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20 CHAPTER 2. STARTING OUT function we supply. A list produced by a comprehension that draws from two lists of length 4 will have a length of 16, provided we don’t filter them. If we have two lists, [2,5,10] and [8,10,11] and we want to get the products of all the possible combinations between numbers in those lists, here’s what we’d do. ghci > [ x*y | x let adjectives = [" lazy "," grouchy "," scheming "] ghci > [ adjective ++ " " ++ noun | adjective [ [ x | x
2.6. TUPLES 21 2.6 Tuples In some ways, tuples are like lists — they are a way to store several values into a single value. However, there are a few fundamental differences. A list of numbers is a list of numbers. That’s its type and it doesn’t matter if it has only one number in it or an infinite amount of numbers. Tuples, however, are used when you know exactly how many values you want to combine and its type depends on how many components it has and the types of the components. They are denoted with parentheses and their components are separated by commas. Another key difference is that they don’t have to be homogenous. Unlike a list, a tuple can contain a combination of several types. Think about how we’d represent a two-dimensional vector in Haskell. One way would be to use a list. That would kind of work. So what if we wanted to put a couple of vectors in a list to represent points of a shape on a twodimensional plane? We could do something like [[1,2],[8,11],[4,5]]. The problem with that method is that we could also do stuff like [[1,2],[8,11,5],[4,5]], which Haskell has no problem with since it’s still a list of lists with numbers but it kind of doesn’t make sense. But a tuple of size two (also called a pair) is its own type, which means that a list can’t have a couple of pairs in it and then a triple (a tuple of size three), so let’s use that instead. Instead of surrounding the vectors with square brackets, we use parentheses: [(1,2),(8,11),(4,5)]. What if we tried to make a shape like [(1,2),(8,11,5),(4,5)]? Well, we’d get this error: Couldn ’t match expected type ‘(t, t1)’ against inferred type ‘(t2 , t3 , t4)’ In the expression : (8 , 11 , 5) In the expression : [(1 , 2) , (8 , 11 , 5) , (4 , 5)] In the definition of ‘it ’: it = [(1 , 2) , (8 , 11 , 5) , (4 , 5)] It’s telling us that we tried to use a pair and a triple in the same list, which is not supposed to happen. You also couldn’t make a list like [(1,2),("One",2)] because the first element of the list is a pair of numbers and the second element is a pair consisting of a string and a number. Tuples can also be used to represent a wide variety of data. For instance, if we wanted to represent someone’s name and age in Haskell, we could use a triple: ("Christopher", "Walken", 55). As seen in this example, tuples can also contain lists. Use tuples when you know in advance how many components some piece of data should have. Tuples are much more rigid because each different size of tuple is its own type, so you can’t write a general function to append an element to a tuple — you’d have to write a function for appending to a pair, one function for appending to a triple, one function for appending to a 4-tuple, etc. While there are singleton lists, there’s no such thing as a singleton tuple. It doesn’t really make much sense when you think about it. A singleton tuple would just be the value it contains and as such would have no benefit to us.
Page 1 and 2: Learn You a Haskell for Great Good!
Page 3 and 4: Contents 1 Introduction 5 1.1 About
Page 5 and 6: Chapter 1 Introduction 1.1 About th
Page 7 and 8: 1.3. WHAT YOU NEED TO DIVE IN 7 sys
Page 9 and 10: Chapter 2 Starting Out 2.1 Ready, s
Page 11 and 12: 2.1. READY, SET, GO! 11 Functions a
Page 13 and 14: 2.3. AN INTRO TO LISTS 13 Now we’
Page 15 and 16: 2.3. AN INTRO TO LISTS 15 If you wa
Page 17 and 18: 2.4. TEXAS RANGES 17 maximum takes
Page 19: 2.5. I’M A LIST COMPREHENSION 19
Page 23 and 24: 2.6. TUPLES 23 add a condition that
Page 25 and 26: Chapter 3 Types and Typeclasses 3.1
Page 27 and 28: 3.2. TYPE VARIABLES 27 factorial ::
Page 29 and 30: 3.3. TYPECLASSES 101 29 ghci > 5 /=
Page 31 and 32: 3.3. TYPECLASSES 101 31 ghci > maxB
Page 33 and 34: Chapter 4 Syntax in Functions 4.1 P
Page 35 and 36: 4.1. PATTERN MATCHING 35 Well, that
Page 37 and 38: 4.2. GUARDS, GUARDS! 37 There’s a
Page 39 and 40: 4.3. WHERE!? 39 Ugh! Not very reada
Page 41 and 42: 4.4. LET IT BE 41 cylinder :: ( Rea
Page 43 and 44: 4.5. CASE EXPRESSIONS 43 case expre
Page 45 and 46: Chapter 5 Recursion 5.1 Hello recur
Page 47 and 48: 5.3. A FEW MORE RECURSIVE FUNCTIONS
Page 49 and 50: 5.4. QUICK, SORT! 49 elem ’ :: (E
Page 51 and 52: Chapter 6 Higher order functions Ha
Page 53 and 54: 6.2. SOME HIGHER-ORDERISM IS IN ORD
Page 55 and 56: 6.2. SOME HIGHER-ORDERISM IS IN ORD
Page 57 and 58: 6.3. MAPS AND FILTERS 57 " GAYBALLS
Page 59 and 60: 6.4. LAMBDAS 59 ghci > chain 30 [30
Page 61 and 62: 6.5. ONLY FOLDS AND HORSES 61 6.5 O
Page 63 and 64: 6.5. ONLY FOLDS AND HORSES 63 The s
Page 65 and 66: 6.7. FUNCTION COMPOSITION 65 ($) ::
Page 67 and 68: 6.7. FUNCTION COMPOSITION 67 fn x =
Page 69 and 70: Chapter 7 Modules 7.1 Loading modul
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7.2. DATA.LIST 71 To search for fun
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7.2. DATA.LIST 73 splitAt takes a n
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7.2. DATA.LIST 75 False ghci > " ca
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7.2. DATA.LIST 77 lines is a useful
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7.3. DATA.CHAR 79 From this, we cle
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7.3. DATA.CHAR 81 All these predica
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7.4. DATA.MAP 83 decode :: Int -> S
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7.4. DATA.MAP 85 It says that it ta
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7.5. DATA.SET 87 7.5 Data.Set The D
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7.6. MAKING OUR OWN MODULES 89 and
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7.6. MAKING OUR OWN MODULES 91 , ar
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Chapter 8 Making Our Own Types and
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8.1. ALGEBRAIC DATA TYPES INTRO 95
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8.2. RECORD SYNTAX 97 O-kay. The fi
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8.3. TYPE PARAMETERS 99 have an [In
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8.4. DERIVED INSTANCES 101 had a ty
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8.4. DERIVED INSTANCES 103 ghci > m
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8.5. TYPE SYNONYMS 105 ghci > Wedne
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8.5. TYPE SYNONYMS 107 Fonzie says:
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8.6. RECURSIVE DATA STRUCTURES 109
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8.6. RECURSIVE DATA STRUCTURES 111
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8.7. TYPECLASSES 102 113 | x > a =
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8.7. TYPECLASSES 102 115 We did it
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8.8. A YES-NO TYPECLASS 117 instanc
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8.9. THE FUNCTOR TYPECLASS 119 inst
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8.9. THE FUNCTOR TYPECLASS 121 In a
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8.10. KINDS AND SOME TYPE-FOO 123 8
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8.10. KINDS AND SOME TYPE-FOO 125 a
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Chapter 9 Input and Output We’ve
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9.1. HELLO, WORLD! 129 So, when wil
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9.1. HELLO, WORLD! 131 name. Rememb
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9.1. HELLO, WORLD! 133 skipped this
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9.1. HELLO, WORLD! 135 $ runhaskell
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9.1. HELLO, WORLD! 137 introduced.
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9.2. FILES AND STREAMS 139 I’m a
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9.2. FILES AND STREAMS 141 i’m sh
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9.2. FILES AND STREAMS 143 what we
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9.2. FILES AND STREAMS 145 contents
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9.2. FILES AND STREAMS 147 main = d
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9.2. FILES AND STREAMS 149 thing li
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9.3. COMMAND LINE ARGUMENTS 151 sec
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9.3. COMMAND LINE ARGUMENTS 153 han
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9.4. RANDOMNESS 155 ber, Haskell is
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9.4. RANDOMNESS 157 with the same g
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9.4. RANDOMNESS 159 characters and
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9.5. BYTESTRINGS 161 9.5 Bytestring
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9.5. BYTESTRINGS 163 chunk even if
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Chapter 10 Functionally Solving Pro
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10.1. REVERSE POLISH NOTATION CALCU
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10.2. HEATHROW TO LONDON 169 natura
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10.2. HEATHROW TO LONDON 171 Now we
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10.2. HEATHROW TO LONDON 173 use Se
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10.2. HEATHROW TO LONDON 175 the ne
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