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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
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16
Index

Sets

Lists are extremely versatile tools that suit many container object applications. But they are not useful when we want to ensure that objects in a list are unique. For example, a song library may contain many songs by the same artist. If we want to sort through the library and create a list of all the artists, we would have to check the list to see whether we've added the artist already, before we add them again.

This is where sets come in. Sets come from mathematics, where they represent an unordered group of unique items. We can try to add an item to a set five times, but the "is a member of a set" doesn't change after the first time we add it.

In Python, sets can hold any hashable object, not just strings or numbers. Hashable objects implement the __hash__() method; these are the same objects that can be used as keys in dictionaries; so again, mutable lists, sets, and dictionaries are out. Like mathematical sets, they can store only one copy of...

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