Python 3 Object-Oriented Programming. - Third Edition

Table of contents

1. Title Page
2. Copyright and Credits
   1. Python 3 Object-Oriented Programming Third Edition
3. Packt Upsell
   1. Why subscribe?
   2. Packt.com
4. Contributors
   1. About the author
   2. About the reviewers
   3. Packt is searching for authors like you
5. Preface
   1. Who this book is for
   2. What this book covers
   3. To get the most out of this book
      1. Download the example code files
      2. Conventions used
   4. Get in touch
      1. Reviews
6. Object-Oriented Design
   1. Introducing object-oriented
   2. Objects and classes
   3. Specifying attributes and behaviors
      1. Data describes objects
      2. Behaviors are actions
   4. Hiding details and creating the public interface
   5. Composition
   6. Inheritance
      1. Inheritance provides abstraction
      2. Multiple inheritance
   7. Case study
   8. Exercises
   9. Summary
7. Objects in Python
   1. Creating Python classes
      1. Adding attributes
      2. Making it do something
         1. Talking to yourself
         2. More arguments
      3. Initializing the object
      4. Explaining yourself
   2. Modules and packages
      1. Organizing modules
         1. Absolute imports
         2. Relative imports
   3. Organizing module content
   4. Who can access my data?
   5. Third-party libraries
   6. Case study
   7. Exercises
   8. Summary
8. When Objects Are Alike
   1. Basic inheritance
      1. Extending built-ins
      2. Overriding and super
   2. Multiple inheritance
      1. The diamond problem
      2. Different sets of arguments
   3. Polymorphism
   4. Abstract base classes
      1. Using an abstract base class
      2. Creating an abstract base class
      3. Demystifying the magic
   5. Case study
   6. Exercises
   7. Summary
9. Expecting the Unexpected
   1. Raising exceptions
      1. Raising an exception
      2. The effects of an exception
      3. Handling exceptions
      4. The exception hierarchy
      5. Defining our own exceptions
   2. Case study
   3. Exercises
   4. Summary
10. When to Use Object-Oriented Programming
    1. Treat objects as objects
    2. Adding behaviors to class data with properties
       1. Properties in detail
       2. Decorators – another way to create properties
       3. Deciding when to use properties
    3. Manager objects
       1. Removing duplicate code
       2. In practice
    4. Case study
    5. Exercises
    6. Summary
11. Python Data Structures
    1. Empty objects
    2. Tuples and named tuples
       1. Named tuples
    3. Dataclasses
    4. Dictionaries
       1. Dictionary use cases
       2. Using defaultdict
          1. Counter
    5. Lists
       1. Sorting lists
    6. Sets
    7. Extending built-in functions
    8. Case study
    9. Exercises
    10. Summary
12. Python Object-Oriented Shortcuts
    1. Python built-in functions
       1. The len() function
       2. Reversed
       3. Enumerate
       4. File I/O
       5. Placing it in context
    2. An alternative to method overloading
       1. Default arguments
       2. Variable argument lists
       3. Unpacking arguments
    3. Functions are objects too
       1. Using functions as attributes
       2. Callable objects
    4. Case study
    5. Exercises
    6. Summary
13. Strings and Serialization
    1. Strings
       1. String manipulation
       2. String formatting
          1. Escaping braces
          2. f-strings can contain Python code
          3. Making it look right
          4. Custom formatters
          5. The format method
       3. Strings are Unicode
          1. Converting bytes to text
          2. Converting text to bytes
       4. Mutable byte strings
    2. Regular expressions
       1. Matching patterns
          1. Matching a selection of characters
          2. Escaping characters
          3. Matching multiple characters
          4. Grouping patterns together
       2. Getting information from regular expressions
          1. Making repeated regular expressions efficient
    3. Filesystem paths
    4. Serializing objects
       1. Customizing pickles
       2. Serializing web objects
    5. Case study
    6. Exercises
    7. Summary
14. The Iterator Pattern
    1. Design patterns in brief
    2. Iterators
       1. The iterator protocol
    3. Comprehensions
       1. List comprehensions
       2. Set and dictionary comprehensions
       3. Generator expressions
    4. Generators
       1. Yield items from another iterable
    5. Coroutines
       1. Back to log parsing
       2. Closing coroutines and throwing exceptions
       3. The relationship between coroutines, generators, and functions
    6. Case study
    7. Exercises
    8. Summary
15. Python Design Patterns I
    1. The decorator pattern
       1. A decorator example
       2. Decorators in Python
    2. The observer pattern
       1. An observer example
    3. The strategy pattern
       1. A strategy example
       2. Strategy in Python
    4. The state pattern
       1. A state example
       2. State versus strategy
       3. State transition as coroutines
    5. The singleton pattern
       1. Singleton implementation
       2. Module variables can mimic singletons
    6. The template pattern
       1. A template example
    7. Exercises
    8. Summary
16. Python Design Patterns II
    1. The adapter pattern
    2. The facade pattern
    3. The flyweight pattern
    4. The command pattern
    5. The abstract factory pattern
    6. The composite pattern
    7. Exercises
    8. Summary
17. Testing Object-Oriented Programs
    1. Why test?
       1. Test-driven development
    2. Unit testing
       1. Assertion methods
       2. Reducing boilerplate and cleaning up
       3. Organizing and running tests
       4. Ignoring broken tests
    3. Testing with pytest
       1. One way to do setup and cleanup
       2. A completely different way to set up variables
       3. Skipping tests with pytest
    4. Imitating expensive objects
    5. How much testing is enough?
    6. Case study
       1. Implementing it
    7. Exercises
    8. Summary
18. Concurrency
    1. Threads
       1. The many problems with threads
          1. Shared memory
          2. The global interpreter lock
       2. Thread overhead
    2. Multiprocessing
       1. Multiprocessing pools
       2. Queues
       3. The problems with multiprocessing
    3. Futures
    4. AsyncIO
       1. AsyncIO in action
       2. Reading an AsyncIO Future
       3. AsyncIO for networking
       4. Using executors to wrap blocking code
          1. Streams
          2. Executors
       5. AsyncIO clients
    5. Case study
    6. Exercises
    7. Summary
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