Mercurial > cpython-lru_cache-weakref
annotate Doc/tutorial/datastructures.rst @ 49955:878d40468c4e legacy-trunk
Issue #4384: Added logging integration with warnings module using captureWarnings(). This change includes a NullHandler which does nothing; it will be of use to library developers who want to avoid the "No handlers could be found for logger XXX" message which can appear if the library user doesn't configure logging.
| author | Vinay Sajip <vinay_sajip@yahoo.co.uk> |
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| date | Wed, 03 Dec 2008 23:22:58 +0000 |
| parents | 75b0dcbc3cc7 |
| children | ee9ced92843a c52177f36852 |
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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 |
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11 .. _tut-morelists: |
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12 |
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13 More on Lists |
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14 ============= |
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15 |
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16 The list data type has some more methods. Here are all of the methods of list |
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17 objects: |
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18 |
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19 |
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20 .. method:: list.append(x) |
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21 :noindex: |
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22 |
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23 Add an item to the end of the list; equivalent to ``a[len(a):] = [x]``. |
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24 |
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25 |
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26 .. method:: list.extend(L) |
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27 :noindex: |
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28 |
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29 Extend the list by appending all the items in the given list; equivalent to |
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30 ``a[len(a):] = L``. |
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31 |
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32 |
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33 .. method:: list.insert(i, x) |
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34 :noindex: |
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35 |
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36 Insert an item at a given position. The first argument is the index of the |
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37 element before which to insert, so ``a.insert(0, x)`` inserts at the front of |
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38 the list, and ``a.insert(len(a), x)`` is equivalent to ``a.append(x)``. |
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39 |
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40 |
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41 .. method:: list.remove(x) |
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42 :noindex: |
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43 |
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44 Remove the first item from the list whose value is *x*. It is an error if there |
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45 is no such item. |
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46 |
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47 |
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48 .. method:: list.pop([i]) |
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49 :noindex: |
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50 |
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51 Remove the item at the given position in the list, and return it. If no index |
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52 is specified, ``a.pop()`` removes and returns the last item in the list. (The |
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53 square brackets around the *i* in the method signature denote that the parameter |
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54 is optional, not that you should type square brackets at that position. You |
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55 will see this notation frequently in the Python Library Reference.) |
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56 |
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57 |
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58 .. method:: list.index(x) |
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59 :noindex: |
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60 |
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61 Return the index in the list of the first item whose value is *x*. It is an |
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62 error if there is no such item. |
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63 |
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64 |
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65 .. method:: list.count(x) |
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66 :noindex: |
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67 |
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68 Return the number of times *x* appears in the list. |
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69 |
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70 |
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71 .. method:: list.sort() |
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72 :noindex: |
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73 |
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74 Sort the items of the list, in place. |
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75 |
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76 |
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77 .. method:: list.reverse() |
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78 :noindex: |
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79 |
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80 Reverse the elements of the list, in place. |
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81 |
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82 An example that uses most of the list methods:: |
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83 |
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84 >>> a = [66.25, 333, 333, 1, 1234.5] |
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85 >>> print a.count(333), a.count(66.25), a.count('x') |
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86 2 1 0 |
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87 >>> a.insert(2, -1) |
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88 >>> a.append(333) |
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89 >>> a |
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90 [66.25, 333, -1, 333, 1, 1234.5, 333] |
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91 >>> a.index(333) |
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92 1 |
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93 >>> a.remove(333) |
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94 >>> a |
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95 [66.25, -1, 333, 1, 1234.5, 333] |
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96 >>> a.reverse() |
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97 >>> a |
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98 [333, 1234.5, 1, 333, -1, 66.25] |
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99 >>> a.sort() |
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100 >>> a |
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101 [-1, 1, 66.25, 333, 333, 1234.5] |
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102 |
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103 |
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104 .. _tut-lists-as-stacks: |
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105 |
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106 Using Lists as Stacks |
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107 --------------------- |
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108 |
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109 .. sectionauthor:: Ka-Ping Yee <ping@lfw.org> |
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110 |
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111 |
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112 The list methods make it very easy to use a list as a stack, where the last |
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113 element added is the first element retrieved ("last-in, first-out"). To add an |
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114 item to the top of the stack, use :meth:`append`. To retrieve an item from the |
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115 top of the stack, use :meth:`pop` without an explicit index. For example:: |
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116 |
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117 >>> stack = [3, 4, 5] |
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118 >>> stack.append(6) |
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119 >>> stack.append(7) |
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120 >>> stack |
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121 [3, 4, 5, 6, 7] |
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122 >>> stack.pop() |
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123 7 |
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124 >>> stack |
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125 [3, 4, 5, 6] |
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126 >>> stack.pop() |
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127 6 |
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128 >>> stack.pop() |
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129 5 |
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130 >>> stack |
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131 [3, 4] |
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132 |
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133 |
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134 .. _tut-lists-as-queues: |
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135 |
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136 Using Lists as Queues |
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137 --------------------- |
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138 |
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139 .. sectionauthor:: Ka-Ping Yee <ping@lfw.org> |
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140 |
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141 |
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142 You can also use a list conveniently as a queue, where the first element added |
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143 is the first element retrieved ("first-in, first-out"). To add an item to the |
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144 back of the queue, use :meth:`append`. To retrieve an item from the front of |
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145 the queue, use :meth:`pop` with ``0`` as the index. For example:: |
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146 |
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147 >>> queue = ["Eric", "John", "Michael"] |
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148 >>> queue.append("Terry") # Terry arrives |
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149 >>> queue.append("Graham") # Graham arrives |
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150 >>> queue.pop(0) |
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151 'Eric' |
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152 >>> queue.pop(0) |
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153 'John' |
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154 >>> queue |
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155 ['Michael', 'Terry', 'Graham'] |
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156 |
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157 |
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158 .. _tut-functional: |
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159 |
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160 Functional Programming Tools |
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161 ---------------------------- |
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162 |
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163 There are three built-in functions that are very useful when used with lists: |
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164 :func:`filter`, :func:`map`, and :func:`reduce`. |
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165 |
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166 ``filter(function, sequence)`` returns a sequence consisting of those items from |
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167 the sequence for which ``function(item)`` is true. If *sequence* is a |
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168 :class:`string` or :class:`tuple`, the result will be of the same type; |
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169 otherwise, it is always a :class:`list`. For example, to compute some primes:: |
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170 |
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171 >>> def f(x): return x % 2 != 0 and x % 3 != 0 |
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172 ... |
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173 >>> filter(f, range(2, 25)) |
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174 [5, 7, 11, 13, 17, 19, 23] |
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175 |
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176 ``map(function, sequence)`` calls ``function(item)`` for each of the sequence's |
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177 items and returns a list of the return values. For example, to compute some |
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178 cubes:: |
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179 |
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180 >>> def cube(x): return x*x*x |
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181 ... |
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182 >>> map(cube, range(1, 11)) |
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183 [1, 8, 27, 64, 125, 216, 343, 512, 729, 1000] |
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184 |
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185 More than one sequence may be passed; the function must then have as many |
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186 arguments as there are sequences and is called with the corresponding item from |
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187 each sequence (or ``None`` if some sequence is shorter than another). For |
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188 example:: |
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189 |
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190 >>> seq = range(8) |
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191 >>> def add(x, y): return x+y |
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192 ... |
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193 >>> map(add, seq, seq) |
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194 [0, 2, 4, 6, 8, 10, 12, 14] |
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195 |
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196 ``reduce(function, sequence)`` returns a single value constructed by calling the |
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197 binary function *function* on the first two items of the sequence, then on the |
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198 result and the next item, and so on. For example, to compute the sum of the |
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199 numbers 1 through 10:: |
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200 |
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201 >>> def add(x,y): return x+y |
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202 ... |
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203 >>> reduce(add, range(1, 11)) |
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204 55 |
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205 |
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206 If there's only one item in the sequence, its value is returned; if the sequence |
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207 is empty, an exception is raised. |
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208 |
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209 A third argument can be passed to indicate the starting value. In this case the |
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210 starting value is returned for an empty sequence, and the function is first |
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211 applied to the starting value and the first sequence item, then to the result |
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212 and the next item, and so on. For example, :: |
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213 |
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214 >>> def sum(seq): |
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215 ... def add(x,y): return x+y |
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216 ... return reduce(add, seq, 0) |
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217 ... |
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218 >>> sum(range(1, 11)) |
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219 55 |
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220 >>> sum([]) |
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221 0 |
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222 |
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223 Don't use this example's definition of :func:`sum`: since summing numbers is |
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224 such a common need, a built-in function ``sum(sequence)`` is already provided, |
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225 and works exactly like this. |
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226 |
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227 .. versionadded:: 2.3 |
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228 |
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229 |
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230 List Comprehensions |
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231 ------------------- |
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232 |
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233 List comprehensions provide a concise way to create lists without resorting to |
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234 use of :func:`map`, :func:`filter` and/or :keyword:`lambda`. The resulting list |
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235 definition tends often to be clearer than lists built using those constructs. |
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236 Each list comprehension consists of an expression followed by a :keyword:`for` |
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237 clause, then zero or more :keyword:`for` or :keyword:`if` clauses. The result |
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238 will be a list resulting from evaluating the expression in the context of the |
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239 :keyword:`for` and :keyword:`if` clauses which follow it. If the expression |
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240 would evaluate to a tuple, it must be parenthesized. :: |
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241 |
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242 >>> freshfruit = [' banana', ' loganberry ', 'passion fruit '] |
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243 >>> [weapon.strip() for weapon in freshfruit] |
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244 ['banana', 'loganberry', 'passion fruit'] |
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245 >>> vec = [2, 4, 6] |
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246 >>> [3*x for x in vec] |
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247 [6, 12, 18] |
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248 >>> [3*x for x in vec if x > 3] |
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249 [12, 18] |
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250 >>> [3*x for x in vec if x < 2] |
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251 [] |
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252 >>> [[x,x**2] for x in vec] |
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253 [[2, 4], [4, 16], [6, 36]] |
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254 >>> [x, x**2 for x in vec] # error - parens required for tuples |
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255 File "<stdin>", line 1, in ? |
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256 [x, x**2 for x in vec] |
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257 ^ |
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258 SyntaxError: invalid syntax |
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259 >>> [(x, x**2) for x in vec] |
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260 [(2, 4), (4, 16), (6, 36)] |
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261 >>> vec1 = [2, 4, 6] |
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262 >>> vec2 = [4, 3, -9] |
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263 >>> [x*y for x in vec1 for y in vec2] |
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264 [8, 6, -18, 16, 12, -36, 24, 18, -54] |
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265 >>> [x+y for x in vec1 for y in vec2] |
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266 [6, 5, -7, 8, 7, -5, 10, 9, -3] |
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267 >>> [vec1[i]*vec2[i] for i in range(len(vec1))] |
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268 [8, 12, -54] |
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269 |
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270 List comprehensions are much more flexible than :func:`map` and can be applied |
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271 to complex expressions and nested functions:: |
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272 |
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273 >>> [str(round(355/113.0, i)) for i in range(1,6)] |
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274 ['3.1', '3.14', '3.142', '3.1416', '3.14159'] |
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275 |
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276 |
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277 Nested List Comprehensions |
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278 -------------------------- |
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279 |
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280 If you've got the stomach for it, list comprehensions can be nested. They are a |
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281 powerful tool but -- like all powerful tools -- they need to be used carefully, |
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282 if at all. |
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283 |
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284 Consider the following example of a 3x3 matrix held as a list containing three |
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285 lists, one list per row:: |
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286 |
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287 >>> mat = [ |
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288 ... [1, 2, 3], |
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289 ... [4, 5, 6], |
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290 ... [7, 8, 9], |
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291 ... ] |
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292 |
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293 Now, if you wanted to swap rows and columns, you could use a list |
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294 comprehension:: |
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295 |
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296 >>> print [[row[i] for row in mat] for i in [0, 1, 2]] |
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297 [[1, 4, 7], [2, 5, 8], [3, 6, 9]] |
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298 |
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299 Special care has to be taken for the *nested* list comprehension: |
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300 |
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301 To avoid apprehension when nesting list comprehensions, read from right to |
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302 left. |
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303 |
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304 A more verbose version of this snippet shows the flow explicitly:: |
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305 |
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306 for i in [0, 1, 2]: |
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307 for row in mat: |
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308 print row[i], |
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309 print |
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310 |
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311 In real world, you should prefer builtin functions to complex flow statements. |
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312 The :func:`zip` function would do a great job for this use case:: |
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313 |
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314 >>> zip(*mat) |
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315 [(1, 4, 7), (2, 5, 8), (3, 6, 9)] |
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316 |
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317 See :ref:`tut-unpacking-arguments` for details on the asterisk in this line. |
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318 |
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319 .. _tut-del: |
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320 |
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321 The :keyword:`del` statement |
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322 ============================ |
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323 |
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324 There is a way to remove an item from a list given its index instead of its |
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325 value: the :keyword:`del` statement. This differs from the :meth:`pop` method |
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326 which returns a value. The :keyword:`del` statement can also be used to remove |
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327 slices from a list or clear the entire list (which we did earlier by assignment |
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328 of an empty list to the slice). For example:: |
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329 |
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330 >>> a = [-1, 1, 66.25, 333, 333, 1234.5] |
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331 >>> del a[0] |
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332 >>> a |
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333 [1, 66.25, 333, 333, 1234.5] |
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334 >>> del a[2:4] |
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335 >>> a |
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336 [1, 66.25, 1234.5] |
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337 >>> del a[:] |
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338 >>> a |
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339 [] |
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340 |
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341 :keyword:`del` can also be used to delete entire variables:: |
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342 |
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343 >>> del a |
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344 |
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345 Referencing the name ``a`` hereafter is an error (at least until another value |
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346 is assigned to it). We'll find other uses for :keyword:`del` later. |
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347 |
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348 |
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349 .. _tut-tuples: |
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350 |
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351 Tuples and Sequences |
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352 ==================== |
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353 |
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354 We saw that lists and strings have many common properties, such as indexing and |
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355 slicing operations. They are two examples of *sequence* data types (see |
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356 :ref:`typesseq`). Since Python is an evolving language, other sequence data |
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357 types may be added. There is also another standard sequence data type: the |
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358 *tuple*. |
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359 |
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360 A tuple consists of a number of values separated by commas, for instance:: |
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361 |
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362 >>> t = 12345, 54321, 'hello!' |
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363 >>> t[0] |
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364 12345 |
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365 >>> t |
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366 (12345, 54321, 'hello!') |
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367 >>> # Tuples may be nested: |
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368 ... u = t, (1, 2, 3, 4, 5) |
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369 >>> u |
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370 ((12345, 54321, 'hello!'), (1, 2, 3, 4, 5)) |
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371 |
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372 As you see, on output tuples are always enclosed in parentheses, so that nested |
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373 tuples are interpreted correctly; they may be input with or without surrounding |
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374 parentheses, although often parentheses are necessary anyway (if the tuple is |
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375 part of a larger expression). |
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376 |
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377 Tuples have many uses. For example: (x, y) coordinate pairs, employee records |
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378 from a database, etc. Tuples, like strings, are immutable: it is not possible |
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379 to assign to the individual items of a tuple (you can simulate much of the same |
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380 effect with slicing and concatenation, though). It is also possible to create |
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381 tuples which contain mutable objects, such as lists. |
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382 |
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383 A special problem is the construction of tuples containing 0 or 1 items: the |
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384 syntax has some extra quirks to accommodate these. Empty tuples are constructed |
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385 by an empty pair of parentheses; a tuple with one item is constructed by |
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386 following a value with a comma (it is not sufficient to enclose a single value |
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387 in parentheses). Ugly, but effective. For example:: |
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388 |
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389 >>> empty = () |
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390 >>> singleton = 'hello', # <-- note trailing comma |
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391 >>> len(empty) |
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392 0 |
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393 >>> len(singleton) |
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394 1 |
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395 >>> singleton |
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396 ('hello',) |
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397 |
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398 The statement ``t = 12345, 54321, 'hello!'`` is an example of *tuple packing*: |
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399 the values ``12345``, ``54321`` and ``'hello!'`` are packed together in a tuple. |
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400 The reverse operation is also possible:: |
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401 |
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402 >>> x, y, z = t |
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403 |
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404 This is called, appropriately enough, *sequence unpacking*. Sequence unpacking |
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405 requires the list of variables on the left to have the same number of elements |
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406 as the length of the sequence. Note that multiple assignment is really just a |
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407 combination of tuple packing and sequence unpacking! |
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408 |
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409 There is a small bit of asymmetry here: packing multiple values always creates |
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410 a tuple, and unpacking works for any sequence. |
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411 |
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412 .. XXX Add a bit on the difference between tuples and lists. |
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413 |
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414 |
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415 .. _tut-sets: |
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416 |
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417 Sets |
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418 ==== |
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419 |
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420 Python also includes a data type for *sets*. A set is an unordered collection |
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421 with no duplicate elements. Basic uses include membership testing and |
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422 eliminating duplicate entries. Set objects also support mathematical operations |
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423 like union, intersection, difference, and symmetric difference. |
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424 |
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425 Here is a brief demonstration:: |
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426 |
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427 >>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] |
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428 >>> fruit = set(basket) # create a set without duplicates |
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429 >>> fruit |
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430 set(['orange', 'pear', 'apple', 'banana']) |
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431 >>> 'orange' in fruit # fast membership testing |
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432 True |
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433 >>> 'crabgrass' in fruit |
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434 False |
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435 |
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436 >>> # Demonstrate set operations on unique letters from two words |
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437 ... |
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438 >>> a = set('abracadabra') |
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439 >>> b = set('alacazam') |
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440 >>> a # unique letters in a |
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441 set(['a', 'r', 'b', 'c', 'd']) |
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442 >>> a - b # letters in a but not in b |
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443 set(['r', 'd', 'b']) |
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444 >>> a | b # letters in either a or b |
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445 set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l']) |
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446 >>> a & b # letters in both a and b |
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447 set(['a', 'c']) |
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448 >>> a ^ b # letters in a or b but not both |
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449 set(['r', 'd', 'b', 'm', 'z', 'l']) |
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450 |
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451 |
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452 .. _tut-dictionaries: |
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453 |
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454 Dictionaries |
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455 ============ |
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456 |
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457 Another useful data type built into Python is the *dictionary* (see |
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458 :ref:`typesmapping`). Dictionaries are sometimes found in other languages as |
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459 "associative memories" or "associative arrays". Unlike sequences, which are |
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460 indexed by a range of numbers, dictionaries are indexed by *keys*, which can be |
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461 any immutable type; strings and numbers can always be keys. Tuples can be used |
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462 as keys if they contain only strings, numbers, or tuples; if a tuple contains |
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463 any mutable object either directly or indirectly, it cannot be used as a key. |
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464 You can't use lists as keys, since lists can be modified in place using index |
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465 assignments, slice assignments, or methods like :meth:`append` and |
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466 :meth:`extend`. |
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467 |
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468 It is best to think of a dictionary as an unordered set of *key: value* pairs, |
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469 with the requirement that the keys are unique (within one dictionary). A pair of |
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470 braces creates an empty dictionary: ``{}``. Placing a comma-separated list of |
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471 key:value pairs within the braces adds initial key:value pairs to the |
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472 dictionary; this is also the way dictionaries are written on output. |
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473 |
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474 The main operations on a dictionary are storing a value with some key and |
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475 extracting the value given the key. It is also possible to delete a key:value |
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476 pair with ``del``. If you store using a key that is already in use, the old |
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477 value associated with that key is forgotten. It is an error to extract a value |
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478 using a non-existent key. |
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479 |
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480 The :meth:`keys` method of a dictionary object returns a list of all the keys |
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481 used in the dictionary, in arbitrary order (if you want it sorted, just apply |
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482 the :meth:`sort` method to the list of keys). To check whether a single key is |
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483 in the dictionary, use the :keyword:`in` keyword. |
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484 |
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485 Here is a small example using a dictionary:: |
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486 |
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487 >>> tel = {'jack': 4098, 'sape': 4139} |
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488 >>> tel['guido'] = 4127 |
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489 >>> tel |
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490 {'sape': 4139, 'guido': 4127, 'jack': 4098} |
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491 >>> tel['jack'] |
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492 4098 |
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493 >>> del tel['sape'] |
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494 >>> tel['irv'] = 4127 |
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495 >>> tel |
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496 {'guido': 4127, 'irv': 4127, 'jack': 4098} |
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497 >>> tel.keys() |
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498 ['guido', 'irv', 'jack'] |
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499 >>> 'guido' in tel |
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500 True |
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501 |
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502 The :func:`dict` constructor builds dictionaries directly from lists of |
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503 key-value pairs stored as tuples. When the pairs form a pattern, list |
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504 comprehensions can compactly specify the key-value list. :: |
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505 |
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506 >>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)]) |
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507 {'sape': 4139, 'jack': 4098, 'guido': 4127} |
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508 >>> dict([(x, x**2) for x in (2, 4, 6)]) # use a list comprehension |
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509 {2: 4, 4: 16, 6: 36} |
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510 |
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511 Later in the tutorial, we will learn about Generator Expressions which are even |
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512 better suited for the task of supplying key-values pairs to the :func:`dict` |
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513 constructor. |
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514 |
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515 When the keys are simple strings, it is sometimes easier to specify pairs using |
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516 keyword arguments:: |
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517 |
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518 >>> dict(sape=4139, guido=4127, jack=4098) |
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519 {'sape': 4139, 'jack': 4098, 'guido': 4127} |
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520 |
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521 |
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522 .. _tut-loopidioms: |
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523 |
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524 Looping Techniques |
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525 ================== |
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526 |
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527 When looping through dictionaries, the key and corresponding value can be |
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528 retrieved at the same time using the :meth:`iteritems` method. :: |
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529 |
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530 >>> knights = {'gallahad': 'the pure', 'robin': 'the brave'} |
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531 >>> for k, v in knights.iteritems(): |
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532 ... print k, v |
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533 ... |
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534 gallahad the pure |
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535 robin the brave |
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536 |
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537 When looping through a sequence, the position index and corresponding value can |
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538 be retrieved at the same time using the :func:`enumerate` function. :: |
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539 |
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540 >>> for i, v in enumerate(['tic', 'tac', 'toe']): |
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541 ... print i, v |
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542 ... |
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543 0 tic |
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544 1 tac |
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545 2 toe |
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546 |
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547 To loop over two or more sequences at the same time, the entries can be paired |
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548 with the :func:`zip` function. :: |
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549 |
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550 >>> questions = ['name', 'quest', 'favorite color'] |
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551 >>> answers = ['lancelot', 'the holy grail', 'blue'] |
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552 >>> for q, a in zip(questions, answers): |
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553 ... print 'What is your {0}? It is {1}.'.format(q, a) |
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554 ... |
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555 What is your name? It is lancelot. |
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556 What is your quest? It is the holy grail. |
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557 What is your favorite color? It is blue. |
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558 |
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559 To loop over a sequence in reverse, first specify the sequence in a forward |
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560 direction and then call the :func:`reversed` function. :: |
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561 |
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562 >>> for i in reversed(xrange(1,10,2)): |
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563 ... print i |
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564 ... |
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565 9 |
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566 7 |
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567 5 |
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568 3 |
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569 1 |
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570 |
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571 To loop over a sequence in sorted order, use the :func:`sorted` function which |
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572 returns a new sorted list while leaving the source unaltered. :: |
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573 |
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574 >>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] |
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575 >>> for f in sorted(set(basket)): |
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576 ... print f |
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577 ... |
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578 apple |
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579 banana |
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580 orange |
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581 pear |
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582 |
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583 |
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584 .. _tut-conditions: |
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585 |
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586 More on Conditions |
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587 ================== |
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588 |
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589 The conditions used in ``while`` and ``if`` statements can contain any |
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590 operators, not just comparisons. |
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591 |
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592 The comparison operators ``in`` and ``not in`` check whether a value occurs |
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593 (does not occur) in a sequence. The operators ``is`` and ``is not`` compare |
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594 whether two objects are really the same object; this only matters for mutable |
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595 objects like lists. All comparison operators have the same priority, which is |
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596 lower than that of all numerical operators. |
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597 |
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598 Comparisons can be chained. For example, ``a < b == c`` tests whether ``a`` is |
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599 less than ``b`` and moreover ``b`` equals ``c``. |
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600 |
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601 Comparisons may be combined using the Boolean operators ``and`` and ``or``, and |
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602 the outcome of a comparison (or of any other Boolean expression) may be negated |
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603 with ``not``. These have lower priorities than comparison operators; between |
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604 them, ``not`` has the highest priority and ``or`` the lowest, so that ``A and |
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605 not B or C`` is equivalent to ``(A and (not B)) or C``. As always, parentheses |
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606 can be used to express the desired composition. |
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607 |
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608 The Boolean operators ``and`` and ``or`` are so-called *short-circuit* |
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609 operators: their arguments are evaluated from left to right, and evaluation |
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610 stops as soon as the outcome is determined. For example, if ``A`` and ``C`` are |
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611 true but ``B`` is false, ``A and B and C`` does not evaluate the expression |
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612 ``C``. When used as a general value and not as a Boolean, the return value of a |
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613 short-circuit operator is the last evaluated argument. |
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614 |
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615 It is possible to assign the result of a comparison or other Boolean expression |
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616 to a variable. For example, :: |
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617 |
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618 >>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance' |
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619 >>> non_null = string1 or string2 or string3 |
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620 >>> non_null |
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621 'Trondheim' |
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622 |
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623 Note that in Python, unlike C, assignment cannot occur inside expressions. C |
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624 programmers may grumble about this, but it avoids a common class of problems |
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625 encountered in C programs: typing ``=`` in an expression when ``==`` was |
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626 intended. |
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627 |
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628 |
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629 .. _tut-comparing: |
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630 |
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631 Comparing Sequences and Other Types |
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632 =================================== |
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633 |
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634 Sequence objects may be compared to other objects with the same sequence type. |
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635 The comparison uses *lexicographical* ordering: first the first two items are |
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636 compared, and if they differ this determines the outcome of the comparison; if |
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637 they are equal, the next two items are compared, and so on, until either |
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638 sequence is exhausted. If two items to be compared are themselves sequences of |
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639 the same type, the lexicographical comparison is carried out recursively. If |
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640 all items of two sequences compare equal, the sequences are considered equal. |
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641 If one sequence is an initial sub-sequence of the other, the shorter sequence is |
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642 the smaller (lesser) one. Lexicographical ordering for strings uses the ASCII |
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643 ordering for individual characters. Some examples of comparisons between |
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644 sequences of the same type:: |
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645 |
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646 (1, 2, 3) < (1, 2, 4) |
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647 [1, 2, 3] < [1, 2, 4] |
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648 'ABC' < 'C' < 'Pascal' < 'Python' |
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649 (1, 2, 3, 4) < (1, 2, 4) |
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650 (1, 2) < (1, 2, -1) |
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651 (1, 2, 3) == (1.0, 2.0, 3.0) |
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652 (1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4) |
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653 |
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654 Note that comparing objects of different types is legal. The outcome is |
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655 deterministic but arbitrary: the types are ordered by their name. Thus, a list |
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656 is always smaller than a string, a string is always smaller than a tuple, etc. |
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657 [#]_ Mixed numeric types are compared according to their numeric value, so 0 |
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658 equals 0.0, etc. |
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659 |
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660 |
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661 .. rubric:: Footnotes |
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662 |
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663 .. [#] The rules for comparing objects of different types should not be relied upon; |
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664 they may change in a future version of the language. |
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665 |
