Opis: The Practice of Computing Using Python - Richard Enbody, William Punch

For CS1 courses in Python Programming (including majors and non-majors). A problem-solving approach to programming with Python. The Practice of Computing Using Python introduces CS1 students (majors and non-majors) to computational thinking using Python.With data-manipulation as a theme, students quickly see the value in what they're learning and leave the course with a set of immediately useful computational skills that can be applied to problems they encounter in future pursuits. The book takes an "object-use-first" approach-writing classes is covered only after students have mastered using objects. This edition is available with MyProgrammingLab, an innovative online homework and assessment tool. Through the power of practice and immediate personalized feedback, MyProgrammingLab helps students fully grasp the logic, semantics, and syntax of programming. Note: If you are purchasing the standalone text or electronic version, MyProgrammingLab does not come automatically packaged with the text. To purchase MyProgrammingLab, please visit: myprogramminglab.com or you can purchase a package of the physical text + MyProgrammingLab by searching for ISBN 10: 0132992833 / ISBN 13: 9780132992831. MyProgrammingLab is not a self-paced technology and should only be purchased when required by an instructorContents -1.0.1 Data Manipulation ... 20 -1.0.2 Problem Solving and Case Studies ... 20 -1.0.3 Code examples ... 20 -1.0.4 Interactive Sessions ... 20 -1.0.5 Exercises and Programming Projects ... 20 -1.0.6 Self-Test Exercises ... 20 -1.0.7 Programming Tips ... 20 I Thinking About Computing 23 0 The Study of Computer Science 25 0.1 Why Computer Science? ... 25 0.1.1 Importance of Computer Science ... 25 0.1.2 Computer Science Around You ... 25 0.1.3 Computer "Science" ... 26 0.1.4 Computer Science Through Computer Programming ... 27 0.2 The Difficulty and Promise of Programming ... 27 0.2.1 Difficulty 1: Two Things at Once ... 27 A une Damoyselle malade ... 27 My Sweet/Cute [One] (Feminine) ... 28 A une Damoyselle malade ... 28 My Sweet Dear ... 29 A une Damoyselle malade ... 29 0.2.2 Difficulty 2: What is a Good Program? ... 29 0.2.3 The Promise of a Computer Program ... 30 0.3 Choosing a Computer Language ... 31 0.3.1 Different Computer Languages ... 31 0.3.2 Why Python? ... 31 0.3.3 Is Python the Best Language? ... 32 0.4 What Is Computation? ... 32 0.5 What Is a computer? ... 33 0.5.1 Computation in Nature ... 33 0.5.2 The Human Computer ... 35 0.6 The Modern, Electronic Computer ... 36 0.6.1 It's the Switch! ... 36 0.6.2 The Transistor ... 37 0.7 A High-Level Look at a Modern Computer ... 41 0.8 Representing Data ... 42 0.8.1 Binary Data ... 43 0.8.2 Working with Binary ... 43 0.8.3 Limits ... 44 0.8.4 Representing Letters ... 44 0.8.5 Representing Other Data ... 45 0.8.6 What Does a Number Represent? ... 46 0.8.7 How to Talk About Quantities of Data ... 46 0.8.8 How Much Data is That? ... 47 0.9 Overview of Coming Chapters ... 48 II Starting to Program 51 1 Beginnings 53 1.1 Practice, Practice, Practice ... 53 1.2 QuickStart, the Circumference Program ... 54 1.2.1 Examining the code ... 55 1.3 An Interactive Session ... 57 1.4 Parts of a Program ... 58 1.4.1 Modules ... 58 1.4.2 Statements and Expressions ... 58 1.4.3 Whitespace ... 59 1.4.4 Comments ... 60 1.4.5 Special Python Elements: Tokens ... 60 1.4.6 Naming Objects ... 61 1.4.7 Recommendations on Naming ... 62 1.5 Variables ... 63 1.5.1 Variable Creation and Assignment ... 63 1.6 Objects and Types ... 66 1.6.1 Numbers ... 68 1.6.2 Other Built-In Types ... 70 1.6.3 Object types: not variable types ... 71 1.6.4 Constructing New Values ... 72 1.7 Operators ... 73 1.7.1 Integer Operators ... 73 1.7.2 Floating Point Operators ... 75 1.7.3 Mixed Operations ... 75 1.7.4 Order of Operations and Parentheses ... 76 1.7.5 Augmented Assignment Operators: A Shortcut! ... 76 1.8 Your First Module, Math ... 79 1.9 Developing an Algorithm ... 80 1.9.1 New rule, testing ... 83 1.10 Visual Vignette: TURTLE GRAPHICS ... 83 1.10.1 Exercises ... 87 1.10.2 Programming Projects ... 90 2 Control 93 2.1 The Selection Statement for Decisions: if ... 93 2.1.1 Booleans for Decisions ... 94 2.1.2 The if Statement ... 95 2.1.3 Example: What Lead is Safe in Basketball? ... 97 2.1.4 Repetition ... 100 2.1.5 Example: Finding Perfect Numbers ... 103 2.1.6 Example: Classifying Numbers ... 107 2.2 In-Depth Control ... 110 2.2.1 True and False: Booleans ... 110 2.2.2 Boolean Variables ... 111 2.2.3 Relational Operators ... 111 2.2.4 Boolean Operators ... 115 2.2.5 Precedence ... 117 2.2.6 Boolean Operators Example ... 117 2.2.7 Another Word on Assignments ... 121 2.2.8 The Selection Statement for Decisions ... 122 2.2.9 More on Python Decision Statements ... 123 2.2.10 Repetition: the while Statement ... 126 2.2.11 Sentinel Loop ... 134 2.2.12 Summary of Repetition ... 134 2.2.13 More on the for Statement ... 134 2.2.14 Nesting ... 137 2.2.15 Hailstone Sequence Example ... 138 2.3 Visual Vignette: Plotting Data with pylab ... 140 2.3.1 First Plot and Using a List ... 140 2.3.2 More Interesting Plot: a Sine Wave ... 141 2.4 Computer Science Perspectives ... 143 2.4.1 Minimal Universal Computing ... 143 2.4.2 Programming Projects ... 152 3 Algorithms and Program Development 155 3.1 What Is an Algorithm? ... 155 3.1.1 Example Algorithms ... 156 3.2 Algorithm Features ... 157 3.2.1 Algorithm versus Program ... 157 3.2.2 Qualities of an Algorithm ... 158 3.2.3 Can We Really Do All That? ... 159 3.3 What is a Program? ... 159 3.3.1 Readability ... 160 3.3.2 Robust ... 162 3.3.3 Correctness ... 163 3.4 Strategies for Program Design ... 3.4.1 Engage and Commit ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 116634 3.4.2 Understand, Then Visualize ... 164 3.4.3 Think Before You Program ... 165 3.4.4 Experiment ... 165 3.4.5 Simplify ... 166 3.4.6 Stop and Think ... 166 3.4.7 Relax: Give Yourself a Break ... 167 3.5 A Simple Example ... 167 3.5.1 Build the Skeleton ... 167 3.5.2 Output ... 168 3.5.3 Input ... 168 3.5.4 Doing the Calculation ... 170 4 Working with Strings 175 4.1 The String Type ... 175 4.1.1 The Triple Quote String ... 176 4.1.2 Non Printing Characters ... 176 4.1.3 String Representation ... 176 4.1.4 Strings as a Sequence ... 177 4.1.5 More Indexing and Slicing ... 178 4.1.6 Strings are Iterable ... 182 4.2 String Operations ... 183 4.2.1 Concatenation (+) and Repetition (*) ... 183 4.2.2 Determining When + Indicates Addition or Concatenation? ... 184 4.2.3 Comparison Operators ... 184 4.2.4 The in Operator ... 185 4.2.5 String Collections are Immutable ... 186 4.3 A Preview of Functions and Methods ... 187 4.3.1 First Cut: What is a Function? ... 188 4.3.2 A String Method ... 189 4.3.3 Determining Method Names and Method Arguments ... 191 4.3.4 String Methods ... 192 4.3.5 String Functions ... 192 4.4 Formatted Output for Strings ... 194 4.4.1 Descriptor Codes ... 195 4.4.2 Width and Alignment Descriptors ... 195 4.4.3 Floating-Point Precision Descriptor ... 197 4.5 Control and Strings ... 198 4.6 Working with Strings ... 201 4.6.1 Example: Reordering a Person's Name ... 201 4.6.2 Palindromes ... 202 4.7 More String Formatting ... 204 4.8 Computer Science Perspectives ... 207 4.8.1 Programming Projects ... 213 5 Files and Exceptions I 217 5.1 What is a File? ... 217 5.2 Accessing Files: Reading Text Files ... 217 5.2.1 What's Really Happening? ... 218 5.3 Accessing Files: Writing Text Files ... 218 5.4 Reading and Writing Text Files ... 219 5.5 File Creation and Overwriting ... 220 5.6 First Cut, Handling Errors ... 221 5.6.1 Error Names ... 222 5.6.2 The try-except construct ... 222 5.6.3 try-except Flow of Control ... 223 5.6.4 Exception example ... 223 5.7 Example: Counting Poker Hands ... 226 5.7.1 Program to Count Poker Hands ... 229 III Functions and Data Structures 239 6 Functions-QuickStart 241 6.1 What Is a Function? ... 241 6.1.1 Why Have Functions? ... 242 6.2 Python Functions ... 243 6.3 Flow of Control with Functions ... 245 6.3.1 Function Flow in Detail ... 246 6.3.2 Parameter Passing ... 246 6.3.3 Another Function Example ... 248 6.3.4 Function Example: Word Puzzle ... 250 6.3.5 Functions Calling Functions ... 254 6.3.6 When to Use a Function ... 254 6.3.7 What If There is No Return Statement? ... 255 6.3.8 What If There Are Multiple Return Statements? ... 256 6.4 Visual Vignette: Turtle Flag ... 256 7 Lists and Tuples 263 7.1 What Is a List? ... 263 7.2 What You Already Know How To Do With Lists ... 265 7.2.1 Iteration ... 265 7.2.2 Indexing and Slicing ... 265 7.2.3 Operators ... 266 7.2.4 Functions ... 268 7.2.5 List Iteration ... 268 7.3 Lists are different than Strings ... 269 7.3.1 Lists are Mutable ... 269 7.3.2 List Methods ... 270 7.4 OLD AND NEW FRIENDS ... 273 7.4.1 Split and Multiple Assignment ... 273 7.4.2 List to String and Back Again, Using join ... 274 7.4.3 The Sorted Function ... 275 7.5 Working with Some Examples ... 276 7.5.1 Anagrams ... 276 7.5.2 Example: File Analysis ... 280 7.6 Mutable Objects and References ... 285 7.6.1 Shallow vs. Deep Copy ... 290 7.6.2 Mutable versus Immutable ... 293 7.7 Tuples ... 295 7.7.1 Tuples from Lists ... 297 7.7.2 Why Tuples? ... 297 7.8 Lists: The Data Structure ... 298 7.8.1 Example Data Structure ... 298 7.8.2 Other Example Data Structures ... 299 7.9 ALGORITHM EXAMPLE ... 300 7.10 Python Diversion: List Comprehension ... 307 7.10.1 Comprehensions, Expressions and the Ternary Operator ... 308 7.11 Visual Vignette: More Plotting ... 309 7.11.1 Numpy Arrays ... 309 7.11.2 Plotting Trigonometric Functions ... 311 7.11.3 Programming Projects ... 320 8 More on Functions 325 8.1 Scope: A First Cut ... 325 8.1.1 Arguments, Parameters, and Namespaces ... 326 8.1.2 Passing Mutable Objects ... 328 8.1.3 Returning a Complex Object ... 330 8.1.4 Refactoring evens ... 331 8.2 DEFAULT VALUES AND PARAMETERS ... 331 8.2.1 Example: Default Values and Parameter Keywords ... 332 8.3 Functions as Objects ... 334 8.3.1 Function Annotations ... 335 8.3.2 Docstrings ... 336 8.4 Example: Determining a Final Grade ... 336 8.4.1 The Data ... 336 8.4.2 The Design ... 337 8.4.3 Function: weighted_grade ... 337 8.4.4 Function: parse_line ... 338 8.4.5 Function: main ... 338 8.4.6 Example Use ... 339 8.5 Esoterica: "by value" or "by reference" ... 339 8.5.1 Programming Projects ... 342 9 Dictionaries and Sets 345 9.1 Dictionaries ... 345 9.1.1 Dictionary Example ... 346 9.1.2 Python Dictionaries ... 346 9.1.3 Dictionary Indexing and Assignment ... 347 9.1.4 Operators ... 348 9.2 Word Count Example ... 352 9.2.1 Count Words in a String ... 352 9.2.2 Word Frequency for Gettysburg Address ... 353 9.2.3 Output and Comments ... 356 9.3 Periodic Table Example ... 357 9.3.1 Working with CSV Files ... 357 9.3.2 Algorithm Overview ... 358 9.3.3 Functions for Divide and Conquer ... 359 9.4 Sets ... 362 9.4.1 History ... 362 9.4.2 What's in a Set? ... 362 9.4.3 Python Sets ... 362 9.4.4 Methods, Operators, and Functions for Python Sets ... 363 9.4.5 Set Methods ... 363 9.5 Set Applications ... 368 9.5.1 Relationship between Words of Different Documents ... 368 9.5.2 Output and Comments ... 370 9.6 Scope: The Full Story ... 371 9.6.1 Namespaces and Scope ... 371 9.6.2 Search Rule for Scope ... 371 9.6.3 Local ... 372 9.6.4 Global ... 372 9.6.5 Built-Ins ... 375 9.6.6 Enclosed ... 376 9.7 PYTHON POINTER ... 377 9.8 Python Diversion: Dictionary and Set Comprehension ... 377 9.9 Visual Vignette: Bar Graph of Word Frequency ... 378 9.9.1 Getting the Data Right ... 378 9.9.2 Labels and the xticks Command ... 379 9.9.3 Plotting ... 379 9.9.4 Programming Projects ... 385 10 More Program Development 389 10.1 Introduction ... 389 10.2 Divide and Conquer ... 389 10.2.1 Top-Down Refinement ... 389 10.3 The Breast Cancer Classifier ... 390 10.3.1 The Problem ... 390 10.3.2 The Approach: Classification ... 390 10.3.3 Training and Testing the Classifier ... 390 10.3.4 Building the Classifier ... 391 10.4 Designing the Classifier Algorithm ... 391 10.4.1 Divided, now Conquer ... 395 10.4.2 Data Structures ... 395 10.4.3 File Format ... 396 10.4.4 The make_training_set Function ... 396 10.4.5 The make_test_set Function ... 400 10.4.6 The train_classifier Function ... 400 10.4.7 train_classifer, Round 2 ... 402 10.4.8 Testing the Classifier on New Data ... 404 10.4.9 The report_results Function ... 408 10.5 Running the Classifier on Full Data ... 409 10.5.1 Training versus Testing ... 409 10.6 Other Interesting Problems ... 412 10.6.1 Tag Clouds ... 412 10.6.2 S&P 500 Predictions ... 413 10.6.3 Predicting Religion with Flags ... 416 10.6.4 Programming Projects ... 419 IV Classes, making your own Data Structures and Algorithms 421 11 Introduction to Classes 423 11.0.5 Simple Student Class ... 423 11.1 Object-Oriented Programming ... 424 11.1.1 Python Is Object-Oriented! ... 424 11.1.2 Characteristics of OOP ... 424 11.2 Working with Object-Oriented Programming ... 424 11.2.1 Class and Instance ... 425 11.3 Working with Classes and Instances ... 426 11.3.1 Built-In Class and Instance ... 426 11.3.2 Our First Class ... 426 11.3.3 Changing Attributes ... 428 11.3.4 The Special Relationship Between an Instance and Class: instance-of ... 429 11.4 Object Methods ... 431 11.4.1 Using Object Methods ... 431 11.4.2 Writing Methods ... 432 11.4.3 The Special Argument self ... 433 11.4.4 Methods are the Interface to a Class Instance ... 435 11.5 Fitting into the Python Class Model ... 435 11.5.1 Making Programmer-Defined Classes ... 435 11.5.2 A Student Class ... 435 11.5.3 Python Standard Methods ... 436 11.5.4 Now There Are Three: Class Designer, Programmer, and User ... 439 11.6 Example: Point Class ... 440 11.6.1 Construction ... 441 11.6.2 Distance ... 441 11.6.3 Summing Two Points ... 441 11.6.4 Improving the Point Class ... 442 11.7 Python and OOP ... 445 11.7.1 Encapsulation ... 445 11.7.2 Inheritance ... 445 11.7.3 Polymorphism ... 445 11.8 An Aside: Python and Other OOP languages ... 446 11.8.1 Public versus Private ... 446 11.8.2 Indicating Privacy Using Double Underscores (__) ... 446 11.8.3 Python's Philosophy ... 447 11.8.4 Modifying an Instance ... 447 11.8.5 Programming Projects ... 450 12 More on Classes 453 12.1 More About Class Properties ... 453 12.1.1 Rational Number (Fraction) Class Example ... 454 12.2 How Does Python Know? ... 455 12.2.1 Classes, Types, and Introspection ... 456 12.2.2 Remember Operator Overloading ... 457 12.3 Creating Your Own Operator Overloading ... 458 12.3.1 Mapping Operators to Special Methods ... 458 12.4 Building the Rational Number Class ... 460 12.4.1 Making the Class ... 461 12.4.2 Review Fraction Addition ... 462 12.4.3 Back to Adding Fractions ... 465 12.4.4 Equality and Reducing Rationals ... 468 12.4.5 Divide and Conquer at Work ... 470 12.5 What Doesn't Work (Yet) ... 470 12.5.1 Introspection ... 471 12.5.2 Repairing "int + Rational" Errors ... 473 12.6 Inheritance ... 474 12.6.1 The "Find the Attribute" Game ... 475 12.6.2 Using Inheritance ... 477 12.6.3 Example: The Standard Model ... 478 13 Program Development with Classes 487 13.1 Predator--Prey Problem ... 487 13.1.1 The Rules ... 488 13.1.2 Simulation Using Object-Oriented Programming ... 488 13.2 Classes ... 489 13.2.1 Island Class ... 489 13.2.2 Predator and Prey, Kinds of Animals ... 490 13.2.3 Predator and Prey Classes ... 493 13.2.4 Object Diagram ... 493 13.2.5 Filling the Island ... 493 13.3 Adding Behavior ... 495 13.3.1 Refinement: Add Movement ... 495 13.3.2 Refinement: Time Simulation Loop ... 497 13.4 Refinement: Eating, Breeding,and Keeping Time ... 498 13.4.1 Improved Time Loop ... 499 13.4.2 Breeding ... 501 13.4.3 Eating ... 502 13.4.4 The Tick of the Clock ... 503 13.5 Refinements ... 504 13.5.1 Refinement: How Many Times to Move? ... 504 13.5.2 Refinement: Graphing Population Size ... 505 V Being a better programmer 507 14 Files and Exceptions II 509 14.1 More Details on Files ... 509 14.1.1 Other File Access Methods, Reading ... 511 14.1.2 Other File Access Methods, Writing ... 512 14.1.3 Universal New Line Format ... 513 14.1.4 Moving Around in a File ... 514 14.1.5 Closing a File ... 515 14.1.6 The with Statement ... 516 14.2 CSV Files ... 517 14.2.1 CSV Module ... 518 14.2.2 CSV Reader ... 518 14.2.3 CSV Writer ... 519 14.2.4 Example: Update Some Grades ... 519 14.3 Module: os ... 521 14.3.1 Directory (Folder) Structure ... 521 14.3.2 os Module Functions ... 522 14.3.3 os Module Example ... 524 14.4 More on Exceptions ... 525 14.4.1 Basic Exception Handling ... 526 14.4.2 A Simple Example ... 527 14.4.3 Events ... 530 14.4.4 A Philosophy Concerning Exceptions ... 530 14.5 Exception: else and finally ... 531 14.5.1 finally and with ... 531 14.5.2 Example: Refactoring the Reprompting of a File Name ... 531 14.6 More on Exceptions ... 532 14.6.1 Raise ... 532 14.6.2 Create Your Own ... 534 14.7 Example: Password Manager ... 534 14.7.1 Programming Projects ... 540 15 Testing 541 15.1 Why Testing? ... 541 15.1.1 Kinds of Errors ... 541 15.1.2 "Bugs" and Debugging ... 542 15.2 Kinds of Testing ... 543 15.2.1 Testing is Hard! ... 544 15.2.2 Importance of Testing ... 544 15.3 Example Problem ... 544 15.3.1 NBA Efficiency ... 544 15.3.2 Basic Algorithm ... 545 15.4 Incorporating Testing ... 547 15.4.1 Catching User Errors ... 547 15.4.2 Catching Developer Errors ... 548 15.5 Automation of Testing ... 549 15.5.1 doctest ... 550 15.5.2 Other Kinds of Testing ... 552 15.5.3 Exercises ... 552 16 Recursion: Another Control Mechanism 553 16.1 What Is Recursion? ... 553 16.2 Mathematics and Rabbits ... 555 16.3 Let's Write Our Own: Reversing a String ... 557 16.4 How Does Recursion Actually Work? ... 559 16.4.1 Stack Data Structure ... 559 16.4.2 Stacks and Function Calls ... 561 16.5 Recursion in Figures ... 563 16.5.1 Recursive Tree ... 563 16.5.2 Sierpinski Triangles ... 564 16.6 Recursion to Non-recursion ... 565 17 Other Fun Stuff with Python 569 17.1 Function Stuff ... 569 17.1.1 Having a Varying Number of Parameters ... 569 17.1.2 Iterators and Generators ... 572 17.1.3 Other Functional Programming Ideas ... 575 17.1.4 Some Functional Tools: map , reduce , filter ... 576 17.1.5 Decorators, Functions calling Functions ... 577 17.2 Classes ... 581 17.2.1 Properties ... 582 17.2.2 Serializing an Instance, pickle ... 584 17.2.3 Random Numbers ... 586 17.3 Other Things in Python ... 588 17.3.1 Data Types ... 588 17.3.2 Built-in Modules ... 588 17.3.3 Modules on the Internet ... 589 A. Getting and Using Python 593 A.1 About Python ... 593 A.1.1 History ... 593 A.1.2 Python 3 ... 593 A.1.3 Python is Free and Portable ... 594 A.1.4 Starting Python Up ... 594 A.1.5 Working with Python ... 596 A.1.6 Making a Program ... 597 A.2 Some Conventions for This Book ... 602 A.2.1 Interactive Code ... 603 A.2.2 Program: Written Code ... 603 A.2.3 Combined Program and Output ... 603 A.3 Summary ... 604 B Simple Drawing with Turtle Graphics 605 B.0.1 What is a Turtle? ... 605 B.0.2 Motion ... 606 B.0.3 Drawing ... 607 B.0.4 Color ... 608 B.0.5 Drawing with Color ... 609 B.0.6 Other commands ... 611 B.1 Tidbits ... 612 B.1.1 Keeping the Window Open ... 612 B.1.2 Working Nicely With IDLE ... 613 C Plotting and Numeric Tools: A Quick Survey 615 C.1 Matplotlib ... 615 C.1.1 Getting matplotlib ... 615 C.2 Working with matplotlib ... 620 C.2.1 Plot Command ... 620 C.2.2 Plot Properties ... 621 C.2.3 Tick Labels ... 621 C.2.4 Bar Graphs ... 622 C.2.5 Histograms ... 622 C.2.6 Pie Charts ... 624 C.3 Numeric Python (Numpy) ... 625 C.3.1 Arrays Are Not Lists ... 625 C.3.2 Creating a numpy Array ... 625 C.3.3 Manipulating Arrays ... 625 D Table of UTF-8 One Byte Encodings 627 G Check Yourself Solutions 635 G.1 Chapter 1 ... 635 G.2 Chapter 2 ... 636 G.3 Chapter 4 ... 637 G.4 Chapter 5 ... 637 G.5 Chapter 6 ... 637 G.6 Chapter 7 ... 638 G.7 Chapter 8 ... 638 G.8 Chapter 9 ... 638 G.9 Chapter 11 ... 639 G.10 Chapter 12 ... 639 G.11 Chapter 14 ... 639

Szczegóły: The Practice of Computing Using Python - Richard Enbody, William Punch

Tytuł: The Practice of Computing Using Python
Autor: Richard Enbody, William Punch
Producent: Pearson
ISBN: 9781292025933
Rok produkcji: 2013
Ilość stron: 743
Oprawa: Miękka
Waga: 1.5 kg

Recenzje: The Practice of Computing Using Python - Richard Enbody, William Punch