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

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Chapter 18 Stacks 18.1 Abstract data types The data types you have seen so far are all concrete, in the sense that we have completely specified how they are implemented. For example, the Card class represents a card using two integers. As we discussed at the time, that is not the only way to represent a card; there are many alternative implementations. An abstract data type, or ADT, specifies a set of operations (or methods) and the semantics of the operations (what they do), but it does not specify the implementation of the operations. That’s what makes it abstract. Whyisthatuseful? • It simplifies the task of specifying an algorithm if you can denote the operations you need without having to think at the same time about how the operations are performed. • Since there are usually many ways to implement an ADT, it might be useful to write an algorithm that can be used with any of the possible implementations. • Well-known ADTs, such as the Stack ADT in this chapter, are often implemented in standard libraries so they can be written once and used by many programmers. • The operations on ADTs provide a common high-level language for specifying and talking about algorithms.
192 Stacks When we talk about ADTs, we often distinguish the code that uses the ADT, called the client code, from the code that implements the ADT, called the provider code. 18.2 The Stack ADT In this chapter, we will look at one common ADT, the stack. A stack is a collection, meaning that it is a data structure that contains multiple elements. Other collections we have seen include dictionaries and lists. An ADT is defined by the operations that can be performed on it, which is called an interface. The interface for a stack consists of these operations: init : Initialize a new empty stack. push: Addanewitemtothestack. pop: Remove and return an item from the stack. The item that is returned is always the last one that was added. isEmpty: Check whether the stack is empty. A stack is sometimes called a “last in, first out” or LIFO data structure, because the last item added is the first to be removed. 18.3 Implementing stacks with Python lists The list operations that Python provides are similar to the operations that define a stack. The interface isn’t exactly what it is supposed to be, but we can write code to translate from the Stack ADT to the built-in operations. This code is called an implementation of the Stack ADT. In general, an implementation is a set of methods that satisfy the syntactic and semantic requirements of an interface. Here is an implementation of the Stack ADT that uses a Python list: class Stack : def __init__(self) : self.items = [] def push(self, item) : self.items.append(item)
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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
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Chapter 9 Tuples 9.1 Mutability and
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9.3 Tuples as return values 99 9.3
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9.6 Counting 101 >>> randomList(8)
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9.7 Many buckets 103 bucketWidth =
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9.9 Glossary 105 9.9 Glossary Assig
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Chapter 10 Dictionaries The compoun
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10.2 Dictionary methods 109 10.2 Di
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10.5 Hints 111 An alternative is to
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10.6 Long integers 113 Using this v
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10.8 Glossary 115 overflow: A numer
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Chapter 11 Files and exceptions Whi
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11.1 Text files 119 The following f
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11.2 Writing variables 121 the str
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11.3 Directories 123 11.3 Directori
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11.5 Exceptions 125 Or trying to op
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11.6 Glossary 127 format sequence:
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Chapter 12 Classes and objects 12.1
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12.3 Instances as arguments 131 con
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12.5 Rectangles 133 >>> p1 = Point(
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12.8 Copying 135 The variables dwid
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12.9 Glossary 137 12.9 Glossary cla
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Chapter 13 Classes and functions 13
Page 170 and 171: 13.3 Modifiers 141 The output of th
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Page 174 and 175: 13.8 Glossary 145 Similarly, the te
Page 176 and 177: Chapter 14 Classes and methods 14.1
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
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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 222 and 223: 18.4 Pushing and popping 193 def po
Page 224 and 225: 18.7 Evaluating postfix 195 Python
Page 226 and 227: 18.9 Glossary 197 18.9 Glossary abs
Page 228 and 229: Chapter 19 Queues This chapter pres
Page 230 and 231: 19.3 Performance characteristics 20
Page 232 and 233: 19.5 Priority queue 203 and it is m
Page 234 and 235: 19.6 The Golfer class 205 19.6 The
Page 236 and 237: Chapter 20 Trees Like linked lists,
Page 238 and 239: 20.2 Traversing trees 209 20.2 Trav
Page 240 and 241: 20.4 Tree traversal 211 def printTr
Page 242 and 243: 20.5 Building an expression tree 21
Page 244 and 245: 20.5 Building an expression tree 21
Page 246 and 247: 20.7 The animal tree 217 Are you th
Page 248 and 249: 20.8 Glossary 219 def yes(ques): fr
Page 250 and 251: Appendix A Debugging Different kind
Page 252 and 253: A.2 Runtime errors 223 A.1.1 I can
Page 254 and 255: A.2 Runtime errors 225 If there is
Page 256 and 257: A.3 Semantic errors 227 A.3 Semanti
Page 258 and 259: A.3 Semantic errors 229 return self
Page 260 and 261: Appendix B Creating a new data type
Page 262 and 263: B.1 Fraction multiplication 233 >>>
Page 264 and 265: B.4 Comparing fractions 235 This re
Page 266 and 267: B.6 Glossary 237 reduce: To change
Page 268 and 269: 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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