🐍 Python Learning Roadmap Repository

Welcome to the Step-by-Step Python Learning repository!
This repository contains notes, exercises, and mini-projects organized by learning stages — from the basics to building real-world Python applications. It's perfect for self-learners or anyone who wants a structured way to learn Python.

🗺️ Roadmap Pembelajaran Python

The learning journey is divided into several stages, from beginner to advanced, with practice projects to reinforce each concept.

Stage 1: Basic Python ✅ (Completed)

The essential foundations of Python that every learner should master first.

• Variable & Data Type
• Input / Output
• Conditional Statement (if)
• Loops (for, while)
• Functions
• Lists & Dictionaries
• Mini CLI Project

📁 Folder: 01-basic-python

Stage 2: Intermediate Python

This stage introduces more advanced Python features with hands-on practice.

• List Comprehension
• Tuples & Sets
• Functions with *args and **kwargs
• Exception Handling (try, except)
• Modularization (import, modules)
• File I/O (reading/writing .txt files)
• Simple Python project folder structure
• Practice Projects: File manager, CLI apps, logic calculator, etc.

📁 Folder: 02-intermediate-python

Stage 3: Object-Oriented Programming (OOP)

Learn the OOP paradigm, a key concept in software development.

• Classes & Objects
• Constructors (__init__)
• Encapsulation, Inheritance, Polymorphism
• OOP-Based Mini Project

📁 Folder: 03-oop-python

Stage 4: Advanced Python

Advanced language features and writing more "Pythonic" code.

• Virtual Environments (venv, pip)
• Testing (unit tests, pytest)
• Lambda Functions, map() / filter() / reduce()
• Decorators & Generators
• Context Managers (with)
• Logging & Debugging

📁 Folder: 04-advanced-python

Stage 5: Building Real Python Applications

Choose your path based on your interests or career goals:

• Web Development: Flask, Django
• Data Science: Pandas, Matplotlib, NumPy
• Automation / Scripting: Selenium, cron
• API Development: Flask REST, FastAPI
• Desktop Applications: Tkinter, PyQt
• AI / Machine Learning: Scikit-learn, TensorFlow, PyTorch

📁 Folder: 05-python-apps

💡 Goals

This repository is created to:

• Document my personal learning journey
• Help others learn Python through a structured path
• Serve as a portfolio of my Python learning progress

🤝 Contributions

Suggestions, improvements, and contributions are welcome!
Feel free to open issues or submit pull requests.

🧑‍💻 License

This project is licensed under the MIT License.

Note

Feel free to reach out if you want to collaborate or learn together.
Happy coding and keep learning! 🚀