Mastering OOP in Python
Unlocking Object-Oriented Programming Paradigms
AI Textbook - 100+ pages
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Dive deep into the world of Object-Oriented Programming (OOP) with Python as your guide. This book is an essential resource for programmers of all levels seeking to harness the power of OOP principles in Python. From foundational concepts for beginners to advanced techniques for seasoned codiles, 'Mastering OOP in Python' offers a structured exploration of classes, inheritance, polymorphism, and more through its comprehensive 12-chapter journey. Learn to write reusable and maintainable code with clarity, bolstered by numerous practical examples and hands-on exercises. Immerse yourself in the elegance of Python's OOP features and elevate your coding expertise to new heights.
- Understanding Classes and Objects
- The Power of Inheritance
- Interfaces and Polymorphism
2. Writing Reusable Code
- Leveraging Modules and Packages
- Design Patterns in Python
- Refactoring for Efficiency
3. Advanced OOP: Beyond the Basics
- Metaclasses and Attributes
- Managing Multiple Inheritance
- Magic Methods & Operator Overloading
4. Practical OOP: Projects and Solutions
- Building a Command-Line Application
- Developing a Web Service with Flask
- Creating a Game with Pygame
5. OOP Design Principles
- SOLID Principles Explained
- Applying the DRY Concept
- Balancing Cohesion and Coupling
6. Python Data Models
- Understanding the Data Model
- Customizing Object Behavior
- The Importance of __slots__
7. Exception Handling in Python
- Basics of Exceptions
- Designing Robust Code
- Custom Exception Types
8. Testing Your OOP Code
- Unit Testing Basics
- Test-Driven Development (TDD)
- Using Mocks and Stubs
9. OOP and Multithreading
- Threads vs. Processes
- Synchronizing Threads
- Threading in GUI Applications
10. Performance Optimization
- Profiling OOP Code
- Optimizing Memory Usage
- Speeding Up Python with Cython
11. Integrating with Other Languages
- Extending Python with C/C++
- Using Python with Java
- The Role of Python in Data Science
12. The Future of OOP in Python
- Keeping Up with Python Updates
- Python's Role in Modern Software
- Evolution of OOP Practices
Table of Contents
1. The Pillars of OOP in Python- Understanding Classes and Objects
- The Power of Inheritance
- Interfaces and Polymorphism
2. Writing Reusable Code
- Leveraging Modules and Packages
- Design Patterns in Python
- Refactoring for Efficiency
3. Advanced OOP: Beyond the Basics
- Metaclasses and Attributes
- Managing Multiple Inheritance
- Magic Methods & Operator Overloading
4. Practical OOP: Projects and Solutions
- Building a Command-Line Application
- Developing a Web Service with Flask
- Creating a Game with Pygame
5. OOP Design Principles
- SOLID Principles Explained
- Applying the DRY Concept
- Balancing Cohesion and Coupling
6. Python Data Models
- Understanding the Data Model
- Customizing Object Behavior
- The Importance of __slots__
7. Exception Handling in Python
- Basics of Exceptions
- Designing Robust Code
- Custom Exception Types
8. Testing Your OOP Code
- Unit Testing Basics
- Test-Driven Development (TDD)
- Using Mocks and Stubs
9. OOP and Multithreading
- Threads vs. Processes
- Synchronizing Threads
- Threading in GUI Applications
10. Performance Optimization
- Profiling OOP Code
- Optimizing Memory Usage
- Speeding Up Python with Cython
11. Integrating with Other Languages
- Extending Python with C/C++
- Using Python with Java
- The Role of Python in Data Science
12. The Future of OOP in Python
- Keeping Up with Python Updates
- Python's Role in Modern Software
- Evolution of OOP Practices