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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

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)
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Index

Concurrency

Concurrency is the art of making a computer do (or appear to do) multiple things at once. Historically, this meant inviting the processor to switch between different tasks many times per second. In modern systems, it can also literally mean doing two or more things simultaneously on separate processor cores.

Concurrency is not inherently an object-oriented topic, but Python's concurrent systems provide object-oriented interfaces, as we've covered throughout the book. This chapter will introduce you to the following topics:

  • Threads
  • Multiprocessing
  • Futures
  • AsyncIO
  • The dining philosophers benchmark

The case study for this chapter will address ways we can speed up model testing and hyperparameter tuning. We can't make the computation go away, but we can leverage a modern, multi-core computer to get it done in less time.

Concurrent processes can become complicated. The basic concepts are fairly simple, but the...

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