Learning Python. 3rd Edition Mark Lutz

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• Learning Python, 3rd Edition
• Dedication
• A Note Regarding Supplemental Files
• Preface
  • About This Third Edition
    • This Editions Python Language Changes
    • This Edition's Python Training Changes
    • This Edition's Structural Changes
    • This Edition's Scope Changes
  • About This Book
    • This Book's Prerequisites
    • This Book's Scope and Other Books
    • This Book's Style and Structure
  • Book Updates
  • About the Programs in This Book
  • Preparing for Python 3.0
  • About This Series
  • Using Code Examples
  • Font Conventions
  • Safari Books Online
  • How to Contact Us
  • 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
      • Internet Scripting
      • Component Integration
      • Database Programming
      • Rapid Prototyping
      • Numeric and Scientific Programming
      • Gaming, Images, AI, XML, Robots, and More
    • What Are Python's Technical Strengths?
      • It's Object Oriented
      • It's Free
      • It's Portable
      • It's Powerful
      • It's Mixable
      • It's Easy to Use
      • It's Easy to Learn
      • It's Named After Monty Python
    • How Does Python Stack Up to Language X?
    • Chapter Summary
  • 2. How Python Runs Programs
    • Introducing the Python Interpreter
    • Program Execution
      • The Programmer's View
      • Python's View
        • Byte code compilation
        • The Python Virtual Machine (PVM)
        • Performance implications
        • Development implications
    • Execution Model Variations
      • Python Implementation Alternatives
        • CPython
        • Jython
        • IronPython
      • Execution Optimization Tools
        • The Psyco just-in-time compiler
        • The Shedskin C++ translator
      • Frozen Binaries
      • Future Possibilities?
    • Chapter Summary
  • 3. How You Run Programs
    • Interactive Coding
      • Using the Interactive Prompt
    • System Command Lines and Files
      • Using Command Lines and Files
      • Unix Executable Scripts (#!)
    • Clicking File Icons
      • Clicking Icons on Windows
      • The raw_input Trick
      • Other Icon-Click Limitations
    • Module Imports and Reloads
      • The Grander Module Story: Attributes
        • Modules and namespaces
      • import and reload Usage Notes
    • The IDLE User Interface
      • IDLE Basics
      • Using IDLE
      • Advanced IDLE Tools
    • Other IDEs
    • Embedding Calls
    • Frozen Binary Executables
    • Text Editor Launch Options
    • Other Launch Options
    • Future Possibilities?
    • Which Option Should I Use?
    • Chapter Summary
    • BRAIN BUILDER
      • Part I Exercises
• II. Types and Operations
  • 4. Introducing Python Object Types
    • Why Use Built-in Types?
      • Python's Core Data Types
    • Numbers
    • Strings
      • Sequence Operations
      • Immutability
      • Type-Specific Methods
      • Getting Help
      • Other Ways to Code Strings
      • Pattern Matching
    • Lists
      • Sequence Operations
      • Type-Specific Operations
      • Bounds Checking
      • Nesting
      • List Comprehensions
    • Dictionaries
      • Mapping Operations
      • Nesting Revisited
      • Sorting Keys: for Loops
      • Iteration and Optimization
      • Missing Keys: if Tests
    • Tuples
      • Why Tuples?
    • Files
      • Other File-Like Tools
    • Other Core Types
      • How to Break Your Code's Flexibility
      • User-Defined Classes
      • And Everything Else
    • Chapter Summary
  • 5. Numbers
    • Python Numeric Types
      • Numeric Literals
      • Built-in Numeric Tools and Extensions
    • Python Expression Operators
      • Mixed Operators Follow Operator Precedence
      • Parentheses Group Subexpressions
      • Mixed Types Are Converted Up
      • Preview: Operator Overloading
    • Numbers in Action
      • Variables and Basic Expressions
      • Numeric Display Formats
      • Division: Classic, Floor, and True
      • Bitwise Operations
      • Long Integers
      • Complex Numbers
      • Hexadecimal and Octal Notation
      • Other Built-in Numeric Tools
    • Other Numeric Types
      • Decimal Numbers
      • Sets
      • Booleans
      • Third-Party Extensions
    • Chapter Summary
  • 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
    • Chapter Summary
  • 7. ofsmallStrings
    • String Literals
      • Single- and Double-Quoted Strings Are the Same
      • Escape Sequences Represent Special Bytes
      • Raw Strings Suppress Escapes
      • Triple Quotes Code Multiline Block Strings
      • Unicode Strings Encode Larger Character Sets
    • Strings in Action
      • Basic Operations
      • Indexing and Slicing
        • Extended slicing: the third limit
      • String Conversion Tools
        • Character code conversions
      • Changing Strings
    • String Formatting
      • Advanced String Formatting
      • Dictionary-Based String Formatting
    • String Methods
      • String Method Examples: Changing Strings
      • String Method Examples: Parsing Text
      • Other Common String Methods in Action
      • The Original string Module
    • General Type Categories
      • Types Share Operation Sets by Categories
      • Mutable Types Can Be Changed In-Place
    • Chapter Summary
  • 8. Lists and Dictionaries
    • Lists
    • Lists in Action
      • Basic List Operations
      • Indexing, Slicing, and Matrixes
      • Changing Lists In-Place
        • Index and slice assignments
        • List method calls
        • Other common list operations
    • Dictionaries
    • Dictionaries in Action
      • Basic Dictionary Operations
      • Changing Dictionaries In-Place
      • More Dictionary Methods
      • A Languages Table
      • Dictionary Usage Notes
        • Using dictionaries to simulate flexible lists
        • Using dictionaries for sparse data structures
        • Avoiding missing-key errors
        • Using dictionaries as "records"
        • Other ways to make dictionaries
    • Chapter Summary
  • 9. Tuples, Files, and Everything Else
    • Tuples
      • Tuples in Action
        • Tuple syntax peculiarities: commas and parentheses
        • Conversions and immutability
      • Why Lists and Tuples?
    • Files
      • Opening Files
      • Using Files
      • Files in Action
        • Storing and parsing Python objects in files
        • Storing native Python objects with pickle
        • Storing and parsing packed binary data in files
      • Other File Tools
    • Type Categories Revisited
    • Object Flexibility
    • References Versus Copies
    • Comparisons, Equality, and Truth
      • The Meaning of True and False in Python
    • Python's Type Hierarchies
    • 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
    • BRAIN BUILDER
      • Part II Exercises
• III. Statements and Syntax
  • 10. Introducing Python Statements
    • Python Program Structure Revisited
      • Python's Statements
    • A Tale of Two ifs
      • What Python Adds
      • What Python Removes
        • Parentheses are optional
        • End of line is end of statement
        • End of indentation is end of block
      • Why Indentation Syntax?
      • A Few Special Cases
        • Statement rule special cases
        • Block rule special case
    • A Quick Example: Interactive Loops
      • A Simple Interactive Loop
      • Doing Math on User Inputs
      • Handling Errors by Testing Inputs
      • Handling Errors with try Statements
      • Nesting Code Three Levels Deep
    • Chapter Summary
  • 11. rwordsAssignment, Expressions, and print
    • Assignment Statements
      • Assignment Statement Forms
      • Sequence Assignments
        • Advanced sequence assignment patterns
      • Multiple-Target Assignments
        • Multiple-target assignment and shared references
      • Augmented Assignments
        • Augmented assignment and shared references
      • Variable Name Rules
        • Naming conventions
        • Names have no type, but objects do
    • Expression Statements
      • Expression Statements and In-Place Changes
    • print Statements
      • The Python "Hello World" Program
      • Redirecting the Output Stream
      • The print >> file Extension
    • Chapter Summary
  • 12. if Tests
    • if Statements
      • General Format
      • Basic Examples
      • Multiway Branching
    • Python Syntax Rules
      • Block Delimiters
      • Statement Delimiters
      • A Few Special Cases
    • Truth Tests
      • The if/else Ternary Expression
    • Chapter Summary
  • 13. while and for Loops
    • while Loops
      • General Format
      • Examples
    • break, continue, pass, and the Loop else
      • General Loop Format
      • Examples
        • pass
        • continue
        • break
        • else
        • More on the loop else clause
    • for Loops
      • General Format
      • Examples
        • Basic usage
        • Other data types
        • Tuple assignment in for
        • Nested for loops
    • Iterators: A First Look
      • File Iterators
      • Other Built-in Type Iterators
      • Other Iteration Contexts
      • User-Defined Iterators
    • Loop Coding Techniques
      • Counter Loops: while and range
      • Nonexhaustive Traversals: range
      • Changing Lists: range
      • Parallel Traversals: zip and map
        • Dictionary construction with zip
      • Generating Both Offsets and Items: enumerate
    • List Comprehensions: A First Look
      • List Comprehension Basics
      • Using List Comprehensions on Files
      • Extended List Comprehension Syntax
    • Chapter Summary
  • 14. The Documentation Interlude
    • Python Documentation Sources
      • # Comments
      • The dir Function
      • Docstrings: _ _doc_ _
        • User-defined docstrings
        • Docstring standards
        • Built-in docstrings
      • PyDoc: The help Function
      • PyDoc: HTML Reports
      • Standard Manual Set
      • Web Resources
      • Published Books
    • Common Coding Gotchas
    • Chapter Summary
    • BRAIN BUILDER
      • Part III Exercises
• IV. Functions
  • 15. Function Basics
    • Why Use Functions?
      • Coding Functions
      • def Statements
      • def Executes at Runtime
    • A First Example: Definitions and Calls
      • Definition
      • Calls
      • Polymorphism in Python
    • A Second Example: Intersecting Sequences
      • Definition
      • Calls
      • Polymorphism Revisited
      • Local Variables
    • Chapter Summary
  • 16. Scopes and Arguments
    • Scope Rules
      • Python Scope Basics
      • Name Resolution: The LEGB Rule
      • Scope Example
      • The Built-in Scope
    • The global Statement
      • Minimize Global Variables
      • Minimize Cross-File Changes
      • Other Ways to Access Globals
    • Scopes and Nested Functions
      • Nested Scope Details
      • Nested Scope Examples
        • Factory functions
        • Retaining enclosing scopes' state with defaults
        • Nested scopes and lambdas
        • Scopes versus defaults with loop variables
        • Arbitrary scope nesting
    • Passing Arguments
      • Arguments and Shared References
      • Avoiding Mutable Argument Changes
      • Simulating Output Parameters
    • Special Argument-Matching Modes
      • Keyword and Default Examples
        • Keywords
        • Defaults
      • Arbitrary Arguments Examples
        • Collecting arguments
        • Unpacking arguments
      • Combining Keywords and Defaults
      • The min Wakeup Call
        • Full credit
        • Bonus points
        • The punch line
      • A More Useful Example: General Set Functions
      • Argument Matching: The Gritty Details
    • Chapter Summary
  • 17. Advanced Function Topics
    • Anonymous Functions: lambda
      • lambda Expressions
      • Why Use lambda?
      • How (Not) to Obfuscate Your Python Code
      • Nested lambdas and Scopes
    • Applying Functions to Arguments
      • The apply Built-in
        • Passing keyword arguments
      • apply-Like Call Syntax
    • Mapping Functions over Sequences: map
    • Functional Programming Tools: filter and reduce
    • List Comprehensions Revisited: Mappings
      • List Comprehension Basics
      • Adding Tests and Nested Loops
      • List Comprehensions and Matrixes
      • Comprehending List Comprehensions
    • Iterators Revisited: Generators
      • Generator Function Example
      • Extended Generator Function Protocol: send Versus next
      • Iterators and Built-in Types
      • Generator Expressions: Iterators Meet List Comprehensions
    • Timing Iteration Alternatives
    • Function Design Concepts
      • Functions Are Objects: Indirect Calls
    • Function Gotchas
      • Local Names Are Detected Statically
      • Defaults and Mutable Objects
      • Functions Without returns
      • Enclosing Scope Loop Variables
    • Chapter Summary
    • BRAIN BUILDER
      • Part IV Exercises
• V. Modules
  • 18. Modules: The Big Picture
    • Why Use Modules?
    • Python Program Architecture
      • How to Structure a Program
      • Imports and Attributes
      • Standard Library Modules
    • How Imports Work
      • 1. Find It
        • The module search path
        • The sys.path list
        • Module file selection
        • Advanced module selection concepts
      • 2. Compile It (Maybe)
      • 3. Run It
    • Chapter Summary
  • 19. Module Coding Basics
    • Module Creation
    • Module Usage
      • The import Statement
      • The from statement
      • The from * Statement
      • Imports Happen Only Once
      • import and from Are Assignments
      • Cross-File Name Changes
      • import and from Equivalence
      • Potential Pitfalls of the from Statement
        • When import is required
    • Module Namespaces
      • Files Generate Namespaces
      • Attribute Name Qualification
      • Imports Versus Scopes
      • Namespace Nesting
    • Reloading Modules
      • reload Basics
      • reload Example
    • Chapter Summary
  • 20. Module Packages
    • Package Import Basics
      • Packages and Search Path Settings
      • Package _ _init_ _.py Files
    • Package Import Example
      • from Versus import with Packages
    • Why Use Package Imports?
      • A Tale of Three Systems
    • Chapter Summary
  • 21. Advanced Module Topics
    • Data Hiding in Modules
      • Minimizing from * Damage: _X and _ _all_ _
    • Enabling Future Language Features
    • Mixed Usage Modes: _ _name_ _ and _ _main_ _
      • Unit Tests with _ _name_ _
    • Changing the Module Search Path
    • The import as Extension
    • Relative Import Syntax
      • Why Relative Imports?
    • Module Design Concepts
      • Modules Are Objects: Metaprograms
    • Module Gotchas
      • Statement Order Matters in Top-Level Code
      • Importing Modules by Name String
      • 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
      • reload Isn't Applied Transitively
      • Recursive from Imports May Not Work
    • Chapter Summary
    • BRAIN BUILDER
      • Part V Exercises
• VI. Classes and OOP
  • 22. OOP: The Big Picture
    • Why Use Classes?
    • OOP from 30,000 Feet
      • Attribute Inheritance Search
      • Classes and Instances
      • Class Method Calls
      • Coding Class Trees
      • OOP Is About Code Reuse
    • Chapter Summary
  • 23. 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
      • Why Use Operator Overloading?
    • The World's Simplest Python Class
    • Chapter Summary
  • 24. Class Coding Details
    • The class Statement
      • General Form
      • Example
    • Methods
      • Example
      • Calling Superclass Constructors
      • Other Method Call Possibilities
    • Inheritance
      • Attribute Tree Construction
      • Specializing Inherited Methods
      • Class Interface Techniques
      • Abstract Superclasses
    • Operator Overloading
      • Common Operator Overloading Methods
      • _ _getitem_ _ Intercepts Index References
      • _ _getitem_ _ and _ _iter_ _ Implement Iteration
      • User-Defined Iterators
        • Multiple iterators on one object
      • _ _getattr_ _ and _ _setattr_ _ Catch Attribute References
      • Emulating Privacy for Instance Attributes
      • _ _repr_ _ and _ _str_ _ Return String Representations
      • _ _radd_ _ Handles Right-Side Addition
      • _ _call_ _ Intercepts Calls
      • Function Interfaces and Callback-Based Code
      • _ _del_ _ Is a Destructor
    • Namespaces: The Whole Story
      • Simple Names: Global Unless Assigned
      • Attribute Names: Object Namespaces
      • The "Zen" of Python Namespaces: Assignments Classify Names
      • Namespace Dictionaries
      • Namespace Links
    • A More Realistic Example
    • Chapter Summary
  • 25. Designing with Classes
    • Python and OOP
      • Overloading by Call Signatures (or Not)
    • Classes As Records
    • OOP and Inheritance: "Is-a" Relationships
    • OOP and Composition: "Has-a" Relationships
      • Stream Processors Revisited
    • OOP and Delegation
    • Multiple Inheritance
    • Classes Are Objects: Generic Object Factories
      • Why Factories?
    • Methods Are Objects: Bound or Unbound
    • Documentation Strings Revisited
    • Classes Versus Modules
    • Chapter Summary
  • 26. Advanced Class Topics
    • Extending Built-in Types
      • Extending Types by Embedding
      • Extending Types by Subclassing
    • Pseudoprivate Class Attributes
      • Name Mangling Overview
      • Why Use Pseudoprivate Attributes?
    • New-Style Classes
      • Diamond Inheritance Change
        • Diamond inheritance example
        • Explicit conflict resolution
      • Other New-Style Class Extensions
        • Static and class methods
        • Instance slots
        • Class properties
        • New _ _getattribute_ _ overloading method
    • Static and Class Methods
      • Using Static and Class Methods
    • Function Decorators
      • Decorator Example
    • Class Gotchas
      • Changing Class Attributes Can Have Side Effects
      • Multiple Inheritance: Order Matters
      • Methods, Classes, and Nested Scopes
      • "Overwrapping-itis"
    • Chapter Summary
    • BRAIN BUILDER
      • Part VI Exercises
• VII. Exceptions and Tools
  • 27. Exception Basics
    • Why Use Exceptions?
      • Exception Roles
    • Exception Handling: The Short Story
    • The try/except/else Statement
      • try Statement Clauses
      • The try/else Clause
      • Example: Default Behavior
      • Example: Catching Built-in Exceptions
    • The try/finally Statement
      • Example: Coding Termination Actions with try/finally
    • Unified try/except/finally
      • Combining finally and except by Nesting
      • Unified try Example
    • The raise Statement
      • Example: Raising and Catching User-Defined Exceptions
      • Example: Passing Extra Data with raise
      • Example: Propagating Exceptions with raise
    • The assert Statement
      • Example: Trapping Constraints (but Not Errors)
    • with/as Context Managers
      • Basic Usage
      • The Context Management Protocol
    • Chapter Summary
  • 28. Exception Objects
    • String-Based Exceptions
      • String Exceptions Are Right Out!
    • Class-Based Exceptions
      • Class Exception Example
      • Why Class Exceptions?
      • Built-in Exception Classes
      • Specifying Exception Text
      • Sending Extra Data and Behavior in Instances
        • Example: Extra data with classes and strings
    • General raise Statement Forms
    • Chapter Summary
  • 29. Designing with Exceptions
    • Nesting Exception Handlers
      • Example: Control-Flow Nesting
      • Example: Syntactic Nesting
    • Exception Idioms
      • Exceptions Aren't Always Errors
      • Functions Signal Conditions with raise
      • Debugging with Outer try Statements
      • Running In-Process Tests
      • More on sys.exc_info
    • Exception Design Tips
      • What Should Be Wrapped
      • Catching Too Much: Avoid Empty excepts
      • Catching Too Little: Use Class-Based Categories
    • Exception Gotchas
      • String Exceptions Match by Identity, Not by Value
      • Catching the Wrong Thing
    • Core Language Summary
      • The Python Toolset
      • Development Tools for Larger Projects
    • Chapter Summary
    • BRAIN BUILDER
      • Part VII Exercises
• VIII. Appendixes
  • A. Installation and Configuration
    • Installing the Python Interpreter
      • Is Python Already Present?
      • Where to Fetch Python
      • Installation Steps
    • Configuring Python
      • Python Environment Variables
      • How to Set Configuration Options
        • Unix/Linux shell variables
        • DOS variables (Windows)
        • Other Windows options
        • Path files
  • B. Solutions to End-of-Part Exercises
    • Part I, Getting Started
    • Part II, Types and Operations
    • Part III, Statements and Syntax
    • Part IV, Functions
    • Part V, Modules
    • Part VI, Classes and OOP
    • Part VII, Exceptions and Tools
• About the Author
• Colophon
• Copyright

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