🐍 Object-Oriented Programming in Python

A Hands-On 2-Hour Tutorial

From zero OOP to building a real abstract-base-class hierarchy — in one Jupyter notebook.

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Overview

This repository contains a self-contained, pedagogically-structured Jupyter notebook that teaches Object-Oriented Programming (OOP) in Python from the ground up. It is designed for learners who already know basic Python (functions, lists, loops) but have never written a class before.

The tutorial covers every core OOP concept, uses consistent, beginner-friendly examples throughout, and culminates in a capstone project that ties every concept together: a mini library management system with abstract base classes, composition, properties, and operator overloading.

Time commitment: ~2 hours of active reading + running cells + doing exercises.

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What You Will Learn

Core concepts ✅ Classes and instances ✅ Instance vs. class variables ✅ Instance, class, and static methods ✅ Inheritance and super() ✅ Method overriding and polymorphism ✅ Special (dunder) methods

Advanced topics ✅ Property decorators (@property, setters, deleters) ✅ Encapsulation & naming conventions ✅ Abstract Base Classes (abc module) ✅ Composition vs. inheritance ✅ Operator overloading (+, ==, <, len, in, [], …)

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Notebook Roadmap

0. Motivation — why do we need classes?
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1. Classes & Instances ─────── your first class, self, __init__
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2. Class Variables ─────────── shared state, the mutable-default trap
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3. Method Types ────────────── instance / class / static
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4. Inheritance ─────────────── super(), overriding, polymorphism, MRO
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5. Dunder Methods ──────────── __repr__, __eq__, __lt__, __add__, __len__ …
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6. Properties ──────────────── getter, setter, deleter, validation
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7. Encapsulation & ABCs ────── _private, @abstractmethod, composition
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8. Capstone: Library Management System
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9. Summary & further reading

Each section ends with a short hands-on exercise so you can test your understanding immediately.

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Getting Started

Prerequisites

• Python 3.10 or later
• jupyter (or an IDE with native notebook support such as VS Code or PyCharm)

Run locally (recommended)

# 1. Clone the repo
git clone https://github.com/demirayonur/OOP-Tutorial.git
cd oop-python-tutorial

# 2. (Optional but recommended) create a virtual environment
python -m venv .venv
source .venv/bin/activate          # macOS / Linux
# .venv\Scripts\activate           # Windows

# 3. Install Jupyter
pip install jupyter

# 4. Launch
jupyter notebook OOP_in_Python_Tutorial.ipynb

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How to Get the Most Out of This Tutorial

Read → Run → Break → Fix → Repeat.

1. Read each markdown cell carefully. The explanations are written to build intuition, not just list facts.
2. Run every code cell yourself. Don't just read the output.
3. Break the code on purpose. Change a class variable to a list. Assign a negative value. See what happens.
4. Fix it. That is where the real learning happens.
5. Do the exercises before reading the solution in the next cell.

Each section is designed so you can stop, take a break, and come back without losing your place.

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Repository Structure

oop-python-tutorial/
├── OOP_in_Python_Tutorial.ipynb     ← the tutorial (start here)
├── README.md                        ← you are here
└── .gitignore                       ← standard Python .gitignore

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Capstone Project: Library Management System

The final section builds a realistic mini-system that uses every concept from the tutorial:

• Abstract base class (LibraryItem) with abstract methods
• Inheritance tree: PrintBook, EBook, AudioBook
• Class-level ID counter auto-assigning unique IDs
• Properties with validation (page count, duration)
• State management (check-out / return logic)
• Dunder methods for equality, ordering, iteration, membership, and length
• Composition: a Library that has items rather than is one
• Alternative constructor via @classmethod
• Static helper via @staticmethod

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FAQ

Do I need to install anything besides Jupyter?

No. The entire tutorial uses only the Python standard library (abc, functools, dataclasses, collections.abc). No pip install ... of third-party packages is required.

Why Python 3.10+?

The tutorial uses modern type-hint syntax like list[Book] and int | None (PEP 604), which require Python 3.10 or later. If you are on 3.9, the notebook still runs thanks to from __future__ import annotations, but upgrading is recommended.

I found a typo / have a suggestion. What should I do?

Open an issue or submit a pull request. See the Contributing section below.

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Contributing

Contributions are warmly welcomed! If you spot a typo, think an explanation could be clearer, or want to add an exercise:

1. Fork the repository
2. Create a feature branch (git checkout -b improve/section-5-examples)
3. Commit your changes (git commit -m 'Improve dunder section example')
4. Push to the branch (git push origin improve/section-5-examples)
5. Open a Pull Request

For larger changes, please open an issue first to discuss what you would like to modify.

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Happy coding. 🐍