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Python 3 Object-oriented Programming Second Edition
Table of Contents
Python 3 Object-oriented Programming Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
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Free access for Packt account holders
Introduction to the second edition
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
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 the modules
Absolute imports
Relative imports
Organizing module contents
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 behavior 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
Dictionaries
Dictionary use cases
Using defaultdict
Counter
Lists
Sorting lists
Sets
Extending built-ins
Queues
FIFO queues
LIFO queues
Priority queues
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
Keyword arguments
Container lookups
Object lookups
Making it look right
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
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
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 py.test
One way to do setup and cleanup
A completely different way to set up variables
Skipping tests with py.test
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
Case study
Exercises
Summary
Index
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