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A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques
Key Features:
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
Book Description:
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 friendly, comprehensive 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. UML class diagrams are generously used throughout the text for you to understand class relationships. Beyond the book’s focus on OOP, it features an in-depth look at Python’s exception handling and how functional programming intersects with OOP. Not one, but two very powerful automated testing systems, unittest and pytest, are introduced in this book. 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.
What You Will Learn:
Implement objects in Python by creating classes and defining methodsExtend class functionality using inheritanceUse exceptions to handle unusual situations cleanlyUnderstand when to use object-oriented features, and more importantly, when not to use themDiscover several widely used design patterns and how they are implemented in PythonUncover the simplicity of unit and integration testing and understand why they are so importantLearn to statically type check your dynamic codeUnderstand concurrency with asyncio and how it speeds up programs
Who this book is for:
If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.
From the Publisher
Topics Covered: Object-Oriented Design When to Use OOP Abstract Classes and Operator Overloading Python Data Structures The Intersection of OOP and Functional Programming Strings, Serialization, and File Paths The Iterator Pattern …and more!
What’s new in this fourth edition of Python Object-Oriented Programming?
This fourth edition builds upon classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. You’ll learn how to tackle a project using OOP from all its different perspectives and see how a design evolves over time.
What’s New:
Updated for Python 3.9+ Expanded to cover abstract base classes and operator overloading Updated to cover latest asyncio features in the concurrency chapter Introduction to new automated testing systems, unit tests, and pytest
How does this book help readers learn about Python Object-Oriented Programming?
Python Object-Oriented Programming, 4th Edition takes you through the fundamentals of object-oriented programming principles and how to effectively implement them in Python, providing clear, intuitive explanations supplemented with useful example code throughout.
This book also shows you how to use Python’s built-in exceptions and data structures, as well as elements of the Python standard library. It also demonstrates how to use various concurrency libraries available as part of Python; this lets you write software that can make use of multiple cores and multiple processors in a modern computer.
We’ve illustrated as many object-oriented programming techniques and situations as possible to provide clear guidance for developers who are trying to expand Python skills. The main goal is to work from foundational object-oriented design concepts through to more sophisticated applications of those concepts.
What makes this book different from other Python OOP books?
Each chapter discusses a case study, which can be solved using a variety of techniques that are unique to that chapter. The idea of a consistent case study with multiple solutions is a valuable part of the book. It’s very important – especially for programmers new to object-oriented design – to see multiple solutions to a problem.
We also feel unit testing is an essential ingredient that’s often omitted from a lot of writing about programming and programming languages. The entire book’s set of examples has a complete unit test suite. This even includes running the mypy tool in strict mode on all the code. In addition to talking about testing in the book, the code repository associated with the book has all the example doctests and the code unit tests for all the examples.
Additionally, we worry about an over-emphasis on object-oriented design and programming. We’ve included a chapter on functional programming techniques because these are part of Python and shouldn’t be shunned through a – possibly – mistaken bias toward class definitions.
Finally, we’ve fully embraced type annotations. We revised all the examples to make use of type hints.
Key Features: In-depth analysis of common object-oriented design patterns that are suitable to Python’s style Work with data (JSON serialization, validation, and more) Catch exceptions, explore authentication, add tests and concurrency, and implement ML algorithms Case studies are part of one large ML project (building a k-NN classifier to classify a species)
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Published Date
July 2, 2021 January 6, 2021 May 28, 2021 December 30, 2022 October 29, 2021
Reader Knowledge Level
Mastering Beginner to intermediate Mastering Intermediate Beginner
Learning Outcome
Clear and intuitive explanations of object-oriented programming principles in Python Industry-approved coding practices to write clean and sustainable Python code A perfect blend of theory and practical exercises to enhance your Python coding skills An essential guide to the functional programming features of Python A holistic understanding of Python programming through concise tutorials and real-life projects
Compatible Version
Python 3.9 Python 3.9 Python 3.9 Python 3.10 Python 3.9
Amazon Rating
4.3 out of 5 4.6 out of 5 4.4 out of 5 5 out of 5 4.7 out of 5
Page Count
630 422 714 576 552
Publisher : Packt Publishing; 4th ed. edition (July 2, 2021)
Language : English
Paperback : 714 pages
ISBN-10 : 1801077266
ISBN-13 : 978-1801077262
Item Weight : 2.68 pounds
Dimensions : 9.25 x 7.5 x 1.47 inches
