Supercharged Python: Take Your Code to the Next Level

About

Features

• Breaks advanced topics down to their essentials, illustrating them with simple examples and practical exercises
• Covers runtime efficiency, lambda functions, regex, binary operators, advanced data formatting, packages, Django, graphics, magic methods, binary files, and more
• Deepens your insight by illuminating design decisions and tricks behind each language feature
• Includes challenging projects to showcase Python’s power
• Instructors can access additional examples, exercises, and resources

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Description

• Copyright 2019
• Dimensions: 7" x 9-1/8"
• Pages: 672
• Edition: 1st

• Book
• ISBN-10: 0-13-515994-6
• ISBN-13: 978-0-13-515994-1

“Brian Overland makes programming simple. . . . To my amazement, his books explain complicated code clearly enough for anyone to understand.”
–Art Sedighi, PhD

Tapping into the full power of Python doesn’t have to be difficult. Supercharged Python is written for people who’ve learned the fundamentals of the language but want to take their skills to the next level.

After a quick review of Python, the book covers: advanced list and string techniques; all the ways to handle text and binary files; financial applications; advanced techniques for writing classes; generators and decorators; and how to master packages such as Numpy (Numeric Python) to supercharge your applications!

• Use profilers and “magic methods” to code like a pro
• Harness the power of regular expressions to process text quickly with a single statement
• Take advantage of 22 coding shortcuts, along with performance tips, to save time and optimize your code
• Create really useful classes and objects, for games, simulations, money, mathematics, and more
• Use multiple modules to build powerful apps while avoiding the “gotchas”
• Import packages to dramatically speed up statistical operations–by as much as 100 times!
• Refer to the five-part language reference to look up fine points of the language

Supercharged Python demonstrates techniques that allow you to write faster and more powerful code, whether you’re manipulating large amounts of data or building sophisticated applications.

Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

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Sample Content

Table of Contents

Preface xxiii
Acknowledgments xxvii
About the Authors xxix

Chapter 1: Review of the Fundamentals 1
1.1 Python Quick Start 1
1.2 Variables and Naming Names 4
1.3 Combined Assignment Operators 4
1.4 Summary of Python Arithmetic Operators 5
1.5 Elementary Data Types: Integer and Floating Point 6
1.6 Basic Input and Output 7
1.7 Function Definitions 9
1.8 The Python “if” Statement 11
1.9 The Python “while” Statement 12
1.10 A Couple of Cool Little Apps 14
1.11 Summary of Python Boolean Operators 15
1.12 Function Arguments and Return Values 16
1.13 The Forward Reference Problem 19
1.14 Python Strings 19
1.15 Python Lists (and a Cool Sorting App) 21
1.16 The “for” Statement and Ranges 23
1.17 Tuples 25
1.18 Dictionaries 26
1.19 Sets 28
1.20 Global and Local Variables 29
Summary 31
Review Questions 31
Suggested Problems 32

Chapter 2: Advanced String Capabilities 33
2.1 Strings Are Immutable 33
2.2 Numeric Conversions, Including Binary 34
2.3 String Operators (+, =, *, >, etc.) 36
2.4 Indexing and Slicing 39
2.5 Single-Character Functions (Character Codes) 42
2.6 Building Strings Using “join” 44
2.7 Important String Functions 46
2.8 Binary, Hex, and Octal Conversion Functions 47
2.9 Simple Boolean (“is”) Methods 48
2.10 Case Conversion Methods 49
2.11 Search-and-Replace Methods 50
2.12 Breaking Up Input Using “split” 53
2.13 Stripping 54
2.14 Justification Methods 55
Summary 56
Review Questions 57
Suggested Problems 57

Chapter 3: Advanced List Capabilities 59
3.1 Creating and Using Python Lists 59
3.2 Copying Lists Versus Copying List Variables 61
3.3 Indexing 61
3.4 Getting Data from Slices 64
3.5 Assigning into Slices 67
3.6 List Operators 67
3.7 Shallow Versus Deep Copying 69
3.8 List Functions 71
3.9 List Methods: Modifying a List 73
3.10 List Methods: Getting Information on Contents 75
3.11 List Methods: Reorganizing 75
3.12 Lists as Stacks: RPN Application 78
3.13 The “reduce” Function 81
3.14 Lambda Functions 83
3.15 List Comprehension 84
3.16 Dictionary and Set Comprehension 87
3.17 Passing Arguments Through a List 89
3.18 Multidimensional Lists 90
Summary 93
Review Questions 93
Suggested Problems 94

Chapter 4: Shortcuts, Command Line, and Packages 95
4.1 Overview 95
4.2 Twenty-Two Programming Shortcuts 95
4.3 Running Python from the Command Line 115
4.4 Writing and Using Doc Strings 117
4.5 Importing Packages 119
4.6 A Guided Tour of Python Packages 121
4.7 Functions as First-Class Objects 123
4.8 Variable-Length Argument Lists 125
4.9 Decorators and Function Profilers 128
4.10 Generators 132
4.11 Accessing Command-Line Arguments 138
Summary 141
Questions for Review 142
Suggested Problems 142

Chapter 5: Formatting Text Precisely 145
5.1 Formatting with the Percent Sign Operator (%) 145
5.2 Percent Sign (%) Format Specifiers 147
5.3 Percent Sign (%) Variable-Length Print Fields 150
5.4 The Global “format” Function 152
5.5 Introduction to the “format” Method 156
5.6 Ordering by Position (Name or Number) 158
5.7 “Repr” Versus String Conversion 161
5.8 The “spec” Field of the “format” Function and Method 162
5.9 Variable-Size Fields 176
Summary 178
Review Questions 179
Suggested Problems 179

Chapter 6: Regular Expressions, Part I 181
6.1 Introduction to Regular Expressions 181
6.2 A Practical Example: Phone Numbers 183
6.3 Refining Matches 185
6.4 How Regular Expressions Work: Compiling Versus Running 188
6.5 Ignoring Case, and Other Function Flags 192
6.6 Regular Expressions: Basic Syntax Summary 193
6.7 A Practical Regular-Expression Example 200
6.8 Using the Match Object 203
6.9 Searching a String for Patterns 205
6.10 Iterative Searching (“findall”) 206
6.11 The “findall” Method and the Grouping Problem 208
6.12 Searching for Repeated Patterns 210
6.13 Replacing Text 211
Summary 213
Review Questions 213
Suggested Problems 214

Chapter 7: Regular Expressions, Part II 215
7.1 Summary of Advanced RegEx Grammar 215
7.2 Noncapture Groups 217
7.3 Greedy Versus Non-Greedy Matching 219
7.4 The Look-Ahead Feature 224
7.5 Checking Multiple Patterns (Look-Ahead) 227
7.6 Negative Look-Ahead 229
7.7 Named Groups 231
7.8 The “re.split” Function 234
7.9 The Scanner Class and the RPN Project 236
7.10 RPN: Doing Even More with Scanner 239
Summary 243
Review Questions 243
Suggested Problems 244

Chapter 8: Text and Binary Files 245
8.1 Two Kinds of Files: Text and Binary 245
8.2 Approaches to Binary Files: A Summary 247
8.3 The File/Directory System 248
8.4 Handling File-Opening Exceptions 249
8.5 Using the “with” Keyword 252
8.6 Summary of Read/Write Operations 252
8.7 Text File Operations in Depth 254
8.8 Using the File Pointer (“seek”) 257
8.9 Reading Text into the RPN Project 258
8.10 Direct Binary Read/Write 268
8.11 Converting Data to Fixed-Length Fields (“struct”) 269
8.12 Using the Pickling Package 278
8.13 Using the “shelve” Package 280
Summary 282
Review Questions 283
Suggested Problems 283

Chapter 9: Classes and Magic Methods 285
9.1 Classes and Objects: Basic Syntax 285
9.2 More About Instance Variables 287
9.3 The “_ _init_ _” and “_ _new_ _” Methods 288
9.4 Classes and the Forward Reference Problem 289
9.5 Methods Generally 290
9.6 Public and Private Variables and Methods 292
9.7 Inheritance 293
9.8 Multiple Inheritance 294
9.9 Magic Methods, Summarized 295
9.10 Magic Methods in Detail 297
9.11 Supporting Multiple Argument Types 320
9.12 Setting and Getting Attributes Dynamically 322
Summary 323
Review Questions 324
Suggested Problems 325

Chapter 10: Decimal, Money, and Other Classes 327
10.1 Overview of Numeric Classes 327
10.2 Limitations of Floating-Point Format 328
10.3 Introducing the Decimal Class 329
10.4 Special Operations on Decimal Objects 332
10.5 A Decimal Class Application 335
10.6 Designing a Money Class 336
10.7 Writing the Basic Money Class (Containment) 337
10.8 Displaying Money Objects (“_ _str_ _”, “_ _repr_ _”) 338
10.9 Other Monetary Operations 339
10.10 Demo: A Money Calculator 342
10.11 Setting the Default Currency 345
10.12 Money and Inheritance 347
10.13 The Fraction Class 349
10.14 The Complex Class 353
Summary 357
Review Questions 357
Suggested Problems 358

Chapter 11: The Random and Math Packages 359
11.1 Overview of the Random Package 359
11.2 A Tour of Random Functions 360
11.3 Testing Random Behavior 361
11.4 A Random-Integer Game 363
11.5 Creating a Deck Object 365
11.6 Adding Pictograms to the Deck 368
11.7 Charting a Normal Distribution 370
11.8 Writing Your Own Random-Number Generator 374
11.9 Overview of the Math Package 376
11.10 A Tour of Math Package Functions 376
11.11 Using Special Values (pi) 377
11.12 Trig Functions: Height of a Tree 378
11.13 Logarithms: Number Guessing Revisited 381
Summary 385
Review Questions 385
Suggested Problems 386

Chapter 12: The “numpy” (Numeric Python) Package 387
12.1 Overview of the “array,” “numpy,” and “matplotlib” Packages 387
12.2 Using the “array” Package 388
12.3 Downloading and Importing “numpy” 390
12.4 Introduction to “numpy”: Sum 1 to 1 Million 391
12.5 Creating “numpy” Arrays 392
12.6 Example: Creating a Multiplication Table 405
12.7 Batch Operations on “numpy” Arrays 406
12.8 Ordering a Slice of “numpy” 410
12.9 Multidimensional Slicing 412
12.10 Boolean Arrays: Mask Out That “numpy”! 415
12.11 “numpy” and the Sieve of Eratosthenes 417
12.12 Getting “numpy” Stats (Standard Deviation) 419
12.13 Getting Data on “numpy” Rows and Columns 424
Summary 429
Review Questions 429
Suggested Problems 430

Chapter 13: Advanced Uses of “numpy” 431
13.1 Advanced Math Operations with “numpy” 431
13.2 Downloading “matplotlib” 434
13.3 Plotting Lines with “numpy” and “matplotlib” 435
13.4 Plotting More Than One Line 441
13.5 Plotting Compound Interest 444
13.6 Creating Histograms with “matplotlib” 446
13.7 Circles and the Aspect Ratio 452
13.8 Creating Pie Charts 455
13.9 Doing Linear Algebra with “numpy” 456
13.10 Three-Dimensional Plotting 463
13.11 “numpy” Financial Applications 464
13.12 Adjusting Axes with “xticks” and “yticks” 467
13.13 “numpy” Mixed-Data Records 469
13.14 Reading and Writing “numpy” Data from Files 471
Summary 475
Review Questions 475
Suggested Problems 476

Chapter 14: Multiple Modules and the RPN Example 477
14.1 Overview of Modules in Python 477
14.2 Simple Two-Module Example 478
14.3 Variations on the “import” Statement 482
14.4 Using the “_ _all_ _” Symbol 484
14.5 Public and Private Module Variables 487
14.6 The Main Module and “_ _main_ _” 488
14.7 Gotcha! Problems with Mutual Importing 490
14.8 RPN Example: Breaking into Two Modules 493
14.9 RPN Example: Adding I/O Directives 496
14.10 Further Changes to the RPN Example 499
14.11 RPN: Putting It All Together 508
Summary 513
Review Questions 514
Suggested Problems 514

Chapter 15: Getting Financial Data off the Internet 517
15.1 Plan of This Chapter 517
15.2 Introducing the Pandas Package 518
15.3 “stock_load”: A Simple Data Reader 519
15.4 Producing a Simple Stock Chart 521
15.5 Adding a Title and Legend 524
15.6 Writing a “makeplot” Function (Refactoring) 525
15.7 Graphing Two Stocks Together 527
15.8 Variations: Graphing Other Data 530
15.9 Limiting the Time Period 534
15.10 Split Charts: Subplot the Volume 536
15.11 Adding a Moving-Average Line 538
15.12 Giving Choices to the User 540
Summary 544
Review Questions 545
Suggested Problems 545

Appendix A Python Operator Precedence Table 547

Appendix B Built-In Python Functions 549

Appendix C Set Methods 577

Appendix D Dictionary Methods 583

Appendix E Statement Reference 587
Variables and Assignments 587
Spacing Issues in Python 589
Alphabetical Statement Reference 590

Index 605

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