Python Object-Oriented Programming - Fourth Edition

Spis treści książki

• Preface
  • Who this book is for
  • What this book covers
  • To get the most out of this book
  • Get in touch
• Object-Oriented Design
  • Introducing object-oriented
  • Objects and classes
  • Specifying attributes and behaviors
    • Data describes object state
    • Behaviors are actions
  • Hiding details and creating the public interface
  • Composition
  • Inheritance
    • Inheritance provides abstraction
    • Multiple inheritance
  • Case study
    • Introduction and problem overview
    • Context view
    • Logical view
    • Process view
    • Development view
    • Physical view
    • Conclusion
  • Recall
  • Exercises
  • Summary
• Objects in Python
  • Introducing type hints
    • Type checking
  • Creating Python classes
    • Adding attributes
    • Making it do something
      • Talking to yourself
      • More arguments
    • Initializing the object
    • Type hints and defaults
    • Explaining yourself with docstrings
  • Modules and packages
    • Organizing modules
      • Absolute imports
      • Relative imports
      • Packages as a whole
    • Organizing our code in modules
  • Who can access my data?
  • Third-party libraries
  • Case study
    • Logical view
    • Samples and their states
    • Sample state transitions
    • Class responsibilities
    • The TrainingData class
  • Recall
  • Exercises
  • Summary
• When Objects Are Alike
  • Basic inheritance
    • Extending built-ins
    • Overriding and super
  • Multiple inheritance
    • The diamond problem
    • Different sets of arguments
  • Polymorphism
  • Case study
    • Logical view
    • Another distance
  • Recall
  • Exercises
  • Summary
• Expecting the Unexpected
  • Raising exceptions
    • Raising an exception
    • The effects of an exception
    • Handling exceptions
    • The exception hierarchy
    • Defining our own exceptions
    • Exceptions arent exceptional
  • Case study
    • Context view
    • Processing view
    • What can go wrong?
    • Bad behavior
    • Creating samples from CSV files
    • Validating enumerated values
    • Reading CSV files
    • Don't repeat yourself
  • Recall
  • Exercises
  • Summary
• 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
    • Input validation
    • Input partitioning
    • The sample class hierarchy
    • The purpose enumeration
    • Property setters
    • Repeated if statements
  • Recall
  • Exercises
  • Summary
• Abstract Base Classes and Operator Overloading
  • Creating an abstract base class
    • The ABCs of collections
    • Abstract base classes and type hints
    • The collections.abc module
    • Creating your own abstract base class
    • Demystifying the magic
  • Operator overloading
  • Extending built-ins
  • Metaclasses
  • Case study
    • Extending the list class with two sublists
    • A shuffling strategy for partitioning
    • An incremental strategy for partitioning
  • Recall
  • Exercises
  • Summary
• Python Data Structures
  • Empty objects
  • Tuples and named tuples
    • Named tuples via typing.NamedTuple
  • Dataclasses
  • Dictionaries
    • Dictionary use cases
    • Using defaultdict
      • Counter
  • Lists
    • Sorting lists
  • Sets
  • Three types of queues
  • Case study
    • Logical model
    • Frozen dataclasses
    • NamedTuple classes
    • Conclusion
  • Recall
  • Exercises
  • Summary
• The Intersection of Object-Oriented and Functional Programming
  • Python built-in functions
    • The len() function
    • The reversed() function
    • The enumerate() function
  • An alternative to method overloading
    • Default values for parameters
      • Additional details on defaults
    • Variable argument lists
    • Unpacking arguments
  • Functions are objects, too
    • Function objects and callbacks
    • Using functions to patch a class
    • Callable objects
  • File I/O
    • Placing it in context
  • Case study
    • Processing overview
    • Splitting the data
    • Rethinking classification
    • The partition() function
    • One-pass partitioning
  • Recall
  • Exercises
  • Summary
• Strings, Serialization, and File Paths
  • 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
      • Decoding bytes to text
      • Encoding text to bytes
      • Mutable byte strings
  • Regular expressions
    • Matching patterns
      • Matching a selection of characters
      • Escaping characters
      • Repeating patterns of characters
      • Grouping patterns together
    • Parsing information with regular expressions
      • Other features of the re module
      • Making regular expressions efficient
  • Filesystem paths
  • Serializing objects
    • Customizing pickles
    • Serializing objects using JSON
  • Case study
    • CSV format designs
    • CSV dictionary reader
    • CSV list reader
    • JSON serialization
    • Newline-delimited JSON
    • JSON validation
  • Recall
  • Exercises
  • Summary
• The Iterator Pattern
  • Design patterns in brief
  • Iterators
    • The iterator protocol
  • Comprehensions
    • List comprehensions
    • Set and dictionary comprehensions
    • Generator expressions
  • Generator functions
    • Yield items from another iterable
    • Generator stacks
  • Case study
    • The Set Builder background
    • Multiple partitions
    • Testing
    • The essential k-NN algorithm
    • k-NN using the bisect module
    • k-NN using the heapq module
    • Conclusion
  • Recall
  • Exercises
  • Summary
• Common Design Patterns
  • 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 Command pattern
    • A Command example
  • The State pattern
    • A State example
    • State versus Strategy
  • The Singleton pattern
    • Singleton implementation
  • Case study
  • Recall
  • Exercises
  • Summary
• Advanced Design Patterns
  • The Adapter pattern
    • An Adapter example
  • The Façade pattern
    • A Façade example
  • The Flyweight pattern
    • A Flyweight example in Python
    • Multiple messages in a buffer
    • Memory optimization via Python's __slots__
  • The Abstract Factory pattern
    • An Abstract Factory example
    • Abstract Factories in Python
  • The Composite pattern
    • A Composite example
  • The Template pattern
    • A Template example
  • Case study
  • Recall
  • Exercises
  • Summary
• Testing Object-Oriented Programs
  • Why test?
    • Test-driven development
    • Testing objectives
    • Testing patterns
  • Unit testing with unittest
  • Unit testing with pytest
    • pytest's setup and teardown functions
    • pytest fixtures for setup and teardown
    • More sophisticated fixtures
    • Skipping tests with pytest
  • Imitating objects using Mocks
    • Additional patching techniques
    • The sentinel object
  • How much testing is enough?
  • Testing and development
  • Case study
    • Unit testing the distance classes
    • Unit testing the Hyperparameter class
  • Recall
  • Exercises
  • Summary
• Concurrency
  • Background on concurrent processing
  • 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
      • Design considerations
    • A log writing demonstration
    • AsyncIO clients
  • The dining philosophers benchmark
  • Case study
  • Recall
  • Exercises
  • Summary
• Other Books You May Enjoy
• Index

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