Module 2: Python 3 Object-Oriented Programming

• chapter 1: Object-oriented Design
  • 1.1 Introducing object-oriented
    • 1.1.1 Linux
  • 1.2 Objects and classes
  • 1.3 Specifying attributes and behaviors
  • 1.4 Hiding details and creating the public interface
  • 1.5 Composition
  • 1.6 Inheritance
  • 1.7 Case study
  • 1.8 Exercises
  • 1.9 Summary
• chapter 2: Objects in Python
  • 2.1 Creating Python classes
    • 2.1.1 Linux
  • 2.2 Modules and packages
  • 2.3 Organizing module contents
  • 2.4 Who can access my data?
  • 2.5 Third-party libraries
  • 2.6 Case study
  • 2.7 Exercises
  • 2.8 Summary
• chapter 3: When Objects Are Alike
  • 3.1 Basic inheritance
    • 3.1.1 Linux
  • 3.2 Multiple inheritance
  • 3.3 Polymorphism
  • 3.4 Abstract base classes
  • 3.5 Case study
  • 3.6 Exercises
  • 3.7 Summary
• chapter 4: Expecting the Unexpected
  • 4.1 Raising exceptions
    • 4.1.1 Linux
  • 4.2 Case study
  • 4.3 Exercises
  • 4.4 Summary
• chapter 5: When to Use Object-oriented Programming
  • 5.1 Treat objects as objects
    • 5.1.1 Linux
  • 5.2 Adding behavior to class data with properties
  • 5.3 Manager objects
  • 5.4 Case study
  • 5.5 Exercises
  • 5.6 Summary
• chapter 6: Python Data Structures
  • 6.1 Empty objects
    • 6.1.1 Linux
  • 6.2 Tuples and named tuples
  • 6.3 Dictionaries
  • 6.4 Lists
  • 6.5 Sets
  • 6.6 Extending built-ins
  • 6.7 Queues
  • 6.8 Case study
  • 6.9 Exercises
  • 6.10 Summary
• chapter 7: Python Object-oriented Shortcuts
  • 7.1 Python built-in functions
    • 7.1.1 Linux
  • 7.2 An alternative to method overloading
  • 7.3 Functions are objects too
  • 7.4 Case study
  • 7.5 Exercises
  • 7.6 Summary
• chapter 8: Strings and Serialization
  • 8.1 Strings
    • 8.1.1 Linux
  • 8.2 Regular expressions
  • 8.3 Serializing objects
  • 8.4 Case study
  • 8.5 Exercises
  • 8.6 Summary
• chapter 9: The Iterator Pattern
  • 9.1 Design patterns in brief
    • 9.1.1 Linux
  • 9.2 Iterators
  • 9.3 Comprehensions
  • 9.4 Generators
  • 9.5 Coroutine
  • 9.6 Case study
  • 9.7 Exercises
  • 9.8 Summary
• chapter 10: Python Design Patterns I
  • 10.1 The decorator pattern
    • 10.1.1 Linux
  • 10.2 The observer pattern
  • 10.3 The strategy pattern
  • 10.4 The state pattern
  • 10.5 The singleton pattern
  • 10.6 The template pattern
  • 10.7 Exercises
  • 10.8 Summary
• chapter 11: Python Design Patterns II
  • 11.1 The adapter pattern
    • 11.1.1 Linux
  • 11.2 The facade pattern
  • 11.3 The flyweight pattern
  • 11.4 The command pattern
  • 11.5 The abstract factory pattern
  • 11.6 The composite pattern
  • 11.7 Exercises
  • 11.8 Summary
• chapter 12: Testing Object-oriented Programs
  • 12.1 Why test?
    • 12.1.1 Linux
  • 12.2 Unit testing
  • 12.3 Testing with py.test
  • 12.4 Imitating expensive objects
  • 12.5 How much testing is enough?
  • 12.6 Case study
  • 12.7 Exercises
  • 12.8 Summary
• chapter 13: Concurrency
  • 13.1 Threads
    • 13.1.1 Linux
  • 13.2 Multiprocessing
  • 13.3 Futures
  • 13.4 AsyncIO
  • 13.5 Case study
  • 13.6 Exercises
  • 13.7 Summary