Part I. Getting Started
1. A Python Q&A Session 3
-
Why Do People Use Python? 3
Software Quality 4
Developer Productivity 5
-
Is Python a “Scripting Language”? 5
-
OK, but What’s the Downside? 7
-
Who Uses Python Today? 9
-
What Can I Do with Python? 10
Systems Programming 11
GUIs 11
Internet Scripting 11
Component Integration 12
Database Programming 12
Rapid Prototyping 13
Numeric and Scientific Programming 13
And More: Gaming, Images, Data Mining, Robots, Excel... 14
-
How Is Python Developed and Supported? 15
Open Source Tradeoffs 15
-
What Are Python’s Technical Strengths? 16
It’s Object-Oriented and Functional 16
It’s Free 17
It’s Portable 17
It’s Powerful 18
It’s Mixable 19
It’s Relatively Easy to Use 19
It’s Relatively Easy to Learn 20
It’s Named After Monty Python 20
-
How Does Python Stack Up to Language X? 21
-
Chapter Summary 22
-
Test Your Knowledge: Quiz 23
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Test Your Knowledge: Answers 23
2. How Python Runs Programs 27
-
Introducing the Python Interpreter 27
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Program Execution 28
The Programmer’s View 28
Python’s View 30
-
Execution Model Variations 33
Python Implementation Alternatives 33
Execution Optimization Tools 37
Frozen Binaries 39
Future Possibilities? 40
-
Chapter Summary 40
-
Test Your Knowledge: Quiz 41
-
Test Your Knowledge: Answers 41
3. How You Run Programs 43
-
The Interactive Prompt 43
Starting an Interactive Session 44
The System Path 45
New Windows Options in 3.3: PATH, Launcher 46
Where to Run: Code Directories 47
What Not to Type: Prompts and Comments 48
Running Code Interactively 49
Why the Interactive Prompt? 50
Usage Notes: The Interactive Prompt 52
-
System Command Lines and Files 54
A First Script 55
Running Files with Command Lines 56
Command-Line Usage Variations 57
Usage Notes: Command Lines and Files 58
-
Unix-Style Executable Scripts: #! 59
Unix Script Basics 59
The Unix env Lookup Trick 60
The Python 3.3 Windows Launcher: #! Comes to Windows 60
-
Clicking File Icons 62
Icon-Click Basics 62
Clicking Icons on Windows 63
The input Trick on Windows 63
Other Icon-Click Limitations 66
-
Module Imports and Reloads 66
Import and Reload Basics 66
The Grander Module Story: Attributes 68
Usage Notes: import and reload 71
-
Using exec to Run Module Files 72
-
The IDLE User Interface 73
IDLE Startup Details 74
IDLE Basic Usage 75
IDLE Usability Features 76
Advanced IDLE Tools 77
Usage Notes: IDLE 78
-
Other IDEs 79
-
Other Launch Options 81
Embedding Calls 81
Frozen Binary Executables 82
Text Editor Launch Options 82
Still Other Launch Options 82
Future Possibilities? 83
-
Which Option Should I Use? 83
-
Chapter Summary 85
-
Test Your Knowledge: Quiz 85
-
Test Your Knowledge: Answers 86
-
Test Your Knowledge: Part I Exercises 87
Part II. Types and Operations
4. Introducing Python Object Types 93
-
The Python Conceptual Hierarchy 93
-
Why Use Built-in Types? 94
-
Python’s Core Data Types 95
-
Numbers 97
-
Strings 99
Sequence Operations 99
Immutability 101
Type-Specific Methods 102
Getting Help 104
Other Ways to Code Strings 105
Unicode Strings 106
Pattern Matching 108
-
Lists 109
Sequence Operations 109
Type-Specific Operations 109
Bounds Checking 110
Nesting 110
Comprehensions 111
-
Dictionaries 113
Mapping Operations 114
Nesting Revisited 115
Missing Keys: if Tests 116
Sorting Keys: for Loops 118
Iteration and Optimization 120
-
Tuples 121
Why Tuples? 122
-
Files 122
Binary Bytes Files 123
Unicode Text Files 124
Other File-Like Tools 126
-
Other Core Types 126
How to Break Your Code’s Flexibility 128
User-Defined Classes 129
And Everything Else 130
-
Chapter Summary 130
-
Test Your Knowledge: Quiz 131
-
Test Your Knowledge: Answers 131
5. Numeric Types 133
-
Numeric Type Basics 133
Numeric Literals 134
Built-in Numeric Tools 136
Python Expression Operators 136
-
Numbers in Action 141
Variables and Basic Expressions 141
Numeric Display Formats 143
Comparisons: Normal and Chained 144
Division: Classic, Floor, and True 146
Integer Precision 150
Complex Numbers 151
Hex, Octal, Binary: Literals and Conversions 151
Bitwise Operations 153
Other Built-in Numeric Tools 155
-
Other Numeric Types 157
Decimal Type 157
Fraction Type 160
Sets 163
－集合中的items是unordered, unique and immutable，like a dictionary's keys
－集合运算需都为set类型，而集合的方法(method)只需函数因变量可变（iterable）即可
－in表达类似于判定集合父集子集，但不用转换为set类型
－{ }在Python2.7以上版本中可用于表示集合，但仍然表示空字典，因此创建一个空集合要用set()
Booleans 171
-
Numeric Extensions 172
-
Chapter Summary 172
-
Test Your Knowledge: Quiz 173
-
Test Your Knowledge: Answers 173
6. The Dynamic Typing Interlude 175
-
The Case of the Missing Declaration Statements 175
Variables, Objects, and References 176
Types Live with Objects, Not Variables 177
Objects Are Garbage-Collected 178
-
Shared References 180
Shared References and In-Place Changes 181
Shared References and Equality 183
-
Dynamic Typing Is Everywhere 185
-
Chapter Summary 186
-
Test Your Knowledge: Quiz 186
-
Test Your Knowledge: Answers 186
7. String Fundamentals 189
-
This Chapter’s Scope 189
Unicode: The Short Story 189
-
String Basics 190
-
String Literals 192
Single- and Double-Quoted Strings Are the Same 193
Escape Sequences Represent Special Characters 193
Raw Strings Suppress Escapes 196
Triple Quotes Code Multiline Block Strings 198
-
Strings in Action 200
Basic Operations 200
Indexing and Slicing 201
String Conversion Tools 205
Changing Strings I 208
-
String Methods 209
Method Call Syntax 209
Methods of Strings 210
String Method Examples: Changing Strings II 211
String Method Examples: Parsing Text 213
Other Common String Methods in Action 214
The Original string Module’s Functions (Gone in 3.X) 215
-
String Formatting Expressions 216
Formatting Expression Basics 217
Advanced Formatting Expression Syntax 218
Advanced Formatting Expression Examples 220
Dictionary-Based Formatting Expressions 221
-
String Formatting Method Calls 222
Formatting Method Basics 222
Adding Keys, Attributes, and Offsets 223
Advanced Formatting Method Syntax 224
Advanced Formatting Method Examples 225
Comparison to the % Formatting Expression 227
Why the Format Method? 230
-
General Type Categories 235
Types Share Operation Sets by Categories 235
Mutable Types Can Be Changed in Place 236
-
Chapter Summary 237
-
Test Your Knowledge: Quiz 237
-
Test Your Knowledge: Answers 237
8. Lists and Dictionaries 239
Lists 239
Lists in Action 242
Basic List Operations 242
List Iteration and Comprehensions 242
Indexing, Slicing, and Matrixes 243
Changing Lists in Place 244
Dictionaries 250
Dictionaries in Action 252
Basic Dictionary Operations 253
Changing Dictionaries in Place 254
More Dictionary Methods 254
Example: Movie Database 256
Dictionary Usage Notes 258
Other Ways to Make Dictionaries 262
Dictionary Changes in Python 3.X and 2.7 264
Chapter Summary 271
Test Your Knowledge: Quiz 272
Test Your Knowledge: Answers 272
Tuples, Files, and Everything Else . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . 275
Tuples
276
Tuples in Action 277
Why Lists and Tuples? 279
Records Revisited: Named Tuples 280
Files 282
Opening Files 283
Using Files 284
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Table of Contents
Files
in Action 285
Text and Binary Files: The Short Story 287
Storing Python Objects in Files: Conversions 288
Storing Native Python Objects: pickle 290
Storing Python Objects in JSON Format 291
Storing Packed Binary Data: struct 293
File Context Managers 294
Other File Tools 294
Core Types Review and Summary 295
Object Flexibility 297
References Versus Copies 297
Comparisons, Equality, and Truth 300
The Meaning of True and False in Python 304
Python’s Type Hierarchies 306
Type Objects 306
Other Types in Python 308
Built-in Type Gotchas 308
Assignment Creates References, Not Copies 308
Repetition Adds One Level Deep 309
Beware of Cyclic Data Structures 310
Immutable Types Can’t Be Changed in Place 311
Chapter Summary 311
Test Your Knowledge: Quiz 311
Test Your Knowledge: Answers 312
Test Your Knowledge: Part II Exercises 313
Part
III. Statements and Syntax
Introducing Python Statements . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 319
The
Python Conceptual Hierarchy Revisited 319
Python’s Statements 320
A Tale of Two ifs 322
What Python Adds 322
What Python Removes 323
Why Indentation Syntax? 324
A Few Special Cases 327
A Quick Example: Interactive Loops 329
A Simple Interactive Loop 329
Doing Math on User Inputs 331
Handling Errors by Testing Inputs 332
Handling Errors with try Statements 333
Nesting Code Three Levels Deep 335
Table
of Contents | xi
Chapter
Summary 336
Test Your Knowledge: Quiz 336
Test Your Knowledge: Answers 336
Assignments, Expressions, and Prints . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 339
Assignment
Statements 339
Assignment Statement Forms 340
Sequence Assignments 341
Extended Sequence Unpacking in Python 3.X 344
Multiple-Target Assignments 348
Augmented Assignments 350
Variable Name Rules 352
Expression Statements 356
Expression Statements and In-Place Changes 357
Print Operations 358
The Python 3.X print Function 359
The Python 2.X print Statement 361
Print Stream Redirection 363
Version-Neutral Printing 366
Chapter Summary 369
Test Your Knowledge: Quiz 370
Test Your Knowledge: Answers 370
- if
Tests and Syntax Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . 371
if
Statements 371
General Format 371
Basic Examples 372
Multiway Branching 372
Python Syntax Revisited 375
Block Delimiters: Indentation Rules 376
Statement Delimiters: Lines and Continuations 378
A Few Special Cases 379
Truth Values and Boolean Tests 380
The if/else Ternary Expression 382
Chapter Summary 385
Test Your Knowledge: Quiz 385
Test Your Knowledge: Answers 386
while and for Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 387
while
Loops 387
General Format 388
Examples 388
break, continue, pass, and the Loop else 389
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General
Loop Format 389
pass 390
continue 391
break 391
Loop else 392
for Loops 395
General Format 395
Examples 395
Loop Coding Techniques 402
Counter Loops: range 402
Sequence Scans: while and range Versus for 403
Sequence Shufflers: range and len 404
Nonexhaustive Traversals: range Versus Slices 405
Changing Lists: range Versus Comprehensions 406
Parallel Traversals: zip and map 407
Generating Both Offsets and Items: enumerate 410
Chapter Summary 413
Test Your Knowledge: Quiz 414
Test Your Knowledge: Answers 414
Iterations and Comprehensions . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 415
Iterations:
A First Look 416
The Iteration Protocol: File Iterators 416
Manual Iteration: iter and next 419
Other Built-in Type Iterables 422
List Comprehensions: A First Detailed Look 424
List Comprehension Basics 425
Using List Comprehensions on Files 426
Extended List Comprehension Syntax 427
Other Iteration Contexts 429
New Iterables in Python 3.X 434
Impacts on 2.X Code: Pros and Cons 434
The range Iterable 435
The map, zip, and filter Iterables 436
Multiple Versus Single Pass Iterators 438
Dictionary View Iterables 439
Other Iteration Topics 440
Chapter Summary 441
Test Your Knowledge: Quiz 441
Test Your Knowledge: Answers 441
The Documentation Interlude . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 443
Python
Documentation Sources 443
Table
of Contents | xiii
Comments 444
The dir Function 444
Docstrings: doc 446
PyDoc: The help Function 449
PyDoc: HTML Reports 452
Beyond docstrings: Sphinx 461
The Standard Manual Set 461
Web Resources 462
Published Books 463
Common Coding Gotchas 463
Chapter Summary 465
Test Your Knowledge: Quiz 466
Test Your Knowledge: Answers 466
Test Your Knowledge: Part III Exercises 467
Part
IV. Functions and Generators
Function Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 473
Why
Use Functions? 474
Coding Functions 475
def Statements 476
def Executes at Runtime 477
A First Example: Definitions and Calls 478
Definition 478
Calls 478
Polymorphism in Python 479
A Second Example: Intersecting Sequences 480
Definition 481
Calls 481
Polymorphism Revisited 482
Local Variables 483
Chapter Summary 483
Test Your Knowledge: Quiz 483
Test Your Knowledge: Answers 484
Scopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . 485
Python
Scope Basics 485
Scope Details 486
Name Resolution: The LEGB Rule 488
Scope Example 490
The Built-in Scope 491
The global Statement 494
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Table of Contents
Program
Design: Minimize Global Variables 495
Program Design: Minimize Cross-File Changes 497
Other Ways to Access Globals 498
Scopes and Nested Functions 499
Nested Scope Details 500
Nested Scope Examples 500
Factory Functions: Closures 501
Retaining Enclosing Scope State with Defaults 504
The nonlocal Statement in 3.X 508
nonlocal Basics 508
nonlocal in Action 509
Why nonlocal? State Retention Options 512
State with nonlocal: 3.X only 512
State with Globals: A Single Copy Only 513
State with Classes: Explicit Attributes (Preview) 513
State with Function Attributes: 3.X and 2.X 515
Chapter Summary 519
Test Your Knowledge: Quiz 519
Test Your Knowledge: Answers 520
Arguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 523
Argument-Passing
Basics 523
Arguments and Shared References 524
Avoiding Mutable Argument Changes 526
Simulating Output Parameters and Multiple Results 527
Special Argument-Matching Modes 528
Argument Matching Basics 529
Argument Matching Syntax 530
The Gritty Details 531
Keyword and Default Examples 532
Arbitrary Arguments Examples 534
Python 3.X Keyword-Only Arguments 539
The min Wakeup Call! 542
Full Credit 542
Bonus Points 544
The Punch Line... 544
Generalized Set Functions 545
Emulating the Python 3.X print Function 547
Using Keyword-Only Arguments 548
Chapter Summary 550
Test Your Knowledge: Quiz 551
Test Your Knowledge: Answers 552
Table
of Contents | xv
Advanced Function Topics . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . 553
Function
Design Concepts 553
Recursive Functions 555
Summation with Recursion 555
Coding Alternatives 556
Loop Statements Versus Recursion 557
Handling Arbitrary Structures 558
Function Objects: Attributes and Annotations 562
Indirect Function Calls: “First Class” Objects 562
Function Introspection 563
Function Attributes 564
Function Annotations in 3.X 565
Anonymous Functions: lambda 567
lambda Basics 568
Why Use lambda? 569
How (Not) to Obfuscate Your Python Code 571
Scopes: lambdas Can Be Nested Too 572
Functional Programming Tools 574
Mapping Functions over Iterables: map 574
Selecting Items in Iterables: filter 576
Combining Items in Iterables: reduce 576
Chapter Summary 578
Test Your Knowledge: Quiz 578
Test Your Knowledge: Answers 578
Comprehensions and Generations . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 581
List
Comprehensions and Functional Tools 581
List Comprehensions Versus map 582
Adding Tests and Nested Loops: filter 583
Example: List Comprehensions and Matrixes 586
Don’t Abuse List Comprehensions: KISS 588
Generator Functions and Expressions 591
Generator Functions: yield Versus return 592
Generator Expressions: Iterables Meet Comprehensions
597
Generator Functions Versus Generator Expressions 602
Generators Are Single-Iteration Objects 604
Generation in Built-in Types, Tools, and Classes 606
Example: Generating Scrambled Sequences 609
Don’t Abuse Generators: EIBTI 614
Example: Emulating zip and map with Iteration Tools 617
Comprehension Syntax Summary 622
Scopes and Comprehension Variables 623
Comprehending Set and Dictionary Comprehensions 624
xvi |
Table of Contents
Extended
Comprehension Syntax for Sets and Dictionaries 625
Chapter Summary 626
Test Your Knowledge: Quiz 626
Test Your Knowledge: Answers 626
The Benchmarking Interlude . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 629
Timing
Iteration Alternatives 629
Timing Module: Homegrown 630
Timing Script 634
Timing Results 635
Timing Module Alternatives 638
Other Suggestions 642
Timing Iterations and Pythons with timeit 642
Basic timeit Usage 643
Benchmark Module and Script: timeit 647
Benchmark Script Results 649
More Fun with Benchmarks 651
Other Benchmarking Topics: pystones 656
Function Gotchas 656
Local Names Are Detected Statically 657
Defaults and Mutable Objects 658
Functions Without returns 660
Miscellaneous Function Gotchas 661
Chapter Summary 661
Test Your Knowledge: Quiz 662
Test Your Knowledge: Answers 662
Test Your Knowledge: Part IV Exercises 663
Part
V. Modules and Packages
Modules: The Big Picture . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 669
Why
Use Modules? 669
Python Program Architecture 670
How to Structure a Program 671
Imports and Attributes 671
Standard Library Modules 673
How Imports Work 674
- Find It 674
- Compile It (Maybe) 675
- Run It 675
Byte Code Files: pycache in Python 3.2+ 676
Byte Code File Models in Action 677
Table
of Contents | xvii
The
Module Search Path 678
Configuring the Search Path 681
Search Path Variations 681
The sys.path List 681
Module File Selection 682
Chapter Summary 685
Test Your Knowledge: Quiz 685
Test Your Knowledge: Answers 685
Module Coding Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 687
Module
Creation 687
Module Filenames 687
Other Kinds of Modules 688
Module Usage 688
The import Statement 689
The from Statement 689
The from * Statement 689
Imports Happen Only Once 690
import and from Are Assignments 691
import and from Equivalence 692
Potential Pitfalls of the from Statement 693
Module Namespaces 694
Files Generate Namespaces 695
Namespace Dictionaries: dict 696
Attribute Name Qualification 697
Imports Versus Scopes 698
Namespace Nesting 699
Reloading Modules 700
reload Basics 701
reload Example 702
Chapter Summary 703
Test Your Knowledge: Quiz 704
Test Your Knowledge: Answers 704
Module Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 707
Package
Import Basics 708
Packages and Search Path Settings 708
Package init.py Files 709
Package Import Example 711
from Versus import with Packages 713
Why Use Package Imports? 713
A Tale of Three Systems 714
Package Relative Imports 717
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Table of Contents
Changes
in Python 3.X 718
Relative Import Basics 718
Why Relative Imports? 720
The Scope of Relative Imports 722
Module Lookup Rules Summary 723
Relative Imports in Action 723
Pitfalls of Package-Relative Imports: Mixed Use 729
Python 3.3 Namespace Packages 734
Namespace Package Semantics 735
Impacts on Regular Packages: Optional init.py 736
Namespace Packages in Action 737
Namespace Package Nesting 738
Files Still Have Precedence over Directories 740
Chapter Summary 742
Test Your Knowledge: Quiz 742
Test Your Knowledge: Answers 742
Advanced Module Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . 745
Module
Design Concepts 745
Data Hiding in Modules 747
Minimizing from * Damage: _X and all 747
Enabling Future Language Features: future 748
Mixed Usage Modes: name and main 749
Unit Tests with name 750
Example: Dual Mode Code 751
Currency Symbols: Unicode in Action 754
Docstrings: Module Documentation at Work 756
Changing the Module Search Path 756
The as Extension for import and from 758
Example: Modules Are Objects 759
Importing Modules by Name String 761
Running Code Strings 762
Direct Calls: Two Options 762
Example: Transitive Module Reloads 763
A Recursive Reloader 764
Alternative Codings 767
Module Gotchas 770
Module Name Clashes: Package and Package-Relative
Imports 771
Statement Order Matters in Top-Level Code 771
from Copies Names but Doesn’t Link 772
from * Can Obscure the Meaning of Variables 773
reload May Not Impact from Imports 773
reload, from, and Interactive Testing 774
Table
of Contents | xix
Recursive
from Imports May Not Work 775
Chapter Summary 776
Test Your Knowledge: Quiz 777
Test Your Knowledge: Answers 777
Test Your Knowledge: Part V Exercises 778
Part
VI. Classes and OOP
OOP: The Big Picture . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 783
Why
Use Classes? 784
OOP from 30,000 Feet 785
Attribute Inheritance Search 785
Classes and Instances 788
Method Calls 788
Coding Class Trees 789
Operator Overloading 791
OOP Is About Code Reuse 792
Chapter Summary 795
Test Your Knowledge: Quiz 795
Test Your Knowledge: Answers 795
Class Coding Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 797
Classes
Generate Multiple Instance Objects 797
Class Objects Provide Default Behavior 798
Instance Objects Are Concrete Items 798
A First Example 799
Classes Are Customized by Inheritance 801
A Second Example 802
Classes Are Attributes in Modules 804
Classes Can Intercept Python Operators 805
A Third Example 806
Why Use Operator Overloading? 808
The World’s Simplest Python Class 809
Records Revisited: Classes Versus Dictionaries 812
Chapter Summary 814
Test Your Knowledge: Quiz 815
Test Your Knowledge: Answers 815
- A
More Realistic Example . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . 817
Step
1: Making Instances 818
Coding Constructors 818
Testing As You Go 819
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Table of Contents
Using
Code Two Ways 820
Step 2: Adding Behavior Methods 822
Coding Methods 824
Step 3: Operator Overloading 826
Providing Print Displays 826
Step 4: Customizing Behavior by Subclassing 828
Coding Subclasses 828
Augmenting Methods: The Bad Way 829
Augmenting Methods: The Good Way 829
Polymorphism in Action 832
Inherit, Customize, and Extend 833
OOP: The Big Idea 833
Step 5: Customizing Constructors, Too 834
OOP Is Simpler Than You May Think 836
Other Ways to Combine Classes 836
Step 6: Using Introspection Tools 840
Special Class Attributes 840
A Generic Display Tool 842
Instance Versus Class Attributes 843
Name Considerations in Tool Classes 844
Our Classes’ Final Form 845
Step 7 (Final): Storing Objects in a Database 847
Pickles and Shelves 847
Storing Objects on a Shelve Database 848
Exploring Shelves Interactively 849
Updating Objects on a Shelve 851
Future Directions 853
Chapter Summary 855
Test Your Knowledge: Quiz 855
Test Your Knowledge: Answers 856
Class Coding Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 859
The
class Statement 859
General Form 860
Example 860
Methods 862
Method Example 863
Calling Superclass Constructors 864
Other Method Call Possibilities 864
Inheritance 865
Attribute Tree Construction 865
Specializing Inherited Methods 866
Class Interface Techniques 867
Table
of Contents | xxi
Abstract
Superclasses 869
Namespaces: The Conclusion 872
Simple Names: Global Unless Assigned 872
Attribute Names: Object Namespaces 872
The “Zen” of Namespaces: Assignments Classify Names 873
Nested Classes: The LEGB Scopes Rule Revisited 875
Namespace Dictionaries: Review 878
Namespace Links: A Tree Climber 880
Documentation Strings Revisited 882
Classes Versus Modules 884
Chapter Summary 884
Test Your Knowledge: Quiz 884
Test Your Knowledge: Answers 885
Operator Overloading . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 887
The
Basics 887
Constructors and Expressions: init and sub 888
Common Operator Overloading Methods 888
Indexing and Slicing: getitem and setitem 890
Intercepting Slices 891
Slicing and Indexing in Python 2.X 893
But 3.X’s index Is Not Indexing! 894
Index Iteration: getitem 894
Iterable Objects: iter and next 895
User-Defined Iterables 896
Multiple Iterators on One Object 899
Coding Alternative: iter plus yield 902
Membership: contains, iter, and getitem 906
Attribute Access: getattr and setattr 909
Attribute Reference 909
Attribute Assignment and Deletion 910
Other Attribute Management Tools 912
Emulating Privacy for Instance Attributes: Part 1 912
String Representation: repr and str 913
Why Two Display Methods? 914
Display Usage Notes 916
Right-Side and In-Place Uses: radd and iadd 917
Right-Side Addition 917
In-Place Addition 920
Call Expressions: call 921
Function Interfaces and Callback-Based Code 923
Comparisons: lt, gt, and Others 925
The cmp Method in Python 2.X 926
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Boolean
Tests: bool and len 927
Boolean Methods in Python 2.X 928
Object Destruction: del 929
Destructor Usage Notes 930
Chapter Summary 931
Test Your Knowledge: Quiz 931
Test Your Knowledge: Answers 931
Designing with Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 933
Python
and OOP 933
Polymorphism Means Interfaces, Not Call Signatures 934
OOP and Inheritance: “Is-a” Relationships 935
OOP and Composition: “Has-a” Relationships 937
Stream Processors Revisited 938
OOP and Delegation: “Wrapper” Proxy Objects 942
Pseudoprivate Class Attributes 944
Name Mangling Overview 945
Why Use Pseudoprivate Attributes? 945
Methods Are Objects: Bound or Unbound 948
Unbound Methods Are Functions in 3.X 950
Bound Methods and Other Callable Objects 951
Classes Are Objects: Generic Object Factories 954
Why Factories? 955
Multiple Inheritance: “Mix-in” Classes 956
Coding Mix-in Display Classes 957
Other Design-Related Topics 977
Chapter Summary 977
Test Your Knowledge: Quiz 978
Test Your Knowledge: Answers 978
Advanced Class Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 979
Extending
Built-in Types 980
Extending Types by Embedding 980
Extending Types by Subclassing 981
The “New Style” Class Model 983
Just How New Is New-Style? 984
New-Style Class Changes 985
Attribute Fetch for Built-ins Skips Instances 987
Type Model Changes 992
All Classes Derive from “object” 995
Diamond Inheritance Change 997
More on the MRO: Method Resolution Order 1001
Example: Mapping Attributes to Inheritance Sources 1004
Table
of Contents | xxiii
New-Style
Class Extensions 1010
Slots: Attribute Declarations 1010
Properties: Attribute Accessors 1020
getattribute and Descriptors: Attribute Tools 1023
Other Class Changes and Extensions 1023
Static and Class Methods 1024
Why the Special Methods? 1024
Static Methods in 2.X and 3.X 1025
Static Method Alternatives 1027
Using Static and Class Methods 1028
Counting Instances with Static Methods 1030
Counting Instances with Class Methods 1031
Decorators and Metaclasses: Part 1 1034
Function Decorator Basics 1035
A First Look at User-Defined Function Decorators 1037
A First Look at Class Decorators and Metaclasses 1038
For More Details 1040
The super Built-in Function: For Better or Worse? 1041
The Great super Debate 1041
Traditional Superclass Call Form: Portable, General
1042
Basic super Usage and Its Tradeoffs 1043
The super Upsides: Tree Changes and Dispatch 1049
Runtime Class Changes and super 1049
Cooperative Multiple Inheritance Method Dispatch 1050
The super Summary 1062
Class Gotchas 1064
Changing Class Attributes Can Have Side Effects 1064
Changing Mutable Class Attributes Can Have Side
Effects, Too 1065
Multiple Inheritance: Order Matters 1066
Scopes in Methods and Classes 1068
Miscellaneous Class Gotchas 1069
KISS Revisited: “Overwrapping-itis” 1070
Chapter Summary 1070
Test Your Knowledge: Quiz 1071
Test Your Knowledge: Answers 1071
Test Your Knowledge: Part VI Exercises 1072
Part
VII. Exceptions and Tools
Exception Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 1081
Why
Use Exceptions? 1081
Exception Roles 1082
xxiv |
Table of Contents
Exceptions:
The Short Story 1083
Default Exception Handler 1083
Catching Exceptions 1084
Raising Exceptions 1085
User-Defined Exceptions 1086
Termination Actions 1087
Chapter Summary 1089
Test Your Knowledge: Quiz 1090
Test Your Knowledge: Answers 1090
Exception Coding Details . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . 1093
The
try/except/else Statement 1093
How try Statements Work 1094
try Statement Clauses 1095
The try else Clause 1098
Example: Default Behavior 1098
Example: Catching Built-in Exceptions 1100
The try/finally Statement 1100
Example: Coding Termination Actions with try/finally
1101
Unified try/except/finally 1102
Unified try Statement Syntax 1104
Combining finally and except by Nesting 1104
Unified try Example 1105
The raise Statement 1106
Raising Exceptions 1107
Scopes and try except Variables 1108
Propagating Exceptions with raise 1110
Python 3.X Exception Chaining: raise from 1110
The assert Statement 1112
Example: Trapping Constraints (but Not Errors!) 1113
with/as Context Managers 1114
Basic Usage 1114
The Context Management Protocol 1116
Multiple Context Managers in 3.1, 2.7, and Later 1118
Chapter Summary 1119
Test Your Knowledge: Quiz 1120
Test Your Knowledge: Answers 1120
Exception Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 1123
Exceptions:
Back to the Future 1124
String Exceptions Are Right Out! 1124
Class-Based Exceptions 1125
Coding Exceptions Classes 1126
Table
of Contents | xxv
Why
Exception Hierarchies? 1128
Built-in Exception Classes 1131
Built-in Exception Categories 1132
Default Printing and State 1133
Custom Print Displays 1135
Custom Data and Behavior 1136
Providing Exception Details 1136
Providing Exception Methods 1137
Chapter Summary 1139
Test Your Knowledge: Quiz 1139
Test Your Knowledge: Answers 1139
Designing with Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 1141
Nesting
Exception Handlers 1141
Example: Control-Flow Nesting 1143
Example: Syntactic Nesting 1143
Exception Idioms 1145
Breaking Out of Multiple Nested Loops: “go to” 1145
Exceptions Aren’t Always Errors 1146
Functions Can Signal Conditions with raise 1147
Closing Files and Server Connections 1148
Debugging with Outer try Statements 1149
Running In-Process Tests 1149
More on sys.exc_info 1150
Displaying Errors and Tracebacks 1151
Exception Design Tips and Gotchas 1152
What Should Be Wrapped 1152
Catching Too Much: Avoid Empty except and Exception
1153
Catching Too Little: Use Class-Based Categories 1155
Core Language Summary 1155
The Python Toolset 1156
Development Tools for Larger Projects 1157
Chapter Summary 1160
Test Your Knowledge: Quiz 1161
Test Your Knowledge: Answers 1161
Test Your Knowledge: Part VII Exercises 1161
Part
VIII. Advanced Topics
Unicode and Byte Strings . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . 1165
String
Changes in 3.X 1166
String Basics 1167
xxvi |
Table of Contents
Character
Encoding Schemes 1167
How Python Stores Strings in Memory 1170
Python’s String Types 1171
Text and Binary Files 1173
Coding Basic Strings 1174
Python 3.X String Literals 1175
Python 2.X String Literals 1176
String Type Conversions 1177
Coding Unicode Strings 1178
Coding ASCII Text 1178
Coding Non-ASCII Text 1179
Encoding and Decoding Non-ASCII text 1180
Other Encoding Schemes 1181
Byte String Literals: Encoded Text 1183
Converting Encodings 1184
Coding Unicode Strings in Python 2.X 1185
Source File Character Set Encoding Declarations 1187
Using 3.X bytes Objects 1189
Method Calls 1189
Sequence Operations 1190
Other Ways to Make bytes Objects 1191
Mixing String Types 1192
Using 3.X/2.6+ bytearray Objects 1192
bytearrays in Action 1193
Python 3.X String Types Summary 1195
Using Text and Binary Files 1195
Text File Basics 1196
Text and Binary Modes in 2.X and 3.X 1197
Type and Content Mismatches in 3.X 1198
Using Unicode Files 1199
Reading and Writing Unicode in 3.X 1199
Handling the BOM in 3.X 1201
Unicode Files in 2.X 1204
Unicode Filenames and Streams 1205
Other String Tool Changes in 3.X 1206
The re Pattern-Matching Module 1206
The struct Binary Data Module 1207
The pickle Object Serialization Module 1209
XML Parsing Tools 1211
Chapter Summary 1215
Test Your Knowledge: Quiz 1215
Test Your Knowledge: Answers 1216
Table
of Contents | xxvii
Managed Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 1219
Why
Manage Attributes? 1219
Inserting Code to Run on Attribute Access 1220
Properties 1221
The Basics 1222
A First Example 1222
Computed Attributes 1224
Coding Properties with Decorators 1224
Descriptors 1226
The Basics 1227
A First Example 1229
Computed Attributes 1231
Using State Information in Descriptors 1232
How Properties and Descriptors Relate 1236
getattr and getattribute 1237
The Basics 1238
A First Example 1241
Computed Attributes 1243
getattr and getattribute Compared 1245
Management Techniques Compared 1246
Intercepting Built-in Operation Attributes 1249
Example: Attribute Validations 1256
Using Properties to Validate 1256
Using Descriptors to Validate 1259
Using getattr to Validate 1263
Using getattribute to Validate 1265
Chapter Summary 1266
Test Your Knowledge: Quiz 1266
Test Your Knowledge: Answers 1267
Decorators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . 1269
What’s
a Decorator? 1269
Managing Calls and Instances 1270
Managing Functions and Classes 1270
Using and Defining Decorators 1271
Why Decorators? 1271
The Basics 1273
Function Decorators 1273
Class Decorators 1277
Decorator Nesting 1279
Decorator Arguments 1281
Decorators Manage Functions and Classes, Too 1282
Coding Function Decorators 1283
xxviii
| Table of Contents
Tracing
Calls 1283
Decorator State Retention Options 1285
Class Blunders I: Decorating Methods 1289
Timing Calls 1295
Adding Decorator Arguments 1298
Coding Class Decorators 1301
Singleton Classes 1301
Tracing Object Interfaces 1303
Class Blunders II: Retaining Multiple Instances 1308
Decorators Versus Manager Functions 1309
Why Decorators? (Revisited) 1310
Managing Functions and Classes Directly 1312
Example: “Private” and “Public” Attributes 1314
Implementing Private Attributes 1314
Implementation Details I 1317
Generalizing for Public Declarations, Too 1318
Implementation Details II 1320
Open Issues 1321
Python Isn’t About Control 1329
Example: Validating Function Arguments 1330
The Goal 1330
A Basic Range-Testing Decorator for Positional
Arguments 1331
Generalizing for Keywords and Defaults, Too 1333
Implementation Details 1336
Open Issues 1338
Decorator Arguments Versus Function Annotations 1340
Other Applications: Type Testing (If You Insist!) 1342
Chapter Summary 1343
Test Your Knowledge: Quiz 1344
Test Your Knowledge: Answers 1345
Metaclasses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 1355
To
Metaclass or Not to Metaclass 1356
Increasing Levels of “Magic” 1357
A Language of Hooks 1358
The Downside of “Helper” Functions 1359
Metaclasses Versus Class Decorators: Round 1 1361
The Metaclass Model 1364
Classes Are Instances of type 1364
Metaclasses Are Subclasses of Type 1366
Class Statement Protocol 1367
Declaring Metaclasses 1368
Declaration in 3.X 1369
Table
of Contents | xxix
Declaration
in 2.X 1369
Metaclass Dispatch in Both 3.X and 2.X 1370
Coding Metaclasses 1370
A Basic Metaclass 1371
Customizing Construction and Initialization 1372
Other Metaclass Coding Techniques 1373
Inheritance and Instance 1378
Metaclass Versus Superclass 1381
Inheritance: The Full Story 1382
Metaclass Methods 1388
Metaclass Methods Versus Class Methods 1389
Operator Overloading in Metaclass Methods 1390
Example: Adding Methods to Classes 1391
Manual Augmentation 1391
Metaclass-Based Augmentation 1393
Metaclasses Versus Class Decorators: Round 2 1394
Example: Applying Decorators to Methods 1400
Tracing with Decoration Manually 1400
Tracing with Metaclasses and Decorators 1401
Applying Any Decorator to Methods 1403
Metaclasses Versus Class Decorators: Round 3 (and Last)
1404
Chapter Summary 1407
Test Your Knowledge: Quiz 1407
Test Your Knowledge: Answers 1408
All Good Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 1409
The
Python Paradox 1409
On “Optional” Language Features 1410
Against Disquieting Improvements 1411
Complexity Versus Power 1412
Simplicity Versus Elitism 1412
Closing Thoughts 1413
Where to Go From Here 1414
Encore: Print Your Own Completion Certificate! 1414
Part
IX. Appendixes
A.
Installation and Configuration . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 1421
Installing
the Python Interpreter 1421
Is Python Already Present? 1421
Where to Get Python 1422
Installation Steps 1423
xxx |
Table of Contents
Configuring
Python 1427
Python Environment Variables 1427
How to Set Configuration Options 1429
Python Command-Line Arguments 1432
Python 3.3 Windows Launcher Command Lines 1435
For More Help 1436
B. The
Python 3.3 Windows Launcher . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . 1437
The
Unix Legacy 1437
The Windows Legacy 1438
Introducing the New Windows Launcher 1439
A Windows Launcher Tutorial 1441
Step 1: Using Version Directives in Files 1441
Step 2: Using Command-Line Version Switches 1444
Step 3: Using and Changing Defaults 1445
Pitfalls of the New Windows Launcher 1447
Pitfall 1: Unrecognized Unix !# Lines Fail 1447
Pitfall 2: The Launcher Defaults to 2.X 1448
Pitfall 3: The New PATH Extension Option 1449
Conclusions: A Net Win for Windows 1450
C.
Python Changes and This Book . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 1451
Major
2.X/3.X Differences 1451
3.X Differences 1452
3.X-Only Extensions 1453
General Remarks: 3.X Changes 1454
Changes in Libraries and Tools 1454
Migrating to 3.X 1455
Fifth Edition Python Changes: 2.7, 3.2, 3.3 1456
Changes in Python 2.7 1456
Changes in Python 3.3 1457
Changes in Python 3.2 1458
Fourth Edition Python Changes: 2.6, 3.0, 3.1 1458
Changes in Python 3.1 1458
Changes in Python 3.0 and 2.6 1459
Specific Language Removals in 3.0 1460
Third Edition Python Changes: 2.3, 2.4, 2.5 1462
Earlier and Later Python Changes 1463
D.
Solutions to End-of-Part Exercises . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 1465
Part
I, Getting Started 1465
Part II, Types and Operations 1467
Part III, Statements and Syntax 1473
Table
of Contents | xxxi
Part
IV, Functions and Generators 1475
Part V, Modules and Packages 1485
Part VI, Classes and OOP 1489
Part VII, Exceptions and Tools 1497
Index
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1507
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