How to Think Like a Computer Scientist - Learning with Python, 2008a

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Chapter 14 Classes and methods 14.1 Object-oriented features Python is an object-oriented programming language, which means that it provides features that support object-oriented programming. It is not easy to define object-oriented programming, but we have already seen some of its characteristics: • Programs are made up of object definitions and function definitions, and most of the computation is expressed in terms of operations on objects. • Each object definition corresponds to some object or concept in the real world, and the functions that operate on that object correspond to the ways real-world objects interact. For example, the Time class defined in Chapter 13 corresponds to the way people record the time of day, and the functions we defined correspond to the kinds of things people do with times. Similarly, the Point and Rectangle classes correspond to the mathematical concepts of a point and a rectangle. So far, we have not taken advantage of the features Python provides to support object-oriented programming. Strictly speaking, these features are not necessary. For the most part, they provide an alternative syntax for things we have already done, but in many cases, the alternative is more concise and more accurately conveys the structure of the program. For example, in the Time program, there is no obvious connection between the class definition and the function definitions that follow. With some examination, it is apparent that every function takes at least one Time object as an argument.
148 Classes and methods This observation is the motivation for methods. We have already seen some methods, such as keys and values, which were invoked on dictionaries. Each method is associated with a class and is intended to be invoked on instances of that class. Methods are just like functions, with two differences: • Methods are defined inside a class definition in order to make the relationship between the class and the method explicit. • The syntax for invoking a method is different from the syntax for calling a function. In the next few sections, we will take the functions from the previous two chapters and transform them into methods. This transformation is purely mechanical; you can do it simply by following a sequence of steps. If you are comfortable converting from one form to another, you will be able to choose the best form for whatever you are doing. 14.2 printTime In Chapter 13, we defined a class named Time and you wrote a function named printTime, which should have looked something like this: class Time: pass def printTime(time): print str(time.hours) + ":" + \ str(time.minutes) + ":" + \ str(time.seconds) To call this function, we passed a Time object as an argument: >>> currentTime = Time() >>> currentTime.hours = 9 >>> currentTime.minutes = 14 >>> currentTime.seconds = 30 >>> printTime(currentTime) To make printTime a method, all we have to do is move the function definition inside the class definition. Notice the change in indentation.
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How to Think Like a Computer Scient
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How to Think Like a Computer Scient
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Foreword By David Beazley As an edu
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Preface By Jeff Elkner This book ow
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make instant changes whenever someo
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call (type) out its name.” Parame
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Contributor List To paraphrase the
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• Paul Sleigh found an error in C
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xvii • Roger Sperberg pointed out
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Contents Foreword v Preface vii Con
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Contents xxi 4.7 Nested conditional
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Contents xxiii 8.15 Matrices . . .
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Contents xxv 14.4 A more complicate
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Contents xxvii 19.4 Improved Linked
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Chapter 1 The way of the program Th
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1.2 What is a program? 3 $ python P
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1.3 What is debugging? 5 1.3.2 Runt
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1.4 Formal and natural languages 7
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1.6 Glossary 9 source code: A progr
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Chapter 2 Variables, expressions an
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2.3 Variable names and keywords 13
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2.4 Statements 15 >>> 76trombones =
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2.6 Operators and operands 17 2.6 O
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2.9 Composition 19 On one hand, thi
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2.11 Glossary 21 state diagram: A g
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Chapter 3 Functions 3.1 Function ca
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3.4 Math functions 25 >>> minute =
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3.6 Adding new functions 27 problem
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3.7 Definitions and use 29 3.7 Defi
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3.10 Variables and parameters are l
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3.12 Functions with results 33 The
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3.13 Glossary 35 local variable: A
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Chapter 4 Conditionals and recursio
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4.4 Conditional execution 39 In gen
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4.7 Nested conditionals 41 Each con
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4.9 Recursion 43 countdown expects
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4.11 Infinite recursion 45 4.11 Inf
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4.13 Glossary 47 block: A group of
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Chapter 5 Fruitful functions 5.1 Re
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5.2 Program development 51 avoid lo
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5.3 Composition 53 3. Once the prog
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5.5 More recursion 55 But the extra
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5.6 Leap of faith 57 __main__ facto
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5.8 Checking types 59 >>> factorial
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Chapter 6 Iteration 6.1 Multiple as
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6.2 The while statement 63 1. Evalu
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6.3 Tables 65 1.0 0.0 2.0 0.6931471
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6.5 Encapsulation and generalizatio
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6.7 Local variables 69 6.7 Local va
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6.9 Functions 71 the function is ca
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Chapter 7 Strings 7.1 A compound da
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7.3 Traversal and the for loop 75 T
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7.6 Strings are immutable 77 Other
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7.9 The string module 79 As an exer
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7.11 Glossary 81 There are other us
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Chapter 8 Lists A list is an ordere
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8.3 List length 85 If you try to re
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8.6 List operations 87 for VARIABLE
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8.9 List deletion 89 >>> list = [
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8.10 Objects and values 91 8.10 Obj
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8.13 List parameters 93 >>> b[0] =
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8.16 Strings and lists 95 might be
Page 126 and 127: Chapter 9 Tuples 9.1 Mutability and
Page 128 and 129: 9.3 Tuples as return values 99 9.3
Page 130 and 131: 9.6 Counting 101 >>> randomList(8)
Page 132 and 133: 9.7 Many buckets 103 bucketWidth =
Page 134 and 135: 9.9 Glossary 105 9.9 Glossary Assig
Page 136 and 137: Chapter 10 Dictionaries The compoun
Page 138 and 139: 10.2 Dictionary methods 109 10.2 Di
Page 140 and 141: 10.5 Hints 111 An alternative is to
Page 142 and 143: 10.6 Long integers 113 Using this v
Page 144 and 145: 10.8 Glossary 115 overflow: A numer
Page 146 and 147: Chapter 11 Files and exceptions Whi
Page 148 and 149: 11.1 Text files 119 The following f
Page 150 and 151: 11.2 Writing variables 121 the str
Page 152 and 153: 11.3 Directories 123 11.3 Directori
Page 154 and 155: 11.5 Exceptions 125 Or trying to op
Page 156 and 157: 11.6 Glossary 127 format sequence:
Page 158 and 159: Chapter 12 Classes and objects 12.1
Page 160 and 161: 12.3 Instances as arguments 131 con
Page 162 and 163: 12.5 Rectangles 133 >>> p1 = Point(
Page 164 and 165: 12.8 Copying 135 The variables dwid
Page 166 and 167: 12.9 Glossary 137 12.9 Glossary cla
Page 168 and 169: Chapter 13 Classes and functions 13
Page 170 and 171: 13.3 Modifiers 141 The output of th
Page 172 and 173: 13.5 Prototype development versus p
Page 174 and 175: 13.8 Glossary 145 Similarly, the te
Page 178 and 179: 14.3 Another example 149 class Time
Page 180 and 181: 14.5 Optional arguments 151 if done
Page 182 and 183: 14.7 Points revisited 153 >>> curre
Page 184 and 185: 14.9 Polymorphism 155 def __mul__(s
Page 186 and 187: 14.10 Glossary 157 Of course, we in
Page 188 and 189: Chapter 15 Sets of objects 15.1 Com
Page 190 and 191: 15.3 Class attributes and the str m
Page 192 and 193: 15.5 Decks 163 def __cmp__(self, ot
Page 194 and 195: 15.7 Shuffling the deck 165 >>> dec
Page 196 and 197: 15.9 Glossary 167 class Deck: ... d
Page 198 and 199: Chapter 16 Inheritance 16.1 Inherit
Page 200 and 201: 16.3 Dealing cards 171 16.3 Dealing
Page 202 and 203: 16.6 OldMaidHand class 173 class Ca
Page 204 and 205: 16.7 OldMaidGame class 175 Hand fra
Page 206 and 207: 16.7 OldMaidGame class 177 class Ol
Page 208 and 209: 16.8 Glossary 179 Hand Allen picked
Page 210 and 211: Chapter 17 Linked lists 17.1 Embedd
Page 212 and 213: 17.3 Lists as collections 183 node1
Page 214 and 215: 17.5 Infinite lists 185 We invoke t
Page 216 and 217: 17.8 Wrappers and helpers 187 def r
Page 218 and 219: 17.10 Invariants 189 tail = self.ne
Page 220 and 221: Chapter 18 Stacks 18.1 Abstract dat
Page 222 and 223: 18.4 Pushing and popping 193 def po
Page 224 and 225: 18.7 Evaluating postfix 195 Python
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18.9 Glossary 197 18.9 Glossary abs
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Chapter 19 Queues This chapter pres
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19.3 Performance characteristics 20
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19.5 Priority queue 203 and it is m
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19.6 The Golfer class 205 19.6 The
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Chapter 20 Trees Like linked lists,
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20.2 Traversing trees 209 20.2 Trav
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20.4 Tree traversal 211 def printTr
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20.5 Building an expression tree 21
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20.5 Building an expression tree 21
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20.7 The animal tree 217 Are you th
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20.8 Glossary 219 def yes(ques): fr
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Appendix A Debugging Different kind
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A.2 Runtime errors 223 A.1.1 I can
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A.2 Runtime errors 225 If there is
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A.3 Semantic errors 227 A.3 Semanti
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A.3 Semantic errors 229 return self
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Appendix B Creating a new data type
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B.1 Fraction multiplication 233 >>>
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B.4 Comparing fractions 235 This re
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B.6 Glossary 237 reduce: To change
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Appendix C Recommendations for furt
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C.2 Recommended general computer sc
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Index Make Way for Ducklings, 75 Py
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Index 245 element, 83, 96 embedded
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Index 247 well-formed, 189 list del
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Index 249 redundancy, 7 reference,
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