Build robust and maintainable object-oriented Python applications and libraries

€9.6 ~~€47.99~~

By Steven F. Lott & Dusty Phillips

Pages 714

Published in Jul 2021

Product Type eBook

Edition 4th Edition

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Key Benefits

Build an intuitive understanding of object-oriented design, from introductory to mature programs

Learn the ins and outs of Python syntax, libraries, and best practices

Examine a machine-learning case study at the end of each chapter

What You Will Learn

Implement objects in Python by creating classes and defining methods

Extend class functionality using inheritance

Use exceptions to handle unusual situations cleanly

Understand when to use object-oriented features, and more importantly, when not to use them

Discover several widely used design patterns and how they are implemented in Python

Uncover the simplicity of unit and integration testing and understand why they are so important

Learn to statically type check your dynamic code

Understand concurrency with asyncio and how it speeds up programs

Who Is This Book For?

If you are new to object-oriented programming or if you have basic Python skills and want to learn how and when to correctly apply OOP principles in Python 3.11 and beyond, this is the book for you. Mid-level Python developers, software engineers, and data scientists will benefit from its practical guidance. Complete with a solid introduction to Python, this book proves to be a useful resource for experienced object-oriented programmers transitioning from other languages or seeking a leg up in the new world of Python. Minimal previous experience with Python programming is necessary.

Book Description

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.

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Lou mauget Jul 30, 2021

Python-experienced or not, I recommend the book to you because it increases one’s knowledge of each topic when contrasted and compared to another language perspective. If you work with object-oriented patterns in any medium, then this book will interest you.There are 750 pages of niceties. I dislike treasure-hunting a line-of-interest from each code example in some books. This book sets emphasized parts of code examples in boldface. In addition, each snippet is color-coded Python for readability. Python is duck-typed, but the authors statically type-checked the book’s accompanying code type flows with the mypy tool. So ... the included code works.The content is organized into four major sections:1. Well-known OOPs principles as reflected in Python — with good practices, case studies, and exercises in each chapter2. Built-in Python features from the OOPs viewpoint — these form a base for a contrast-and-compare with other languages3. Popular OOPS Design patterns4. Testing and concurrencyI liked Chapter 5 – When to use Object-Oriented Programming. It presents balanced coverage of a trade-off between an object-oriented rendition of an example and a more data-oriented version or a functional version. It addresses Python’s lack of private members. The coverage delved into reasonable alternatives within typical OOPS design decisions.Chapter 8 — The Intersection of Object Oriented and Functional Programming, caught my eye. Functional programming has become cool after lurking in an academic setting while OOPS enjoyed two decades of limelight. The authors made a credible case for melding the two paths. They point out that Python functions are objects as well.Chapter 11 — Common Design Patterns, and Chapter 12 — Advanced Design Patterns, give 12 well-known design patterns their Python spins. The discussion about the singleton pattern was interesting. Python has no private constructor capability. Instead, a Python module is a singleton, so there’s the singleton container.Testing is well-covered in chapter 14 (pun intended).Concurrency is difficult. Chapter 14 covers usual concurrency topics. It was the most interesting chapter to me. It enhanced my general understanding of these topics by letting me contrast and compare Python-based approaches to those I knew in other languages and libraries. You don’t need to know much Python to benefit from this chapter. It's a readable language. The Python GIL may be unique, however. The text doesn’t explicitly state that the interpreter runs in a single CPU core, where threads must time-share that core, as gated by the GIL. The text says that the multiprocessing interface supports multiple concurrent core processes. Concurrency diagrams would have been helpful (especially the floorplan of Constantine and Mo’s diner).I say “get this book.” The authors have vast experience. I relate to the ancient one of the pair who has been programming forever. He lives on a boat that he relocates. I wrote my first program in machine language on a vacuum tube computer in 1961. Yes, but I live in a simple non-moving house.

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Matthew Emerick Jul 16, 2021

About This BookThere are many programming paradigms, but the paradigm that is the most used is still object-oriented. In this book, you learn all about object-oriented programming (OOP) using Python. The book covers the basics of what an object is, moves onto Python-specific features used for OOP, examines several design patterns, and finishes with issues regarding testing and concurrency.Who Is This For?This is a good book for anyone new to OOP so long as they have some Python programming knowledge. This book has great coverage of the most important OOP concepts and ensures that the reader has enough knowledge to put them into practice.OrganizationThe book is organized into four sections: core concepts, Python’s built-in OOP features, common design patterns, and chapters on testing and concurrency. Each chapter covers its topic and then has sections for recall, exercises, and a summary. There is a common case study throughout the book on the AI/ML concept of k-NN.Did This Book Succeed?This is a great book to learn the basics of OOP, refresh yourself on OOP, or learn how to program Python using OOP. It is well organized and easy to read. Someone new to OOP can easily come up to speed with practical examples of the paradigm.Rating and Final ThoughtsOverall, I give this book a 5 out of 5.If you are a Python programmer and want to learn OOP or improve your understanding, this is an excellent book. It’s not for the expert Python programmer or someone who only programs in a different OOP-focused language like Java or C++. I would recommend it very much for college students taking a software engineering course.

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Moses Kayanda Jul 30, 2021

If you, like me, have just recently started programming in Python and are still learning the language in detail, you would find this to be one of the best books available for covering the concepts of Object-Oriented Programming in a simple yet detailed manner. The authors have done a fantastic job explaining the Object-Oriented Approach by teaching how to structure programs in Python.The book has 14 chapters that teach the design patterns used in Python, how to statically type-check your dynamic code, when to use Object-Oriented Features (and when not to use them), and other topics. In teaching good design, the authors teach OOP key concepts such as Inheritance, Polymorphism, and Encapsulation.You get the latest Python Syntax as the book examples test with Python 3.9.5. I realized some of the codes in the 3rd Edition were not running well because of typing errors. But that’s what makes Programming fun and why we have the issues page in Github, right? Yes, you get all the codes in the book on the provided Github link, which, in my opinion, makes it easier for reference.In every chapter, you get the background of the subject concept, detailed examples, best practices, common mistakes to avoid, a section to recall the chapter, structured exercises to test what you have learned, and, finally, a chapter summary. The case studies section gives the reader a detailed perspective of real-world scenarios and how to navigate them. You also get illustrated summaries and examples in the form of tables and figures throughout the book.++++++++++++++++++++Who this book is for?I would highly recommend this book to anyone in or starting out in Data Science and, specifically, from a non-Computer Science, background as the book clearly explains concepts that are new to non-traditional Computer Science students. The book considers the role of Python in Data Science and, hence, integrates Math and Statistics in examples of how to apply OOP concepts. Regardless of your path or field, these are skills that once you get right, everything else feels less uphill in your learning.++++++++++++I will give this book a 5/5 review. In an age of half-baked online tutorials, you need a well-written book like this one.

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Austen Aug 26, 2021

Very practical book with real world examples, that can help any beginner interested in python to get up and running quickly, while also providing a lot of depth to teach even a python export a new thing or two.Each chapter is well laid out and organized with end of chapter highlights, exercises, and recap so you can test what you learned, while also allowing those with more experience to skip ahead to topics they want to explore more.I especially enjoyed following along using the working code provided in the book, and seeing how the examples built on each other towards a complex and meaningful application.

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Gabe Rigall Jul 23, 2021

BLUF: This book should be in every Python programmer's library. It's not a "Python basics" book but picks up the torch shortly thereafter and runs with it.PROS:This book is a comprehensive look at object-oriented design and programming. It takes an iterative approach to teaching, kept my attention throughout, and engaged my critical thinking processes. There were little interjections of humor now and again that I enjoyed. There were also in-text reading recommendations for further learning should one be interested in going down a particular rabbit-hole.CONS:None so far that I've found. I do prefer code snippets to be in color but that's a minor gripe.

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Python Object-Oriented Programming , Fourth Edition

Build robust and maintainable object-oriented Python applications and libraries

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Python Object-Oriented Programming , Fourth Edition

Build robust and maintainable object-oriented Python applications and libraries

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