

Writing a simple script
Data doesn’t need to track its own state
Operations are independent

Use classes when:

Multiple related pieces of data belong together
Data needs to track its own state (like the bite counter)
I need to create many similar objects with the same structure
Code is growing complex and needs organization

For example, a game with multiple enemies works well with classes:

class Enemy:
    def __init__(self, name, health, damage):
        self.name = name
        self.health = health
        self.max_health = health
        self.damage = damage

    def attack(self):
        return self.damage

    def take_damage(self, amount):
        self.health -= amount
        if self.health <= 0:
            print(f"{self.name} was defeated!")

    def heal(self, amount):
        self.health = min(self.health + amount, self.max_health)

# Create multiple enemies
goblin = Enemy("Goblin", 30, 5)
dragon = Enemy("Dragon", 100, 20)

# Each enemy tracks its own state
goblin.take_damage(10)
dragon.take_damage(50)

print(goblin.health)  # 20
print(dragon.health)  # 50

A Learning Path That Works

Based on my experience, here’s how I would approach learning classes:

Week 1: Classes as Data Containers

Learn just __init__ and instance variables
Practice creating classes that hold data
Don’t worry about methods yet

Week 2: Add Methods

Add functions that operate on the class’s data
Understand self as “this object”
Practice with 2-3 concrete examples (User, Product, Card)

Week 3: Practice with Real Examples

Build something practical (a simple game, address book, etc.)
See how classes organize code better than functions
Read simple class-based code

Week 4: Inheritance (Optional)

Learn how classes can extend other classes
Skip this if overwhelmed - come back later

Ongoing: Read Real Code

Look at Django models, Pygame sprites, or other real Python code
See how professionals use classes in production

Common Mistakes I Made

I want to share mistakes that slowed me down:

Mistake 1: Trying to Learn Everything at Once

I tried to understand inheritance, polymorphism, and encapsulation before I even understood basic classes. This was overwhelming.

Better approach: Master simple classes first. Treat advanced OOP concepts as separate topics to learn later.

Mistake 2: Memorizing Syntax Without Understanding

I tried to memorize “always write def method(self)” without understanding why self was needed.

Better approach: Understand that self refers to the specific object. The syntax will follow naturally.

Mistake 3: Starting With Complex Frameworks

I tried to learn Django classes before understanding basic Python classes. Django’s classes have lots of magic that confused me.

Better approach: Learn basic classes first, then tackle framework-specific classes later.

Mistake 4: Not Writing Enough Code

I watched tutorials and read docs without actually writing class-based code.

Better approach: Write code. Create classes. Make mistakes. Fix them. Repeat.

The Key Insight

Classes felt hard because I was trying to learn:

New syntax
New concepts
A new way of thinking

All at the same time.

Once I started simple - treating classes as bundles of related data and functions - things began to click. I practiced with concrete examples, didn’t rush into advanced concepts, and wrote lots of code.

Now classes feel natural. I can’t imagine writing complex programs without them.

Summary

In this post, I explained why Python classes feel confusing for beginners and shared a practical learning path. The key points are:

Classes require a paradigm shift from procedural to object-oriented thinking
Multiple new concepts appear at once (self, init, objects, methods)
The syntax looks unfamiliar compared to functions
Start simple: treat classes as data containers, then add behavior
Practice with concrete examples before tackling advanced OOP

If you’re struggling with classes, you’re not alone. Take it step by step, write lots of code, and don’t rush into inheritance and polymorphism until basic classes feel comfortable.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

👨‍💻 Reddit: I cannot understand Classes and Objects clearly and logically
👨‍💻 Python Official Documentation on Classes
👨‍💻 Real Python: Object-Oriented Programming (OOP) in Python 3

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!