Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/boltons/iterutils.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 # -*- coding: utf-8 -*- |
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2 """:mod:`itertools` is full of great examples of Python generator |
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3 usage. However, there are still some critical gaps. ``iterutils`` |
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4 fills many of those gaps with featureful, tested, and Pythonic |
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5 solutions. |
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6 |
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7 Many of the functions below have two versions, one which |
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8 returns an iterator (denoted by the ``*_iter`` naming pattern), and a |
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9 shorter-named convenience form that returns a list. Some of the |
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10 following are based on examples in itertools docs. |
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11 """ |
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12 |
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13 import os |
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14 import math |
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15 import time |
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16 import codecs |
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17 import random |
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18 import itertools |
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19 |
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20 try: |
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21 from collections.abc import Mapping, Sequence, Set, ItemsView, Iterable |
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22 except ImportError: |
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23 from collections import Mapping, Sequence, Set, ItemsView, Iterable |
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24 |
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25 |
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26 try: |
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27 from typeutils import make_sentinel |
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28 _UNSET = make_sentinel('_UNSET') |
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29 _REMAP_EXIT = make_sentinel('_REMAP_EXIT') |
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30 except ImportError: |
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31 _REMAP_EXIT = object() |
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32 _UNSET = object() |
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33 |
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34 try: |
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35 from future_builtins import filter |
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36 from itertools import izip |
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37 _IS_PY3 = False |
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38 except ImportError: |
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39 # Python 3 compat |
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40 _IS_PY3 = True |
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41 basestring = (str, bytes) |
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42 unicode = str |
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43 izip, xrange = zip, range |
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44 |
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45 |
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46 def is_iterable(obj): |
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47 """Similar in nature to :func:`callable`, ``is_iterable`` returns |
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48 ``True`` if an object is `iterable`_, ``False`` if not. |
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49 |
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50 >>> is_iterable([]) |
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51 True |
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52 >>> is_iterable(object()) |
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53 False |
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54 |
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55 .. _iterable: https://docs.python.org/2/glossary.html#term-iterable |
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56 """ |
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57 try: |
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58 iter(obj) |
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59 except TypeError: |
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60 return False |
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61 return True |
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62 |
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63 |
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64 def is_scalar(obj): |
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65 """A near-mirror of :func:`is_iterable`. Returns ``False`` if an |
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66 object is an iterable container type. Strings are considered |
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67 scalar as well, because strings are more often treated as whole |
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68 values as opposed to iterables of 1-character substrings. |
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69 |
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70 >>> is_scalar(object()) |
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71 True |
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72 >>> is_scalar(range(10)) |
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73 False |
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74 >>> is_scalar('hello') |
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75 True |
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76 """ |
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77 return not is_iterable(obj) or isinstance(obj, basestring) |
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78 |
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79 |
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80 def is_collection(obj): |
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81 """The opposite of :func:`is_scalar`. Returns ``True`` if an object |
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82 is an iterable other than a string. |
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83 |
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84 >>> is_collection(object()) |
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85 False |
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86 >>> is_collection(range(10)) |
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87 True |
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88 >>> is_collection('hello') |
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89 False |
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90 """ |
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91 return is_iterable(obj) and not isinstance(obj, basestring) |
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92 |
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93 |
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94 def split(src, sep=None, maxsplit=None): |
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95 """Splits an iterable based on a separator. Like :meth:`str.split`, |
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96 but for all iterables. Returns a list of lists. |
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97 |
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98 >>> split(['hi', 'hello', None, None, 'sup', None, 'soap', None]) |
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99 [['hi', 'hello'], ['sup'], ['soap']] |
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100 |
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101 See :func:`split_iter` docs for more info. |
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102 """ |
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103 return list(split_iter(src, sep, maxsplit)) |
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104 |
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105 |
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106 def split_iter(src, sep=None, maxsplit=None): |
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107 """Splits an iterable based on a separator, *sep*, a max of |
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108 *maxsplit* times (no max by default). *sep* can be: |
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109 |
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110 * a single value |
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111 * an iterable of separators |
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112 * a single-argument callable that returns True when a separator is |
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113 encountered |
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114 |
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115 ``split_iter()`` yields lists of non-separator values. A separator will |
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116 never appear in the output. |
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117 |
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118 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None, 'soap', None])) |
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119 [['hi', 'hello'], ['sup'], ['soap']] |
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120 |
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121 Note that ``split_iter`` is based on :func:`str.split`, so if |
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122 *sep* is ``None``, ``split()`` **groups** separators. If empty lists |
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123 are desired between two contiguous ``None`` values, simply use |
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124 ``sep=[None]``: |
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125 |
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126 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None])) |
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127 [['hi', 'hello'], ['sup']] |
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128 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None], sep=[None])) |
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129 [['hi', 'hello'], [], ['sup'], []] |
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130 |
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131 Using a callable separator: |
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132 |
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133 >>> falsy_sep = lambda x: not x |
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134 >>> list(split_iter(['hi', 'hello', None, '', 'sup', False], falsy_sep)) |
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135 [['hi', 'hello'], [], ['sup'], []] |
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136 |
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137 See :func:`split` for a list-returning version. |
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138 |
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139 """ |
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140 if not is_iterable(src): |
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141 raise TypeError('expected an iterable') |
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142 |
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143 if maxsplit is not None: |
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144 maxsplit = int(maxsplit) |
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145 if maxsplit == 0: |
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146 yield [src] |
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147 return |
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148 |
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149 if callable(sep): |
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150 sep_func = sep |
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151 elif not is_scalar(sep): |
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152 sep = frozenset(sep) |
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153 sep_func = lambda x: x in sep |
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154 else: |
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155 sep_func = lambda x: x == sep |
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156 |
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157 cur_group = [] |
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158 split_count = 0 |
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159 for s in src: |
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160 if maxsplit is not None and split_count >= maxsplit: |
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161 sep_func = lambda x: False |
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162 if sep_func(s): |
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163 if sep is None and not cur_group: |
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164 # If sep is none, str.split() "groups" separators |
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165 # check the str.split() docs for more info |
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166 continue |
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167 split_count += 1 |
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168 yield cur_group |
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169 cur_group = [] |
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170 else: |
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171 cur_group.append(s) |
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172 |
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173 if cur_group or sep is not None: |
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174 yield cur_group |
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175 return |
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176 |
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177 |
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178 def lstrip(iterable, strip_value=None): |
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179 """Strips values from the beginning of an iterable. Stripped items will |
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180 match the value of the argument strip_value. Functionality is analigous |
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181 to that of the method str.lstrip. Returns a list. |
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182 |
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183 >>> lstrip(['Foo', 'Bar', 'Bam'], 'Foo') |
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184 ['Bar', 'Bam'] |
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185 |
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186 """ |
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187 return list(lstrip_iter(iterable, strip_value)) |
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188 |
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189 |
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190 def lstrip_iter(iterable, strip_value=None): |
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191 """Strips values from the beginning of an iterable. Stripped items will |
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192 match the value of the argument strip_value. Functionality is analigous |
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193 to that of the method str.lstrip. Returns a generator. |
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194 |
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195 >>> list(lstrip_iter(['Foo', 'Bar', 'Bam'], 'Foo')) |
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196 ['Bar', 'Bam'] |
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197 |
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198 """ |
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199 iterator = iter(iterable) |
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200 for i in iterator: |
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201 if i != strip_value: |
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202 yield i |
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203 break |
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204 for i in iterator: |
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205 yield i |
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206 |
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207 |
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208 def rstrip(iterable, strip_value=None): |
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209 """Strips values from the end of an iterable. Stripped items will |
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210 match the value of the argument strip_value. Functionality is analigous |
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211 to that of the method str.rstrip. Returns a list. |
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212 |
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213 >>> rstrip(['Foo', 'Bar', 'Bam'], 'Bam') |
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214 ['Foo', 'Bar'] |
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215 |
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216 """ |
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217 return list(rstrip_iter(iterable,strip_value)) |
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218 |
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219 |
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220 def rstrip_iter(iterable, strip_value=None): |
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221 """Strips values from the end of an iterable. Stripped items will |
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222 match the value of the argument strip_value. Functionality is analigous |
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223 to that of the method str.rstrip. Returns a generator. |
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224 |
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225 >>> list(rstrip_iter(['Foo', 'Bar', 'Bam'], 'Bam')) |
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226 ['Foo', 'Bar'] |
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227 |
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228 """ |
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229 iterator = iter(iterable) |
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230 for i in iterator: |
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231 if i == strip_value: |
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232 cache = list() |
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233 cache.append(i) |
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234 broken = False |
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235 for i in iterator: |
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236 if i == strip_value: |
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237 cache.append(i) |
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238 else: |
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239 broken = True |
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240 break |
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241 if not broken: # Return to caller here because the end of the |
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242 return # iterator has been reached |
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243 for t in cache: |
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244 yield t |
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245 yield i |
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246 |
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247 |
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248 def strip(iterable, strip_value=None): |
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249 """Strips values from the beginning and end of an iterable. Stripped items |
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250 will match the value of the argument strip_value. Functionality is |
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251 analigous to that of the method str.strip. Returns a list. |
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252 |
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253 >>> strip(['Fu', 'Foo', 'Bar', 'Bam', 'Fu'], 'Fu') |
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254 ['Foo', 'Bar', 'Bam'] |
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255 |
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256 """ |
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257 return list(strip_iter(iterable,strip_value)) |
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258 |
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259 |
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260 def strip_iter(iterable,strip_value=None): |
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261 """Strips values from the beginning and end of an iterable. Stripped items |
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262 will match the value of the argument strip_value. Functionality is |
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263 analigous to that of the method str.strip. Returns a generator. |
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264 |
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265 >>> list(strip_iter(['Fu', 'Foo', 'Bar', 'Bam', 'Fu'], 'Fu')) |
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266 ['Foo', 'Bar', 'Bam'] |
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267 |
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268 """ |
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269 return rstrip_iter(lstrip_iter(iterable,strip_value),strip_value) |
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270 |
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271 |
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272 def chunked(src, size, count=None, **kw): |
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273 """Returns a list of *count* chunks, each with *size* elements, |
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274 generated from iterable *src*. If *src* is not evenly divisible by |
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275 *size*, the final chunk will have fewer than *size* elements. |
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276 Provide the *fill* keyword argument to provide a pad value and |
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277 enable padding, otherwise no padding will take place. |
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278 |
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279 >>> chunked(range(10), 3) |
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280 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
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281 >>> chunked(range(10), 3, fill=None) |
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282 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
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283 >>> chunked(range(10), 3, count=2) |
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284 [[0, 1, 2], [3, 4, 5]] |
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285 |
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286 See :func:`chunked_iter` for more info. |
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287 """ |
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288 chunk_iter = chunked_iter(src, size, **kw) |
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289 if count is None: |
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290 return list(chunk_iter) |
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291 else: |
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292 return list(itertools.islice(chunk_iter, count)) |
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293 |
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294 |
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295 def chunked_iter(src, size, **kw): |
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296 """Generates *size*-sized chunks from *src* iterable. Unless the |
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297 optional *fill* keyword argument is provided, iterables not evenly |
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298 divisible by *size* will have a final chunk that is smaller than |
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299 *size*. |
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300 |
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301 >>> list(chunked_iter(range(10), 3)) |
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302 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
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303 >>> list(chunked_iter(range(10), 3, fill=None)) |
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304 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
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305 |
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306 Note that ``fill=None`` in fact uses ``None`` as the fill value. |
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307 """ |
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308 # TODO: add count kwarg? |
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309 if not is_iterable(src): |
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310 raise TypeError('expected an iterable') |
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311 size = int(size) |
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312 if size <= 0: |
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313 raise ValueError('expected a positive integer chunk size') |
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314 do_fill = True |
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315 try: |
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316 fill_val = kw.pop('fill') |
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317 except KeyError: |
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318 do_fill = False |
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319 fill_val = None |
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320 if kw: |
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321 raise ValueError('got unexpected keyword arguments: %r' % kw.keys()) |
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322 if not src: |
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323 return |
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324 postprocess = lambda chk: chk |
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325 if isinstance(src, basestring): |
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326 postprocess = lambda chk, _sep=type(src)(): _sep.join(chk) |
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327 if _IS_PY3 and isinstance(src, bytes): |
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328 postprocess = lambda chk: bytes(chk) |
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329 src_iter = iter(src) |
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330 while True: |
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331 cur_chunk = list(itertools.islice(src_iter, size)) |
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332 if not cur_chunk: |
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333 break |
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334 lc = len(cur_chunk) |
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335 if lc < size and do_fill: |
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336 cur_chunk[lc:] = [fill_val] * (size - lc) |
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337 yield postprocess(cur_chunk) |
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338 return |
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339 |
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340 |
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341 def pairwise(src): |
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342 """Convenience function for calling :func:`windowed` on *src*, with |
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343 *size* set to 2. |
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344 |
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345 >>> pairwise(range(5)) |
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346 [(0, 1), (1, 2), (2, 3), (3, 4)] |
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347 >>> pairwise([]) |
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348 [] |
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349 |
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350 The number of pairs is always one less than the number of elements |
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351 in the iterable passed in, except on empty inputs, which returns |
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352 an empty list. |
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353 """ |
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354 return windowed(src, 2) |
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355 |
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356 |
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357 def pairwise_iter(src): |
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358 """Convenience function for calling :func:`windowed_iter` on *src*, |
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359 with *size* set to 2. |
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360 |
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361 >>> list(pairwise_iter(range(5))) |
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362 [(0, 1), (1, 2), (2, 3), (3, 4)] |
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363 >>> list(pairwise_iter([])) |
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364 [] |
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365 |
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366 The number of pairs is always one less than the number of elements |
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367 in the iterable passed in, or zero, when *src* is empty. |
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368 |
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369 """ |
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370 return windowed_iter(src, 2) |
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371 |
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372 |
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373 def windowed(src, size): |
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374 """Returns tuples with exactly length *size*. If the iterable is |
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375 too short to make a window of length *size*, no tuples are |
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376 returned. See :func:`windowed_iter` for more. |
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377 """ |
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378 return list(windowed_iter(src, size)) |
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379 |
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380 |
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381 def windowed_iter(src, size): |
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382 """Returns tuples with length *size* which represent a sliding |
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383 window over iterable *src*. |
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384 |
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385 >>> list(windowed_iter(range(7), 3)) |
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386 [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)] |
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387 |
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388 If the iterable is too short to make a window of length *size*, |
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389 then no window tuples are returned. |
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390 |
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391 >>> list(windowed_iter(range(3), 5)) |
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392 [] |
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393 """ |
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394 # TODO: lists? (for consistency) |
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395 tees = itertools.tee(src, size) |
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396 try: |
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397 for i, t in enumerate(tees): |
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398 for _ in xrange(i): |
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399 next(t) |
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400 except StopIteration: |
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401 return izip([]) |
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402 return izip(*tees) |
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403 |
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404 |
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405 def xfrange(stop, start=None, step=1.0): |
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406 """Same as :func:`frange`, but generator-based instead of returning a |
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407 list. |
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408 |
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409 >>> tuple(xfrange(1, 3, step=0.75)) |
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410 (1.0, 1.75, 2.5) |
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411 |
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412 See :func:`frange` for more details. |
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413 """ |
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414 if not step: |
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415 raise ValueError('step must be non-zero') |
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416 if start is None: |
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417 start, stop = 0.0, stop * 1.0 |
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418 else: |
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419 # swap when all args are used |
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420 stop, start = start * 1.0, stop * 1.0 |
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421 cur = start |
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422 while cur < stop: |
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423 yield cur |
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424 cur += step |
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425 |
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426 |
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427 def frange(stop, start=None, step=1.0): |
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428 """A :func:`range` clone for float-based ranges. |
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429 |
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430 >>> frange(5) |
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431 [0.0, 1.0, 2.0, 3.0, 4.0] |
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432 >>> frange(6, step=1.25) |
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433 [0.0, 1.25, 2.5, 3.75, 5.0] |
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434 >>> frange(100.5, 101.5, 0.25) |
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435 [100.5, 100.75, 101.0, 101.25] |
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436 >>> frange(5, 0) |
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437 [] |
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438 >>> frange(5, 0, step=-1.25) |
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439 [5.0, 3.75, 2.5, 1.25] |
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440 """ |
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441 if not step: |
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442 raise ValueError('step must be non-zero') |
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443 if start is None: |
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444 start, stop = 0.0, stop * 1.0 |
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445 else: |
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446 # swap when all args are used |
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447 stop, start = start * 1.0, stop * 1.0 |
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448 count = int(math.ceil((stop - start) / step)) |
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449 ret = [None] * count |
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450 if not ret: |
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451 return ret |
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452 ret[0] = start |
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453 for i in xrange(1, count): |
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454 ret[i] = ret[i - 1] + step |
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455 return ret |
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456 |
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457 |
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458 def backoff(start, stop, count=None, factor=2.0, jitter=False): |
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459 """Returns a list of geometrically-increasing floating-point numbers, |
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460 suitable for usage with `exponential backoff`_. Exactly like |
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461 :func:`backoff_iter`, but without the ``'repeat'`` option for |
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462 *count*. See :func:`backoff_iter` for more details. |
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463 |
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464 .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
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465 |
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466 >>> backoff(1, 10) |
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467 [1.0, 2.0, 4.0, 8.0, 10.0] |
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468 """ |
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469 if count == 'repeat': |
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470 raise ValueError("'repeat' supported in backoff_iter, not backoff") |
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471 return list(backoff_iter(start, stop, count=count, |
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472 factor=factor, jitter=jitter)) |
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473 |
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474 |
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475 def backoff_iter(start, stop, count=None, factor=2.0, jitter=False): |
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476 """Generates a sequence of geometrically-increasing floats, suitable |
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477 for usage with `exponential backoff`_. Starts with *start*, |
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478 increasing by *factor* until *stop* is reached, optionally |
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479 stopping iteration once *count* numbers are yielded. *factor* |
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480 defaults to 2. In general retrying with properly-configured |
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481 backoff creates a better-behaved component for a larger service |
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482 ecosystem. |
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483 |
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484 .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
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485 |
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486 >>> list(backoff_iter(1.0, 10.0, count=5)) |
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487 [1.0, 2.0, 4.0, 8.0, 10.0] |
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488 >>> list(backoff_iter(1.0, 10.0, count=8)) |
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489 [1.0, 2.0, 4.0, 8.0, 10.0, 10.0, 10.0, 10.0] |
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490 >>> list(backoff_iter(0.25, 100.0, factor=10)) |
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491 [0.25, 2.5, 25.0, 100.0] |
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492 |
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493 A simplified usage example: |
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494 |
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495 .. code-block:: python |
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496 |
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497 for timeout in backoff_iter(0.25, 5.0): |
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498 try: |
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499 res = network_call() |
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500 break |
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501 except Exception as e: |
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502 log(e) |
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503 time.sleep(timeout) |
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504 |
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505 An enhancement for large-scale systems would be to add variation, |
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506 or *jitter*, to timeout values. This is done to avoid a thundering |
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507 herd on the receiving end of the network call. |
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508 |
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509 Finally, for *count*, the special value ``'repeat'`` can be passed to |
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510 continue yielding indefinitely. |
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511 |
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512 Args: |
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513 |
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514 start (float): Positive number for baseline. |
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515 stop (float): Positive number for maximum. |
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516 count (int): Number of steps before stopping |
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517 iteration. Defaults to the number of steps between *start* and |
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518 *stop*. Pass the string, `'repeat'`, to continue iteration |
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519 indefinitely. |
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520 factor (float): Rate of exponential increase. Defaults to `2.0`, |
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521 e.g., `[1, 2, 4, 8, 16]`. |
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522 jitter (float): A factor between `-1.0` and `1.0`, used to |
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523 uniformly randomize and thus spread out timeouts in a distributed |
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524 system, avoiding rhythm effects. Positive values use the base |
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525 backoff curve as a maximum, negative values use the curve as a |
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526 minimum. Set to 1.0 or `True` for a jitter approximating |
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527 Ethernet's time-tested backoff solution. Defaults to `False`. |
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528 |
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529 """ |
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530 start = float(start) |
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531 stop = float(stop) |
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532 factor = float(factor) |
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533 if start < 0.0: |
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534 raise ValueError('expected start >= 0, not %r' % start) |
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535 if factor < 1.0: |
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536 raise ValueError('expected factor >= 1.0, not %r' % factor) |
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537 if stop == 0.0: |
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538 raise ValueError('expected stop >= 0') |
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539 if stop < start: |
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540 raise ValueError('expected stop >= start, not %r' % stop) |
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541 if count is None: |
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542 denom = start if start else 1 |
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543 count = 1 + math.ceil(math.log(stop/denom, factor)) |
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544 count = count if start else count + 1 |
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545 if count != 'repeat' and count < 0: |
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546 raise ValueError('count must be positive or "repeat", not %r' % count) |
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547 if jitter: |
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548 jitter = float(jitter) |
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549 if not (-1.0 <= jitter <= 1.0): |
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550 raise ValueError('expected jitter -1 <= j <= 1, not: %r' % jitter) |
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551 |
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552 cur, i = start, 0 |
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553 while count == 'repeat' or i < count: |
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554 if not jitter: |
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555 cur_ret = cur |
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556 elif jitter: |
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557 cur_ret = cur - (cur * jitter * random.random()) |
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558 yield cur_ret |
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559 i += 1 |
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560 if cur == 0: |
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561 cur = 1 |
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562 elif cur < stop: |
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563 cur *= factor |
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564 if cur > stop: |
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565 cur = stop |
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566 return |
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567 |
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568 |
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569 def bucketize(src, key=bool, value_transform=None, key_filter=None): |
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570 """Group values in the *src* iterable by the value returned by *key*. |
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571 |
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572 >>> bucketize(range(5)) |
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573 {False: [0], True: [1, 2, 3, 4]} |
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574 >>> is_odd = lambda x: x % 2 == 1 |
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575 >>> bucketize(range(5), is_odd) |
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576 {False: [0, 2, 4], True: [1, 3]} |
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577 |
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578 *key* is :class:`bool` by default, but can either be a callable or a string |
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579 name of the attribute on which to bucketize objects. |
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580 |
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581 >>> bucketize([1+1j, 2+2j, 1, 2], key='real') |
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582 {1.0: [(1+1j), 1], 2.0: [(2+2j), 2]} |
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583 |
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584 Value lists are not deduplicated: |
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585 |
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586 >>> bucketize([None, None, None, 'hello']) |
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587 {False: [None, None, None], True: ['hello']} |
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588 |
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589 Bucketize into more than 3 groups |
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590 |
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591 >>> bucketize(range(10), lambda x: x % 3) |
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592 {0: [0, 3, 6, 9], 1: [1, 4, 7], 2: [2, 5, 8]} |
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593 |
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594 ``bucketize`` has a couple of advanced options useful in certain |
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595 cases. *value_transform* can be used to modify values as they are |
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596 added to buckets, and *key_filter* will allow excluding certain |
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597 buckets from being collected. |
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598 |
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599 >>> bucketize(range(5), value_transform=lambda x: x*x) |
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600 {False: [0], True: [1, 4, 9, 16]} |
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601 |
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602 >>> bucketize(range(10), key=lambda x: x % 3, key_filter=lambda k: k % 3 != 1) |
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603 {0: [0, 3, 6, 9], 2: [2, 5, 8]} |
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604 |
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605 Note in some of these examples there were at most two keys, ``True`` and |
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606 ``False``, and each key present has a list with at least one |
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607 item. See :func:`partition` for a version specialized for binary |
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608 use cases. |
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609 |
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610 """ |
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611 if not is_iterable(src): |
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612 raise TypeError('expected an iterable') |
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613 |
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614 if isinstance(key, basestring): |
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615 key_func = lambda x: getattr(x, key, x) |
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616 elif callable(key): |
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617 key_func = key |
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618 else: |
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619 raise TypeError('expected key to be callable or a string') |
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620 |
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621 if value_transform is None: |
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622 value_transform = lambda x: x |
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623 if not callable(value_transform): |
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624 raise TypeError('expected callable value transform function') |
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625 |
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626 ret = {} |
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627 for val in src: |
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628 key_of_val = key_func(val) |
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629 if key_filter is None or key_filter(key_of_val): |
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630 ret.setdefault(key_of_val, []).append(value_transform(val)) |
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631 return ret |
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632 |
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633 |
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634 def partition(src, key=bool): |
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635 """No relation to :meth:`str.partition`, ``partition`` is like |
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636 :func:`bucketize`, but for added convenience returns a tuple of |
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637 ``(truthy_values, falsy_values)``. |
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638 |
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639 >>> nonempty, empty = partition(['', '', 'hi', '', 'bye']) |
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640 >>> nonempty |
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641 ['hi', 'bye'] |
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642 |
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643 *key* defaults to :class:`bool`, but can be carefully overridden to |
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644 use either a function that returns either ``True`` or ``False`` or |
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645 a string name of the attribute on which to partition objects. |
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646 |
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647 >>> import string |
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648 >>> is_digit = lambda x: x in string.digits |
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649 >>> decimal_digits, hexletters = partition(string.hexdigits, is_digit) |
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650 >>> ''.join(decimal_digits), ''.join(hexletters) |
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651 ('0123456789', 'abcdefABCDEF') |
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652 """ |
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653 bucketized = bucketize(src, key) |
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654 return bucketized.get(True, []), bucketized.get(False, []) |
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655 |
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656 |
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657 def unique(src, key=None): |
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658 """``unique()`` returns a list of unique values, as determined by |
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659 *key*, in the order they first appeared in the input iterable, |
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660 *src*. |
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661 |
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662 >>> ones_n_zeros = '11010110001010010101010' |
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663 >>> ''.join(unique(ones_n_zeros)) |
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664 '10' |
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665 |
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666 See :func:`unique_iter` docs for more details. |
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667 """ |
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668 return list(unique_iter(src, key)) |
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669 |
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670 |
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671 def unique_iter(src, key=None): |
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672 """Yield unique elements from the iterable, *src*, based on *key*, |
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673 in the order in which they first appeared in *src*. |
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674 |
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675 >>> repetitious = [1, 2, 3] * 10 |
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676 >>> list(unique_iter(repetitious)) |
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677 [1, 2, 3] |
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678 |
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679 By default, *key* is the object itself, but *key* can either be a |
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680 callable or, for convenience, a string name of the attribute on |
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681 which to uniqueify objects, falling back on identity when the |
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682 attribute is not present. |
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683 |
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684 >>> pleasantries = ['hi', 'hello', 'ok', 'bye', 'yes'] |
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685 >>> list(unique_iter(pleasantries, key=lambda x: len(x))) |
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686 ['hi', 'hello', 'bye'] |
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687 """ |
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688 if not is_iterable(src): |
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689 raise TypeError('expected an iterable, not %r' % type(src)) |
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690 if key is None: |
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691 key_func = lambda x: x |
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692 elif callable(key): |
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693 key_func = key |
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694 elif isinstance(key, basestring): |
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695 key_func = lambda x: getattr(x, key, x) |
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696 else: |
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697 raise TypeError('"key" expected a string or callable, not %r' % key) |
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698 seen = set() |
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699 for i in src: |
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700 k = key_func(i) |
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701 if k not in seen: |
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702 seen.add(k) |
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703 yield i |
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704 return |
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705 |
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706 |
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707 def redundant(src, key=None, groups=False): |
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708 """The complement of :func:`unique()`. |
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709 |
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710 By default returns non-unique/duplicate values as a list of the |
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711 *first* redundant value in *src*. Pass ``groups=True`` to get |
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712 groups of all values with redundancies, ordered by position of the |
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713 first redundant value. This is useful in conjunction with some |
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714 normalizing *key* function. |
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715 |
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716 >>> redundant([1, 2, 3, 4]) |
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717 [] |
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718 >>> redundant([1, 2, 3, 2, 3, 3, 4]) |
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719 [2, 3] |
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720 >>> redundant([1, 2, 3, 2, 3, 3, 4], groups=True) |
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721 [[2, 2], [3, 3, 3]] |
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722 |
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723 An example using a *key* function to do case-insensitive |
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724 redundancy detection. |
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725 |
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726 >>> redundant(['hi', 'Hi', 'HI', 'hello'], key=str.lower) |
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727 ['Hi'] |
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728 >>> redundant(['hi', 'Hi', 'HI', 'hello'], groups=True, key=str.lower) |
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729 [['hi', 'Hi', 'HI']] |
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|
730 |
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|
731 *key* should also be used when the values in *src* are not hashable. |
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|
732 |
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733 .. note:: |
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734 |
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735 This output of this function is designed for reporting |
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736 duplicates in contexts when a unique input is desired. Due to |
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737 the grouped return type, there is no streaming equivalent of |
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738 this function for the time being. |
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739 |
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740 """ |
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741 if key is None: |
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742 pass |
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743 elif callable(key): |
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744 key_func = key |
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745 elif isinstance(key, basestring): |
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746 key_func = lambda x: getattr(x, key, x) |
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747 else: |
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748 raise TypeError('"key" expected a string or callable, not %r' % key) |
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749 seen = {} # key to first seen item |
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750 redundant_order = [] |
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751 redundant_groups = {} |
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752 for i in src: |
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753 k = key_func(i) if key else i |
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754 if k not in seen: |
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755 seen[k] = i |
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756 else: |
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757 if k in redundant_groups: |
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758 if groups: |
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759 redundant_groups[k].append(i) |
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760 else: |
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761 redundant_order.append(k) |
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762 redundant_groups[k] = [seen[k], i] |
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763 if not groups: |
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764 ret = [redundant_groups[k][1] for k in redundant_order] |
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765 else: |
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766 ret = [redundant_groups[k] for k in redundant_order] |
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767 return ret |
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768 |
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769 |
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770 def one(src, default=None, key=None): |
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771 """Along the same lines as builtins, :func:`all` and :func:`any`, and |
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772 similar to :func:`first`, ``one()`` returns the single object in |
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773 the given iterable *src* that evaluates to ``True``, as determined |
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774 by callable *key*. If unset, *key* defaults to :class:`bool`. If |
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|
775 no such objects are found, *default* is returned. If *default* is |
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|
776 not passed, ``None`` is returned. |
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|
777 |
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778 If *src* has more than one object that evaluates to ``True``, or |
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779 if there is no object that fulfills such condition, return |
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|
780 *default*. It's like an `XOR`_ over an iterable. |
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|
781 |
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|
782 >>> one((True, False, False)) |
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783 True |
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784 >>> one((True, False, True)) |
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|
785 >>> one((0, 0, 'a')) |
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|
786 'a' |
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787 >>> one((0, False, None)) |
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788 >>> one((True, True), default=False) |
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789 False |
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790 >>> bool(one(('', 1))) |
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791 True |
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792 >>> one((10, 20, 30, 42), key=lambda i: i > 40) |
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793 42 |
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794 |
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795 See `MartÃn Gaitán's original repo`_ for further use cases. |
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796 |
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797 .. _MartÃn Gaitán's original repo: https://github.com/mgaitan/one |
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798 .. _XOR: https://en.wikipedia.org/wiki/Exclusive_or |
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799 |
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800 """ |
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801 ones = list(itertools.islice(filter(key, src), 2)) |
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802 return ones[0] if len(ones) == 1 else default |
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803 |
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804 |
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805 def first(iterable, default=None, key=None): |
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806 """Return first element of *iterable* that evaluates to ``True``, else |
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807 return ``None`` or optional *default*. Similar to :func:`one`. |
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808 |
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809 >>> first([0, False, None, [], (), 42]) |
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810 42 |
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811 >>> first([0, False, None, [], ()]) is None |
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812 True |
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813 >>> first([0, False, None, [], ()], default='ohai') |
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814 'ohai' |
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815 >>> import re |
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816 >>> m = first(re.match(regex, 'abc') for regex in ['b.*', 'a(.*)']) |
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817 >>> m.group(1) |
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818 'bc' |
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819 |
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820 The optional *key* argument specifies a one-argument predicate function |
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821 like that used for *filter()*. The *key* argument, if supplied, should be |
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822 in keyword form. For example, finding the first even number in an iterable: |
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823 |
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824 >>> first([1, 1, 3, 4, 5], key=lambda x: x % 2 == 0) |
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825 4 |
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826 |
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827 Contributed by Hynek Schlawack, author of `the original standalone module`_. |
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828 |
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829 .. _the original standalone module: https://github.com/hynek/first |
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830 """ |
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831 return next(filter(key, iterable), default) |
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832 |
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833 |
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834 def flatten_iter(iterable): |
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835 """``flatten_iter()`` yields all the elements from *iterable* while |
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836 collapsing any nested iterables. |
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837 |
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838 >>> nested = [[1, 2], [[3], [4, 5]]] |
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839 >>> list(flatten_iter(nested)) |
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840 [1, 2, 3, 4, 5] |
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841 """ |
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842 for item in iterable: |
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843 if isinstance(item, Iterable) and not isinstance(item, basestring): |
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844 for subitem in flatten_iter(item): |
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845 yield subitem |
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846 else: |
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847 yield item |
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848 |
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849 def flatten(iterable): |
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850 """``flatten()`` returns a collapsed list of all the elements from |
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851 *iterable* while collapsing any nested iterables. |
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852 |
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853 >>> nested = [[1, 2], [[3], [4, 5]]] |
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854 >>> flatten(nested) |
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855 [1, 2, 3, 4, 5] |
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856 """ |
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857 return list(flatten_iter(iterable)) |
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858 |
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859 |
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860 def same(iterable, ref=_UNSET): |
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861 """``same()`` returns ``True`` when all values in *iterable* are |
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862 equal to one another, or optionally a reference value, |
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863 *ref*. Similar to :func:`all` and :func:`any` in that it evaluates |
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864 an iterable and returns a :class:`bool`. ``same()`` returns |
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865 ``True`` for empty iterables. |
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866 |
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867 >>> same([]) |
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868 True |
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869 >>> same([1]) |
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870 True |
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871 >>> same(['a', 'a', 'a']) |
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872 True |
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873 >>> same(range(20)) |
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874 False |
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875 >>> same([[], []]) |
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876 True |
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877 >>> same([[], []], ref='test') |
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878 False |
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879 |
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880 """ |
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881 iterator = iter(iterable) |
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882 if ref is _UNSET: |
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883 ref = next(iterator, ref) |
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884 return all(val == ref for val in iterator) |
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885 |
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886 |
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887 def default_visit(path, key, value): |
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888 # print('visit(%r, %r, %r)' % (path, key, value)) |
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889 return key, value |
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890 |
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891 # enable the extreme: monkeypatching iterutils with a different default_visit |
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892 _orig_default_visit = default_visit |
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893 |
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894 |
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895 def default_enter(path, key, value): |
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896 # print('enter(%r, %r)' % (key, value)) |
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897 if isinstance(value, basestring): |
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898 return value, False |
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899 elif isinstance(value, Mapping): |
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900 return value.__class__(), ItemsView(value) |
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901 elif isinstance(value, Sequence): |
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902 return value.__class__(), enumerate(value) |
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903 elif isinstance(value, Set): |
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904 return value.__class__(), enumerate(value) |
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905 else: |
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906 # files, strings, other iterables, and scalars are not |
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907 # traversed |
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908 return value, False |
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909 |
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910 |
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911 def default_exit(path, key, old_parent, new_parent, new_items): |
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912 # print('exit(%r, %r, %r, %r, %r)' |
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913 # % (path, key, old_parent, new_parent, new_items)) |
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914 ret = new_parent |
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915 if isinstance(new_parent, Mapping): |
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916 new_parent.update(new_items) |
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917 elif isinstance(new_parent, Sequence): |
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918 vals = [v for i, v in new_items] |
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919 try: |
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920 new_parent.extend(vals) |
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921 except AttributeError: |
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922 ret = new_parent.__class__(vals) # tuples |
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923 elif isinstance(new_parent, Set): |
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924 vals = [v for i, v in new_items] |
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925 try: |
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926 new_parent.update(vals) |
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927 except AttributeError: |
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928 ret = new_parent.__class__(vals) # frozensets |
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929 else: |
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930 raise RuntimeError('unexpected iterable type: %r' % type(new_parent)) |
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931 return ret |
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932 |
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933 |
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934 def remap(root, visit=default_visit, enter=default_enter, exit=default_exit, |
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935 **kwargs): |
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936 """The remap ("recursive map") function is used to traverse and |
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937 transform nested structures. Lists, tuples, sets, and dictionaries |
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938 are just a few of the data structures nested into heterogenous |
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939 tree-like structures that are so common in programming. |
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940 Unfortunately, Python's built-in ways to manipulate collections |
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941 are almost all flat. List comprehensions may be fast and succinct, |
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942 but they do not recurse, making it tedious to apply quick changes |
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943 or complex transforms to real-world data. |
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944 |
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945 remap goes where list comprehensions cannot. |
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946 |
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947 Here's an example of removing all Nones from some data: |
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948 |
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949 >>> from pprint import pprint |
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950 >>> reviews = {'Star Trek': {'TNG': 10, 'DS9': 8.5, 'ENT': None}, |
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951 ... 'Babylon 5': 6, 'Dr. Who': None} |
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952 >>> pprint(remap(reviews, lambda p, k, v: v is not None)) |
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953 {'Babylon 5': 6, 'Star Trek': {'DS9': 8.5, 'TNG': 10}} |
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954 |
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955 Notice how both Nones have been removed despite the nesting in the |
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956 dictionary. Not bad for a one-liner, and that's just the beginning. |
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957 See `this remap cookbook`_ for more delicious recipes. |
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958 |
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959 .. _this remap cookbook: http://sedimental.org/remap.html |
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960 |
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961 remap takes four main arguments: the object to traverse and three |
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962 optional callables which determine how the remapped object will be |
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963 created. |
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964 |
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965 Args: |
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966 |
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967 root: The target object to traverse. By default, remap |
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968 supports iterables like :class:`list`, :class:`tuple`, |
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969 :class:`dict`, and :class:`set`, but any object traversable by |
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970 *enter* will work. |
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971 visit (callable): This function is called on every item in |
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972 *root*. It must accept three positional arguments, *path*, |
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973 *key*, and *value*. *path* is simply a tuple of parents' |
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974 keys. *visit* should return the new key-value pair. It may |
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975 also return ``True`` as shorthand to keep the old item |
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976 unmodified, or ``False`` to drop the item from the new |
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977 structure. *visit* is called after *enter*, on the new parent. |
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978 |
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979 The *visit* function is called for every item in root, |
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980 including duplicate items. For traversable values, it is |
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981 called on the new parent object, after all its children |
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982 have been visited. The default visit behavior simply |
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983 returns the key-value pair unmodified. |
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984 enter (callable): This function controls which items in *root* |
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985 are traversed. It accepts the same arguments as *visit*: the |
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986 path, the key, and the value of the current item. It returns a |
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987 pair of the blank new parent, and an iterator over the items |
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988 which should be visited. If ``False`` is returned instead of |
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989 an iterator, the value will not be traversed. |
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990 |
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991 The *enter* function is only called once per unique value. The |
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992 default enter behavior support mappings, sequences, and |
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993 sets. Strings and all other iterables will not be traversed. |
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994 exit (callable): This function determines how to handle items |
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995 once they have been visited. It gets the same three |
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996 arguments as the other functions -- *path*, *key*, *value* |
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997 -- plus two more: the blank new parent object returned |
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998 from *enter*, and a list of the new items, as remapped by |
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999 *visit*. |
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1000 |
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1001 Like *enter*, the *exit* function is only called once per |
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1002 unique value. The default exit behavior is to simply add |
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1003 all new items to the new parent, e.g., using |
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1004 :meth:`list.extend` and :meth:`dict.update` to add to the |
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1005 new parent. Immutable objects, such as a :class:`tuple` or |
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1006 :class:`namedtuple`, must be recreated from scratch, but |
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1007 use the same type as the new parent passed back from the |
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1008 *enter* function. |
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1009 reraise_visit (bool): A pragmatic convenience for the *visit* |
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1010 callable. When set to ``False``, remap ignores any errors |
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1011 raised by the *visit* callback. Items causing exceptions |
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1012 are kept. See examples for more details. |
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1013 |
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1014 remap is designed to cover the majority of cases with just the |
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1015 *visit* callable. While passing in multiple callables is very |
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1016 empowering, remap is designed so very few cases should require |
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1017 passing more than one function. |
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1018 |
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1019 When passing *enter* and *exit*, it's common and easiest to build |
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1020 on the default behavior. Simply add ``from boltons.iterutils import |
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1021 default_enter`` (or ``default_exit``), and have your enter/exit |
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1022 function call the default behavior before or after your custom |
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1023 logic. See `this example`_. |
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1024 |
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1025 Duplicate and self-referential objects (aka reference loops) are |
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1026 automatically handled internally, `as shown here`_. |
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1027 |
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1028 .. _this example: http://sedimental.org/remap.html#sort_all_lists |
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1029 .. _as shown here: http://sedimental.org/remap.html#corner_cases |
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1030 |
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1031 """ |
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1032 # TODO: improve argument formatting in sphinx doc |
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1033 # TODO: enter() return (False, items) to continue traverse but cancel copy? |
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1034 if not callable(visit): |
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1035 raise TypeError('visit expected callable, not: %r' % visit) |
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1036 if not callable(enter): |
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1037 raise TypeError('enter expected callable, not: %r' % enter) |
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1038 if not callable(exit): |
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1039 raise TypeError('exit expected callable, not: %r' % exit) |
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1040 reraise_visit = kwargs.pop('reraise_visit', True) |
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1041 if kwargs: |
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1042 raise TypeError('unexpected keyword arguments: %r' % kwargs.keys()) |
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1043 |
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1044 path, registry, stack = (), {}, [(None, root)] |
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1045 new_items_stack = [] |
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1046 while stack: |
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1047 key, value = stack.pop() |
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1048 id_value = id(value) |
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1049 if key is _REMAP_EXIT: |
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1050 key, new_parent, old_parent = value |
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1051 id_value = id(old_parent) |
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1052 path, new_items = new_items_stack.pop() |
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1053 value = exit(path, key, old_parent, new_parent, new_items) |
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1054 registry[id_value] = value |
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1055 if not new_items_stack: |
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1056 continue |
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1057 elif id_value in registry: |
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1058 value = registry[id_value] |
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1059 else: |
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1060 res = enter(path, key, value) |
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1061 try: |
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1062 new_parent, new_items = res |
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1063 except TypeError: |
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1064 # TODO: handle False? |
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1065 raise TypeError('enter should return a tuple of (new_parent,' |
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1066 ' items_iterator), not: %r' % res) |
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1067 if new_items is not False: |
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1068 # traverse unless False is explicitly passed |
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1069 registry[id_value] = new_parent |
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1070 new_items_stack.append((path, [])) |
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1071 if value is not root: |
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1072 path += (key,) |
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1073 stack.append((_REMAP_EXIT, (key, new_parent, value))) |
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1074 if new_items: |
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1075 stack.extend(reversed(list(new_items))) |
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1076 continue |
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1077 if visit is _orig_default_visit: |
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1078 # avoid function call overhead by inlining identity operation |
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1079 visited_item = (key, value) |
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1080 else: |
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1081 try: |
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1082 visited_item = visit(path, key, value) |
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1083 except Exception: |
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1084 if reraise_visit: |
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1085 raise |
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1086 visited_item = True |
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1087 if visited_item is False: |
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1088 continue # drop |
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1089 elif visited_item is True: |
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1090 visited_item = (key, value) |
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1091 # TODO: typecheck? |
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1092 # raise TypeError('expected (key, value) from visit(),' |
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1093 # ' not: %r' % visited_item) |
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1094 try: |
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1095 new_items_stack[-1][1].append(visited_item) |
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1096 except IndexError: |
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1097 raise TypeError('expected remappable root, not: %r' % root) |
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1098 return value |
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1099 |
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1100 |
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1101 class PathAccessError(KeyError, IndexError, TypeError): |
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1102 """An amalgamation of KeyError, IndexError, and TypeError, |
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1103 representing what can occur when looking up a path in a nested |
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1104 object. |
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1105 """ |
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1106 def __init__(self, exc, seg, path): |
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1107 self.exc = exc |
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1108 self.seg = seg |
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1109 self.path = path |
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1110 |
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1111 def __repr__(self): |
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1112 cn = self.__class__.__name__ |
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1113 return '%s(%r, %r, %r)' % (cn, self.exc, self.seg, self.path) |
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1114 |
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1115 def __str__(self): |
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1116 return ('could not access %r from path %r, got error: %r' |
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1117 % (self.seg, self.path, self.exc)) |
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1118 |
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1119 |
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1120 def get_path(root, path, default=_UNSET): |
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1121 """Retrieve a value from a nested object via a tuple representing the |
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1122 lookup path. |
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1123 |
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1124 >>> root = {'a': {'b': {'c': [[1], [2], [3]]}}} |
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1125 >>> get_path(root, ('a', 'b', 'c', 2, 0)) |
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1126 3 |
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1127 |
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1128 The path format is intentionally consistent with that of |
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1129 :func:`remap`. |
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1130 |
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1131 One of get_path's chief aims is improved error messaging. EAFP is |
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1132 great, but the error messages are not. |
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1133 |
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1134 For instance, ``root['a']['b']['c'][2][1]`` gives back |
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1135 ``IndexError: list index out of range`` |
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1136 |
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1137 What went out of range where? get_path currently raises |
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1138 ``PathAccessError: could not access 2 from path ('a', 'b', 'c', 2, |
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1139 1), got error: IndexError('list index out of range',)``, a |
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1140 subclass of IndexError and KeyError. |
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1141 |
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1142 You can also pass a default that covers the entire operation, |
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1143 should the lookup fail at any level. |
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1144 |
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1145 Args: |
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1146 root: The target nesting of dictionaries, lists, or other |
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1147 objects supporting ``__getitem__``. |
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1148 path (tuple): A list of strings and integers to be successively |
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1149 looked up within *root*. |
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1150 default: The value to be returned should any |
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1151 ``PathAccessError`` exceptions be raised. |
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1152 """ |
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1153 if isinstance(path, basestring): |
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1154 path = path.split('.') |
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1155 cur = root |
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1156 try: |
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1157 for seg in path: |
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1158 try: |
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1159 cur = cur[seg] |
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1160 except (KeyError, IndexError) as exc: |
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1161 raise PathAccessError(exc, seg, path) |
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1162 except TypeError as exc: |
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1163 # either string index in a list, or a parent that |
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1164 # doesn't support indexing |
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1165 try: |
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1166 seg = int(seg) |
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1167 cur = cur[seg] |
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1168 except (ValueError, KeyError, IndexError, TypeError): |
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1169 if not is_iterable(cur): |
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1170 exc = TypeError('%r object is not indexable' |
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1171 % type(cur).__name__) |
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1172 raise PathAccessError(exc, seg, path) |
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1173 except PathAccessError: |
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1174 if default is _UNSET: |
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1175 raise |
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1176 return default |
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1177 return cur |
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1178 |
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1179 |
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1180 def research(root, query=lambda p, k, v: True, reraise=False): |
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1181 """The :func:`research` function uses :func:`remap` to recurse over |
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1182 any data nested in *root*, and find values which match a given |
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1183 criterion, specified by the *query* callable. |
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1184 |
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1185 Results are returned as a list of ``(path, value)`` pairs. The |
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1186 paths are tuples in the same format accepted by |
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1187 :func:`get_path`. This can be useful for comparing values nested |
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1188 in two or more different structures. |
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1189 |
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1190 Here's a simple example that finds all integers: |
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1191 |
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1192 >>> root = {'a': {'b': 1, 'c': (2, 'd', 3)}, 'e': None} |
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1193 >>> res = research(root, query=lambda p, k, v: isinstance(v, int)) |
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1194 >>> print(sorted(res)) |
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1195 [(('a', 'b'), 1), (('a', 'c', 0), 2), (('a', 'c', 2), 3)] |
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1196 |
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1197 Note how *query* follows the same, familiar ``path, key, value`` |
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1198 signature as the ``visit`` and ``enter`` functions on |
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1199 :func:`remap`, and returns a :class:`bool`. |
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1200 |
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1201 Args: |
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1202 root: The target object to search. Supports the same types of |
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1203 objects as :func:`remap`, including :class:`list`, |
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1204 :class:`tuple`, :class:`dict`, and :class:`set`. |
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1205 query (callable): The function called on every object to |
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1206 determine whether to include it in the search results. The |
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1207 callable must accept three arguments, *path*, *key*, and |
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1208 *value*, commonly abbreviated *p*, *k*, and *v*, same as |
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1209 *enter* and *visit* from :func:`remap`. |
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1210 reraise (bool): Whether to reraise exceptions raised by *query* |
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1211 or to simply drop the result that caused the error. |
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1212 |
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1213 |
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1214 With :func:`research` it's easy to inspect the details of a data |
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1215 structure, like finding values that are at a certain depth (using |
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1216 ``len(p)``) and much more. If more advanced functionality is |
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1217 needed, check out the code and make your own :func:`remap` |
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1218 wrapper, and consider `submitting a patch`_! |
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1219 |
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1220 .. _submitting a patch: https://github.com/mahmoud/boltons/pulls |
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1221 """ |
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1222 ret = [] |
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1223 |
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1224 if not callable(query): |
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1225 raise TypeError('query expected callable, not: %r' % query) |
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1226 |
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1227 def enter(path, key, value): |
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1228 try: |
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1229 if query(path, key, value): |
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1230 ret.append((path + (key,), value)) |
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1231 except Exception: |
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1232 if reraise: |
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1233 raise |
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1234 return default_enter(path, key, value) |
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1235 |
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1236 remap(root, enter=enter) |
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1237 return ret |
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1238 |
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1239 |
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1240 # TODO: recollect() |
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1241 # TODO: refilter() |
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1242 # TODO: reiter() |
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1243 |
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1244 |
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1245 # GUID iterators: 10x faster and somewhat more compact than uuid. |
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1246 |
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1247 class GUIDerator(object): |
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1248 """The GUIDerator is an iterator that yields a globally-unique |
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1249 identifier (GUID) on every iteration. The GUIDs produced are |
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1250 hexadecimal strings. |
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1251 |
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1252 Testing shows it to be around 12x faster than the uuid module. By |
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1253 default it is also more compact, partly due to its default 96-bit |
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1254 (24-hexdigit) length. 96 bits of randomness means that there is a |
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1255 1 in 2 ^ 32 chance of collision after 2 ^ 64 iterations. If more |
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1256 or less uniqueness is desired, the *size* argument can be adjusted |
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1257 accordingly. |
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1258 |
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1259 Args: |
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1260 size (int): character length of the GUID, defaults to 24. Lengths |
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1261 between 20 and 36 are considered valid. |
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1262 |
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1263 The GUIDerator has built-in fork protection that causes it to |
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1264 detect a fork on next iteration and reseed accordingly. |
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1265 |
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1266 """ |
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1267 def __init__(self, size=24): |
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1268 self.size = size |
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1269 if size < 20 or size > 36: |
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1270 raise ValueError('expected 20 < size <= 36') |
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1271 import hashlib |
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1272 self._sha1 = hashlib.sha1 |
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1273 self.count = itertools.count() |
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1274 self.reseed() |
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1275 |
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1276 def reseed(self): |
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1277 import socket |
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1278 self.pid = os.getpid() |
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1279 self.salt = '-'.join([str(self.pid), |
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1280 socket.gethostname() or b'<nohostname>', |
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1281 str(time.time()), |
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1282 codecs.encode(os.urandom(6), |
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1283 'hex_codec').decode('ascii')]) |
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1284 # that codecs trick is the best/only way to get a bytes to |
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1285 # hexbytes in py2/3 |
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1286 return |
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1287 |
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1288 def __iter__(self): |
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1289 return self |
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1290 |
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1291 if _IS_PY3: |
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1292 def __next__(self): |
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1293 if os.getpid() != self.pid: |
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1294 self.reseed() |
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1295 target_bytes = (self.salt + str(next(self.count))).encode('utf8') |
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1296 hash_text = self._sha1(target_bytes).hexdigest()[:self.size] |
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1297 return hash_text |
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1298 else: |
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1299 def __next__(self): |
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1300 if os.getpid() != self.pid: |
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1301 self.reseed() |
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1302 return self._sha1(self.salt + |
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1303 str(next(self.count))).hexdigest()[:self.size] |
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1304 |
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1305 next = __next__ |
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1306 |
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1307 |
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1308 class SequentialGUIDerator(GUIDerator): |
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1309 """Much like the standard GUIDerator, the SequentialGUIDerator is an |
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1310 iterator that yields a globally-unique identifier (GUID) on every |
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1311 iteration. The GUIDs produced are hexadecimal strings. |
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1312 |
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1313 The SequentialGUIDerator differs in that it picks a starting GUID |
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1314 value and increments every iteration. This yields GUIDs which are |
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1315 of course unique, but also ordered and lexicographically sortable. |
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1316 |
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1317 The SequentialGUIDerator is around 50% faster than the normal |
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1318 GUIDerator, making it almost 20x as fast as the built-in uuid |
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1319 module. By default it is also more compact, partly due to its |
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1320 96-bit (24-hexdigit) default length. 96 bits of randomness means that |
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1321 there is a 1 in 2 ^ 32 chance of collision after 2 ^ 64 |
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1322 iterations. If more or less uniqueness is desired, the *size* |
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1323 argument can be adjusted accordingly. |
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1324 |
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1325 Args: |
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1326 size (int): character length of the GUID, defaults to 24. |
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1327 |
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1328 Note that with SequentialGUIDerator there is a chance of GUIDs |
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1329 growing larger than the size configured. The SequentialGUIDerator |
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1330 has built-in fork protection that causes it to detect a fork on |
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1331 next iteration and reseed accordingly. |
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1332 |
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1333 """ |
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1334 |
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1335 if _IS_PY3: |
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1336 def reseed(self): |
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1337 super(SequentialGUIDerator, self).reseed() |
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1338 start_str = self._sha1(self.salt.encode('utf8')).hexdigest() |
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1339 self.start = int(start_str[:self.size], 16) |
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1340 self.start |= (1 << ((self.size * 4) - 2)) |
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1341 else: |
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1342 def reseed(self): |
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1343 super(SequentialGUIDerator, self).reseed() |
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1344 start_str = self._sha1(self.salt).hexdigest() |
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1345 self.start = int(start_str[:self.size], 16) |
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1346 self.start |= (1 << ((self.size * 4) - 2)) |
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1347 |
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1348 def __next__(self): |
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1349 if os.getpid() != self.pid: |
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1350 self.reseed() |
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1351 return '%x' % (next(self.count) + self.start) |
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1352 |
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1353 next = __next__ |
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1354 |
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1355 |
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1356 guid_iter = GUIDerator() |
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1357 seq_guid_iter = SequentialGUIDerator() |
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1358 |
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1359 |
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1360 def soft_sorted(iterable, first=None, last=None, key=None, reverse=False): |
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1361 """For when you care about the order of some elements, but not about |
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1362 others. |
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1363 |
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1364 Use this to float to the top and/or sink to the bottom a specific |
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1365 ordering, while sorting the rest of the elements according to |
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1366 normal :func:`sorted` rules. |
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1367 |
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1368 >>> soft_sorted(['two', 'b', 'one', 'a'], first=['one', 'two']) |
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1369 ['one', 'two', 'a', 'b'] |
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1370 >>> soft_sorted(range(7), first=[6, 15], last=[2, 4], reverse=True) |
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1371 [6, 5, 3, 1, 0, 2, 4] |
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1372 >>> import string |
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1373 >>> ''.join(soft_sorted(string.hexdigits, first='za1', last='b', key=str.lower)) |
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1374 'aA1023456789cCdDeEfFbB' |
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1375 |
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1376 Args: |
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1377 iterable (list): A list or other iterable to sort. |
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1378 first (list): A sequence to enforce for elements which should |
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1379 appear at the beginning of the returned list. |
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1380 last (list): A sequence to enforce for elements which should |
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1381 appear at the end of the returned list. |
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1382 key (callable): Callable used to generate a comparable key for |
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1383 each item to be sorted, same as the key in |
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1384 :func:`sorted`. Note that entries in *first* and *last* |
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1385 should be the keys for the items. Defaults to |
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1386 passthrough/the identity function. |
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1387 reverse (bool): Whether or not elements not explicitly ordered |
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1388 by *first* and *last* should be in reverse order or not. |
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1389 |
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1390 Returns a new list in sorted order. |
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1391 """ |
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1392 first = first or [] |
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1393 last = last or [] |
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1394 key = key or (lambda x: x) |
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1395 seq = list(iterable) |
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1396 other = [x for x in seq if not ((first and key(x) in first) or (last and key(x) in last))] |
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1397 other.sort(key=key, reverse=reverse) |
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1398 |
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1399 if first: |
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1400 first = sorted([x for x in seq if key(x) in first], key=lambda x: first.index(key(x))) |
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1401 if last: |
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1402 last = sorted([x for x in seq if key(x) in last], key=lambda x: last.index(key(x))) |
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1403 return first + other + last |
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1404 |
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1405 |
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1406 def untyped_sorted(iterable, key=None, reverse=False): |
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1407 """A version of :func:`sorted` which will happily sort an iterable of |
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1408 heterogenous types and return a new list, similar to legacy Python's |
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1409 behavior. |
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1410 |
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1411 >>> untyped_sorted(['abc', 2.0, 1, 2, 'def']) |
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1412 [1, 2.0, 2, 'abc', 'def'] |
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1413 |
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1414 Note how mutually orderable types are sorted as expected, as in |
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1415 the case of the integers and floats above. |
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1416 |
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1417 .. note:: |
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1418 |
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1419 Results may vary across Python versions and builds, but the |
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1420 function will produce a sorted list, except in the case of |
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1421 explicitly unorderable objects. |
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1422 |
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1423 """ |
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1424 class _Wrapper(object): |
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1425 slots = ('obj',) |
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1426 |
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1427 def __init__(self, obj): |
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1428 self.obj = obj |
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1429 |
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1430 def __lt__(self, other): |
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1431 obj = key(self.obj) if key is not None else self.obj |
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1432 other = key(other.obj) if key is not None else other.obj |
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1433 try: |
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1434 ret = obj < other |
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1435 except TypeError: |
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1436 ret = ((type(obj).__name__, id(type(obj)), obj) |
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1437 < (type(other).__name__, id(type(other)), other)) |
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1438 return ret |
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1439 |
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1440 if key is not None and not callable(key): |
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1441 raise TypeError('expected function or callable object for key, not: %r' |
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1442 % key) |
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1443 |
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1444 return sorted(iterable, key=_Wrapper, reverse=reverse) |
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1445 |
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1446 """ |
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1447 May actually be faster to do an isinstance check for a str path |
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1448 |
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1449 $ python -m timeit -s "x = [1]" "x[0]" |
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1450 10000000 loops, best of 3: 0.0207 usec per loop |
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1451 $ python -m timeit -s "x = [1]" "try: x[0] \nexcept: pass" |
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1452 10000000 loops, best of 3: 0.029 usec per loop |
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1453 $ python -m timeit -s "x = [1]" "try: x[1] \nexcept: pass" |
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1454 1000000 loops, best of 3: 0.315 usec per loop |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1455 # setting up try/except is fast, only around 0.01us |
4f3585e2f14b
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1456 # actually triggering the exception takes almost 10x as long |
4f3585e2f14b
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1457 |
4f3585e2f14b
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1458 $ python -m timeit -s "x = [1]" "isinstance(x, basestring)" |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1459 10000000 loops, best of 3: 0.141 usec per loop |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1460 $ python -m timeit -s "x = [1]" "isinstance(x, str)" |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1461 10000000 loops, best of 3: 0.131 usec per loop |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1462 $ python -m timeit -s "x = [1]" "try: x.split('.')\n except: pass" |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1463 1000000 loops, best of 3: 0.443 usec per loop |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1464 $ python -m timeit -s "x = [1]" "try: x.split('.') \nexcept AttributeError: pass" |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1465 1000000 loops, best of 3: 0.544 usec per loop |
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"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
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1466 """ |