Think Python - Denison University

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Copyright©2008 AllenDowney.Printinghistory:April 2002: Firsteditionof How toThink LikeaComputer Scientist.August 2007: Majorrevision, changed titleto How toThinkLike a(Python) Programmer.June2008: Major revision,changed titleto Think Python: How toThinkLike aComputer Scientist.Green Tea Press9Washburn AveNeedham MA02492Permission is granted to copy, distribute, and/or modify this document under the terms of the GNU Free DocumentationLicense, Version 1.1 or any later version published by the Free Software Foundation; with noInvariant Sections,no Front-CoverTexts,and withno Back-Cover Texts.The GNU Free Documentation License is available from www.gnu.org or by writing to the Free SoftwareFoundation, Inc., 59Temple Place, Suite330, Boston,MA02111-1307, USA.The original form of this book is LATEX source code. Compiling this LATEX source has the effect of generatingadevice-independent representation of atextbook, whichcan be converted toother formatsand printed.TheLATEX sourcefor thisbook isavailable fromhttp://www.thinkpython.com
PrefaceThe strangehistoryof thisbookIn January 1999 I was preparing to teach an introductory programming class in Java. I had taughtit three times and I was getting frustrated. The failure rate in the class was too high and, even forstudents who succeeded, the overall level of achievement was too low.OneoftheproblemsIsawwasthebooks. Theyweretoobig,withtoomuchunnecessarydetailaboutJava,andnotenoughhigh-levelguidanceabouthowtoprogram. Andtheyallsufferedfromthetrapdooreffect: theywouldstartouteasy,proceedgradually,andthensomewherearoundChapter5thebottom would fall out. The students would get too much new material, too fast, and I would spendtherest ofthe semester picking up thepieces.Two weeks before thefirst day of classes,Idecided towritemy own book. Mygoals were:• Keep itshort. Itisbetter for students toread 10 pages than not read 50 pages.• Be careful withvocabulary. I triedtominimize the jargon and define each termat firstuse.• Build gradually. To avoid trap doors, I took the most difficult topics and split them into aseries ofsmall steps.• Focusonprogramming,nottheprogramminglanguage. Iincludedtheminimumusefulsubsetof Java and left out the rest.Ineeded atitle,soon awhim I chose How toThink Like aComputer Scientist.My first version was rough, but it worked. Students did the reading, and they understood enoughthat I could spend class time on the hard topics, the interesting topics and (most important) lettingthestudents practice.IreleasedthebookundertheGNUFreeDocumentationLicense,whichallowsuserstocopy,modify,and distributethebook.Whathappenednextisthecoolpart. JeffElkner,ahighschoolteacherinVirginia,adoptedmybookandtranslateditintoPython. Hesentmeacopyofhistranslation,andIhadtheunusualexperienceof learning Python by reading myown book.Jeff and I revised the book, incorporated a case study by Chris Meyers, and in 2001 we releasedHow to Think Like a Computer Scientist: Learning with Python, also under the GNU Free DocumentationLicense. As Green Tea Press, I published the book and started selling hard copiesthrough Amazon.com and college book stores. Other books from Green Tea Press are available atgreenteapress.com.
Page 1: Think PythonHowto Think LikeaComput
Page 6 and 7: viChapter 0. PrefaceIn 2003 I start
Page 8 and 9: viiiChapter 0. Preface• Keith Ver
Page 10 and 11: xChapter 0. Preface• Patryk Wolow
Page 12 and 13: xiiContents3 Functions 173.1 Functi
Page 14 and 15: xivContents7 Iteration 637.1 Multip
Page 16 and 17: xviContents12 Tuples 11512.1 Tuples
Page 18 and 19: xviiiContents17 Classes and methods
Page 20 and 21: xxContents
Page 22: 2 Chapter 1. The way of theprogramp
Page 25 and 26: 1.4. Formal and natural languages 5
Page 27 and 28: 1.7. Glossary 7Your job is to be a
Page 29 and 30: Chapter 2Variables,expressions ands
Page 31 and 32: 2.3. Variable names and keywords 11
Page 33 and 34: 2.6. Expressions 132.6 ExpressionsA
Page 35 and 36: 2.10. Debugging 152.10 DebuggingAtt
Page 37 and 38: Chapter 3Functions3.1 Functioncalls
Page 39 and 40: 3.4. Composition 19>>> math.sqrt(2)
Page 41 and 42: 3.7. Flow of execution 21def repeat
Page 43 and 44: 3.10. Stack diagrams 23Thisfunction
Page 45 and 46: 3.12. Why functions? 253.12 Whyfunc
Page 47 and 48: 3.15. Exercises 27Here’s an examp
Page 49 and 50: Chapter 4Case study: interfacedesig
Page 51 and 52: 4.3. Exercises 31The syntax of a fo
Page 53 and 54: 4.6. Interface design 33This draws
Page 55 and 56:
4.8. A development plan 354.8 Adeve
Page 57 and 58:
4.12. Exercises 37Exercise 4.2 Writ
Page 59 and 60:
Chapter 5Conditionals and recursion
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5.5. Alternative execution 41if sta
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5.9. Stack diagrams for recursive f
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5.11. Keyboard input 455.11 Keyboar
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5.14. Exercises 47relational operat
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5.14. Exercises 492. Write a functi
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Chapter 6Fruitfulfunctions6.1 Retur
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6.2. Incremental development 53>>>
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6.5. More recursion 55It is common
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6.6. Leap of faith 57__main__factor
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6.9. Debugging 59The first base cas
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6.11. Exercises 61sum = x + y + zpo
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Chapter 7Iteration7.1 Multipleassig
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7.4. break 652. Iftheconditionisfal
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7.6. Algorithms 672.00001024003>>>
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7.9. Exercises 69decrement: An upda
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Chapter 8Strings8.1 Astringis a seq
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8.4. String slices 73Thefollowingex
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8.7. Looping and counting 75This is
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8.10. String comparison 778.10 Stri
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8.12. Glossary 798.12 Glossaryobjec
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Chapter 9Case study: word play9.1 R
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9.3. Search 83Exercise 9.6 Write a
Page 105 and 106:
9.5. Debugging 85Here is a version
Page 107 and 108:
9.7. Exercises 87Write a Python pro
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Chapter 10Lists10.1 Alist isasequen
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10.3. Traversing alist 9110.3 Trave
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10.7. Map, filter and reduce 93List
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10.9. Listsand strings 95>>> t = ['
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10.12. Listarguments 97The statedia
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10.14. Glossary 99word = word.strip
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10.15. Exercises 101Exercise 10.6 W
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Chapter 11DictionariesAdictionaryis
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11.1. Dictionary as asetof counters
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11.4. Dictionaries and lists 107Thi
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11.5. Memos 109corresponding locati
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11.7. Long integers 111count = 0def
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11.10. Exercises 113implementation:
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Chapter 12Tuples12.1 Tuples areimmu
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12.3. Tuples as return values 117>>
Page 139 and 140:
12.6. Dictionaries and tuples 119If
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12.7. Comparing tuples 12112.7 Comp
Page 143 and 144:
12.10. Glossary 123>>> t3 = [1, 2,
Page 145 and 146:
Chapter 13Case study: data structur
Page 147 and 148:
13.3. Word histogram 12713.3 Word h
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13.6. Dictionary subtraction 129num
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13.9. Datastructures 131In this tex
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13.11. Glossary 133reading: Examine
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Chapter 14Files14.1 PersistenceMost
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14.4. Filenames and paths 137>>> '%
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14.6. Databases 139Python starts by
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14.9. Writingmodules 141The argumen
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14.11. Glossary 14314.11 Glossarype
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Chapter 15Classes and objects15.1 U
Page 167 and 168:
15.3. Rectangles 147>>> print '(%g,
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15.6. Copying 149>>> print box.widt
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15.8. Glossary 151>>> hasattr(p, 'x
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Chapter 16Classes and functions16.1
Page 175 and 176:
16.3. Modifiers 155if sum.second >=
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16.5. Debugging 157But if we have t
Page 179 and 180:
Chapter 17Classes and methods17.1 O
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17.3. Another example 161Inside the
Page 183 and 184:
17.6. The str method 163>>> time =
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17.9. Polymorphism 165Unfortunately
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17.12. Exercises 167object-oriented
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Chapter 18InheritanceIn this chapte
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18.3. Comparing cards 171Thefirstel
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18.6. Add, remove, shuffle and sort
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18.8. Classdiagrams 175So when you
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18.10. Glossary 177might get the on
Page 199 and 200:
18.11. Exercises 1796. Print a tabl
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Chapter 19Case study: Tkinter19.1 G
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19.3. Canvas widgets 183Exercise 19
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19.6. Packing widgets 185>>> text.i
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19.6. Packing widgets 187self.bu(te
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19.8. Binding 18919.8 BindingAbindi
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19.9. Debugging 19119.9 DebuggingOn
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19.11. Exercises 193image = PIL.ope
Page 215 and 216:
Appendix ADebuggingDifferentkindsof
Page 217 and 218:
A.2. Runtime errors 197A.2 Runtime
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A.3. Semantic errors 199• You are
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A.3. Semantic errors 201The explici
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Indexabecedarian, 72, 83abs functio
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Index 205experimental, 4superstitio
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Index 207raw input, 45recursive, 43
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Index 209map pattern, 93, 100map to
Page 231 and 232:
Index 211poker, 169, 178polygon fun
Page 233 and 234:
Index 213knowing the answer, 53leap
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Think Python - Denison University

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