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Building Robust Object-Oriented Python Applications and Libraries

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Object-Oriented Design

Getting Started Introducing Object-Oriented Paradigm Objects and Classes Attributes and Behaviors Hiding Details and Creating the Public Interface Composition and Aggregation Inheritance Case Study Context View Logical View Process View Development View Physical View Challenge: Design an Order Processing System Solution: Design an Order Processing System Quiz: Object-Oriented Design Summary

Objects in Python

Type Hints Type Checking Creating Python Classes Initializing the Object Type Hints and Defaults Modules and Packages Organizing Modules Organizing Code in Modules Who Can Access My Data?Case Study Samples and Their States Sample State Transitions Class Responsibilities The TrainingData Class Challenge: Build a To-Do Application Solution: Build a To-Do Application Quiz: Objects in Python Summary

When Objects Are Alike

Basics of Inheritance Extending Built-in Functions Overriding and Super Functions Multiple Inheritance The Diamond Problem Different Sets of Arguments Polymorphism Case Study Logical View Challenge: Build a Testing System Solution: Build a Testing System Quiz: When Objects Are Alike Summary

Expecting the Unexpected

Exceptions Raising an Exception The Effects of an Exception Handling Exceptions The Exception Hierarchy Defining Our Own Exceptions Exceptions Aren’t Exceptional Case Study Context and Processing View Bad Data and Bad Behavior Creating Samples From CSV Files Validating Enumerated Values Reading CSV Files Quiz: Expecting the Unexpected 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 Case Study The Sample Class Hierarchy The Purpose Enumeration Challenge: Build a Banking System Solution: Build a Banking System Quiz: When to Use Object-Oriented Programming Summary

Abstract Base Classes and Operator Overloading

Introduction Abstract Base Class and Concrete Class The ABCs of Collections Abstract Base Classes and Type Hints The collections.abc Module Creating Our Own Abstract Base Class Demystifying the Magic Operator Overloading Extending Built-ins Metaclasses Case Study A Shuffling Strategy for Partitioning An Incremental Strategy for Partitioning Challenge: Construct a Library Management System Solution: Construct a Library Management System Quiz: Abstract Base Classes and Operator Overloading Summary

Python Data Structures

Tuples and Named Tuples

Named Tuples via typing.NamedTuple

Dictionary: Use Cases

Using defaultdict

Types of Queues

Frozen Dataclasses

NamedTuple Classes

Challenge: Create a Customer Relationship Management System

Solution: Create a Customer Relationship Management System

Quiz: Python Data Structures

Object-Oriented and Functional Programming Intersection

Introduction Python Built-in Functions An Alternative to Method Overloading Default Values for Parameters Variable Argument Lists Unpacking Arguments Functions Are Objects, Too Function Objects and Callbacks Using Functions to Patch a Class Callable Objects File I/O Context Management Case Study Data Classification Partition Function Challenge: Build a Sales Report Generator Solution: Build a Sales Report Generator Quiz: Object-Oriented and Functional Programming Intersection Summary

Strings, Serialization, and File Paths

Introduction to Strings String Manipulation String Formatting f-strings Containing Python Code Custom Formatters Strings Are Unicode Regular Expressions Matching a Selection of Characters Repeating and Grouping Characters Patterns Parsing Information With Regular Expressions Filesystem Paths Serializing Objects Customizing Pickles Serializing Objects Using JSON Case Study CSV Dictionary Reader CSV List Reader JSON Serialization JSON Validation Challenge: Create a Data Management System Solution: Create a Data Management System Quiz: Strings, Serialization, and File Paths Summary

The Iterator Pattern

Introduction Iterators Comprehensions Set and Dictionary Comprehensions Generator Expressions Generator Functions Yield Items From Another Iterable Generator Stacks Case Study Multiple Partitions Testing The Essential k-NN Algorithm Challenge: Students Performance Tracking System Solution: Students Performance Tracking System Quiz: The Iterator Pattern Summary

Common Design Patterns

Introduction The Decorator Pattern Decorators in Python The Observer Pattern The Strategy Pattern The Command Pattern The State Pattern The Singleton Pattern Case Study Challenge: Create a Company's Logging System Solution: Create a Company's Logging System Quiz: Common Design Patterns Summary

Advanced Design Patterns

Introduction The Adapter Pattern The Facade Pattern The Flyweight Pattern A Flyweight Example In Python The Abstract Factory Pattern Abstract Factories In Python The Composite Pattern The Template Pattern Case Study Challenge: Develop a Data Aggregation System Solution: Develop a Data Aggregation System Quiz: Advanced Design Patterns Summary

Testing Object-Oriented Programs

Introduction Coding With Tests Unit Testing With unittest Unit Testing With pytest Skipping Tests With pytest Imitating Objects Using Mocks Test-Driven Development Insights Case Study Unit Testing the Hyperparameter Class Quiz: Testing Object-Oriented Programs Summary

Concurrency

Introduction Threads Problems with threads Multiprocessing Multiprocessing Pools Queues Problems with Multiprocessing Futures AsyncIO AsyncIO for Networking A Log Writing Demonstration AsyncIO Clients The Dining Philosophers Benchmark Case Study Challenge: Build a Sensor Monitoring System Solution: Build a Sensor Monitoring System Quiz: Concurrency Summary

Conclusion

Quiz: Python Data Structures

Test yourself on the knowledge you learned about Python data structures.

Python Data Structures

1

What is the recommended approach for using classes and objects in Python?

A)

Use classes and objects only when memory is not a concern.

B)

Store unknown attribute values in empty objects.

C)

Use object-oriented features for purely data-driven scenarios.

D)

Specify both data and behaviors in classes and objects.

Question 1 of 60 attempted

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