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

More documents

Recommendations

Info

1.3 What is debugging? 5 1.3.2 Runtime errors The second type of error is a runtime error, so called because the error does not appear until you run the program. These errors are also called exceptions because they usually indicate that something exceptional (and bad) has happened. Runtime errors are rare in the simple programs you will see in the first few chapters, so it might be a while before you encounter one. 1.3.3 Semantic errors The third type of error is the semantic error. If there is a semantic error in your program, it will run successfully, in the sense that the computer will not generate any error messages, but it will not do the right thing. It will do something else. Specifically, it will do what you told it to do. The problem is that the program you wrote is not the program you wanted to write. The meaning of the program (its semantics) is wrong. Identifying semantic errors can be tricky because it requires you to work backward by looking at the output of the program and trying to figure out what it is doing. 1.3.4 Experimental debugging One of the most important skills you will acquire is debugging. Although it can be frustrating, debugging is one of the most intellectually rich, challenging, and interesting parts of programming. In some ways, debugging is like detective work. You are confronted with clues, and you have to infer the processes and events that led to the results you see. Debugging is also like an experimental science. Once you have an idea what is going wrong, you modify your program and try again. If your hypothesis was correct, then you can predict the result of the modification, and you take a step closer to a working program. If your hypothesis was wrong, you have to come up with a new one. As Sherlock Holmes pointed out, “When you have eliminated the impossible, whatever remains, however improbable, must be the truth.” (A. Conan Doyle, The Sign of Four) For some people, programming and debugging are the same thing. That is, programming is the process of gradually debugging a program until it does what you want. The idea is that you should start with a program that does something and make small modifications, debugging them as you go, so that you always have a working program.
6 The way of the program For example, Linux is an operating system that contains thousands of lines of code, but it started out as a simple program Linus Torvalds used to explore the Intel 80386 chip. According to Larry Greenfield, “One of Linus’s earlier projects was a program that would switch between printing AAAA and BBBB. This later evolved to Linux.” (The Linux Users’ Guide Beta Version 1) Later chapters will make more suggestions about debugging and other programming practices. 1.4 Formal and natural languages Natural languages are the languages that people speak, such as English, Spanish, and French. They were not designed by people (although people try to impose some order on them); they evolved naturally. Formal languages are languages that are designed by people for specific applications. For example, the notation that mathematicians use is a formal language that is particularly good at denoting relationships among numbers and symbols. Chemists use a formal language to represent the chemical structure of molecules. And most importantly: Programming languages are formal languages that have been designed to express computations. Formal languages tend to have strict rules about syntax. For example, 3 + 3 = 6 is a syntactically correct mathematical statement, but 3=+6$ is not. H 2 O is a syntactically correct chemical name, but 2 Zz is not. Syntax rules come in two flavors, pertaining to tokens and structure. Tokens are the basic elements of the language, such as words, numbers, and chemical elements. One of the problems with 3=+6$ is that $ is not a legal token in mathematics (at least as far as we know). Similarly, 2 Zz is not legal because there is no element with the abbreviation Zz. The second type of syntax error pertains to the structure of a statement—that is, the way the tokens are arranged. The statement 3=+6$ is structurally illegal because you can’t place a plus sign immediately after an equal sign. Similarly, molecular formulas have to have subscripts after the element name, not before. As an exercise, create what appears to be a well-structured English sentence with unrecognizable tokens in it. Then write another sentence with all valid tokens but with invalid structure.
Page 2 and 3: How to Think Like a Computer Scient
Page 4 and 5: How to Think Like a Computer Scient
Page 6 and 7: Foreword By David Beazley As an edu
Page 8 and 9: Preface By Jeff Elkner This book ow
Page 10 and 11: make instant changes whenever someo
Page 12 and 13: call (type) out its name.” Parame
Page 14 and 15: Contributor List To paraphrase the
Page 16 and 17: • Paul Sleigh found an error in C
Page 18 and 19: xvii • Roger Sperberg pointed out
Page 20 and 21: Contents Foreword v Preface vii Con
Page 22 and 23: Contents xxi 4.7 Nested conditional
Page 24 and 25: Contents xxiii 8.15 Matrices . . .
Page 26 and 27: Contents xxv 14.4 A more complicate
Page 28 and 29: Contents xxvii 19.4 Improved Linked
Page 30 and 31: Chapter 1 The way of the program Th
Page 32 and 33: 1.2 What is a program? 3 $ python P
Page 36 and 37: 1.4 Formal and natural languages 7
Page 38 and 39: 1.6 Glossary 9 source code: A progr
Page 40 and 41: Chapter 2 Variables, expressions an
Page 42 and 43: 2.3 Variable names and keywords 13
Page 44 and 45: 2.4 Statements 15 >>> 76trombones =
Page 46 and 47: 2.6 Operators and operands 17 2.6 O
Page 48 and 49: 2.9 Composition 19 On one hand, thi
Page 50 and 51: 2.11 Glossary 21 state diagram: A g
Page 52 and 53: Chapter 3 Functions 3.1 Function ca
Page 54 and 55: 3.4 Math functions 25 >>> minute =
Page 56 and 57: 3.6 Adding new functions 27 problem
Page 58 and 59: 3.7 Definitions and use 29 3.7 Defi
Page 60 and 61: 3.10 Variables and parameters are l
Page 62 and 63: 3.12 Functions with results 33 The
Page 64 and 65: 3.13 Glossary 35 local variable: A
Page 66 and 67: Chapter 4 Conditionals and recursio
Page 68 and 69: 4.4 Conditional execution 39 In gen
Page 70 and 71: 4.7 Nested conditionals 41 Each con
Page 72 and 73: 4.9 Recursion 43 countdown expects
Page 74 and 75: 4.11 Infinite recursion 45 4.11 Inf
Page 76 and 77: 4.13 Glossary 47 block: A group of
Page 78 and 79: Chapter 5 Fruitful functions 5.1 Re
Page 80 and 81: 5.2 Program development 51 avoid lo
Page 82 and 83: 5.3 Composition 53 3. Once the prog
Page 84 and 85:
5.5 More recursion 55 But the extra
Page 86 and 87:
5.6 Leap of faith 57 __main__ facto
Page 88 and 89:
5.8 Checking types 59 >>> factorial
Page 90 and 91:
Chapter 6 Iteration 6.1 Multiple as
Page 92 and 93:
6.2 The while statement 63 1. Evalu
Page 94 and 95:
6.3 Tables 65 1.0 0.0 2.0 0.6931471
Page 96 and 97:
6.5 Encapsulation and generalizatio
Page 98 and 99:
6.7 Local variables 69 6.7 Local va
Page 100 and 101:
6.9 Functions 71 the function is ca
Page 102 and 103:
Chapter 7 Strings 7.1 A compound da
Page 104 and 105:
7.3 Traversal and the for loop 75 T
Page 106 and 107:
7.6 Strings are immutable 77 Other
Page 108 and 109:
7.9 The string module 79 As an exer
Page 110 and 111:
7.11 Glossary 81 There are other us
Page 112 and 113:
Chapter 8 Lists A list is an ordere
Page 114 and 115:
8.3 List length 85 If you try to re
Page 116 and 117:
8.6 List operations 87 for VARIABLE
Page 118 and 119:
8.9 List deletion 89 >>> list = [
Page 120 and 121:
8.10 Objects and values 91 8.10 Obj
Page 122 and 123:
8.13 List parameters 93 >>> b[0] =
Page 124 and 125:
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 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
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
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
Page 270 and 271:
C.2 Recommended general computer sc
Page 272 and 273:
Index Make Way for Ducklings, 75 Py
Page 274 and 275:
Index 245 element, 83, 96 embedded
Page 276 and 277:
Index 247 well-formed, 189 list del
Page 278 and 279:
Index 249 redundancy, 7 reference,
show all

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

Create successful ePaper yourself

Delete template?

Save as template?