annotate Doc/tutorial/datastructures.rst @ 60008:0dfd62076ded

Blocked revisions 79402,79406 via svnmerge ........ r79402 | benjamin.peterson | 2010-03-24 20:03:51 -0500 (Wed, 24 Mar 2010) | 1 line set bsddb eol style ........ r79406 | benjamin.peterson | 2010-03-24 20:05:57 -0500 (Wed, 24 Mar 2010) | 1 line fix eol properties on capsule files ........
author Benjamin Peterson <benjamin@python.org>
date Thu, 25 Mar 2010 01:11:10 +0000
parents 575ec773dda4
children fd5c0ea2870b
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1 .. _tut-structures:
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2
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3 ***************
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4 Data Structures
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5 ***************
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6
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7 This chapter describes some things you've learned about already in more detail,
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8 and adds some new things as well.
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9
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10 .. _tut-morelists:
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11
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12 More on Lists
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13 =============
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14
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15 The list data type has some more methods. Here are all of the methods of list
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16 objects:
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19 .. method:: list.append(x)
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20 :noindex:
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22 Add an item to the end of the list; equivalent to ``a[len(a):] = [x]``.
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25 .. method:: list.extend(L)
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28 Extend the list by appending all the items in the given list; equivalent to
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29 ``a[len(a):] = L``.
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32 .. method:: list.insert(i, x)
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33 :noindex:
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35 Insert an item at a given position. The first argument is the index of the
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36 element before which to insert, so ``a.insert(0, x)`` inserts at the front of
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37 the list, and ``a.insert(len(a), x)`` is equivalent to ``a.append(x)``.
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40 .. method:: list.remove(x)
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43 Remove the first item from the list whose value is *x*. It is an error if there
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44 is no such item.
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47 .. method:: list.pop([i])
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50 Remove the item at the given position in the list, and return it. If no index
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51 is specified, ``a.pop()`` removes and returns the last item in the list. (The
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52 square brackets around the *i* in the method signature denote that the parameter
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53 is optional, not that you should type square brackets at that position. You
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54 will see this notation frequently in the Python Library Reference.)
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57 .. method:: list.index(x)
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60 Return the index in the list of the first item whose value is *x*. It is an
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61 error if there is no such item.
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64 .. method:: list.count(x)
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65 :noindex:
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67 Return the number of times *x* appears in the list.
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70 .. method:: list.sort()
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71 :noindex:
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73 Sort the items of the list, in place.
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76 .. method:: list.reverse()
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77 :noindex:
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79 Reverse the elements of the list, in place.
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80
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81 An example that uses most of the list methods::
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82
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83 >>> a = [66.25, 333, 333, 1, 1234.5]
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84 >>> print(a.count(333), a.count(66.25), a.count('x'))
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85 2 1 0
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86 >>> a.insert(2, -1)
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87 >>> a.append(333)
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88 >>> a
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89 [66.25, 333, -1, 333, 1, 1234.5, 333]
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90 >>> a.index(333)
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91 1
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92 >>> a.remove(333)
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93 >>> a
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94 [66.25, -1, 333, 1, 1234.5, 333]
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95 >>> a.reverse()
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96 >>> a
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97 [333, 1234.5, 1, 333, -1, 66.25]
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98 >>> a.sort()
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99 >>> a
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100 [-1, 1, 66.25, 333, 333, 1234.5]
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101
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102
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103 .. _tut-lists-as-stacks:
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104
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105 Using Lists as Stacks
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106 ---------------------
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107
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108 .. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
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109
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110
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111 The list methods make it very easy to use a list as a stack, where the last
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112 element added is the first element retrieved ("last-in, first-out"). To add an
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113 item to the top of the stack, use :meth:`append`. To retrieve an item from the
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114 top of the stack, use :meth:`pop` without an explicit index. For example::
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115
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116 >>> stack = [3, 4, 5]
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117 >>> stack.append(6)
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118 >>> stack.append(7)
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119 >>> stack
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120 [3, 4, 5, 6, 7]
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121 >>> stack.pop()
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122 7
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123 >>> stack
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124 [3, 4, 5, 6]
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125 >>> stack.pop()
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126 6
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127 >>> stack.pop()
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128 5
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129 >>> stack
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130 [3, 4]
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131
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132
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133 .. _tut-lists-as-queues:
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134
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135 Using Lists as Queues
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136 ---------------------
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137
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138 .. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
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139
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140
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141 You can also use a list conveniently as a queue, where the first element added
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142 is the first element retrieved ("first-in, first-out"). To add an item to the
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143 back of the queue, use :meth:`append`. To retrieve an item from the front of
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144 the queue, use :meth:`pop` with ``0`` as the index. For example::
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145
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146 >>> queue = ["Eric", "John", "Michael"]
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147 >>> queue.append("Terry") # Terry arrives
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148 >>> queue.append("Graham") # Graham arrives
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149 >>> queue.pop(0)
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150 'Eric'
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151 >>> queue.pop(0)
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152 'John'
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153 >>> queue
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154 ['Michael', 'Terry', 'Graham']
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155
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156 However, since lists are implemented as an array of elements, they are not the
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157 optimal data structure to use as a queue (the ``pop(0)`` needs to move all
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158 following elements). See :ref:`tut-list-tools` for a look at
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159 :class:`collections.deque`, which is designed to work efficiently as a queue.
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160
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161
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162 .. _tut-listcomps:
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163
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164 List Comprehensions
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165 -------------------
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166
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167 List comprehensions provide a concise way to create lists from sequences.
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168 Common applications are to make lists where each element is the result of
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169 some operations applied to each member of the sequence, or to create a
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170 subsequence of those elements that satisfy a certain condition.
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171
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172 A list comprehension consists of brackets containing an expression followed
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173 by a :keyword:`for` clause, then zero or more :keyword:`for` or :keyword:`if`
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174 clauses. The result will be a list resulting from evaluating the expression in
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175 the context of the :keyword:`for` and :keyword:`if` clauses which follow it. If
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176 the expression would evaluate to a tuple, it must be parenthesized.
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177
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178 Here we take a list of numbers and return a list of three times each number::
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179
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180 >>> vec = [2, 4, 6]
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181 >>> [3*x for x in vec]
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182 [6, 12, 18]
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183
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184 Now we get a little fancier::
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185
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186 >>> [[x, x**2] for x in vec]
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187 [[2, 4], [4, 16], [6, 36]]
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188
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189 Here we apply a method call to each item in a sequence::
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190
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191 >>> freshfruit = [' banana', ' loganberry ', 'passion fruit ']
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192 >>> [weapon.strip() for weapon in freshfruit]
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193 ['banana', 'loganberry', 'passion fruit']
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194
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195 Using the :keyword:`if` clause we can filter the stream::
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196
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197 >>> [3*x for x in vec if x > 3]
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198 [12, 18]
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199 >>> [3*x for x in vec if x < 2]
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200 []
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201
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202 Tuples can often be created without their parentheses, but not here::
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203
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204 >>> [x, x**2 for x in vec] # error - parens required for tuples
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205 File "<stdin>", line 1, in ?
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206 [x, x**2 for x in vec]
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207 ^
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208 SyntaxError: invalid syntax
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209 >>> [(x, x**2) for x in vec]
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210 [(2, 4), (4, 16), (6, 36)]
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211
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212 Here are some nested for loops and other fancy behavior::
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213
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214 >>> vec1 = [2, 4, 6]
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215 >>> vec2 = [4, 3, -9]
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216 >>> [x*y for x in vec1 for y in vec2]
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217 [8, 6, -18, 16, 12, -36, 24, 18, -54]
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218 >>> [x+y for x in vec1 for y in vec2]
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219 [6, 5, -7, 8, 7, -5, 10, 9, -3]
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220 >>> [vec1[i]*vec2[i] for i in range(len(vec1))]
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221 [8, 12, -54]
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222
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223 List comprehensions can be applied to complex expressions and nested functions::
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224
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225 >>> [str(round(355/113, i)) for i in range(1, 6)]
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226 ['3.1', '3.14', '3.142', '3.1416', '3.14159']
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227
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228
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229 Nested List Comprehensions
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230 --------------------------
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231
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232 If you've got the stomach for it, list comprehensions can be nested. They are a
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233 powerful tool but -- like all powerful tools -- they need to be used carefully,
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234 if at all.
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235
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236 Consider the following example of a 3x3 matrix held as a list containing three
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237 lists, one list per row::
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238
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239 >>> mat = [
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240 ... [1, 2, 3],
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241 ... [4, 5, 6],
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242 ... [7, 8, 9],
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243 ... ]
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244
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245 Now, if you wanted to swap rows and columns, you could use a list
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246 comprehension::
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247
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248 >>> print([[row[i] for row in mat] for i in [0, 1, 2]])
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249 [[1, 4, 7], [2, 5, 8], [3, 6, 9]]
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250
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251 Special care has to be taken for the *nested* list comprehension:
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252
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253 To avoid apprehension when nesting list comprehensions, read from right to
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254 left.
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255
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256 A more verbose version of this snippet shows the flow explicitly::
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257
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258 for i in [0, 1, 2]:
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259 for row in mat:
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260 print(row[i], end="")
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261 print()
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262
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263 In real world, you should prefer built-in functions to complex flow statements.
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264 The :func:`zip` function would do a great job for this use case::
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265
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266 >>> list(zip(*mat))
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267 [(1, 4, 7), (2, 5, 8), (3, 6, 9)]
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268
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269 See :ref:`tut-unpacking-arguments` for details on the asterisk in this line.
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270
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271 .. _tut-del:
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272
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273 The :keyword:`del` statement
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274 ============================
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275
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276 There is a way to remove an item from a list given its index instead of its
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277 value: the :keyword:`del` statement. This differs from the :meth:`pop` method
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278 which returns a value. The :keyword:`del` statement can also be used to remove
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279 slices from a list or clear the entire list (which we did earlier by assignment
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280 of an empty list to the slice). For example::
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281
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282 >>> a = [-1, 1, 66.25, 333, 333, 1234.5]
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283 >>> del a[0]
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284 >>> a
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285 [1, 66.25, 333, 333, 1234.5]
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286 >>> del a[2:4]
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287 >>> a
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288 [1, 66.25, 1234.5]
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289 >>> del a[:]
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290 >>> a
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291 []
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292
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293 :keyword:`del` can also be used to delete entire variables::
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294
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295 >>> del a
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296
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297 Referencing the name ``a`` hereafter is an error (at least until another value
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298 is assigned to it). We'll find other uses for :keyword:`del` later.
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299
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300
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301 .. _tut-tuples:
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302
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303 Tuples and Sequences
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304 ====================
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305
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306 We saw that lists and strings have many common properties, such as indexing and
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307 slicing operations. They are two examples of *sequence* data types (see
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308 :ref:`typesseq`). Since Python is an evolving language, other sequence data
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309 types may be added. There is also another standard sequence data type: the
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310 *tuple*.
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311
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312 A tuple consists of a number of values separated by commas, for instance::
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313
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314 >>> t = 12345, 54321, 'hello!'
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315 >>> t[0]
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316 12345
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317 >>> t
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318 (12345, 54321, 'hello!')
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319 >>> # Tuples may be nested:
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320 ... u = t, (1, 2, 3, 4, 5)
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321 >>> u
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322 ((12345, 54321, 'hello!'), (1, 2, 3, 4, 5))
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323
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324 As you see, on output tuples are always enclosed in parentheses, so that nested
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325 tuples are interpreted correctly; they may be input with or without surrounding
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326 parentheses, although often parentheses are necessary anyway (if the tuple is
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327 part of a larger expression).
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328
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329 Tuples have many uses. For example: (x, y) coordinate pairs, employee records
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330 from a database, etc. Tuples, like strings, are immutable: it is not possible
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331 to assign to the individual items of a tuple (you can simulate much of the same
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332 effect with slicing and concatenation, though). It is also possible to create
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333 tuples which contain mutable objects, such as lists.
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334
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335 A special problem is the construction of tuples containing 0 or 1 items: the
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336 syntax has some extra quirks to accommodate these. Empty tuples are constructed
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337 by an empty pair of parentheses; a tuple with one item is constructed by
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338 following a value with a comma (it is not sufficient to enclose a single value
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339 in parentheses). Ugly, but effective. For example::
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340
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341 >>> empty = ()
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342 >>> singleton = 'hello', # <-- note trailing comma
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343 >>> len(empty)
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344 0
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345 >>> len(singleton)
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346 1
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347 >>> singleton
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348 ('hello',)
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349
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350 The statement ``t = 12345, 54321, 'hello!'`` is an example of *tuple packing*:
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351 the values ``12345``, ``54321`` and ``'hello!'`` are packed together in a tuple.
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352 The reverse operation is also possible::
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353
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354 >>> x, y, z = t
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355
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356 This is called, appropriately enough, *sequence unpacking* and works for any
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357 sequence on the right-hand side. Sequence unpacking requires that there are as
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358 many variables on the left side of the equals sign as there are elements in the
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359 sequence. Note that multiple assignment is really just a combination of tuple
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360 packing and sequence unpacking.
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361
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362 .. XXX Add a bit on the difference between tuples and lists.
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363
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364
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365 .. _tut-sets:
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366
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367 Sets
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368 ====
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369
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370 Python also includes a data type for *sets*. A set is an unordered collection
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371 with no duplicate elements. Basic uses include membership testing and
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372 eliminating duplicate entries. Set objects also support mathematical operations
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373 like union, intersection, difference, and symmetric difference.
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374
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375 Curly braces or the :func:`set` function can be use to create sets. Note: To
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376 create an empty set you have to use ``set()``, not ``{}``; the latter creates an
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377 empty dictionary, a data structure that we discuss in the next section.
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378
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379 Here is a brief demonstration::
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380
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381 >>> basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
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382 >>> print(basket)
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383 {'orange', 'banana', 'pear', 'apple'}
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384 >>> fruit = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
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385 >>> fruit = set(basket) # create a set without duplicates
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386 >>> fruit
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387 {'orange', 'pear', 'apple', 'banana'}
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388 >>> fruit = {'orange', 'apple'} # {} syntax is equivalent to [] for lists
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389 >>> fruit
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390 {'orange', 'apple'}
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391 >>> 'orange' in fruit # fast membership testing
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392 True
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393 >>> 'crabgrass' in fruit
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394 False
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395
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396 >>> # Demonstrate set operations on unique letters from two words
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397 ...
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398 >>> a = set('abracadabra')
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399 >>> b = set('alacazam')
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400 >>> a # unique letters in a
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401 {'a', 'r', 'b', 'c', 'd'}
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402 >>> a - b # letters in a but not in b
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403 {'r', 'd', 'b'}
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404 >>> a | b # letters in either a or b
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405 {'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'}
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406 >>> a & b # letters in both a and b
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407 {'a', 'c'}
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408 >>> a ^ b # letters in a or b but not both
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409 {'r', 'd', 'b', 'm', 'z', 'l'}
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410
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411 Like :ref:`for lists <tut-listcomps>`, there is a set comprehension syntax::
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412
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413 >>> a = {x for x in 'abracadabra' if x not in 'abc'}
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414 >>> a
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415 {'r', 'd'}
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416
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417
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418
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419 .. _tut-dictionaries:
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420
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421 Dictionaries
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422 ============
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423
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424 Another useful data type built into Python is the *dictionary* (see
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425 :ref:`typesmapping`). Dictionaries are sometimes found in other languages as
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Georg Brandl <georg@python.org>
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426 "associative memories" or "associative arrays". Unlike sequences, which are
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427 indexed by a range of numbers, dictionaries are indexed by *keys*, which can be
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428 any immutable type; strings and numbers can always be keys. Tuples can be used
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429 as keys if they contain only strings, numbers, or tuples; if a tuple contains
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430 any mutable object either directly or indirectly, it cannot be used as a key.
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431 You can't use lists as keys, since lists can be modified in place using index
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432 assignments, slice assignments, or methods like :meth:`append` and
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433 :meth:`extend`.
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434
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435 It is best to think of a dictionary as an unordered set of *key: value* pairs,
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436 with the requirement that the keys are unique (within one dictionary). A pair of
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437 braces creates an empty dictionary: ``{}``. Placing a comma-separated list of
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438 key:value pairs within the braces adds initial key:value pairs to the
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439 dictionary; this is also the way dictionaries are written on output.
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440
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441 The main operations on a dictionary are storing a value with some key and
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442 extracting the value given the key. It is also possible to delete a key:value
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443 pair with ``del``. If you store using a key that is already in use, the old
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444 value associated with that key is forgotten. It is an error to extract a value
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445 using a non-existent key.
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446
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447 Performing ``list(d.keys())`` on a dictionary returns a list of all the keys
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448 used in the dictionary, in arbitrary order (if you want it sorted, just use
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449 ``sorted(d.keys())`` instead). [1]_ To check whether a single key is in the
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450 dictionary, use the :keyword:`in` keyword.
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451
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452 Here is a small example using a dictionary::
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453
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454 >>> tel = {'jack': 4098, 'sape': 4139}
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455 >>> tel['guido'] = 4127
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456 >>> tel
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457 {'sape': 4139, 'guido': 4127, 'jack': 4098}
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458 >>> tel['jack']
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459 4098
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460 >>> del tel['sape']
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461 >>> tel['irv'] = 4127
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462 >>> tel
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463 {'guido': 4127, 'irv': 4127, 'jack': 4098}
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464 >>> list(tel.keys())
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465 ['irv', 'guido', 'jack']
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466 >>> sorted(tel.keys())
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467 ['guido', 'irv', 'jack']
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468 >>> 'guido' in tel
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469 True
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470 >>> 'jack' not in tel
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471 False
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472
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473 The :func:`dict` constructor builds dictionaries directly from sequences of
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Raymond Hettinger <python@rcn.com>
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474 key-value pairs::
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475
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476 >>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
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477 {'sape': 4139, 'jack': 4098, 'guido': 4127}
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478
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479 In addition, dict comprehensions can be used to create dictionaries from
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480 arbitrary key and value expressions::
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481
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482 >>> {x: x**2 for x in (2, 4, 6)}
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483 {2: 4, 4: 16, 6: 36}
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484
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485 When the keys are simple strings, it is sometimes easier to specify pairs using
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486 keyword arguments::
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487
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488 >>> dict(sape=4139, guido=4127, jack=4098)
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489 {'sape': 4139, 'jack': 4098, 'guido': 4127}
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490
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491
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492 .. _tut-loopidioms:
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493
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494 Looping Techniques
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495 ==================
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496
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497 When looping through dictionaries, the key and corresponding value can be
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498 retrieved at the same time using the :meth:`items` method. ::
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499
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500 >>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
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501 >>> for k, v in knights.items():
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502 ... print(k, v)
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503 ...
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504 gallahad the pure
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Georg Brandl <georg@python.org>
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505 robin the brave
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506
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507 When looping through a sequence, the position index and corresponding value can
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Georg Brandl <georg@python.org>
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508 be retrieved at the same time using the :func:`enumerate` function. ::
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509
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510 >>> for i, v in enumerate(['tic', 'tac', 'toe']):
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511 ... print(i, v)
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512 ...
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513 0 tic
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514 1 tac
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515 2 toe
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516
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Georg Brandl <georg@python.org>
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517 To loop over two or more sequences at the same time, the entries can be paired
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Georg Brandl <georg@python.org>
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518 with the :func:`zip` function. ::
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519
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520 >>> questions = ['name', 'quest', 'favorite color']
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521 >>> answers = ['lancelot', 'the holy grail', 'blue']
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522 >>> for q, a in zip(questions, answers):
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Benjamin Peterson <benjamin@python.org>
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523 ... print('What is your {0}? It is {1}.'.format(q, a))
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Georg Brandl <georg@python.org>
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524 ...
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525 What is your name? It is lancelot.
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526 What is your quest? It is the holy grail.
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Georg Brandl <georg@python.org>
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527 What is your favorite color? It is blue.
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528
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529 To loop over a sequence in reverse, first specify the sequence in a forward
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Georg Brandl <georg@python.org>
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530 direction and then call the :func:`reversed` function. ::
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531
43201
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532 >>> for i in reversed(range(1, 10, 2)):
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533 ... print(i)
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534 ...
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535 9
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536 7
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537 5
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538 3
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539 1
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540
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541 To loop over a sequence in sorted order, use the :func:`sorted` function which
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542 returns a new sorted list while leaving the source unaltered. ::
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543
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544 >>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
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545 >>> for f in sorted(set(basket)):
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546 ... print(f)
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547 ...
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548 apple
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549 banana
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550 orange
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551 pear
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552
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553
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Georg Brandl <georg@python.org>
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554 .. _tut-conditions:
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555
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556 More on Conditions
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Georg Brandl <georg@python.org>
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557 ==================
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558
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559 The conditions used in ``while`` and ``if`` statements can contain any
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Georg Brandl <georg@python.org>
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560 operators, not just comparisons.
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561
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562 The comparison operators ``in`` and ``not in`` check whether a value occurs
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563 (does not occur) in a sequence. The operators ``is`` and ``is not`` compare
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564 whether two objects are really the same object; this only matters for mutable
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565 objects like lists. All comparison operators have the same priority, which is
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566 lower than that of all numerical operators.
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567
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568 Comparisons can be chained. For example, ``a < b == c`` tests whether ``a`` is
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569 less than ``b`` and moreover ``b`` equals ``c``.
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570
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571 Comparisons may be combined using the Boolean operators ``and`` and ``or``, and
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572 the outcome of a comparison (or of any other Boolean expression) may be negated
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573 with ``not``. These have lower priorities than comparison operators; between
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574 them, ``not`` has the highest priority and ``or`` the lowest, so that ``A and
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575 not B or C`` is equivalent to ``(A and (not B)) or C``. As always, parentheses
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576 can be used to express the desired composition.
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577
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Georg Brandl <georg@python.org>
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578 The Boolean operators ``and`` and ``or`` are so-called *short-circuit*
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579 operators: their arguments are evaluated from left to right, and evaluation
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Georg Brandl <georg@python.org>
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580 stops as soon as the outcome is determined. For example, if ``A`` and ``C`` are
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Georg Brandl <georg@python.org>
parents:
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581 true but ``B`` is false, ``A and B and C`` does not evaluate the expression
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582 ``C``. When used as a general value and not as a Boolean, the return value of a
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583 short-circuit operator is the last evaluated argument.
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584
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585 It is possible to assign the result of a comparison or other Boolean expression
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Georg Brandl <georg@python.org>
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586 to a variable. For example, ::
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587
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588 >>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
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589 >>> non_null = string1 or string2 or string3
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590 >>> non_null
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591 'Trondheim'
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592
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593 Note that in Python, unlike C, assignment cannot occur inside expressions. C
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594 programmers may grumble about this, but it avoids a common class of problems
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Georg Brandl <georg@python.org>
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595 encountered in C programs: typing ``=`` in an expression when ``==`` was
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Georg Brandl <georg@python.org>
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596 intended.
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Georg Brandl <georg@python.org>
parents:
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597
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598
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Georg Brandl <georg@python.org>
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599 .. _tut-comparing:
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600
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Georg Brandl <georg@python.org>
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601 Comparing Sequences and Other Types
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Georg Brandl <georg@python.org>
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602 ===================================
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603
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604 Sequence objects may be compared to other objects with the same sequence type.
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Georg Brandl <georg@python.org>
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605 The comparison uses *lexicographical* ordering: first the first two items are
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Georg Brandl <georg@python.org>
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606 compared, and if they differ this determines the outcome of the comparison; if
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607 they are equal, the next two items are compared, and so on, until either
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Georg Brandl <georg@python.org>
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608 sequence is exhausted. If two items to be compared are themselves sequences of
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609 the same type, the lexicographical comparison is carried out recursively. If
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Georg Brandl <georg@python.org>
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610 all items of two sequences compare equal, the sequences are considered equal.
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611 If one sequence is an initial sub-sequence of the other, the shorter sequence is
54769
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612 the smaller (lesser) one. Lexicographical ordering for strings uses the Unicode
eea4d237c16d Expand a bit on dict views.
Georg Brandl <georg@python.org>
parents: 54632
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613 codepoint number to order individual characters. Some examples of comparisons
eea4d237c16d Expand a bit on dict views.
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parents: 54632
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614 between sequences of the same type::
42604
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615
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Georg Brandl <georg@python.org>
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616 (1, 2, 3) < (1, 2, 4)
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617 [1, 2, 3] < [1, 2, 4]
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Georg Brandl <georg@python.org>
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618 'ABC' < 'C' < 'Pascal' < 'Python'
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Georg Brandl <georg@python.org>
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619 (1, 2, 3, 4) < (1, 2, 4)
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Georg Brandl <georg@python.org>
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620 (1, 2) < (1, 2, -1)
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diff changeset
621 (1, 2, 3) == (1.0, 2.0, 3.0)
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parents:
diff changeset
622 (1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4)
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Georg Brandl <georg@python.org>
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623
43497
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parents: 43303
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624 Note that comparing objects of different types with ``<`` or ``>`` is legal
6614d42d7f0a #1228: new comparison behavior.
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parents: 43303
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625 provided that the objects have appropriate comparison methods. For example,
6614d42d7f0a #1228: new comparison behavior.
Georg Brandl <georg@python.org>
parents: 43303
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626 mixed numeric types are compared according to their numeric value, so 0 equals
6614d42d7f0a #1228: new comparison behavior.
Georg Brandl <georg@python.org>
parents: 43303
diff changeset
627 0.0, etc. Otherwise, rather than providing an arbitrary ordering, the
6614d42d7f0a #1228: new comparison behavior.
Georg Brandl <georg@python.org>
parents: 43303
diff changeset
628 interpreter will raise a :exc:`TypeError` exception.
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629
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630
eea4d237c16d Expand a bit on dict views.
Georg Brandl <georg@python.org>
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631 .. rubric:: Footnotes
eea4d237c16d Expand a bit on dict views.
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632
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Georg Brandl <georg@python.org>
parents: 54632
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633 .. [1] Calling ``d.keys()`` will return a :dfn:`dictionary view` object. It
eea4d237c16d Expand a bit on dict views.
Georg Brandl <georg@python.org>
parents: 54632
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634 supports operations like membership test and iteration, but its contents
eea4d237c16d Expand a bit on dict views.
Georg Brandl <georg@python.org>
parents: 54632
diff changeset
635 are not independent of the original dictionary -- it is only a *view*.