Mercurial > repos > shellac > guppy_basecaller
annotate env/lib/python3.7/site-packages/boltons/iterutils.py @ 3:758bc20232e8 draft
"planemo upload commit 2a0fe2cc28b09e101d37293e53e82f61762262ec"
author | shellac |
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date | Thu, 14 May 2020 16:20:52 -0400 |
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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 socket |
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19 import hashlib |
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20 import itertools |
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21 |
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22 try: |
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23 from collections.abc import Mapping, Sequence, Set, ItemsView, Iterable |
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24 except ImportError: |
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25 from collections import Mapping, Sequence, Set, ItemsView, Iterable |
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26 |
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27 |
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28 try: |
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29 from typeutils import make_sentinel |
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30 _UNSET = make_sentinel('_UNSET') |
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31 _REMAP_EXIT = make_sentinel('_REMAP_EXIT') |
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32 except ImportError: |
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33 _REMAP_EXIT = object() |
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34 _UNSET = object() |
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35 |
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36 try: |
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37 from future_builtins import filter |
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38 from itertools import izip |
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39 _IS_PY3 = False |
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40 except ImportError: |
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41 # Python 3 compat |
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42 _IS_PY3 = True |
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43 basestring = (str, bytes) |
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44 unicode = str |
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45 izip, xrange = zip, range |
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46 |
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47 |
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48 def is_iterable(obj): |
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49 """Similar in nature to :func:`callable`, ``is_iterable`` returns |
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50 ``True`` if an object is `iterable`_, ``False`` if not. |
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51 |
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52 >>> is_iterable([]) |
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53 True |
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54 >>> is_iterable(object()) |
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55 False |
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56 |
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57 .. _iterable: https://docs.python.org/2/glossary.html#term-iterable |
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58 """ |
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59 try: |
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60 iter(obj) |
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61 except TypeError: |
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62 return False |
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63 return True |
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64 |
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65 |
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66 def is_scalar(obj): |
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67 """A near-mirror of :func:`is_iterable`. Returns ``False`` if an |
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68 object is an iterable container type. Strings are considered |
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69 scalar as well, because strings are more often treated as whole |
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70 values as opposed to iterables of 1-character substrings. |
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71 |
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72 >>> is_scalar(object()) |
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73 True |
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74 >>> is_scalar(range(10)) |
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75 False |
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76 >>> is_scalar('hello') |
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77 True |
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78 """ |
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79 return not is_iterable(obj) or isinstance(obj, basestring) |
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80 |
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81 |
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82 def is_collection(obj): |
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83 """The opposite of :func:`is_scalar`. Returns ``True`` if an object |
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84 is an iterable other than a string. |
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85 |
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86 >>> is_collection(object()) |
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87 False |
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88 >>> is_collection(range(10)) |
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89 True |
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90 >>> is_collection('hello') |
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91 False |
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92 """ |
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93 return is_iterable(obj) and not isinstance(obj, basestring) |
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94 |
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95 |
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96 def split(src, sep=None, maxsplit=None): |
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97 """Splits an iterable based on a separator. Like :meth:`str.split`, |
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98 but for all iterables. Returns a list of lists. |
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99 |
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100 >>> split(['hi', 'hello', None, None, 'sup', None, 'soap', None]) |
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101 [['hi', 'hello'], ['sup'], ['soap']] |
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102 |
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103 See :func:`split_iter` docs for more info. |
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104 """ |
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105 return list(split_iter(src, sep, maxsplit)) |
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106 |
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107 |
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108 def split_iter(src, sep=None, maxsplit=None): |
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109 """Splits an iterable based on a separator, *sep*, a max of |
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110 *maxsplit* times (no max by default). *sep* can be: |
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111 |
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112 * a single value |
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113 * an iterable of separators |
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114 * a single-argument callable that returns True when a separator is |
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115 encountered |
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116 |
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117 ``split_iter()`` yields lists of non-separator values. A separator will |
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118 never appear in the output. |
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119 |
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120 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None, 'soap', None])) |
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121 [['hi', 'hello'], ['sup'], ['soap']] |
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122 |
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123 Note that ``split_iter`` is based on :func:`str.split`, so if |
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124 *sep* is ``None``, ``split()`` **groups** separators. If empty lists |
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125 are desired between two contiguous ``None`` values, simply use |
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126 ``sep=[None]``: |
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127 |
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128 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None])) |
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129 [['hi', 'hello'], ['sup']] |
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130 >>> list(split_iter(['hi', 'hello', None, None, 'sup', None], sep=[None])) |
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131 [['hi', 'hello'], [], ['sup'], []] |
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132 |
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133 Using a callable separator: |
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134 |
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135 >>> falsy_sep = lambda x: not x |
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136 >>> list(split_iter(['hi', 'hello', None, '', 'sup', False], falsy_sep)) |
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137 [['hi', 'hello'], [], ['sup'], []] |
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138 |
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139 See :func:`split` for a list-returning version. |
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140 |
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141 """ |
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142 if not is_iterable(src): |
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143 raise TypeError('expected an iterable') |
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144 |
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145 if maxsplit is not None: |
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146 maxsplit = int(maxsplit) |
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147 if maxsplit == 0: |
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148 yield [src] |
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149 return |
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150 |
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151 if callable(sep): |
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152 sep_func = sep |
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153 elif not is_scalar(sep): |
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154 sep = frozenset(sep) |
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155 sep_func = lambda x: x in sep |
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156 else: |
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157 sep_func = lambda x: x == sep |
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158 |
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159 cur_group = [] |
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160 split_count = 0 |
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161 for s in src: |
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162 if maxsplit is not None and split_count >= maxsplit: |
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163 sep_func = lambda x: False |
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164 if sep_func(s): |
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165 if sep is None and not cur_group: |
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166 # If sep is none, str.split() "groups" separators |
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167 # check the str.split() docs for more info |
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168 continue |
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169 split_count += 1 |
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170 yield cur_group |
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171 cur_group = [] |
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172 else: |
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173 cur_group.append(s) |
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174 |
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175 if cur_group or sep is not None: |
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176 yield cur_group |
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177 return |
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178 |
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179 |
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180 def chunked(src, size, count=None, **kw): |
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181 """Returns a list of *count* chunks, each with *size* elements, |
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182 generated from iterable *src*. If *src* is not evenly divisible by |
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183 *size*, the final chunk will have fewer than *size* elements. |
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184 Provide the *fill* keyword argument to provide a pad value and |
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185 enable padding, otherwise no padding will take place. |
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186 |
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187 >>> chunked(range(10), 3) |
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188 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
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189 >>> chunked(range(10), 3, fill=None) |
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190 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
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191 >>> chunked(range(10), 3, count=2) |
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192 [[0, 1, 2], [3, 4, 5]] |
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193 |
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194 See :func:`chunked_iter` for more info. |
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195 """ |
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196 chunk_iter = chunked_iter(src, size, **kw) |
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197 if count is None: |
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198 return list(chunk_iter) |
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199 else: |
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200 return list(itertools.islice(chunk_iter, count)) |
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201 |
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202 |
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203 def chunked_iter(src, size, **kw): |
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204 """Generates *size*-sized chunks from *src* iterable. Unless the |
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205 optional *fill* keyword argument is provided, iterables not evenly |
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206 divisible by *size* will have a final chunk that is smaller than |
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207 *size*. |
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208 |
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209 >>> list(chunked_iter(range(10), 3)) |
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210 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
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211 >>> list(chunked_iter(range(10), 3, fill=None)) |
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212 [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
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213 |
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214 Note that ``fill=None`` in fact uses ``None`` as the fill value. |
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215 """ |
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216 # TODO: add count kwarg? |
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217 if not is_iterable(src): |
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218 raise TypeError('expected an iterable') |
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219 size = int(size) |
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220 if size <= 0: |
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221 raise ValueError('expected a positive integer chunk size') |
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222 do_fill = True |
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223 try: |
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224 fill_val = kw.pop('fill') |
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225 except KeyError: |
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226 do_fill = False |
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227 fill_val = None |
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228 if kw: |
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229 raise ValueError('got unexpected keyword arguments: %r' % kw.keys()) |
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230 if not src: |
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231 return |
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232 postprocess = lambda chk: chk |
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233 if isinstance(src, basestring): |
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234 postprocess = lambda chk, _sep=type(src)(): _sep.join(chk) |
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235 if _IS_PY3 and isinstance(src, bytes): |
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236 postprocess = lambda chk: bytes(chk) |
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237 src_iter = iter(src) |
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238 while True: |
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239 cur_chunk = list(itertools.islice(src_iter, size)) |
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240 if not cur_chunk: |
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241 break |
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242 lc = len(cur_chunk) |
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243 if lc < size and do_fill: |
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244 cur_chunk[lc:] = [fill_val] * (size - lc) |
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245 yield postprocess(cur_chunk) |
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246 return |
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247 |
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248 |
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249 def pairwise(src): |
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250 """Convenience function for calling :func:`windowed` on *src*, with |
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251 *size* set to 2. |
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252 |
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253 >>> pairwise(range(5)) |
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254 [(0, 1), (1, 2), (2, 3), (3, 4)] |
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255 >>> pairwise([]) |
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256 [] |
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257 |
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258 The number of pairs is always one less than the number of elements |
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259 in the iterable passed in, except on empty inputs, which returns |
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260 an empty list. |
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261 """ |
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262 return windowed(src, 2) |
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263 |
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264 |
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265 def pairwise_iter(src): |
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266 """Convenience function for calling :func:`windowed_iter` on *src*, |
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267 with *size* set to 2. |
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268 |
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269 >>> list(pairwise_iter(range(5))) |
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270 [(0, 1), (1, 2), (2, 3), (3, 4)] |
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271 >>> list(pairwise_iter([])) |
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272 [] |
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273 |
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274 The number of pairs is always one less than the number of elements |
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275 in the iterable passed in, or zero, when *src* is empty. |
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276 |
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277 """ |
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278 return windowed_iter(src, 2) |
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279 |
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280 |
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281 def windowed(src, size): |
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282 """Returns tuples with exactly length *size*. If the iterable is |
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283 too short to make a window of length *size*, no tuples are |
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284 returned. See :func:`windowed_iter` for more. |
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285 """ |
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286 return list(windowed_iter(src, size)) |
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287 |
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288 |
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289 def windowed_iter(src, size): |
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290 """Returns tuples with length *size* which represent a sliding |
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291 window over iterable *src*. |
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292 |
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293 >>> list(windowed_iter(range(7), 3)) |
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294 [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)] |
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295 |
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296 If the iterable is too short to make a window of length *size*, |
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297 then no window tuples are returned. |
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298 |
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299 >>> list(windowed_iter(range(3), 5)) |
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300 [] |
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301 """ |
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302 # TODO: lists? (for consistency) |
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303 tees = itertools.tee(src, size) |
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304 try: |
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305 for i, t in enumerate(tees): |
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306 for _ in xrange(i): |
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307 next(t) |
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308 except StopIteration: |
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309 return izip([]) |
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310 return izip(*tees) |
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311 |
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312 |
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313 def xfrange(stop, start=None, step=1.0): |
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314 """Same as :func:`frange`, but generator-based instead of returning a |
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315 list. |
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316 |
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317 >>> tuple(xfrange(1, 3, step=0.75)) |
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318 (1.0, 1.75, 2.5) |
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319 |
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320 See :func:`frange` for more details. |
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321 """ |
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322 if not step: |
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323 raise ValueError('step must be non-zero') |
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324 if start is None: |
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325 start, stop = 0.0, stop * 1.0 |
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326 else: |
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327 # swap when all args are used |
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328 stop, start = start * 1.0, stop * 1.0 |
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329 cur = start |
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330 while cur < stop: |
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331 yield cur |
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332 cur += step |
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333 |
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334 |
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335 def frange(stop, start=None, step=1.0): |
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336 """A :func:`range` clone for float-based ranges. |
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337 |
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338 >>> frange(5) |
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339 [0.0, 1.0, 2.0, 3.0, 4.0] |
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340 >>> frange(6, step=1.25) |
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341 [0.0, 1.25, 2.5, 3.75, 5.0] |
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342 >>> frange(100.5, 101.5, 0.25) |
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343 [100.5, 100.75, 101.0, 101.25] |
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344 >>> frange(5, 0) |
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345 [] |
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346 >>> frange(5, 0, step=-1.25) |
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347 [5.0, 3.75, 2.5, 1.25] |
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348 """ |
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349 if not step: |
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350 raise ValueError('step must be non-zero') |
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351 if start is None: |
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352 start, stop = 0.0, stop * 1.0 |
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353 else: |
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354 # swap when all args are used |
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355 stop, start = start * 1.0, stop * 1.0 |
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356 count = int(math.ceil((stop - start) / step)) |
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357 ret = [None] * count |
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358 if not ret: |
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359 return ret |
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360 ret[0] = start |
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361 for i in xrange(1, count): |
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362 ret[i] = ret[i - 1] + step |
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363 return ret |
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364 |
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365 |
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366 def backoff(start, stop, count=None, factor=2.0, jitter=False): |
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367 """Returns a list of geometrically-increasing floating-point numbers, |
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368 suitable for usage with `exponential backoff`_. Exactly like |
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369 :func:`backoff_iter`, but without the ``'repeat'`` option for |
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370 *count*. See :func:`backoff_iter` for more details. |
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371 |
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372 .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
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373 |
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374 >>> backoff(1, 10) |
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375 [1.0, 2.0, 4.0, 8.0, 10.0] |
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376 """ |
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377 if count == 'repeat': |
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378 raise ValueError("'repeat' supported in backoff_iter, not backoff") |
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379 return list(backoff_iter(start, stop, count=count, |
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380 factor=factor, jitter=jitter)) |
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381 |
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382 |
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383 def backoff_iter(start, stop, count=None, factor=2.0, jitter=False): |
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384 """Generates a sequence of geometrically-increasing floats, suitable |
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385 for usage with `exponential backoff`_. Starts with *start*, |
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386 increasing by *factor* until *stop* is reached, optionally |
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387 stopping iteration once *count* numbers are yielded. *factor* |
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388 defaults to 2. In general retrying with properly-configured |
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389 backoff creates a better-behaved component for a larger service |
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390 ecosystem. |
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391 |
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392 .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
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393 |
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394 >>> list(backoff_iter(1.0, 10.0, count=5)) |
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395 [1.0, 2.0, 4.0, 8.0, 10.0] |
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396 >>> list(backoff_iter(1.0, 10.0, count=8)) |
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397 [1.0, 2.0, 4.0, 8.0, 10.0, 10.0, 10.0, 10.0] |
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398 >>> list(backoff_iter(0.25, 100.0, factor=10)) |
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399 [0.25, 2.5, 25.0, 100.0] |
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400 |
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401 A simplified usage example: |
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402 |
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403 .. code-block:: python |
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404 |
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405 for timeout in backoff_iter(0.25, 5.0): |
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406 try: |
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407 res = network_call() |
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408 break |
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409 except Exception as e: |
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410 log(e) |
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411 time.sleep(timeout) |
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412 |
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413 An enhancement for large-scale systems would be to add variation, |
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414 or *jitter*, to timeout values. This is done to avoid a thundering |
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415 herd on the receiving end of the network call. |
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416 |
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417 Finally, for *count*, the special value ``'repeat'`` can be passed to |
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418 continue yielding indefinitely. |
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419 |
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420 Args: |
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421 |
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422 start (float): Positive number for baseline. |
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423 stop (float): Positive number for maximum. |
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424 count (int): Number of steps before stopping |
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425 iteration. Defaults to the number of steps between *start* and |
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426 *stop*. Pass the string, `'repeat'`, to continue iteration |
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427 indefinitely. |
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428 factor (float): Rate of exponential increase. Defaults to `2.0`, |
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429 e.g., `[1, 2, 4, 8, 16]`. |
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430 jitter (float): A factor between `-1.0` and `1.0`, used to |
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431 uniformly randomize and thus spread out timeouts in a distributed |
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432 system, avoiding rhythm effects. Positive values use the base |
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433 backoff curve as a maximum, negative values use the curve as a |
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434 minimum. Set to 1.0 or `True` for a jitter approximating |
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435 Ethernet's time-tested backoff solution. Defaults to `False`. |
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436 |
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437 """ |
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438 start = float(start) |
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439 stop = float(stop) |
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440 factor = float(factor) |
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441 if start < 0.0: |
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442 raise ValueError('expected start >= 0, not %r' % start) |
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443 if factor < 1.0: |
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444 raise ValueError('expected factor >= 1.0, not %r' % factor) |
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445 if stop == 0.0: |
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446 raise ValueError('expected stop >= 0') |
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447 if stop < start: |
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448 raise ValueError('expected stop >= start, not %r' % stop) |
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449 if count is None: |
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450 denom = start if start else 1 |
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451 count = 1 + math.ceil(math.log(stop/denom, factor)) |
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452 count = count if start else count + 1 |
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453 if count != 'repeat' and count < 0: |
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454 raise ValueError('count must be positive or "repeat", not %r' % count) |
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455 if jitter: |
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456 jitter = float(jitter) |
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457 if not (-1.0 <= jitter <= 1.0): |
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458 raise ValueError('expected jitter -1 <= j <= 1, not: %r' % jitter) |
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459 |
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460 cur, i = start, 0 |
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461 while count == 'repeat' or i < count: |
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462 if not jitter: |
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463 cur_ret = cur |
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464 elif jitter: |
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465 cur_ret = cur - (cur * jitter * random.random()) |
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466 yield cur_ret |
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467 i += 1 |
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468 if cur == 0: |
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469 cur = 1 |
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470 elif cur < stop: |
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471 cur *= factor |
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472 if cur > stop: |
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473 cur = stop |
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474 return |
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475 |
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476 |
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477 def bucketize(src, key=bool, value_transform=None, key_filter=None): |
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478 """Group values in the *src* iterable by the value returned by *key*. |
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479 |
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480 >>> bucketize(range(5)) |
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481 {False: [0], True: [1, 2, 3, 4]} |
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482 >>> is_odd = lambda x: x % 2 == 1 |
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483 >>> bucketize(range(5), is_odd) |
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484 {False: [0, 2, 4], True: [1, 3]} |
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485 |
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486 *key* is :class:`bool` by default, but can either be a callable or a string |
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487 name of the attribute on which to bucketize objects. |
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488 |
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489 >>> bucketize([1+1j, 2+2j, 1, 2], key='real') |
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490 {1.0: [(1+1j), 1], 2.0: [(2+2j), 2]} |
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491 |
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492 Value lists are not deduplicated: |
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493 |
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494 >>> bucketize([None, None, None, 'hello']) |
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495 {False: [None, None, None], True: ['hello']} |
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496 |
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497 Bucketize into more than 3 groups |
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498 |
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499 >>> bucketize(range(10), lambda x: x % 3) |
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500 {0: [0, 3, 6, 9], 1: [1, 4, 7], 2: [2, 5, 8]} |
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501 |
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502 ``bucketize`` has a couple of advanced options useful in certain |
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503 cases. *value_transform* can be used to modify values as they are |
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504 added to buckets, and *key_filter* will allow excluding certain |
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505 buckets from being collected. |
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506 |
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507 >>> bucketize(range(5), value_transform=lambda x: x*x) |
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508 {False: [0], True: [1, 4, 9, 16]} |
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509 |
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510 >>> bucketize(range(10), key=lambda x: x % 3, key_filter=lambda k: k % 3 != 1) |
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511 {0: [0, 3, 6, 9], 2: [2, 5, 8]} |
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512 |
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513 Note in some of these examples there were at most two keys, ``True`` and |
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514 ``False``, and each key present has a list with at least one |
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515 item. See :func:`partition` for a version specialized for binary |
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516 use cases. |
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517 |
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518 """ |
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519 if not is_iterable(src): |
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520 raise TypeError('expected an iterable') |
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521 |
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522 if isinstance(key, basestring): |
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523 key_func = lambda x: getattr(x, key, x) |
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524 elif callable(key): |
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525 key_func = key |
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526 else: |
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527 raise TypeError('expected key to be callable or a string') |
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528 |
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529 if value_transform is None: |
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530 value_transform = lambda x: x |
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531 if not callable(value_transform): |
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532 raise TypeError('expected callable value transform function') |
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533 |
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534 ret = {} |
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535 for val in src: |
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536 key_of_val = key_func(val) |
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537 if key_filter is None or key_filter(key_of_val): |
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538 ret.setdefault(key_of_val, []).append(value_transform(val)) |
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539 return ret |
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540 |
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541 |
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542 def partition(src, key=bool): |
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543 """No relation to :meth:`str.partition`, ``partition`` is like |
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544 :func:`bucketize`, but for added convenience returns a tuple of |
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545 ``(truthy_values, falsy_values)``. |
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546 |
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547 >>> nonempty, empty = partition(['', '', 'hi', '', 'bye']) |
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548 >>> nonempty |
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549 ['hi', 'bye'] |
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550 |
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551 *key* defaults to :class:`bool`, but can be carefully overridden to |
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552 use either a function that returns either ``True`` or ``False`` or |
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553 a string name of the attribute on which to partition objects. |
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554 |
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555 >>> import string |
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556 >>> is_digit = lambda x: x in string.digits |
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557 >>> decimal_digits, hexletters = partition(string.hexdigits, is_digit) |
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558 >>> ''.join(decimal_digits), ''.join(hexletters) |
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559 ('0123456789', 'abcdefABCDEF') |
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560 """ |
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561 bucketized = bucketize(src, key) |
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562 return bucketized.get(True, []), bucketized.get(False, []) |
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563 |
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564 |
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565 def unique(src, key=None): |
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566 """``unique()`` returns a list of unique values, as determined by |
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567 *key*, in the order they first appeared in the input iterable, |
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568 *src*. |
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569 |
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570 >>> ones_n_zeros = '11010110001010010101010' |
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571 >>> ''.join(unique(ones_n_zeros)) |
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572 '10' |
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573 |
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574 See :func:`unique_iter` docs for more details. |
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575 """ |
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576 return list(unique_iter(src, key)) |
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577 |
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578 |
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579 def unique_iter(src, key=None): |
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580 """Yield unique elements from the iterable, *src*, based on *key*, |
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581 in the order in which they first appeared in *src*. |
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582 |
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583 >>> repetitious = [1, 2, 3] * 10 |
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584 >>> list(unique_iter(repetitious)) |
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585 [1, 2, 3] |
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586 |
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587 By default, *key* is the object itself, but *key* can either be a |
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588 callable or, for convenience, a string name of the attribute on |
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589 which to uniqueify objects, falling back on identity when the |
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590 attribute is not present. |
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591 |
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592 >>> pleasantries = ['hi', 'hello', 'ok', 'bye', 'yes'] |
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593 >>> list(unique_iter(pleasantries, key=lambda x: len(x))) |
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594 ['hi', 'hello', 'bye'] |
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595 """ |
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596 if not is_iterable(src): |
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597 raise TypeError('expected an iterable, not %r' % type(src)) |
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598 if key is None: |
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599 key_func = lambda x: x |
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600 elif callable(key): |
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601 key_func = key |
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602 elif isinstance(key, basestring): |
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603 key_func = lambda x: getattr(x, key, x) |
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604 else: |
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605 raise TypeError('"key" expected a string or callable, not %r' % key) |
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606 seen = set() |
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607 for i in src: |
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608 k = key_func(i) |
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609 if k not in seen: |
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610 seen.add(k) |
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611 yield i |
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612 return |
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613 |
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614 |
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615 def redundant(src, key=None, groups=False): |
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616 """The complement of :func:`unique()`. |
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617 |
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618 By default returns non-unique values as a list of the *first* |
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619 redundant value in *src*. Pass ``groups=True`` to get groups of |
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620 all values with redundancies, ordered by position of the first |
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621 redundant value. This is useful in conjunction with some |
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622 normalizing *key* function. |
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623 |
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624 >>> redundant([1, 2, 3, 4]) |
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625 [] |
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626 >>> redundant([1, 2, 3, 2, 3, 3, 4]) |
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627 [2, 3] |
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628 >>> redundant([1, 2, 3, 2, 3, 3, 4], groups=True) |
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629 [[2, 2], [3, 3, 3]] |
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630 |
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631 An example using a *key* function to do case-insensitive |
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632 redundancy detection. |
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633 |
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634 >>> redundant(['hi', 'Hi', 'HI', 'hello'], key=str.lower) |
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635 ['Hi'] |
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636 >>> redundant(['hi', 'Hi', 'HI', 'hello'], groups=True, key=str.lower) |
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637 [['hi', 'Hi', 'HI']] |
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638 |
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639 *key* should also be used when the values in *src* are not hashable. |
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640 |
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641 .. note:: |
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642 |
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643 This output of this function is designed for reporting |
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644 duplicates in contexts when a unique input is desired. Due to |
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645 the grouped return type, there is no streaming equivalent of |
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646 this function for the time being. |
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647 |
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648 """ |
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649 if key is None: |
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650 pass |
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651 elif callable(key): |
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652 key_func = key |
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653 elif isinstance(key, basestring): |
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654 key_func = lambda x: getattr(x, key, x) |
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655 else: |
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656 raise TypeError('"key" expected a string or callable, not %r' % key) |
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657 seen = {} # key to first seen item |
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658 redundant_order = [] |
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659 redundant_groups = {} |
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660 for i in src: |
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661 k = key_func(i) if key else i |
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662 if k not in seen: |
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663 seen[k] = i |
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664 else: |
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665 if k in redundant_groups: |
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666 if groups: |
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667 redundant_groups[k].append(i) |
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668 else: |
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669 redundant_order.append(k) |
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670 redundant_groups[k] = [seen[k], i] |
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671 if not groups: |
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672 ret = [redundant_groups[k][1] for k in redundant_order] |
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673 else: |
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674 ret = [redundant_groups[k] for k in redundant_order] |
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675 return ret |
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676 |
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677 |
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678 def one(src, default=None, key=None): |
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679 """Along the same lines as builtins, :func:`all` and :func:`any`, and |
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680 similar to :func:`first`, ``one()`` returns the single object in |
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681 the given iterable *src* that evaluates to ``True``, as determined |
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682 by callable *key*. If unset, *key* defaults to :class:`bool`. If |
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683 no such objects are found, *default* is returned. If *default* is |
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684 not passed, ``None`` is returned. |
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685 |
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686 If *src* has more than one object that evaluates to ``True``, or |
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687 if there is no object that fulfills such condition, return |
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688 *default*. It's like an `XOR`_ over an iterable. |
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689 |
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690 >>> one((True, False, False)) |
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691 True |
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692 >>> one((True, False, True)) |
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693 >>> one((0, 0, 'a')) |
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694 'a' |
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695 >>> one((0, False, None)) |
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696 >>> one((True, True), default=False) |
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697 False |
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698 >>> bool(one(('', 1))) |
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699 True |
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700 >>> one((10, 20, 30, 42), key=lambda i: i > 40) |
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701 42 |
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702 |
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703 See `MartÃn Gaitán's original repo`_ for further use cases. |
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704 |
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705 .. _MartÃn Gaitán's original repo: https://github.com/mgaitan/one |
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706 .. _XOR: https://en.wikipedia.org/wiki/Exclusive_or |
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707 |
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708 """ |
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709 ones = list(itertools.islice(filter(key, src), 2)) |
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710 return ones[0] if len(ones) == 1 else default |
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711 |
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712 |
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713 def first(iterable, default=None, key=None): |
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714 """Return first element of *iterable* that evaluates to ``True``, else |
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715 return ``None`` or optional *default*. Similar to :func:`one`. |
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716 |
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717 >>> first([0, False, None, [], (), 42]) |
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718 42 |
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719 >>> first([0, False, None, [], ()]) is None |
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720 True |
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721 >>> first([0, False, None, [], ()], default='ohai') |
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722 'ohai' |
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723 >>> import re |
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724 >>> m = first(re.match(regex, 'abc') for regex in ['b.*', 'a(.*)']) |
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725 >>> m.group(1) |
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726 'bc' |
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727 |
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728 The optional *key* argument specifies a one-argument predicate function |
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729 like that used for *filter()*. The *key* argument, if supplied, should be |
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730 in keyword form. For example, finding the first even number in an iterable: |
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731 |
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732 >>> first([1, 1, 3, 4, 5], key=lambda x: x % 2 == 0) |
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733 4 |
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734 |
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735 Contributed by Hynek Schlawack, author of `the original standalone module`_. |
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736 |
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737 .. _the original standalone module: https://github.com/hynek/first |
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738 """ |
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739 return next(filter(key, iterable), default) |
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740 |
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741 |
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742 def flatten_iter(iterable): |
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743 """``flatten_iter()`` yields all the elements from *iterable* while |
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744 collapsing any nested iterables. |
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745 |
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746 >>> nested = [[1, 2], [[3], [4, 5]]] |
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747 >>> list(flatten_iter(nested)) |
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748 [1, 2, 3, 4, 5] |
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749 """ |
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750 for item in iterable: |
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751 if isinstance(item, Iterable) and not isinstance(item, basestring): |
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752 for subitem in flatten_iter(item): |
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753 yield subitem |
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|
754 else: |
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755 yield item |
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|
756 |
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757 def flatten(iterable): |
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758 """``flatten()`` returns a collapsed list of all the elements from |
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759 *iterable* while collapsing any nested iterables. |
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760 |
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761 >>> nested = [[1, 2], [[3], [4, 5]]] |
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762 >>> flatten(nested) |
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|
763 [1, 2, 3, 4, 5] |
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764 """ |
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765 return list(flatten_iter(iterable)) |
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766 |
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767 |
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768 def same(iterable, ref=_UNSET): |
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769 """``same()`` returns ``True`` when all values in *iterable* are |
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770 equal to one another, or optionally a reference value, |
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771 *ref*. Similar to :func:`all` and :func:`any` in that it evaluates |
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772 an iterable and returns a :class:`bool`. ``same()`` returns |
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773 ``True`` for empty iterables. |
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774 |
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775 >>> same([]) |
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776 True |
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777 >>> same([1]) |
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778 True |
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779 >>> same(['a', 'a', 'a']) |
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780 True |
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781 >>> same(range(20)) |
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782 False |
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783 >>> same([[], []]) |
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784 True |
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785 >>> same([[], []], ref='test') |
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786 False |
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787 |
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788 """ |
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789 iterator = iter(iterable) |
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790 if ref is _UNSET: |
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791 ref = next(iterator, ref) |
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792 return all(val == ref for val in iterator) |
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793 |
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|
794 |
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795 def default_visit(path, key, value): |
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796 # print('visit(%r, %r, %r)' % (path, key, value)) |
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797 return key, value |
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|
798 |
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799 # enable the extreme: monkeypatching iterutils with a different default_visit |
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800 _orig_default_visit = default_visit |
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801 |
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802 |
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803 def default_enter(path, key, value): |
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804 # print('enter(%r, %r)' % (key, value)) |
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805 if isinstance(value, basestring): |
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806 return value, False |
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807 elif isinstance(value, Mapping): |
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808 return value.__class__(), ItemsView(value) |
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809 elif isinstance(value, Sequence): |
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810 return value.__class__(), enumerate(value) |
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811 elif isinstance(value, Set): |
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812 return value.__class__(), enumerate(value) |
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813 else: |
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814 # files, strings, other iterables, and scalars are not |
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815 # traversed |
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816 return value, False |
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817 |
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818 |
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819 def default_exit(path, key, old_parent, new_parent, new_items): |
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820 # print('exit(%r, %r, %r, %r, %r)' |
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821 # % (path, key, old_parent, new_parent, new_items)) |
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822 ret = new_parent |
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823 if isinstance(new_parent, Mapping): |
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824 new_parent.update(new_items) |
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825 elif isinstance(new_parent, Sequence): |
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826 vals = [v for i, v in new_items] |
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827 try: |
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828 new_parent.extend(vals) |
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829 except AttributeError: |
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830 ret = new_parent.__class__(vals) # tuples |
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831 elif isinstance(new_parent, Set): |
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832 vals = [v for i, v in new_items] |
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833 try: |
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834 new_parent.update(vals) |
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835 except AttributeError: |
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836 ret = new_parent.__class__(vals) # frozensets |
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837 else: |
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838 raise RuntimeError('unexpected iterable type: %r' % type(new_parent)) |
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839 return ret |
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840 |
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841 |
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842 def remap(root, visit=default_visit, enter=default_enter, exit=default_exit, |
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843 **kwargs): |
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844 """The remap ("recursive map") function is used to traverse and |
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845 transform nested structures. Lists, tuples, sets, and dictionaries |
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846 are just a few of the data structures nested into heterogenous |
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847 tree-like structures that are so common in programming. |
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848 Unfortunately, Python's built-in ways to manipulate collections |
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849 are almost all flat. List comprehensions may be fast and succinct, |
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850 but they do not recurse, making it tedious to apply quick changes |
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851 or complex transforms to real-world data. |
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852 |
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853 remap goes where list comprehensions cannot. |
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854 |
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855 Here's an example of removing all Nones from some data: |
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856 |
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857 >>> from pprint import pprint |
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858 >>> reviews = {'Star Trek': {'TNG': 10, 'DS9': 8.5, 'ENT': None}, |
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859 ... 'Babylon 5': 6, 'Dr. Who': None} |
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860 >>> pprint(remap(reviews, lambda p, k, v: v is not None)) |
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861 {'Babylon 5': 6, 'Star Trek': {'DS9': 8.5, 'TNG': 10}} |
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862 |
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863 Notice how both Nones have been removed despite the nesting in the |
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864 dictionary. Not bad for a one-liner, and that's just the beginning. |
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865 See `this remap cookbook`_ for more delicious recipes. |
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866 |
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867 .. _this remap cookbook: http://sedimental.org/remap.html |
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868 |
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869 remap takes four main arguments: the object to traverse and three |
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870 optional callables which determine how the remapped object will be |
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871 created. |
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872 |
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873 Args: |
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874 |
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875 root: The target object to traverse. By default, remap |
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876 supports iterables like :class:`list`, :class:`tuple`, |
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877 :class:`dict`, and :class:`set`, but any object traversable by |
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878 *enter* will work. |
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879 visit (callable): This function is called on every item in |
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880 *root*. It must accept three positional arguments, *path*, |
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881 *key*, and *value*. *path* is simply a tuple of parents' |
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882 keys. *visit* should return the new key-value pair. It may |
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883 also return ``True`` as shorthand to keep the old item |
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884 unmodified, or ``False`` to drop the item from the new |
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885 structure. *visit* is called after *enter*, on the new parent. |
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886 |
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887 The *visit* function is called for every item in root, |
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888 including duplicate items. For traversable values, it is |
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889 called on the new parent object, after all its children |
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890 have been visited. The default visit behavior simply |
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891 returns the key-value pair unmodified. |
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892 enter (callable): This function controls which items in *root* |
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893 are traversed. It accepts the same arguments as *visit*: the |
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894 path, the key, and the value of the current item. It returns a |
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895 pair of the blank new parent, and an iterator over the items |
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896 which should be visited. If ``False`` is returned instead of |
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897 an iterator, the value will not be traversed. |
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898 |
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899 The *enter* function is only called once per unique value. The |
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900 default enter behavior support mappings, sequences, and |
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901 sets. Strings and all other iterables will not be traversed. |
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902 exit (callable): This function determines how to handle items |
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903 once they have been visited. It gets the same three |
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904 arguments as the other functions -- *path*, *key*, *value* |
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905 -- plus two more: the blank new parent object returned |
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906 from *enter*, and a list of the new items, as remapped by |
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907 *visit*. |
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908 |
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909 Like *enter*, the *exit* function is only called once per |
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910 unique value. The default exit behavior is to simply add |
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911 all new items to the new parent, e.g., using |
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912 :meth:`list.extend` and :meth:`dict.update` to add to the |
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913 new parent. Immutable objects, such as a :class:`tuple` or |
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914 :class:`namedtuple`, must be recreated from scratch, but |
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915 use the same type as the new parent passed back from the |
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916 *enter* function. |
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917 reraise_visit (bool): A pragmatic convenience for the *visit* |
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918 callable. When set to ``False``, remap ignores any errors |
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919 raised by the *visit* callback. Items causing exceptions |
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920 are kept. See examples for more details. |
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921 |
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922 remap is designed to cover the majority of cases with just the |
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923 *visit* callable. While passing in multiple callables is very |
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924 empowering, remap is designed so very few cases should require |
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925 passing more than one function. |
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926 |
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927 When passing *enter* and *exit*, it's common and easiest to build |
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928 on the default behavior. Simply add ``from boltons.iterutils import |
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929 default_enter`` (or ``default_exit``), and have your enter/exit |
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930 function call the default behavior before or after your custom |
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931 logic. See `this example`_. |
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932 |
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933 Duplicate and self-referential objects (aka reference loops) are |
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934 automatically handled internally, `as shown here`_. |
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935 |
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936 .. _this example: http://sedimental.org/remap.html#sort_all_lists |
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937 .. _as shown here: http://sedimental.org/remap.html#corner_cases |
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938 |
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939 """ |
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940 # TODO: improve argument formatting in sphinx doc |
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941 # TODO: enter() return (False, items) to continue traverse but cancel copy? |
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942 if not callable(visit): |
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943 raise TypeError('visit expected callable, not: %r' % visit) |
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944 if not callable(enter): |
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945 raise TypeError('enter expected callable, not: %r' % enter) |
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946 if not callable(exit): |
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947 raise TypeError('exit expected callable, not: %r' % exit) |
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948 reraise_visit = kwargs.pop('reraise_visit', True) |
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949 if kwargs: |
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950 raise TypeError('unexpected keyword arguments: %r' % kwargs.keys()) |
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951 |
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952 path, registry, stack = (), {}, [(None, root)] |
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953 new_items_stack = [] |
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954 while stack: |
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955 key, value = stack.pop() |
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956 id_value = id(value) |
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957 if key is _REMAP_EXIT: |
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958 key, new_parent, old_parent = value |
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959 id_value = id(old_parent) |
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960 path, new_items = new_items_stack.pop() |
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961 value = exit(path, key, old_parent, new_parent, new_items) |
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962 registry[id_value] = value |
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963 if not new_items_stack: |
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964 continue |
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965 elif id_value in registry: |
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966 value = registry[id_value] |
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967 else: |
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968 res = enter(path, key, value) |
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969 try: |
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970 new_parent, new_items = res |
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971 except TypeError: |
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972 # TODO: handle False? |
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973 raise TypeError('enter should return a tuple of (new_parent,' |
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974 ' items_iterator), not: %r' % res) |
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975 if new_items is not False: |
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976 # traverse unless False is explicitly passed |
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977 registry[id_value] = new_parent |
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978 new_items_stack.append((path, [])) |
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979 if value is not root: |
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980 path += (key,) |
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981 stack.append((_REMAP_EXIT, (key, new_parent, value))) |
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982 if new_items: |
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983 stack.extend(reversed(list(new_items))) |
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984 continue |
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985 if visit is _orig_default_visit: |
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986 # avoid function call overhead by inlining identity operation |
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987 visited_item = (key, value) |
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988 else: |
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989 try: |
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990 visited_item = visit(path, key, value) |
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991 except Exception: |
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992 if reraise_visit: |
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993 raise |
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994 visited_item = True |
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995 if visited_item is False: |
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996 continue # drop |
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997 elif visited_item is True: |
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998 visited_item = (key, value) |
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999 # TODO: typecheck? |
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1000 # raise TypeError('expected (key, value) from visit(),' |
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1001 # ' not: %r' % visited_item) |
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1002 try: |
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1003 new_items_stack[-1][1].append(visited_item) |
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1004 except IndexError: |
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1005 raise TypeError('expected remappable root, not: %r' % root) |
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1006 return value |
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1007 |
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1008 |
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1009 class PathAccessError(KeyError, IndexError, TypeError): |
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1010 """An amalgamation of KeyError, IndexError, and TypeError, |
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1011 representing what can occur when looking up a path in a nested |
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1012 object. |
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1013 """ |
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1014 def __init__(self, exc, seg, path): |
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1015 self.exc = exc |
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1016 self.seg = seg |
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1017 self.path = path |
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1018 |
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1019 def __repr__(self): |
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1020 cn = self.__class__.__name__ |
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1021 return '%s(%r, %r, %r)' % (cn, self.exc, self.seg, self.path) |
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1022 |
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1023 def __str__(self): |
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1024 return ('could not access %r from path %r, got error: %r' |
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1025 % (self.seg, self.path, self.exc)) |
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1026 |
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1027 |
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1028 def get_path(root, path, default=_UNSET): |
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1029 """Retrieve a value from a nested object via a tuple representing the |
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1030 lookup path. |
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1031 |
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1032 >>> root = {'a': {'b': {'c': [[1], [2], [3]]}}} |
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1033 >>> get_path(root, ('a', 'b', 'c', 2, 0)) |
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1034 3 |
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1035 |
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1036 The path format is intentionally consistent with that of |
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1037 :func:`remap`. |
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1038 |
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1039 One of get_path's chief aims is improved error messaging. EAFP is |
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1040 great, but the error messages are not. |
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1041 |
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1042 For instance, ``root['a']['b']['c'][2][1]`` gives back |
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1043 ``IndexError: list index out of range`` |
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1044 |
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1045 What went out of range where? get_path currently raises |
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1046 ``PathAccessError: could not access 2 from path ('a', 'b', 'c', 2, |
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1047 1), got error: IndexError('list index out of range',)``, a |
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1048 subclass of IndexError and KeyError. |
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1049 |
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1050 You can also pass a default that covers the entire operation, |
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1051 should the lookup fail at any level. |
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1052 |
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1053 Args: |
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1054 root: The target nesting of dictionaries, lists, or other |
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1055 objects supporting ``__getitem__``. |
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1056 path (tuple): A list of strings and integers to be successively |
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1057 looked up within *root*. |
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1058 default: The value to be returned should any |
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1059 ``PathAccessError`` exceptions be raised. |
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1060 """ |
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1061 if isinstance(path, basestring): |
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1062 path = path.split('.') |
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1063 cur = root |
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1064 try: |
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1065 for seg in path: |
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1066 try: |
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1067 cur = cur[seg] |
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1068 except (KeyError, IndexError) as exc: |
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1069 raise PathAccessError(exc, seg, path) |
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1070 except TypeError as exc: |
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1071 # either string index in a list, or a parent that |
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1072 # doesn't support indexing |
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1073 try: |
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1074 seg = int(seg) |
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1075 cur = cur[seg] |
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1076 except (ValueError, KeyError, IndexError, TypeError): |
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1077 if not is_iterable(cur): |
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1078 exc = TypeError('%r object is not indexable' |
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1079 % type(cur).__name__) |
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1080 raise PathAccessError(exc, seg, path) |
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1081 except PathAccessError: |
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1082 if default is _UNSET: |
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1083 raise |
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1084 return default |
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1085 return cur |
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1086 |
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1087 |
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1088 def research(root, query=lambda p, k, v: True, reraise=False): |
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1089 """The :func:`research` function uses :func:`remap` to recurse over |
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1090 any data nested in *root*, and find values which match a given |
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1091 criterion, specified by the *query* callable. |
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1092 |
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1093 Results are returned as a list of ``(path, value)`` pairs. The |
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1094 paths are tuples in the same format accepted by |
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1095 :func:`get_path`. This can be useful for comparing values nested |
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1096 in two or more different structures. |
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1097 |
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1098 Here's a simple example that finds all integers: |
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1099 |
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1100 >>> root = {'a': {'b': 1, 'c': (2, 'd', 3)}, 'e': None} |
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1101 >>> res = research(root, query=lambda p, k, v: isinstance(v, int)) |
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1102 >>> print(sorted(res)) |
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1103 [(('a', 'b'), 1), (('a', 'c', 0), 2), (('a', 'c', 2), 3)] |
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1104 |
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1105 Note how *query* follows the same, familiar ``path, key, value`` |
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1106 signature as the ``visit`` and ``enter`` functions on |
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1107 :func:`remap`, and returns a :class:`bool`. |
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1108 |
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1109 Args: |
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1110 root: The target object to search. Supports the same types of |
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1111 objects as :func:`remap`, including :class:`list`, |
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1112 :class:`tuple`, :class:`dict`, and :class:`set`. |
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1113 query (callable): The function called on every object to |
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1114 determine whether to include it in the search results. The |
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1115 callable must accept three arguments, *path*, *key*, and |
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1116 *value*, commonly abbreviated *p*, *k*, and *v*, same as |
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1117 *enter* and *visit* from :func:`remap`. |
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1118 reraise (bool): Whether to reraise exceptions raised by *query* |
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1119 or to simply drop the result that caused the error. |
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1120 |
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1121 |
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1122 With :func:`research` it's easy to inspect the details of a data |
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1123 structure, like finding values that are at a certain depth (using |
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1124 ``len(p)``) and much more. If more advanced functionality is |
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1125 needed, check out the code and make your own :func:`remap` |
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1126 wrapper, and consider `submitting a patch`_! |
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1127 |
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1128 .. _submitting a patch: https://github.com/mahmoud/boltons/pulls |
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1129 """ |
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1130 ret = [] |
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1131 |
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1132 if not callable(query): |
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1133 raise TypeError('query expected callable, not: %r' % query) |
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1134 |
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1135 def enter(path, key, value): |
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1136 try: |
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1137 if query(path, key, value): |
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1138 ret.append((path + (key,), value)) |
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1139 except Exception: |
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1140 if reraise: |
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1141 raise |
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1142 return default_enter(path, key, value) |
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1143 |
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1144 remap(root, enter=enter) |
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1145 return ret |
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1146 |
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1147 |
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1148 # TODO: recollect() |
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1149 # TODO: refilter() |
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1150 # TODO: reiter() |
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1151 |
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1152 |
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1153 # GUID iterators: 10x faster and somewhat more compact than uuid. |
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1154 |
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1155 class GUIDerator(object): |
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1156 """The GUIDerator is an iterator that yields a globally-unique |
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1157 identifier (GUID) on every iteration. The GUIDs produced are |
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1158 hexadecimal strings. |
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1159 |
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1160 Testing shows it to be around 12x faster than the uuid module. By |
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1161 default it is also more compact, partly due to its default 96-bit |
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1162 (24-hexdigit) length. 96 bits of randomness means that there is a |
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1163 1 in 2 ^ 32 chance of collision after 2 ^ 64 iterations. If more |
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1164 or less uniqueness is desired, the *size* argument can be adjusted |
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1165 accordingly. |
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1166 |
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1167 Args: |
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1168 size (int): character length of the GUID, defaults to 24. Lengths |
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1169 between 20 and 36 are considered valid. |
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1170 |
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1171 The GUIDerator has built-in fork protection that causes it to |
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1172 detect a fork on next iteration and reseed accordingly. |
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1173 |
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1174 """ |
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1175 def __init__(self, size=24): |
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1176 self.size = size |
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1177 if size < 20 or size > 36: |
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1178 raise ValueError('expected 20 < size <= 36') |
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1179 self.count = itertools.count() |
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1180 self.reseed() |
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1181 |
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1182 def reseed(self): |
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1183 self.pid = os.getpid() |
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1184 self.salt = '-'.join([str(self.pid), |
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1185 socket.gethostname() or b'<nohostname>', |
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1186 str(time.time()), |
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1187 codecs.encode(os.urandom(6), |
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1188 'hex_codec').decode('ascii')]) |
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1189 # that codecs trick is the best/only way to get a bytes to |
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1190 # hexbytes in py2/3 |
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1191 return |
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1192 |
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1193 def __iter__(self): |
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1194 return self |
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1195 |
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1196 if _IS_PY3: |
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1197 def __next__(self): |
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1198 if os.getpid() != self.pid: |
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1199 self.reseed() |
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1200 target_bytes = (self.salt + str(next(self.count))).encode('utf8') |
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1201 hash_text = hashlib.sha1(target_bytes).hexdigest()[:self.size] |
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1202 return hash_text |
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1203 else: |
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1204 def __next__(self): |
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1205 if os.getpid() != self.pid: |
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1206 self.reseed() |
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1207 return hashlib.sha1(self.salt + |
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1208 str(next(self.count))).hexdigest()[:self.size] |
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1209 |
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1210 next = __next__ |
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1211 |
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1212 |
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1213 class SequentialGUIDerator(GUIDerator): |
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1214 """Much like the standard GUIDerator, the SequentialGUIDerator is an |
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1215 iterator that yields a globally-unique identifier (GUID) on every |
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1216 iteration. The GUIDs produced are hexadecimal strings. |
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1217 |
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1218 The SequentialGUIDerator differs in that it picks a starting GUID |
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1219 value and increments every iteration. This yields GUIDs which are |
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1220 of course unique, but also ordered and lexicographically sortable. |
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1221 |
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1222 The SequentialGUIDerator is around 50% faster than the normal |
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1223 GUIDerator, making it almost 20x as fast as the built-in uuid |
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1224 module. By default it is also more compact, partly due to its |
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1225 96-bit (24-hexdigit) default length. 96 bits of randomness means that |
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1226 there is a 1 in 2 ^ 32 chance of collision after 2 ^ 64 |
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1227 iterations. If more or less uniqueness is desired, the *size* |
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1228 argument can be adjusted accordingly. |
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1229 |
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1230 Args: |
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1231 size (int): character length of the GUID, defaults to 24. |
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1232 |
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1233 Note that with SequentialGUIDerator there is a chance of GUIDs |
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1234 growing larger than the size configured. The SequentialGUIDerator |
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1235 has built-in fork protection that causes it to detect a fork on |
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1236 next iteration and reseed accordingly. |
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1237 |
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1238 """ |
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1239 |
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1240 if _IS_PY3: |
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1241 def reseed(self): |
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1242 super(SequentialGUIDerator, self).reseed() |
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1243 start_str = hashlib.sha1(self.salt.encode('utf8')).hexdigest() |
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1244 self.start = int(start_str[:self.size], 16) |
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1245 self.start |= (1 << ((self.size * 4) - 2)) |
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1246 else: |
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1247 def reseed(self): |
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1248 super(SequentialGUIDerator, self).reseed() |
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1249 start_str = hashlib.sha1(self.salt).hexdigest() |
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1250 self.start = int(start_str[:self.size], 16) |
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1251 self.start |= (1 << ((self.size * 4) - 2)) |
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1252 |
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1253 def __next__(self): |
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1254 if os.getpid() != self.pid: |
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1255 self.reseed() |
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1256 return '%x' % (next(self.count) + self.start) |
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1257 |
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1258 next = __next__ |
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1259 |
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1260 |
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1261 guid_iter = GUIDerator() |
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1262 seq_guid_iter = SequentialGUIDerator() |
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1263 |
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1264 |
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1265 def soft_sorted(iterable, first=None, last=None, key=None, reverse=False): |
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1266 """For when you care about the order of some elements, but not about |
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1267 others. |
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1268 |
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1269 Use this to float to the top and/or sink to the bottom a specific |
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1270 ordering, while sorting the rest of the elements according to |
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1271 normal :func:`sorted` rules. |
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1272 |
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1273 >>> soft_sorted(['two', 'b', 'one', 'a'], first=['one', 'two']) |
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1274 ['one', 'two', 'a', 'b'] |
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1275 >>> soft_sorted(range(7), first=[6, 15], last=[2, 4], reverse=True) |
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1276 [6, 5, 3, 1, 0, 2, 4] |
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1277 >>> import string |
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1278 >>> ''.join(soft_sorted(string.hexdigits, first='za1', last='b', key=str.lower)) |
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1279 'aA1023456789cCdDeEfFbB' |
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1280 |
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1281 Args: |
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1282 iterable (list): A list or other iterable to sort. |
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1283 first (list): A sequence to enforce for elements which should |
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1284 appear at the beginning of the returned list. |
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1285 last (list): A sequence to enforce for elements which should |
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1286 appear at the end of the returned list. |
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1287 key (callable): Callable used to generate a comparable key for |
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1288 each item to be sorted, same as the key in |
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1289 :func:`sorted`. Note that entries in *first* and *last* |
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1290 should be the keys for the items. Defaults to |
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1291 passthrough/the identity function. |
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1292 reverse (bool): Whether or not elements not explicitly ordered |
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1293 by *first* and *last* should be in reverse order or not. |
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1294 |
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1295 Returns a new list in sorted order. |
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1296 """ |
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1297 first = first or [] |
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1298 last = last or [] |
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1299 key = key or (lambda x: x) |
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1300 seq = list(iterable) |
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1301 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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1302 other.sort(key=key, reverse=reverse) |
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1303 |
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1304 if first: |
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1305 first = sorted([x for x in seq if key(x) in first], key=lambda x: first.index(key(x))) |
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1306 if last: |
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1307 last = sorted([x for x in seq if key(x) in last], key=lambda x: last.index(key(x))) |
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1308 return first + other + last |
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1309 |
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1310 """ |
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1311 May actually be faster to do an isinstance check for a str path |
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1312 |
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1313 $ python -m timeit -s "x = [1]" "x[0]" |
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1314 10000000 loops, best of 3: 0.0207 usec per loop |
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1315 $ python -m timeit -s "x = [1]" "try: x[0] \nexcept: pass" |
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1316 10000000 loops, best of 3: 0.029 usec per loop |
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1317 $ python -m timeit -s "x = [1]" "try: x[1] \nexcept: pass" |
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1318 1000000 loops, best of 3: 0.315 usec per loop |
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1319 # setting up try/except is fast, only around 0.01us |
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1320 # actually triggering the exception takes almost 10x as long |
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1321 |
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1322 $ python -m timeit -s "x = [1]" "isinstance(x, basestring)" |
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1323 10000000 loops, best of 3: 0.141 usec per loop |
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1324 $ python -m timeit -s "x = [1]" "isinstance(x, str)" |
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1325 10000000 loops, best of 3: 0.131 usec per loop |
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1326 $ python -m timeit -s "x = [1]" "try: x.split('.')\n except: pass" |
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1327 1000000 loops, best of 3: 0.443 usec per loop |
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1328 $ python -m timeit -s "x = [1]" "try: x.split('.') \nexcept AttributeError: pass" |
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1329 1000000 loops, best of 3: 0.544 usec per loop |
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1330 """ |