Introduction
I recently completed a challenging learning journey through advanced Python concepts, and I wanted to share my experience with fellow learners. The repository is available at github.com/hejhdiss/itx-oop-python-decorators.
Full disclosure: I'm still a beginner in Python programming.
What This Repository Contains
This collection includes three comprehensive workbooks that I created with the help of AI (asking questions and learning through conversation):
- oop.pdf - Python OOP concepts covering the four pillars, inheritance, MRO (Method Resolution Order), encapsulation, properties, and metaclasses
- itxxxxxxx.pdf - Deep dive into iterables, iterators, and generators
- decorator.pdf - Comprehensive guide to decorators and context managers
A Word of Caution ⚠️
Since these PDFs were generated with AI assistance, there may be errors or inaccuracies in some sections. I encourage you to:
- Cross-reference concepts with official Python documentation
- Test the code examples yourself
- Use these as a starting point, not the final authority
- Join communities like Stack Overflow or Reddit's r/learnpython if you find confusing parts
My Current Level (And Why That Matters)
I want to be transparent: I'm still a beginner in Python programming. Even after working through these materials, I'm continuing to learn and grow.
If you're in the same boat, this repository might be perfect for you. It's created by a beginner, for beginners trying to level up.
What Makes This Different?
Most OOP tutorials assume you're already comfortable with intermediate concepts. These workbooks try to bridge that gap by:
- Providing exercises at Simple, Medium, and Hard difficulty levels
- Including detailed solutions with explanations
- Offering scenario-based exercises that simulate real-world problems
- Explaining the "why" behind concepts, not just the "how"
Topics Covered
Object-Oriented Programming
- The four pillars (Encapsulation, Inheritance, Polymorphism, Abstraction)
- Method Resolution Order (MRO) and the diamond problem
- Properties and attribute control
- Abstract Base Classes vs Protocols
- Metaclasses and the
__new__method
Iterators and Generators
- Understanding the iterator protocol
- Custom iterators
- Generator functions and expressions
- Memory management with lazy evaluation
- The sentinel pattern with
iter()
Decorators and Context Managers
- Function decorators with and without arguments
- Decorator stacking
- Generator-based context managers with
@contextmanager - Exception handling in context managers
- Combining decorators and context managers
My Honest Take: The Learning Never Stops
The Python ecosystem is enormous. After completing these workbooks, I realize there's still much more to learn ahead—standard libraries, frameworks, and beyond.
And that's the journey of programming. You don't need to know everything to be productive.
Who This Repository Is For
This is ideal if you:
- Know Python basics (functions, classes, loops, conditionals)
- Want to understand intermediate/advanced OOP concepts
- Learn better with hands-on exercises
- Appreciate learning from someone at a similar level (not an expert)
- Are okay with occasionally encountering errors to debug
This is not for you if:
- You're looking for production-ready, error-free code
- You want expert-level insights
- You need framework-specific tutorials
- You're preparing for technical interviews (though it might help!)
How to Use This Repository
- Clone or download the repository
- Read through one workbook at a time (don't rush!)
- Try the exercises yourself first before looking at solutions
- Test the code in your own Python environment
- Take notes on what confuses you
- Google extensively - these materials should supplement, not replace, other resources
Final Thoughts
Programming is humbling. Every time I think I'm getting somewhere, I discover ten new things I don't understand. But that's also what makes it exciting.
These materials will help you to understand concepts that you'd been struggling with. They won't make you an expert, but they might help you get unstuck.
If you're a fellow beginner navigating the vast ocean of Python programming, I hope this repository serves as a helpful companion on your journey.
Contributing
Since I'm still learning, I welcome corrections, improvements, and suggestions! If you spot errors or have better explanations, please open an issue or pull request on the GitHub repository.
Remember: Every expert was once a beginner who refused to give up. Keep learning, keep coding, and don't be afraid to be confused. That's where growth happens.
Happy coding! 🐍
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