پایتون سوپرشارژ: کد خود را به سطح بعدی ببرید (ویرایش اول)

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. Using the example-driven approach featured in Python Without Fear, Brian Overland and John Bennett start with simple examples and carefully build more complex applications. After briefly reviewing the fundamental concepts of Python, the authors carefully explain more advanced topics, including text formatting, regular expressions, and chart plotting. The book reviews advanced techniques for list and string classes, and then covers all the ways of handling text and binary files; decimal, money, and other special classes; advanced techniques for writing classes; generators and decorators; and the random, math, and Numpy (Numeric Python) packages, which can 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 About This eBook Half Title Title Page Copyright Page Dedication Page Contents Preface What Makes Python Special? Paths to Learning: Where Do I Start? Clarity and Examples Are Everything Learning Aids: Icons What You’ll Learn Have Fun Acknowledgments About the Authors 1. Review of the Fundamentals 1.1 Python Quick Start 1.2 Variables and Naming Names 1.3 Combined Assignment Operators 1.4 Summary of Python Arithmetic Operators 1.5 Elementary Data Types: Integer and Floating Point 1.6 Basic Input and Output 1.7 Function Definitions 1.8 The Python “if” Statement 1.9 The Python “while” Statement 1.10 A Couple of Cool Little Apps 1.11 Summary of Python Boolean Operators 1.12 Function Arguments and Return Values 1.13 The Forward Reference Problem 1.14 Python Strings 1.15 Python Lists (and a Cool Sorting App) 1.16 The “for” Statement and Ranges 1.17 Tuples 1.18 Dictionaries 1.19 Sets 1.20 Global and Local Variables Summary Review Questions Suggested Problems 2. Advanced String Capabilities 2.1 Strings Are Immutable 2.2 Numeric Conversions, Including Binary 2.3 String Operators (+, =, *, >, etc.) 2.4 Indexing and Slicing 2.5 Single-Character Functions (Character Codes) 2.6 Building Strings Using “join” 2.7 Important String Functions 2.8 Binary, Hex, and Octal Conversion Functions 2.9 Simple Boolean (“is”) Methods 2.10 Case Conversion Methods 2.11 Search-and-Replace Methods 2.12 Breaking Up Input Using “split” 2.13 Stripping 2.14 Justification Methods Summary Review Questions Suggested Problems 3. Advanced List Capabilities 3.1 Creating and Using Python Lists 3.2 Copying Lists Versus Copying List Variables 3.3 Indexing 3.4 Getting Data from Slices 3.5 Assigning into Slices 3.6 List Operators 3.7 Shallow Versus Deep Copying 3.8 List Functions 3.9 List Methods: Modifying a List 3.10 List Methods: Getting Information on Contents 3.11 List Methods: Reorganizing 3.12 Lists as Stacks: RPN Application 3.13 The “reduce” Function 3.14 Lambda Functions 3.15 List Comprehension 3.16 Dictionary and Set Comprehension 3.17 Passing Arguments Through a List 3.18 Multidimensional Lists Summary Review Questions Suggested Problems 4. Shortcuts, Command Line, and Packages 4.1 Overview 4.2 Twenty-Two Programming Shortcuts 4.3 Running Python from the Command Line 4.4 Writing and Using Doc Strings 4.5 Importing Packages 4.6 A Guided Tour of Python Packages 4.7 Functions as First-Class Objects 4.8 Variable-Length Argument Lists 4.9 Decorators and Function Profilers 4.10 Generators 4.11 Accessing Command-Line Arguments Summary Questions for Review Suggested Problems 5. Formatting Text Precisely 5.1 Formatting with the Percent Sign Operator (%) 5.2 Percent Sign (%) Format Specifiers 5.3 Percent Sign (%) Variable-Length Print Fields 5.4 The Global “format” Function 5.5 Introduction to the “format” Method 5.6 Ordering by Position (Name or Number) 5.7 “Repr” Versus String Conversion 5.8 The “spec” Field of the “format” Function and Method 5.9 Variable-Size Fields Summary Review Questions Suggested Problems 6. Regular Expressions, Part I 6.1 Introduction to Regular Expressions 6.2 A Practical Example: Phone Numbers 6.3 Refining Matches 6.4 How Regular Expressions Work: Compiling Versus Running 6.5 Ignoring Case, and Other Function Flags 6.6 Regular Expressions: Basic Syntax Summary 6.7 A Practical Regular-Expression Example 6.8 Using the Match Object 6.9 Searching a String for Patterns 6.10 Iterative Searching (“findall”) 6.11 The “findall” Method and the Grouping Problem 6.12 Searching for Repeated Patterns 6.13 Replacing Text Summary Review Questions Suggested Problems 7. Regular Expressions, Part II 7.1 Summary of Advanced RegEx Grammar 7.2 Noncapture Groups 7.3 Greedy Versus Non-Greedy Matching 7.4 The Look-Ahead Feature 7.5 Checking Multiple Patterns (Look-Ahead) 7.6 Negative Look-Ahead 7.7 Named Groups 7.8 The “re.split” Function 7.9 The Scanner Class and the RPN Project 7.10 RPN: Doing Even More with Scanner Summary Review Questions Suggested Problems 8. Text and Binary Files 8.1 Two Kinds of Files: Text and Binary 8.2 Approaches to Binary Files: A Summary 8.3 The File/Directory System 8.4 Handling File-Opening Exceptions 8.5 Using the “with” Keyword 8.6 Summary of Read/Write Operations 8.7 Text File Operations in Depth 8.8 Using the File Pointer (“seek”) 8.9 Reading Text into the RPN Project 8.10 Direct Binary Read/Write 8.11 Converting Data to Fixed-Length Fields (“struct”) 8.12 Using the Pickling Package 8.13 Using the “shelve” Package Summary Review Questions Suggested Problems 9. Classes and Magic Methods 9.1 Classes and Objects: Basic Syntax 9.2 More About Instance Variables 9.3 The “_ _init_ _” and “_ _new_ _” Methods 9.4 Classes and the Forward Reference Problem 9.5 Methods Generally 9.6 Public and Private Variables and Methods 9.7 Inheritance 9.8 Multiple Inheritance 9.9 Magic Methods, Summarized 9.10 Magic Methods in Detail 9.11 Supporting Multiple Argument Types 9.12 Setting and Getting Attributes Dynamically Summary Review Questions Suggested Problems 10. Decimal, Money, and Other Classes 10.1 Overview of Numeric Classes 10.2 Limitations of Floating-Point Format 10.3 Introducing the Decimal Class 10.4 Special Operations on Decimal Objects 10.5 A Decimal Class Application 10.6 Designing a Money Class 10.7 Writing the Basic Money Class (Containment) 10.8 Displaying Money Objects (“_ _str_ _”, “_ _repr_ _”) 10.9 Other Monetary Operations 10.10 Demo: A Money Calculator 10.11 Setting the Default Currency 10.12 Money and Inheritance 10.13 The Fraction Class 10.14 The Complex Class Summary Review Questions Suggested Problems 11. The Random and Math Packages 11.1 Overview of the Random Package 11.2 A Tour of Random Functions 11.3 Testing Random Behavior 11.4 A Random-Integer Game 11.5 Creating a Deck Object 11.6 Adding Pictograms to the Deck 11.7 Charting a Normal Distribution 11.8 Writing Your Own Random-Number Generator 11.9 Overview of the Math Package 11.10 A Tour of Math Package Functions 11.11 Using Special Values (pi) 11.12 Trig Functions: Height of a Tree 11.13 Logarithms: Number Guessing Revisited Summary Review Questions Suggested Problems 12. The “numpy” (Numeric Python) Package 12.1 Overview of the “array,” “numpy,” and “matplotlib” Packages 12.2 Using the “array” Package 12.3 Downloading and Importing “numpy” 12.4 Introduction to “numpy”: Sum 1 to 1 Million 12.5 Creating “numpy” Arrays 12.6 Example: Creating a Multiplication Table 12.7 Batch Operations on “numpy” Arrays 12.8 Ordering a Slice of “numpy” 12.9 Multidimensional Slicing 12.10 Boolean Arrays: Mask Out That “numpy”! 12.11 “numpy” and the Sieve of Eratosthenes 12.12 Getting “numpy” Stats (Standard Deviation) 12.13 Getting Data on “numpy” Rows and Columns Summary Review Questions Suggested Problems 13. Advanced Uses of “numpy” 13.1 Advanced Math Operations with “numpy” 13.2 Downloading “matplotlib” 13.3 Plotting Lines with “numpy” and “matplotlib” 13.4 Plotting More Than One Line 13.5 Plotting Compound Interest 13.6 Creating Histograms with “matplotlib” 13.7 Circles and the Aspect Ratio 13.8 Creating Pie Charts 13.9 Doing Linear Algebra with “numpy” 13.10 Three-Dimensional Plotting 13.11 “numpy” Financial Applications 13.12 Adjusting Axes with “xticks” and “yticks” 13.13 “numpy” Mixed-Data Records 13.14 Reading and Writing “numpy” Data from Files Summary Review Questions Suggested Problems 14. Multiple Modules and the RPN Example 14.1 Overview of Modules in Python 14.2 Simple Two-Module Example 14.3 Variations on the “import” Statement 14.4 Using the “_ _all_ _” Symbol 14.5 Public and Private Module Variables 14.6 The Main Module and “_ _main_ _” 14.7 Gotcha! Problems with Mutual Importing 14.8 RPN Example: Breaking into Two Modules 14.9 RPN Example: Adding I/O Directives 14.10 Further Changes to the RPN Example 14.11 RPN: Putting It All Together Summary Review Questions Suggested Problems 15. Getting Financial Data off the Internet 15.1 Plan of This Chapter 15.2 Introducing the Pandas Package 15.3 “stock_load”: A Simple Data Reader 15.4 Producing a Simple Stock Chart 15.5 Adding a Title and Legend 15.6 Writing a “makeplot” Function (Refactoring) 15.7 Graphing Two Stocks Together 15.8 Variations: Graphing Other Data 15.9 Limiting the Time Period 15.10 Split Charts: Subplot the Volume 15.11 Adding a Moving-Average Line 15.12 Giving Choices to the User Summary Review Questions Suggested Problems A. Python Operator Precedence Table B. Built-In Python Functions abs(x) all(iterable) any(iterable) ascii(obj) bin(n) bool(obj) bytes(source, encoding) callable(obj) chr(n) compile(cmd_str, filename, mode_str, flags=0, dont_inherit=False, optimize=–1) complex(real=0, imag=0) complex(complex_str) delattr(obj, name_str) dir([obj]) divmod(a, b) enumerate(iterable, start=0) eval(expr_str [, globals [, locals]] ) exec(object [,global [,locals]]) filter(function,iterable) float([x]) format(obj, [format_spec]) frozenset([iterable]) getattr(obj,name_str [,default]) globals() hasattr(obj,name_str) hash(obj) help([obj]) hex(n) id(obj) input([prompt_str]) int(x,base=10) int() isinstance(obj,class) issubclass(class1,class2) iter(obj) len(sequence) list([iterable]) locals() map(function,iterable1 [,iterable2...]) max(arg1 [, arg2]...) max(iterable) min(arg1 [, arg2]...) min(iterable) oct(n) open(file_name_str,mode=‘rt’) ord(char_str) pow(x,y [,z]) print(objects,sep=‘‘,end=‘\n‘,file=sys.stdout) range(n) range(start,stop [,step]) repr(obj) reversed(iterable) round(x [,ndigits]) set([iterable]) setattr(obj,name_str,value) sorted(iterable [,key] [,reverse]) str(obj=‘‘) str(obj=b‘‘ [,encoding=‘utf-8‘]) sum(iterable [,start]) super(type) tuple([iterable]) type(obj) zip(*iterables) C. Set Methods set_obj.add(obj) set_obj.clear() set_obj.copy() set_obj.difference(other_set) set_obj.difference_update(other_set) set_obj.discard(obj) set_obj.intersection(other_set) set_obj.intersection_update(other_set) set_obj.isdisjoint(other_set) set_obj.issubset(other_set) set_obj.issuperset(other_set) set_obj.pop() set_obj.remove(obj) set_obj.symmetric_difference(other_set) set_obj.symmetric_difference_update(other_set) set_obj.union(other_set) set_obj.union_update(other_set) D. Dictionary Methods dict_obj.clear() dict_obj.copy() dict_obj.get(key_obj, default_val = None) dict_obj.items() dict_obj.keys() dict_obj.pop(key [,default_value]) dict_obj.popitem() dict_obj.setdefault(key,default_value=None) dict_obj.values() dict_obj.update(sequence) E. Statement Reference Variables and Assignments Spacing Issues in Python Alphabetical Statement Reference Index Code Snippets “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