Book Image

Python Object-Oriented Programming - Fourth Edition

By : Steven F. Lott, Dusty Phillips
2 (2)
Book Image

Python Object-Oriented Programming - Fourth Edition

2 (2)
By: Steven F. Lott, Dusty Phillips

Overview of this book

Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python’s classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python’s exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs.
Table of Contents (17 chapters)
15
Other Books You May Enjoy
16
Index

Exercises

We've covered several different concurrency paradigms in this chapter and still don't have a clear idea of when each one is useful. In the case study, we hinted that it's generally best to develop a few different strategies before committing to one that is measurably better than the others. The final choice must be based on measurements of the performance of multi-threaded and multi-processing solutions.

Concurrency is a huge topic. As your first exercise, we encourage you to search the web to discover what are considered to be the latest Python concurrency best practices. It can help to investigate material that isn't Python-specific to understand the operating system primitives like semaphores, locks, and queues.

If you have used threads in a recent application, take a look at the code and see how you can make it more readable and less bug-prone by using futures. Compare thread and multiprocessing futures to see whether you can gain anything...