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Python Object-Oriented Programming

Python Object-Oriented Programming - Fourth Edition

By : Steven F. Lott, Dusty Phillips
3.9 (34)
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Python Object-Oriented Programming

Python Object-Oriented Programming

3.9 (34)
By: Steven F. Lott, Dusty Phillips

Overview of this book

Python Object-Oriented Programming, Fourth Edition is a practical guide to advancing your OOP skills with modern Python. Going beyond the fundamentals, it helps you work with Python as an OOP language, explore both common and advanced design patterns, and apply these concepts to data manipulation and testing of complex OOP systems. Each chapter features newly written open-ended exercises as well as a real-world case study, aligned with the improvements in Python 3.11—bringing faster execution and memory efficiency to your applications. Authors Steven F. Lott and Dusty Phillips provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, showing how they integrate with Python’s classes and data structures to facilitate good design. The book also introduces two powerful automated testing systems, unittest and pytest, and explores Python's concurrent programming ecosystem in depth. By the end of the book, you’ll have a thorough understanding of how to think about and apply object-oriented principles using Python syntax to create robust and reliable programs.
Table of Contents (17 chapters)
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15
Other Books You May Enjoy
16
Index

Recall

This chapter looked at a design pattern that seems ubiquitous in Python, the iterator. The Python iterator concept is a foundation of the language and is used widely. In this chapter we examined a number of aspects:

  • Design patterns are good ideas we see repeated in software implementations, designs, and architectures. A good design pattern has a name, and a context where it's usable. Because it's only a pattern, not reusable code, the implementation details will vary each time the pattern is followed.
  • The Iterator protocol is one of the most powerful design patterns because it provides a consistent way to work with data collections. We can view strings, tuples, lists, sets, and even files as iterable collections. A mapping contains a number of iterable collections including the keys, the values, and the items (key and value pairs.)
  • List, set, and dictionary comprehensions are short, pithy summaries of how to create a new collection from an...
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Python Object-Oriented Programming
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