D

data attributes, Example

data structures, Why Use Built-in Types?, Why Use Built-in Types?, Using dictionaries for sparse data structures: Tuple keys, The Meaning of True and False in Python, Beware of Cyclic Data Structures, Handling Arbitrary Structures–More recursion examples

about, Why Use Built-in Types?

arbitrary, Handling Arbitrary Structures–More recursion examples

built-in object types and, Why Use Built-in Types?

cyclic, Beware of Cyclic Data Structures

dictionaries and, Using dictionaries for sparse data structures: Tuple keys

empty, The Meaning of True and False in Python

data types, Python’s Core Data Types (see object types)

database programming, Database Programming

databases, access-by-key, Nesting Revisited (see access-by-key databases and filesystems)

dbm module, Pickles and Shelves

__debug__ built-in variable, The assert Statement, A Basic Range-Testing Decorator for Positional Arguments

debugging Python code, Advanced IDLE Tools, Which Option Should I Use?–Which Option Should I Use?, Usage variation: Showing underscore name values, Debugging with Outer try Statements, Development Tools for Larger Projects

about, Which Option Should I Use?–Which Option Should I Use?

IDLE debugger, Advanced IDLE Tools

string issues, Usage variation: Showing underscore name values

tools supporting, Development Tools for Larger Projects

with try statement, Debugging with Outer try Statements

decimal module, Decimal basics

decimals (decimal object), Numbers, Other Core Types, Decimal Type–Decimal basics, Decimal basics, Setting decimal precision globally, Setting decimal precision globally, Decimal context manager, Decimal context manager, Decimal context manager, Numeric accuracy in fractions and decimals

about, Numbers, Other Core Types, Decimal Type–Decimal basics

context manager, Decimal context manager

from_float method, Decimal basics

getcontext method, Setting decimal precision globally

localcontext method, Decimal context manager

numeric accuracy in, Numeric accuracy in fractions and decimals

resetting precision temporarily, Decimal context manager

setting precision globally, Setting decimal precision globally

decoding, Unicode: The Short Story (see encoding and decoding)

decorators, Timing Script, Abstract superclasses in Python 3.X and 2.6+: Preview, Decorators and Metaclasses: Part 1, Decorators and Metaclasses: Part 1, Coding Properties with Decorators–Setter and deleter decorators, What’s a Decorator?, Managing Calls and Instances, Managing Functions and Classes, Using and Defining Decorators–Why Decorators?, Using and Defining Decorators, Why Decorators?, Decorator Nesting–Decorator Nesting, Decorator Arguments, Decorators Manage Functions and Classes, Too, Class Blunders I: Decorating Methods–Using descriptors to decorate methods, Adding Decorator Arguments–Timing with decorator arguments, Decorators Versus Manager Functions, Why Decorators? (Revisited), Why Decorators? (Revisited), Managing Functions and Classes Directly–Managing Functions and Classes Directly, Example: “Private” and “Public” Attributes–Python Isn’t About Control, Example: Validating Function Arguments–Other Applications: Type Testing (If You Insist!), A Basic Range-Testing Decorator for Positional Arguments–Other Applications: Type Testing (If You Insist!), Decorator nesting, Decorator Arguments Versus Function Annotations–Decorator Arguments Versus Function Annotations, Test Your Knowledge: Quiz–Test Your Knowledge: Answers, Example: Applying Decorators to Methods–Metaclasses Versus Class Decorators: Round 3 (and Last)

(see also class decorators; function decorators)

about, Decorators and Metaclasses: Part 1, What’s a Decorator?

abstract superclasses and, Abstract superclasses in Python 3.X and 2.6+: Preview

arguments and, Decorator Arguments, Adding Decorator Arguments–Timing with decorator arguments, Example: Validating Function Arguments–Other Applications: Type Testing (If You Insist!), Decorator Arguments Versus Function Annotations–Decorator Arguments Versus Function Annotations

coding properties, Coding Properties with Decorators–Setter and deleter decorators

defining, Using and Defining Decorators

encapsulation and, Why Decorators? (Revisited)

macros versus, Why Decorators?

manager functions versus, Decorators Versus Manager Functions

managing calls and instances, Managing Calls and Instances

managing functions and classes, Managing Functions and Classes, Decorators Manage Functions and Classes, Too, Managing Functions and Classes Directly–Managing Functions and Classes Directly

methods and, Class Blunders I: Decorating Methods–Using descriptors to decorate methods, Example: Applying Decorators to Methods–Metaclasses Versus Class Decorators: Round 3 (and Last)

nesting, Decorator Nesting–Decorator Nesting, Decorator nesting

private and public attributes, Example: “Private” and “Public” Attributes–Python Isn’t About Control

quiz questions and answers, Test Your Knowledge: Quiz–Test Your Knowledge: Answers

range-testing for positional arguments, A Basic Range-Testing Decorator for Positional Arguments–Other Applications: Type Testing (If You Insist!)

timing alternatives, Timing Script

usage considerations, Using and Defining Decorators–Why Decorators?, Why Decorators? (Revisited)

def statement, Python’s Statements, Coding Functions, def Statements, def Executes at Runtime, def Executes at Runtime, Python Scope Basics, Scope Details, Name Resolution: The LEGB Rule, Name Resolution: The LEGB Rule, Nested scopes, defaults, and lambdas, Loop variables may require defaults, not scopes, Coding Class Trees, The class Statement, Managing Calls and Instances, Usage

about, Python’s Statements, def Statements

class statement and, The class Statement

coding functions, Coding Functions

decorators and, Managing Calls and Instances, Usage

lambda expressions and, Nested scopes, defaults, and lambdas

name resolution and, Name Resolution: The LEGB Rule

nesting, def Executes at Runtime, Loop variables may require defaults, not scopes, Coding Class Trees

runtime execution, def Executes at Runtime

scope and, Python Scope Basics, Scope Details, Name Resolution: The LEGB Rule

default exception handler, Default Exception Handler

__del__ method, Common Operator Overloading Methods, Object Destruction: __del__–Destructor Usage Notes, A First Example, Using descriptors to decorate methods

about, Common Operator Overloading Methods

descriptors and, Using descriptors to decorate methods

managing attributes, A First Example

object destruction and, Object Destruction: __del__–Destructor Usage Notes

del statement, Other common list operations, Python’s Statements

__delattr__ method, Common Operator Overloading Methods, __getattr__ and __getattribute__

delegation, OOP and Delegation: “Wrapper” Proxy Objects, OOP and Delegation: “Wrapper” Proxy Objects–OOP and Delegation: “Wrapper” Proxy Objects, Why the lookup change?, Decorators and Metaclasses: Part 1, Delegation-based classes in 3.X: __getattr__ and built-ins, Inheritance versus delegation, Caveat: Implicitly run operator overloading methods fail to delegate under 3.X–Implementation alternatives: __getattribute__ inserts, call stack inspection

about, OOP and Delegation: “Wrapper” Proxy Objects

class gotchas, Delegation-based classes in 3.X: __getattr__ and built-ins

function decorators and, Decorators and Metaclasses: Part 1

inheritance versus, Inheritance versus delegation

OOP considerations, OOP and Delegation: “Wrapper” Proxy Objects–OOP and Delegation: “Wrapper” Proxy Objects

operator overloading and, Caveat: Implicitly run operator overloading methods fail to delegate under 3.X–Implementation alternatives: __getattribute__ inserts, call stack inspection

proxy classes and, Why the lookup change?

__delete__ method, Common Operator Overloading Methods, A First Example

deleting, Other common list operations, Dictionaries

dictionary items, Dictionaries

list items, Other common list operations

delimiters, Block Delimiters: Indentation Rules–Avoid mixing tabs and spaces: New error checking in 3.X, Statement Delimiters: Lines and Continuations

blocks of code, Block Delimiters: Indentation Rules–Avoid mixing tabs and spaces: New error checking in 3.X

statement, Statement Delimiters: Lines and Continuations

__delitem__ method, Common Operator Overloading Methods

deprecation protocol for Python, Variable Name Rules

depth-first, left-to-right (DFLR) path, Multiple Inheritance: “Mix-in” Classes, Diamond Inheritance Change

derived classes, Attribute Inheritance Search, All Classes Derive from “object”–Implications for defaults

descriptors, Example, Attribute Tree Construction, Other Attribute Management Tools, __getattribute__ and Descriptors: Attribute Tools, Inserting Code to Run on Attribute Access, Descriptors–Descriptors and slots and more, Read-only descriptors, Using State Information in Descriptors–Using State Information in Descriptors, How Properties and Descriptors Relate–Descriptors and slots and more, Descriptors and slots and more, Management Techniques Compared–Management Techniques Compared, Using Descriptors to Validate–Option 2: Validating with per-client-instance state, Using descriptors to decorate methods–Using descriptors to decorate methods, Coding variations: Routers, descriptors, automation, The descriptors special case, The descriptors special case–Assignment inheritance

about, Example, __getattribute__ and Descriptors: Attribute Tools, Descriptors–Descriptors and slots and more

attribute access and, Inserting Code to Run on Attribute Access

builtins routing mixin, Coding variations: Routers, descriptors, automation

decorating methods with, Using descriptors to decorate methods–Using descriptors to decorate methods

inheritance and, Attribute Tree Construction, The descriptors special case–Assignment inheritance

management techniques compared, Management Techniques Compared–Management Techniques Compared

managing attributes, Other Attribute Management Tools

metaclasses and, The descriptors special case

properties and, How Properties and Descriptors Relate–Descriptors and slots and more

read-only, Read-only descriptors

slots and, Descriptors and slots and more

state information in, Using State Information in Descriptors–Using State Information in Descriptors

validating with, Using Descriptors to Validate–Option 2: Validating with per-client-instance state

design patterns, Factory Functions: Closures–Closures versus classes, round 1

destructor method, Object Destruction: __del__–Destructor Usage Notes

development considerations, Is Python a “Scripting Language”?, Database Programming, Rapid Prototyping, How Is Python Developed and Supported?, Development implications, Development implications, Built-in Type Gotchas–Immutable Types Can’t Be Changed in Place, Common Coding Gotchas–Common Coding Gotchas, Coding Functions–def Executes at Runtime, Program Design: Minimize Global Variables, Program Design: Minimize Cross-File Changes–Program Design: Minimize Cross-File Changes, Coding Alternatives, How (Not) to Obfuscate Your Python Code–How (Not) to Obfuscate Your Python Code, Don’t Abuse Generators: EIBTI–On the other hand: Space and time, conciseness, expressiveness, Function Gotchas–Hiding built-ins by assignment: Shadowing, Module Coding Basics–Test Your Knowledge: Answers, Coding Class Trees–Coding Class Trees, OOP Is About Code Reuse–Programming by customization, Coding Constructors, Coding Methods–Coding Methods, Coding Subclasses, Room for improvement: MRO, slots, GUIs–Room for improvement: MRO, slots, GUIs, Class Gotchas–KISS Revisited: “Overwrapping-itis”, Exception Coding Details–Test Your Knowledge: Answers, Coding Exceptions Classes–Coding Exceptions Classes, Designing with Exceptions–Test Your Knowledge: Part VII Exercises, Development Tools for Larger Projects–Development Tools for Larger Projects, Coding Basic Strings–String Type Conversions, Coding Function Decorators–Timing with decorator arguments, Coding Class Decorators–Why Decorators? (Revisited), Coding Metaclasses–Overloading class creation calls with metaclasses

built-in type gotchas, Built-in Type Gotchas–Immutable Types Can’t Be Changed in Place

class gotchas, Class Gotchas–KISS Revisited: “Overwrapping-itis”

code reuse, OOP Is About Code Reuse–Programming by customization

coding class decorators, Coding Class Decorators–Why Decorators? (Revisited)

coding class trees, Coding Class Trees–Coding Class Trees

coding constructors, Coding Constructors

coding exception classes, Coding Exceptions Classes–Coding Exceptions Classes

coding exception details, Exception Coding Details–Test Your Knowledge: Answers, Designing with Exceptions–Test Your Knowledge: Part VII Exercises

coding function decorators, Coding Function Decorators–Timing with decorator arguments

coding functions, Coding Functions–def Executes at Runtime, Coding Alternatives, How (Not) to Obfuscate Your Python Code–How (Not) to Obfuscate Your Python Code

coding metaclasses, Coding Metaclasses–Overloading class creation calls with metaclasses

coding methods, Coding Methods–Coding Methods

coding strings, Coding Basic Strings–String Type Conversions

coding subclasses, Coding Subclasses

common coding gotchas, Common Coding Gotchas–Common Coding Gotchas

database programming, Database Programming

development community, How Is Python Developed and Supported?

EIBTI acronym, Don’t Abuse Generators: EIBTI–On the other hand: Space and time, conciseness, expressiveness

function gotchas, Function Gotchas–Hiding built-ins by assignment: Shadowing

improvement suggestions, Room for improvement: MRO, slots, GUIs–Room for improvement: MRO, slots, GUIs

for larger projects, Development Tools for Larger Projects–Development Tools for Larger Projects

minimizing cross-file changes, Program Design: Minimize Cross-File Changes–Program Design: Minimize Cross-File Changes

minimizing global variables, Program Design: Minimize Global Variables

module coding, Module Coding Basics–Test Your Knowledge: Answers

program execution, Development implications

rapid development cycle, Is Python a “Scripting Language”?, Development implications

rapid prototyping, Rapid Prototyping

DFLR (depth-first, left-to-right) path, Multiple Inheritance: “Mix-in” Classes, Diamond Inheritance Change

diamond patterns, Multiple Inheritance: “Mix-in” Classes, Multiple Inheritance: “Mix-in” Classes, New-Style Class Changes, Diamond Inheritance Change–Example: Mapping Attributes to Inheritance Sources

about, Multiple Inheritance: “Mix-in” Classes

attribute searches, Multiple Inheritance: “Mix-in” Classes

inheritance search order, New-Style Class Changes, Diamond Inheritance Change–Example: Mapping Attributes to Inheritance Sources

__dict__ attribute, How (Not) to Obfuscate Your Python Code, Files Generate Namespaces, Namespace Dictionaries: __dict__, Example: Modules Are Objects, Example: Modules Are Objects, The World’s Simplest Python Class, Special Class Attributes, Instance Versus Class Attributes, OOP and Delegation: “Wrapper” Proxy Objects, Listing instance attributes with __dict__–Listing instance attributes with __dict__, Listing attributes per object in class trees, Slots and namespace dictionaries–Slots and namespace dictionaries, Using __dict__ and __slots__ (and other virtual names)

about, Special Class Attributes, Instance Versus Class Attributes

listing attributes in class trees, Listing attributes per object in class trees

listing instance attributes, Listing instance attributes with __dict__–Listing instance attributes with __dict__

metaprogram example, Example: Modules Are Objects

namespace dictionaries and, Namespace Dictionaries: __dict__

namespaces and, How (Not) to Obfuscate Your Python Code, Files Generate Namespaces

private attributes and, Using __dict__ and __slots__ (and other virtual names)

slots and, Slots and namespace dictionaries–Slots and namespace dictionaries

usage example, Example: Modules Are Objects, The World’s Simplest Python Class

wrapper classes and, OOP and Delegation: “Wrapper” Proxy Objects

dict built-in function, Type Objects, Other Iteration Contexts

dictionaries (dict object), Python’s Core Data Types, Python’s Core Data Types, Dictionaries, Dictionaries, Mapping Operations, Mapping Operations, Mapping Operations, Nesting Revisited, Missing Keys: if Tests–Missing Keys: if Tests, Missing Keys: if Tests–Missing Keys: if Tests, Missing Keys: if Tests, Missing Keys: if Tests, Sorting Keys: for Loops–Sorting Keys: for Loops, Sorting Keys: for Loops, Iteration and Optimization, Iteration and Optimization, Python Expression Operators, Dictionary-Based Formatting Expressions, Adding Keys, Attributes, and Offsets, Dictionaries–Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Dictionaries, Basic Dictionary Operations, Basic Dictionary Operations, Basic Dictionary Operations, Changing Dictionaries in Place, Changing Dictionaries in Place, More Dictionary Methods–More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, More Dictionary Methods, Example: Movie Database–Preview: Mapping values to keys, Preview: Mapping values to keys, Dictionary Usage Notes–Nesting in dictionaries, Dictionary Usage Notes, Dictionary Usage Notes, Using dictionaries to simulate flexible lists: Integer keys, Using dictionaries for sparse data structures: Tuple keys, Avoiding missing-key errors, Nesting in dictionaries, Other Ways to Make Dictionaries, Other Ways to Make Dictionaries, Dictionary Changes in Python 3.X and 2.7–The has_key method is dead in 3.X: Long live in!, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary Changes in Python 3.X and 2.7, Dictionary comprehensions in 3.X and 2.7, Dictionary views in 3.X (and 2.7 via new methods), Dictionary views in 3.X (and 2.7 via new methods), Dictionary views in 3.X (and 2.7 via new methods), Dictionary views in 3.X (and 2.7 via new methods)–Dictionary views and sets, Sorting dictionary keys in 3.X, Sorting dictionary keys in 3.X, Dictionary magnitude comparisons no longer work in 3.X, The has_key method is dead in 3.X: Long live in!, The has_key method is dead in 3.X: Long live in!, Test Your Knowledge: Quiz, References Versus Copies, Comparisons, Equality, and Truth, Python 2.X and 3.X dictionary comparisons, Python 2.X and 3.X dictionary comparisons, Tuple assignment in for loops, Dictionary construction with zip, Other Built-in Type Iterables, Other Built-in Type Iterables, New Iterables in Python 3.X, New Iterables in Python 3.X, New Iterables in Python 3.X, Dictionary View Iterables–Dictionary View Iterables, Dictionary View Iterables–Dictionary View Iterables, Using Keyword-Only Arguments, Generators and function application, Records Revisited: Classes Versus Dictionaries–Records Revisited: Classes Versus Dictionaries

about, Python’s Core Data Types, Dictionaries, Dictionaries–Dictionaries

adding keys, Adding Keys, Attributes, and Offsets

alternate ways to make, Other Ways to Make Dictionaries

changing in place, Changing Dictionaries in Place

classes versus, Records Revisited: Classes Versus Dictionaries–Records Revisited: Classes Versus Dictionaries

clear method, Dictionaries

common operations, Dictionaries, Basic Dictionary Operations

comparison operations, Dictionary magnitude comparisons no longer work in 3.X, Comparisons, Equality, and Truth

copy method, Dictionaries, References Versus Copies

data structures and, Using dictionaries for sparse data structures: Tuple keys

deleting items, Dictionaries

dictionary views, Dictionary views in 3.X (and 2.7 via new methods)–Dictionary views and sets, Dictionary View Iterables–Dictionary View Iterables

empty dictionaries, Dictionaries

fromkeys method, Dictionary comprehensions in 3.X and 2.7

get method, Missing Keys: if Tests, Dictionaries, More Dictionary Methods, Avoiding missing-key errors

has_key method, Missing Keys: if Tests, Dictionary Changes in Python 3.X and 2.7, The has_key method is dead in 3.X: Long live in!

indexing, Mapping Operations, Dictionaries, Dictionary Usage Notes

interface considerations, The has_key method is dead in 3.X: Long live in!

items method, Python Expression Operators, Dictionaries, More Dictionary Methods, Dictionary Changes in Python 3.X and 2.7, Dictionary views in 3.X (and 2.7 via new methods), Python 2.X and 3.X dictionary comparisons, Tuple assignment in for loops, New Iterables in Python 3.X

iteration in, Iteration and Optimization, Basic Dictionary Operations, Other Built-in Type Iterables, Dictionary View Iterables–Dictionary View Iterables

keys method, Sorting Keys: for Loops, Dictionaries, Basic Dictionary Operations, More Dictionary Methods, Dictionary Changes in Python 3.X and 2.7, Dictionary views in 3.X (and 2.7 via new methods), Sorting dictionary keys in 3.X, Other Built-in Type Iterables, New Iterables in Python 3.X

keyword arguments, Mapping Operations

lists versus, Using dictionaries to simulate flexible lists: Integer keys, Other Ways to Make Dictionaries

literals, Python’s Core Data Types, Dictionaries

mapping operations, Mapping Operations, Missing Keys: if Tests–Missing Keys: if Tests, Preview: Mapping values to keys

missing keys, Missing Keys: if Tests–Missing Keys: if Tests

movie database example, Example: Movie Database–Preview: Mapping values to keys

mutable nature of, Dictionaries

nesting, Nesting Revisited, Dictionaries, Changing Dictionaries in Place, Nesting in dictionaries

optimization in, Iteration and Optimization

OrderedDict subclass, More Dictionary Methods

pop method, Dictionaries, More Dictionary Methods, Using Keyword-Only Arguments

popitem method, Dictionaries

quiz questions and answers, Test Your Knowledge: Quiz

sequence operations and, Dictionary Usage Notes

setdefault method, Dictionaries

sorting keys, Sorting Keys: for Loops–Sorting Keys: for Loops, Sorting dictionary keys in 3.X

string formatting expressions, Dictionary-Based Formatting Expressions

type-specific methods, Dictionaries, More Dictionary Methods–More Dictionary Methods

update method, Dictionaries, More Dictionary Methods

usage considerations, Dictionary Usage Notes–Nesting in dictionaries

values method, Dictionaries, More Dictionary Methods, Dictionary Changes in Python 3.X and 2.7, Dictionary views in 3.X (and 2.7 via new methods), New Iterables in Python 3.X, Generators and function application

version considerations, Dictionary Changes in Python 3.X and 2.7–The has_key method is dead in 3.X: Long live in!, Python 2.X and 3.X dictionary comparisons

viewitems method, Dictionary Changes in Python 3.X and 2.7

viewkeys method, Dictionaries, Dictionary Changes in Python 3.X and 2.7

viewvalues method, Dictionary Changes in Python 3.X and 2.7

zip built-in function and, Dictionary construction with zip

dictionary comprehensions, Other Ways to Make Dictionaries, Dictionary comprehensions in 3.X and 2.7–Dictionary comprehensions in 3.X and 2.7, Other Iteration Contexts, Comprehending Set and Dictionary Comprehensions–Extended Comprehension Syntax for Sets and Dictionaries

dir built-in function, Getting Help, Python Documentation Sources–The dir Function, Files Generate Namespaces, Example: Modules Are Objects, Instance Versus Class Attributes, Listing inherited attributes with dir–Listing inherited attributes with dir

about, Getting Help

customizing version of, Example: Modules Are Objects

as documentation source, Python Documentation Sources–The dir Function

inheritance and, Instance Versus Class Attributes, Listing inherited attributes with dir–Listing inherited attributes with dir

inspecting namespaces, Files Generate Namespaces

directives, What Not to Type: Prompts and Comments

directories, file precedence over, Files Still Have Precedence over Directories–Files Still Have Precedence over Directories

diretory walkers, Generators and library tools: Directory walkers

display formats, Numeric Display Formats, Neutralizing display differences with code–Neutralizing display differences with code, Providing Print Displays–Providing Print Displays, A Generic Display Tool, Custom Print Displays

generic display tool, A Generic Display Tool

neutralizing difference with code, Neutralizing display differences with code–Neutralizing display differences with code

numeric, Numeric Display Formats

print operations, Providing Print Displays–Providing Print Displays, Custom Print Displays

distutils modules, Optimized byte code files, Fix 2: Full path absolute import, Development Tools for Larger Projects

division operations, Division: Classic, Floor, and True, Division: Classic, Floor, and True–Supporting either Python, Division: Classic, Floor, and True–Why does truncation matter?, Division: Classic, Floor, and True–Why does truncation matter?

about, Division: Classic, Floor, and True

floor division, Division: Classic, Floor, and True–Why does truncation matter?

truncating division, Division: Classic, Floor, and True–Why does truncation matter?

version considerations, Division: Classic, Floor, and True–Supporting either Python

__ doc__ attribute, Python Documentation Sources, Docstrings: __doc__–Built-in docstrings, Namespace Dictionaries: Review, Documentation Strings Revisited

doctest module, Mixed Usage Modes: __name__ and __main__, Development Tools for Larger Projects

documentation, What Not to Type: Prompts and Comments, A First Script, Getting Help, Getting Help, Getting Help, Variables and Basic Expressions, Triple Quotes Code Multiline Block Strings, Other Common String Methods in Action, Python Syntax Revisited, Python Documentation Sources, Python Documentation Sources, Python Documentation Sources–The dir Function, Python Documentation Sources, Python Documentation Sources, Python Documentation Sources, Python Documentation Sources, Python Documentation Sources, # Comments, Docstrings: __doc__–Built-in docstrings, PyDoc: The help Function–Python 3.2 and earlier: GUI client, PyDoc: The help Function–PyDoc: The help Function, Beyond docstrings: Sphinx, The Standard Manual Set–Published Books, Test Your Knowledge: Quiz, Standard Library Modules

# comments, What Not to Type: Prompts and Comments, A First Script, Variables and Basic Expressions, Python Documentation Sources, # Comments

about, Python Documentation Sources

additional resources, Python Documentation Sources, The Standard Manual Set–Published Books, Standard Library Modules

dir built-in function, Getting Help, Python Documentation Sources–The dir Function

docstrings, Triple Quotes Code Multiline Block Strings, Python Syntax Revisited, Python Documentation Sources, Docstrings: __doc__–Built-in docstrings

help built-in function, Getting Help, Other Common String Methods in Action, Python Documentation Sources, PyDoc: The help Function–PyDoc: The help Function

PyDoc system, Getting Help, Python Documentation Sources, PyDoc: The help Function–Python 3.2 and earlier: GUI client

quiz questions and answers, Test Your Knowledge: Quiz

Sphinx tool, Python Documentation Sources, Beyond docstrings: Sphinx

documentation strings, Triple Quotes Code Multiline Block Strings, Python Syntax Revisited, Python Documentation Sources, Docstrings: __doc__–Built-in docstrings, Docstrings: Module Documentation at Work, Documentation Strings Revisited, Development Tools for Larger Projects

about, Python Documentation Sources, Docstrings: __doc__–Built-in docstrings, Documentation Strings Revisited, Development Tools for Larger Projects

modules and, Docstrings: Module Documentation at Work

triple-quoted strings, Triple Quotes Code Multiline Block Strings

usage considerations, Python Syntax Revisited

DOM parsing, XML Parsing Tools

dot path syntax, Packages and Search Path Settings

duck typing, Polymorphism in Python

dynamic typing, It’s Powerful, Python’s Core Data Types, The Case of the Missing Declaration Statements, Variables, Objects, and References–Types Live with Objects, Not Variables, Variables, Objects, and References–Objects Are Garbage-Collected, Variables, Objects, and References, Shared References–Shared References and Equality, Dynamic Typing Is Everywhere, Test Your Knowledge: Quiz

about, It’s Powerful, Python’s Core Data Types, The Case of the Missing Declaration Statements, Dynamic Typing Is Everywhere

objects and, Variables, Objects, and References–Objects Are Garbage-Collected

quiz questions and answers, Test Your Knowledge: Quiz

references and, Variables, Objects, and References, Shared References–Shared References and Equality

variables and, Variables, Objects, and References–Types Live with Objects, Not Variables