Learning Python: Powerful Object-Oriented Programming

Description

Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz's popular training course, this updated sixth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow self-paced tutorial gets you started with Python 3.12 and all other releases in use today. With a pragmatic focus on what you need to know, it also introduces some advanced language features that have become increasingly common in Python code. This book helps you: Explore Python's built-in object types such as strings, lists, dictionaries, and files Create and process objects with Python statements, and learn Python's syntax model Use functions and functional programming to avoid redundancy and maximize reuse Organize code into larger components with modules and packages Code robust programs with Python's exception handling and development tools Apply object-oriented programming and classes to make code customizable Survey advanced Python tools including decorators, descriptors, and metaclasses Write idiomatic Python code that runs portably across a wide variety of platforms Preface Python This Book This Edition Media Choices Updates and Examples Conventions and Reuse Acknowledgments I. Getting Started 1. A Python Q&A Session Why Do People Use Python? Software Quality Developer Productivity Is Python a “Scripting Language”? OK, but What’s the Downside? Who Uses Python Today? What Can I Do with Python? Systems Programming GUIs and UIs Internet and Web Scripting Component Integration Database Access Rapid Prototyping Numeric and Scientific Programming And More: AI, Games, Images, QA, Excel, Apps… What Are Python’s Technical Strengths? It’s Object-Oriented and Functional It’s Free and Open It’s Portable It’s Powerful It’s Mixable It’s Relatively Easy to Use It’s Relatively Easy to Learn Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 2. How Python Runs Programs Introducing the Python Interpreter Program Execution The Programmer’s View Python’s View Execution-Model Variations Python Implementation Alternatives Standalone Executables Future Possibilities Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 3. How You Run Programs Installing Python Interactive Code Starting an Interactive REPL Where to Run: Code Folders What Not to Type: Prompts and Comments Other Python REPLs Running Code Interactively Why the Interactive Prompt? Program Files A First Script Running Files with Command Lines Command-Line Usage Variations Other Ways to Run Files Clicking and Tapping File Icons The IDLE Graphical User Interface Other IDEs for Python Smartphone Apps WebAssembly for Browsers Jupyter Notebooks for Science Ahead-of-Time Compilers for Speed Running Code in Code Other Launch Options Which Option Should I Use? Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part I Exercises II. Objects and Operations 4. Introducing Python Objects The Python Conceptual Hierarchy Why Use Built-in Objects? Python’s Core Object Types Numbers Strings Sequence Operations Immutability Type-Specific Methods Getting Help Other Ways to Code Strings Unicode Strings Lists Sequence Operations Type-Specific Operations Bounds Checking Nesting Comprehensions Dictionaries Mapping Operations Nesting Revisited Missing Keys: if Tests Item Iteration: for Loops Tuples Why Tuples? Files Unicode and Byte Files Other File-Like Tools Other Object Types Sets Booleans and None Types Type Hinting User-Defined Objects And Everything Else Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 5. Numbers and Expressions Numeric Object Basics Numeric Literals Built-in Numeric Tools Python Expression Operators Mixed Operators: Precedence Parentheses Group Subexpressions Mixed Types Are Converted Up Preview: Operator Overloading and Polymorphism Numbers in Action Variables and Basic Expressions Numeric Display Formats Comparison Operators Division Operators Integer Precision Complex Numbers Hex, Octal, and Binary Bitwise Operations Underscore Separators in Numbers Other Built-in Numeric Tools Other Numeric Objects Decimal Objects Fraction Objects Set Objects Boolean Objects Numeric Extensions Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 6. The Dynamic Typing Interlude The Case of the Missing Declaration Statements Variables, Objects, and References Types Live with Objects, Not Variables Objects Are Garbage-Collected Shared References Shared References and In-Place Changes Shared References and Equality Dynamic Typing Is Everywhere Type Hinting: Optional, Unused, and Why? Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 7. String Fundamentals String Object Basics String Literals Single and Double Quotes Are the Same Escape Sequences Are Special Characters Raw Strings Suppress Escapes Triple Quotes and Multiline Strings Strings in Action Basic Operations Indexing and Slicing String Conversion Tools “Changing” Strings Part 1: Sequence Operations String Methods Method Call Syntax All String Methods (Today) “Changing” Strings, Part 2: String Methods More String Methods: Parsing Text Other Common String Methods String Formatting: The Triathlon String-Formatting Options The String-Formatting Expression The String-Formatting Method The F-String Formatting Literal And the Winner Is… General Type Categories Types Share Operation Sets by Categories Mutable Types Can Be Changed in Place Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 8. Lists and Dictionaries Lists Lists in Action Basic List Operations Indexing and Slicing Changing Lists in Place More List Methods Iteration, Comprehensions, and Unpacking Other List Operations Dictionaries Dictionaries in Action Basic Dictionary Operations Changing Dictionaries in Place More Dictionary Methods Other Dictionary Makers Dictionary Comprehensions Key Insertion Ordering Dictionary “Union” Operator Intermission: Books Database Dictionary Usage Tips Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 9. Tuples, Files, and Everything Else Tuples Tuples in Action Why Lists and Tuples? Records Revisited: Named Tuples Files Opening Files Using Files Files in Action Text and Binary Files: The Short Story Storing Objects with Conversions Storing Objects with pickle Storing Objects with JSON Storing Objects with Other Tools File Context Managers Other File Tools Core Types Review and Summary Object Flexibility References Versus Copies Comparisons, Equality, and Truth The Meaning of True and False in Python Python’s Type Hierarchies Type Objects Other Types in Python Built-in Type Gotchas Assignment Creates References, Not Copies Repetition Adds One Level Deep Beware of Cyclic Data Structures Immutable Types Can’t Be Changed in Place Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part II Exercises III. Statements and Syntax 10. Introducing Python Statements The Python Conceptual Hierarchy Revisited Python’s Statements A Tale of Two ifs What Python Adds What Python Removes Why Indentation Syntax? A Few Special Cases A Quick Example: Interactive Loops A Simple Interactive Loop Doing Math on User Inputs Handling Errors by Testing Inputs Handling Errors with try Statements Supporting Floating-Point Numbers Nesting Code Three Levels Deep Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 11. Assignments, Expressions, and Prints Assignments Assignment Syntax Forms Basic Assignments Sequence Assignments Extended-Unpacking Assignments Multiple-Target Assignments Augmented Assignments Named Assignment Expressions Variable Name Rules Expression Statements Expression Statements and In-Place Changes Print Operations The print Function Print Stream Redirection Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 12. if and match Selections if Statements General Format Basic Examples Multiple-Choice Selections match Statements Basic match Usage Advanced match Usage Python Syntax Revisited Block Delimiters: Indentation Rules Statement Delimiters: Lines and Continuations Special Syntax Cases in Action Truth Values Revisited The if/else Ternary Expression Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 13. while and for Loops while Loops General Format Examples break, continue, pass, and the Loop else General Loop Format pass continue break Loop else for Loops General Format Examples Loop Coding Techniques Counter Loops: range Sequence Scans: while, range, and for Sequence Shufflers: range and len Skipping Items: range and Slices Changing Lists: range and Comprehensions Parallel Traversals: zip Offsets and Items: enumerate Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 14. Iterations and Comprehensions Iterations The Iteration Protocol Other Built-in Iterables Comprehensions List Comprehension Basics List Comprehensions and Files Extended List Comprehension Syntax Comprehensions Cliff-Hanger Iteration Tools Other Iteration Topics Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 15. The Documentation Interlude Python Documentation Sources # Comments The dir Function Docstrings and __doc__ Pydoc: The help Function Pydoc: HTML Reports Beyond Docstrings: Sphinx The Standard Manuals Web Resources Common Coding Gotchas Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part III Exercises IV. Functions and Generators 16. Function Basics Why Use Functions? Function Coding Overview Basic Function Tools Advanced Function Tools General Function Concepts def Statements return Statements def Executes at Runtime lambda Makes Anonymous Functions A First Example: Definitions and Calls Definition Calls Polymorphism in Python A Second Example: Intersecting Sequences Definition Calls Polymorphism Revisited Segue: Local Variables Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 17. Scopes Python Scopes Basics Scopes Overview Name Resolution: The LEGB Rule Scopes Examples The Built-in Scope The global Statement Program Design: Minimize Global Variables Program Design: Minimize Cross-File Changes Other Ways to Access Globals Nested Functions and Scopes Nested Scopes Overview Nested Scopes Examples Closures and Factory Functions Arbitrary Scope Nesting The nonlocal Statement nonlocal Basics nonlocal in Action nonlocal Boundary Cases State-Retention Options Nonlocals: Changeable, Per-Call, LEGB Globals: Changeable but Shared Function Attributes: Changeable, Per-Call, Explicit Classes: Changeable, Per-Call, OOP And the Winner Is… Scopes and Argument Defaults Loops Require Defaults, Not Scopes Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 18. Arguments Argument-Passing Basics Arguments and Shared References Avoiding Mutable Argument Changes Simulating Output Parameters and Multiple Results Special Argument-Matching Modes Argument Matching Overview Argument Matching Syntax Argument Passing Details Keyword and Default Examples Arbitrary Arguments Examples Keyword-Only Arguments Positional-Only Arguments Argument Ordering: The Gritty Details Definition Ordering Calls Ordering Example: The min Wakeup Call Full Credit Bonus Points The Punch Line Example: Generalized Set Functions Testing the Code Example: Rolling Your Own Print Using Keyword-Only Arguments Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 19. Function Odds and Ends Function Design Concepts Recursive Functions Summation with Recursion Coding Alternatives Loop Statements Versus Recursion Handling Arbitrary Structures Function Tools: Attributes, Annotations, Etc. The First-Class Object Model Function Introspection Function Attributes Function Annotations and Decorations Anonymous Functions: lambda lambda Basics Why Use lambda? How (Not) to Obfuscate Your Python Code Scopes: lambdas Can Be Nested Too Functional Programming Tools Mapping Functions over Iterables: map Selecting Items in Iterables: filter Combining Items in Iterables: reduce Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 20. Comprehensions and Generations Comprehensions: The Final Act List Comprehensions Review Formal Comprehension Syntax Example: List Comprehensions and Matrixes Generator Functions and Expressions Generator Functions: yield Versus return Generator Expressions: Iterables Meet Comprehensions Generator Functions Versus Generator Expressions Generator Odds and Ends Example: Shuffling Sequences Scrambling Sequences Permutating Sequences Example: Emulating zip and map Coding Your Own map Coding Your Own zip and 2.X map Asynchronous Functions: The Short Story Async Basics The Async Wrap-Up Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 21. The Benchmarking Interlude Benchmarking with Homegrown Tools Timer Module: Take 1 Timer Module: Take 2 Timing Runner and Script Iteration Results More Module Mods Benchmarking with Python’s timeit Basic timeit Usage Automating timeit Benchmarking Function Gotchas Local Names Are Detected Statically Defaults and Mutable Objects Functions Without returns Miscellaneous Function Gotchas Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part IV Exercises V. Modules and Packages 22. Modules: The Big Picture Module Essentials Why Use Modules? Python Program Architecture How to Structure a Program Imports and Attributes Standard-Library Modules How Imports Work Step 1: Find It Step 2: Compile It (Maybe) Step 3: Run It The Module Search Path Search-Path Components Configuring the Search Path The sys.path List Module File Selection Path Outliers: Standalones and Packages Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 23. Module Coding Basics Creating Modules Module Filenames Other Kinds of Modules Using Modules The import Statement The from Statement The from * Statement Imports Happen Only Once Imports Are Runtime Assignments import and from Equivalence Potential Pitfalls of the from Statement Module Namespaces How Files Generate Namespaces Namespace Dictionaries: __dict__ Attribute Name Qualification Imports Versus Scopes Namespace Nesting Reloading Modules reload Basics reload Example reload Odds and Ends Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 24. Module Packages Using Packages Package Imports Packages and the Module Search Path Creating Packages Basic Package Structure Package __init__.py Files Package __main__.py Files Why Packages? A Tale of Two Systems The Roles of __init__.py Files Package-Relative Imports Relative and Absolute Imports Relative-Import Rationales and Trade-Offs Package-Relative Imports in Action Namespace Packages Python Import Models Namespace-Package Rationales The Module Search Algorithm Namespace Packages in Action Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 25. Module Odds and Ends Module Design Concepts Data Hiding in Modules Minimizing from * Damage: _X and __all__ Managing Attribute Access: __getattr__ and __dir__ Enabling Language Changes: __future__ Dual-Usage Modes: __name__ and __main__ Example: Unit Tests with __name__ The as Extension for import and from Module Introspection Example: Listing Modules with __dict__ Importing Modules by Name String Running Code Strings Direct Calls: Two Options Example: Transitive Module Reloads Module Gotchas Module Name Clashes: Package and Package-Relative Imports Statement Order Matters in Top-Level Code from Copies Names but Doesn’t Link from * Can Obscure the Meaning of Variables reload May Not Impact from Imports reload, from, and Interactive Testing Recursive from Imports May Not Work Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part V Exercises VI. Classes and OOP 26. OOP: The Big Picture Why Use Classes? OOP from 30,000 Feet Attribute Inheritance Search Classes and Instances Method Calls Coding Class Trees Operator Overloading OOP Is About Code Reuse Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 27. Class Coding Basics Classes Generate Multiple Instance Objects Class Objects Provide Default Behavior Instance Objects Are Concrete Items A First Example Classes Are Customized by Inheritance A Second Example Classes Are Attributes in Modules Classes Can Intercept Python Operators A Third Example The World’s Simplest Python Class Classes: Under the Hood Records Revisited: Classes Versus Dictionaries Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 28. A More Realistic Example Step 1: Making Instances Coding Constructors Testing as You Go Using Code Two Ways Step 2: Adding Behavior Methods Coding Methods Step 3: Operator Overloading Providing Print Displays Step 4: Customizing Behavior by Subclassing Coding Subclasses Augmenting Methods: The Bad Way Augmenting Methods: The Good Way Polymorphism in Action Inherit, Customize, and Extend OOP: The Big Idea Step 5: Customizing Constructors, Too OOP Is Simpler Than You May Think Other Ways to Combine Classes: Composites Step 6: Using Introspection Tools Special Class Attributes A Generic Display Tool Instance Versus Class Attributes Name Considerations in Tool Classes Our Classes’ Final Form Step 7 (Final): Storing Objects in a Database Pickles and Shelves Storing Objects on a shelve Database Exploring Shelves Interactively Updating Objects on a Shelf Future Directions Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 29. Class Coding Details The class Statement General Syntax and Usage Example: Class Attributes Methods Method Example Other Method-Call Possibilities Inheritance Attribute Tree Construction Inheritance Fine Print Specializing Inherited Methods Class Interface Techniques Abstract Superclasses Namespaces: The Conclusion Simple Names: Global Unless Assigned Attribute Names: Object Namespaces The “Zen” of Namespaces: Assignments Classify Names Nested Classes: The LEGB Scopes Rule Revisited Namespace Dictionaries: Review Namespace Links: A Tree Climber Documentation Strings Revisited Classes Versus Modules Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 30. Operator Overloading The Basics Constructors and Expressions: __init__ and __sub__ Common Operator-Overloading Methods Indexing and Slicing: __getitem__ and __setitem__ Intercepting Slices Intercepting Item Assignments But __index__ Means As-Integer Index Iteration: __getitem__ Iterable Objects: __iter__ and __next__ User-Defined Iterables Multiple Iterators on One Object Coding Alternative: __iter__ Plus yield Membership: __contains__, __iter__, and __getitem__ Attribute Access: __getattr__ and __setattr__ Attribute Reference Attribute Assignment and Deletion Other Attribute-Management Tools Emulating Privacy for Instance Attributes: Part 1 String Representation: __repr__ and __str__ Why Two Display Methods? Display Usage Notes Right-Side and In-Place Ops: __radd__ and __iadd__ Right-Side Addition In-Place Addition Call Expressions: __call__ Function Interfaces and Callback-Based Code Comparisons: __lt__, __gt__, and Others Boolean Tests: __bool__ and __len__ Object Destruction: __del__ Destructor Usage Notes Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 31. Designing with Classes Python and OOP Polymorphism Means Interfaces, Not Call Signatures OOP and Inheritance: “Is-a” Relationships OOP and Composition: “Has-a” Relationships Stream Processors Revisited OOP and Delegation: “Like-a” Relationships Pseudoprivate Class Attributes Name Mangling Overview Why Use Pseudoprivate Attributes? Method Objects: Bound or Not Bound Methods in Action Classes Are Objects: Generic Object Factories Why Factories? Multiple Inheritance and the MRO How Multiple Inheritance Works How the MRO Works Attribute Conflict Resolution Example: “Mix-in” Attribute Listers Example: Mapping Attributes to Inheritance Sources Other Design-Related Topics Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 32. Class Odds and Ends Extending Built-in Object Types Extending Types by Embedding Extending Types by Subclassing The Python Object Model Classes Are Types Are Classes Some Instances Are More Equal Than Others The Inheritance Bifurcation The Metaclass/Class Dichotomy And One “object” to Rule Them All Advanced Attribute Tools Slots: Attribute Declarations Properties: Attribute Accessors __getattribute__ and Descriptors: Attribute Implementations Static and Class Methods Why the Special Methods? Plain-Function Methods Static Method Alternatives Using Static and Class Methods Counting Instances with Static Methods Counting Instances with Class Methods Decorators and Metaclasses Function Decorator Basics A First Look at User-Defined Function Decorators A First Look at Class Decorators and Metaclasses For More Details The super Function The super Basics The super Details The super Wrap-Up Class Gotchas Changing Class Attributes Can Have Side Effects Changing Mutable Class Attributes Can Have Side Effects, Too Multiple Inheritance: Order Matters Scopes in Methods and Classes Miscellaneous Class Gotchas “Overwrapping-itis” Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part VI Exercises VII. Exceptions 33. Exception Basics Why Use Exceptions? Exception Roles Exceptions: The Short Story Default Exception Handler Catching Exceptions Raising Exceptions User-Defined Exceptions Termination Actions Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 34. Exception Coding Details The try Statement try Statement Clauses The except and else Clauses The finally Clause Combined try Clauses The raise Statement Raising Exceptions The except as hook Scopes and except as Propagating Exceptions with raise Exception Chaining: raise from The assert Statement Example: Trapping Constraints (but Not Errors!) The with Statement and Context Managers Basic with Usage The Context-Management Protocol Multiple Context Managers The Termination-Handlers Shoot-Out Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 35. Exception Objects Exception Classes Coding Exceptions Classes Why Exception Hierarchies? Built-in Exception Classes Built-in Exception Categories Default Printing and State Custom Print Displays Custom State and Behavior Providing Exception Details Providing Exception Methods Exception Groups: Yet Another Star! Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 36. Exception Odds and Ends Nesting Exception Handlers Example: Control-Flow Nesting Example: Syntactic Nesting Exception Idioms Breaking Out of Multiple Nested Loops: “go to” Exceptions Aren’t Always Errors Functions Can Signal Conditions with raise Closing Files and Server Connections Debugging with Outer try Statements Running In-Process Tests More on sys.exc_info Displaying Errors and Tracebacks Exception Design Tips and Gotchas What Should Be Wrapped Catching Too Much: Avoid Empty except and Exception Catching Too Little: Use Class-Based Categories Core Language Wrap-Up The Python Toolset Development Tools for Larger Projects Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers Test Your Knowledge: Part VII Exercises VIII. Advanced Topics 37. Unicode and Byte Strings Unicode Foundations Character Representations Character Encodings Introducing Python String Tools The str Object The bytes Object The bytearray Object Text and Binary Files Using Text Strings Literals and Basic Properties String Type Conversions Coding Unicode Strings in Python Source-File Encoding Declarations Using Byte Strings Methods Sequence Operations Formatting Other Ways to Make Bytes Mixing String Types The bytearray Object Using Text and Binary Files Text-File Basics Text and Binary Modes Unicode-Text Files Unicode, Bytes, and Other String Tools The re Pattern-Matching Module The struct Binary-Data Module The pickle and json Serialization Modules Filenames in open and Other Filename Tools The Unicode Twilight Zone Dropping the BOM in Python Unicode Normalization: Whither Standard? Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 38. Managed Attributes Why Manage Attributes? Inserting Code to Run on Attribute Access Properties The Basics A First Example Computed Attributes Coding Properties with Decorators Descriptors The Basics A First Example Computed Attributes Using State Information in Descriptors How Properties and Descriptors Relate __getattr__ and __getattribute__ The Basics A First Example Computed Attributes __getattr__ and __getattribute__ Compared Management Techniques Compared Intercepting Built-in Operation Attributes Example: Attribute Validations Using Properties to Validate Using Descriptors to Validate Using __getattr__ to Validate Using __getattribute__ to Validate Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 39. Decorators What’s a Decorator? Managing Calls and Instances Managing Functions and Classes Using and Defining Decorators Why Decorators? The Basics Function Decorator Basics Class Decorator Basics Decorator Nesting Decorator Arguments Decorators Manage Functions and Classes, Too Coding Function Decorators Tracing Function Calls Decorator State Retention Options Class Pitfall: Decorating Methods Timing Function Calls Adding Decorator Arguments Coding Class Decorators Singleton Classes Tracing Object Interfaces Class Pitfall: Retaining Multiple Instances Example: “Private” and “Public” Attributes Implementing Private Attributes Implementation Details I Generalizing for Public Declarations Implementation Details II Delegating Built-In Operations Example: Validating Function Arguments The Goal A Basic Range-Testing Decorator for Positional Arguments Generalizing for Keywords and Defaults Implementation Details Open Issues Decorator Arguments Versus Function Annotations Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 40. Metaclasses and Inheritance To Metaclass or Not to Metaclass The Downside of “Helper” Functions Metaclasses Versus Class Decorators: Round 1 The Metaclass Model Classes Are Instances of type Metaclasses Are Subclasses of type Class Statements Call a type Class Statements Can Choose a type Metaclass Method Protocol Coding Metaclasses A Basic Metaclass Customizing Construction and Initialization Other Metaclass Coding Techniques Managing Classes with Metaclasses and Decorators Inheritance: The Finale Metaclass Versus Superclass Metaclass Inheritance Python Inheritance Algorithm: The Simple Version Python Inheritance Algorithm: The Less Simple Version The Inheritance Wrap-Up Metaclass Methods Metaclass Methods Versus Class Methods Operator Overloading in Metaclass Methods Metaclass Methods Versus Instance Methods Chapter Summary Test Your Knowledge: Quiz Test Your Knowledge: Answers 41. All Good Things The Python Tsunami The Python Sandbox The Python Upside Closing Thoughts Where to Go from Here Encore: Print Your Own Completion Certificate! IX. Appendixes A. Platform Usage Tips Using Python on Windows Using Python on macOS Using Python on Linux Using Python on Android Using Python on iOS Standalone Apps and Executables Etcetera B. Solutions to End-of-Part Exercises Part I, Getting Started Part II, Objects and Operations Part III, Statements and Syntax Part IV, Functions and Generators Part V, Modules and Packages Part VI, Classes and OOP Part VII, Exceptions Index About the Author