Mastering Object-Oriented Python, 2nd Edition
English | June 14th, 2019 | ISBN: 1789531365 | 770 pages
Gain comprehensive insights into programming practices, and code portability and reuse to build flexible and maintainable apps using object-oriented principles
• Extend core OOP techniques to increase integration of classes created with Python
• Explore various Python libraries for handling persistence and object serialization
• Learn alternative approaches for solving programming problems, with different attributes to address your problem domain
Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language’s unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you’ll be shown how to effectively implement OOP in Python, and even explore Python 3.x.
Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you’ll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you’ll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs.
By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
What you will learn
• Explore a variety of different design patterns for the init() method
• Learn to use Flask to build a RESTful web service
• Discover SOLID design patterns and principles
• Use the features of Python 3’s abstract base
• Create classes for your own applications
• Design testable code using pytest and fixtures
• Understand how to design context managers that leverage the ‘with’ statement
• Create a new type of collection using standard library and design techniques
• Develop new number types above and beyond the built-in classes of numbers
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