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Python 3 Object-Oriented Programming
ThirdEdition
Build robust and maintainable software with object-oriented design patterns in Python 3.8
Dusty Phillips
BIRMINGHAM
- MUMBAI
Python 3 Object-Oriented Programming Third Edition
Copyright © 2018 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
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Third edition: October 2018
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Contributors
About the author
Dusty Phillips is a Canadian software developer and author currently living in New Brunswick. He has been active in the open source community for two decades and has been programming in Python for nearly as long. He holds a master's degree in computer science and has worked for Facebook, the United Nations, and several start-ups. He's currently researching privacy-preserving technology at beanstalk.network.
Python3Object-OrientedProgrammingwas his first book. He has also written CreatingAppsinKivy, and self-published Hacking Happy, a journey to mental wellness for the technically inclined. A work of fiction is coming as well, so stay tuned!
About the reviewers
Yogendra Sharma is a developer with experience of the architecture, design, and development of scalable and distributed applications. He was awarded a bachelor's degree from Rajasthan Technical University in computer science. With a core interest in microservices and Spring, he also has hands-on experience technologies such as AWS Cloud, Python, J2EE, Node.js, JavaScript, Angular, MongoDB, and Docker. Currently, he works as an IoT and cloud architect at Intelizign Engineering Services, Pune.
Josh Smith has been coding professionally in Python, JavaScript, and C# for over 5 years, but has loved programming since learning Pascal over 20 years ago. Python is his default language for personal and professional projects. He believes code should be simple, goaloriented, and maintainable. Josh works in data automation and lives in St. Louis, Missouri, with his wife and two children.
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Table of Contents
Title Page
Copyright and Credits
Python 3 Object-Oriented Programming Third Edition
Packt Upsell
Why subscribe?
Packt.com
Contributors
About the author
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Conventions used
Get in touch
Reviews
1. Object-Oriented Design
Introducing object-oriented
Objects and classes
Specifying attributes and behaviors
Data describes objects
Behaviors are actions
Hiding details and creating the public interface
Composition
Inheritance
Inheritance provides abstraction
Multiple inheritance
Case study
Exercises
Summary
2. Objects in Python
Creating Python classes
Adding attributes
Making it do something
Talking to yourself
More arguments
Initializing the object
Explaining yourself
Modules and packages
Organizing modules
Absolute imports
Relative imports
Organizing module content
Who can access my data?
Third-party libraries
Case study
Exercises
Summary
3. When Objects Are Alike
Basic inheritance
Extending built-ins
Overriding and super
Multiple inheritance
The diamond problem
Different sets of arguments
Polymorphism
Abstract base classes
Using an abstract base class
Creating an abstract base class
Demystifying the magic
Case study
Exercises
Summary
4. Expecting the Unexpected
Raising exceptions
Raising an exception
The effects of an exception
Handling exceptions
The exception hierarchy
Defining our own exceptions
Case study
Exercises
Summary
5. When to Use Object-Oriented Programming
Treat objects as objects
Adding behaviors to class data with properties
Properties in detail
Decorators – another way to create properties
Deciding when to use properties
Manager objects
Removing duplicate code
In practice
Case study
Exercises
Summary
6. Python Data Structures
Empty objects
Tuples and named tuples
Named tuples
Dataclasses
Dictionaries
Dictionary use cases
Using defaultdict
Counter
Lists
Sorting lists
Sets
Extending built-in functions
Case study
Exercises
Summary
7. Python Object-Oriented Shortcuts
Python built-in functions
The len() function
Reversed
Enumerate
File I/O
Placing it in context
An alternative to method overloading
Default arguments
Variable argument lists
Unpacking arguments
Functions are objects too
Using functions as attributes
Callable objects
Case study
Exercises
Summary
8. Strings and Serialization
Strings
String manipulation
String formatting
Escaping braces
f-strings can contain Python code
Making it look right
Custom formatters
The format method
Strings are Unicode
Converting bytes to text
Converting text to bytes
Mutable byte strings
Regular expressions
Matching patterns
Matching a selection of characters
Escaping characters
Matching multiple characters
Grouping patterns together
Getting information from regular expressions
Making repeated regular expressions efficient
Filesystem paths
Serializing objects
Customizing pickles
Serializing web objects
Case study
Exercises
Summary
9. The Iterator Pattern
Design patterns in brief
Iterators
The iterator protocol
Comprehensions
List comprehensions
Set and dictionary comprehensions
Generator expressions
Generators
Yield items from another iterable
Coroutines
Back to log parsing
Closing coroutines and throwing exceptions
The relationship between coroutines, generators, and functions
Case study
Exercises
Summary
10. Python Design Patterns I
The decorator pattern
A decorator example
Decorators in Python
The observer pattern
An observer example
The strategy pattern
A strategy example
Strategy in Python
The state pattern
A state example
State versus strategy
State transition as coroutines
The singleton pattern
Singleton implementation
Module variables can mimic singletons
The template pattern
A template example
Exercises
Summary
11. Python Design Patterns II
The adapter pattern
The facade pattern
The flyweight pattern
The command pattern
The abstract factory pattern
The composite pattern
Exercises
Summary
12. Testing Object-Oriented Programs
Why test?
Test-driven development
Unit testing
Assertion methods
Reducing boilerplate and cleaning up
Organizing and running tests
Ignoring broken tests
Testing with pytest
One way to do setup and cleanup
A completely different way to set up variables
Skipping tests with pytest
Imitating expensive objects
How much testing is enough?
Case study
Implementing it
Exercises
Summary
13. Concurrency
Threads
The many problems with threads
Shared memory
The global interpreter lock
Thread overhead
Multiprocessing
Multiprocessing pools
Queues
The problems with multiprocessing Futures
AsyncIO
AsyncIO in action
Reading an AsyncIO Future
AsyncIO for networking
Using executors to wrap blocking code
Streams
Executors
AsyncIO clients
Case study
Exercises
Summary
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
This book introduces the terminology of the object-oriented paradigm. It focuses on object-oriented design with step-by-step examples. It guides us from simple inheritance, one of the most useful tools in the object-oriented programmer's toolbox, through exception handling to design patterns, an object-oriented way of looking at object-oriented concepts.
Along the way, we'll learn how to integrate the object-oriented and the not-so-object-oriented aspects of the Python programming language. We will learn the complexities of string and file manipulation, emphasizing the difference between binary and textual data.
We'll then cover the joys of unit testing, using not one, but two unit testing frameworks. Finally, we'll explore, through Python's various concurrency paradigms, how to make objects work well together at the same time.
Each chapter includes relevant examples and a case study that collects the chapter's contents into a working (if not complete) program.
Who this book is for
This book specifically targets people who are new to object-oriented programming. It assumes you have basic Python skills. You'll learn object-oriented principles in depth. It is particularly useful for system administrators who have used Python as a gluelanguage and would like to improve their programming skills.
Alternatively, if you are familiar with object-oriented programming in other languages, then this book will help you understand the idiomatic ways to apply your knowledge in the Python ecosystem.
What this book covers
This book is loosely divided into four major parts. In the first four chapters, we will dive into the formal principles of object-oriented programming and how Python leverages them. In Chapter 5, Whento UseObject-OrientedProgramming, through Chapter 8, Stringsand Serialization, we will cover some of Python's idiosyncratic applications of these principles by learning how they are applied to a variety of Python's built-in functions. Chapter 9, TheIteratorPattern, through Chapter 11, PythonDesignPatternsII, cover design patterns, and the final two chapters discuss two bonus topics related to Python programming that may be of interest.
Chapter 1, Object-OrientedDesign, covers important object-oriented concepts. It deals mainly with terminology such as abstraction, classes, encapsulation, and inheritance. We also briefly look at UML to model our classes and objects.
Chapter 2, ObjectsinPython, discusses classes and objects as they are used in Python. We will learn about attributes and behaviors of Python objects, and the organization of classes into packages and modules. Lastly, we will see how to protect our data.
Chapter 3, WhenObjectsAreAlike, gives us a more in-depth look into inheritance. It covers multiple inheritance and shows us how to extend built-in. This chapter also covers how polymorphism and duck typing work in Python.
Chapter 4, ExpectingtheUnexpected, looks into exceptions and exception handling. We will learn how to create our own exceptions and how to use exceptions for program flow control.
Chapter 5, WhentoUseObject-OrientedProgramming, deals with creating and using objects. We will see how to wrap data using
properties and restrict data access. This chapter also discusses the DRY principle and how not to repeat code.
Chapter 6, PythonDataStructures, covers the object-oriented features of Python's built-in classes. We'll cover tuples, dictionaries, lists, and sets, as well as a few more advanced collections. We'll also see how to extend these standard objects.
Chapter 7, PythonObject-OrientedShortcuts, as the name suggests, deals with time-savers in Python. We will look at many useful built-in functions, such as method overloading using default arguments. We'll also see that functions themselves are objects and how this is useful.
Chapter 8, StringsandSerialization, looks at strings, files, and formatting. We'll discuss the difference between strings, bytes, and byte arrays, as well as various ways to serialize textual, object, and binary data to several canonical representations.
Chapter 9, TheIteratorPattern, introduces the concept of design patterns and covers Python's iconic implementation of the iterator pattern. We'll learn about list, set, and dictionary comprehensions. We'll also demystify generators and coroutines.
Chapter 10, PythonDesignPatternsI, covers several design patterns, including the decorator, observer, strategy, state, singleton, and template patterns. Each pattern is discussed with suitable examples and programs implemented in Python.
Chapter 11, PythonDesignPatternsII, wraps up our discussion of design patterns with coverage of the adapter, facade, flyweight, command, abstract, and composite patterns. More examples of how idiomatic Python code differs from canonical implementations are provided.
Chapter 12, TestingObject-OrientedPrograms, opens with why testing is so important in Python applications. It focuses on test-driven
development and introduces two different testing suites: unittest and py.test. Finally, it discusses mocking test objects and code coverage.
Chapter 13, Concurrency, is a whirlwind tour of Python's support (and lack thereof) of concurrency patterns. It discusses threads, multiprocessing, futures, and the modern AsyncIO library.
To get the most out of this book
All the examples in this book rely on the Python 3 interpreter. Make sure you are not using Python 2.7 or earlier. At the time of writing, Python 3.7 was the latest release of Python. Many examples will work on earlier revisions of Python 3, but you'll likely experience a lot of frustration if you're using anything older than 3.5.
All of the examples should run on any operating system supported by Python. If this is not the case, please report it as a bug.
Some of the examples need a working internet connection. You'll probably want to have one of these for extracurricular research and debugging anyway!
In addition, some of the examples in this book rely on third-party libraries that do not ship with Python. They are introduced within the book at the time they are used, so you do not need to install them in advance.
Download the example code files
You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.
You can download the code files by following these steps:
1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.
Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:
WinRAR/7-Zip for Windows
Zipeg/iZip/UnRarX for Mac 7-Zip/PeaZip for Linux
The code bundle for the book is also hosted on GitHub at https://githu b.com/PacktPublishing/Python-3-Object-Oriented-Programming-Third-Edition. In case there's an update to the code, it will be updated on the existing GitHub repository.
We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system."
A block of code is set as follows:
class Point: def init (self, x=0, y=0): self.move(x, y)
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
import database
db = database Database()
# Do queries on db
Any command-line input or output is written as follows:
>>> print(secret string SecretString plain string)
ACME: Top Secret
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Most object-oriented programming languages have the concept of a constructor."
Warningsorimportantnotesappearlikethis.
Tipsandtricksappearlikethis.
Get in touch
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