Mercurial > hg
annotate tests/test-ancestor.py @ 29588:1bb94666b9fc
commandserver: use SOMAXCONN as queue size of pending connections
The old value 5 was arbitrary chosen. Since there's no practical reason to
limit the backlog, this patch simply uses SOMAXCONN as a value large enough.
author | Yuya Nishihara <yuya@tcha.org> |
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date | Sat, 16 Jul 2016 14:48:58 +0900 |
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1 from __future__ import absolute_import, print_function |
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2 |
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3 import binascii |
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4 import getopt |
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5 import math |
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6 import os |
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7 import random |
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8 import sys |
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9 import time |
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10 |
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11 from mercurial.node import nullrev |
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12 from mercurial import ( |
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13 ancestor, |
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14 commands, |
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15 hg, |
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16 ui as uimod, |
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17 util, |
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18 ) |
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19 |
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20 def buildgraph(rng, nodes=100, rootprob=0.05, mergeprob=0.2, prevprob=0.7): |
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21 '''nodes: total number of nodes in the graph |
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22 rootprob: probability that a new node (not 0) will be a root |
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23 mergeprob: probability that, excluding a root a node will be a merge |
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24 prevprob: probability that p1 will be the previous node |
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25 |
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26 return value is a graph represented as an adjacency list. |
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27 ''' |
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28 graph = [None] * nodes |
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29 for i in xrange(nodes): |
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30 if i == 0 or rng.random() < rootprob: |
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31 graph[i] = [nullrev] |
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32 elif i == 1: |
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33 graph[i] = [0] |
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34 elif rng.random() < mergeprob: |
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35 if i == 2 or rng.random() < prevprob: |
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36 # p1 is prev |
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37 p1 = i - 1 |
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38 else: |
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39 p1 = rng.randrange(i - 1) |
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40 p2 = rng.choice(range(0, p1) + range(p1 + 1, i)) |
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41 graph[i] = [p1, p2] |
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42 elif rng.random() < prevprob: |
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43 graph[i] = [i - 1] |
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44 else: |
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45 graph[i] = [rng.randrange(i - 1)] |
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46 |
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47 return graph |
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48 |
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49 def buildancestorsets(graph): |
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50 ancs = [None] * len(graph) |
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51 for i in xrange(len(graph)): |
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52 ancs[i] = set([i]) |
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53 if graph[i] == [nullrev]: |
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54 continue |
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55 for p in graph[i]: |
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56 ancs[i].update(ancs[p]) |
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57 return ancs |
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58 |
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59 class naiveincrementalmissingancestors(object): |
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60 def __init__(self, ancs, bases): |
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61 self.ancs = ancs |
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62 self.bases = set(bases) |
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63 def addbases(self, newbases): |
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64 self.bases.update(newbases) |
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65 def removeancestorsfrom(self, revs): |
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66 for base in self.bases: |
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67 if base != nullrev: |
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68 revs.difference_update(self.ancs[base]) |
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69 revs.discard(nullrev) |
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70 def missingancestors(self, revs): |
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71 res = set() |
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72 for rev in revs: |
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73 if rev != nullrev: |
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74 res.update(self.ancs[rev]) |
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75 for base in self.bases: |
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76 if base != nullrev: |
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77 res.difference_update(self.ancs[base]) |
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78 return sorted(res) |
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79 |
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80 def test_missingancestors(seed, rng): |
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81 # empirically observed to take around 1 second |
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82 graphcount = 100 |
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83 testcount = 10 |
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84 inccount = 10 |
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85 nerrs = [0] |
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86 # the default mu and sigma give us a nice distribution of mostly |
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87 # single-digit counts (including 0) with some higher ones |
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88 def lognormrandom(mu, sigma): |
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89 return int(math.floor(rng.lognormvariate(mu, sigma))) |
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90 |
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91 def samplerevs(nodes, mu=1.1, sigma=0.8): |
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92 count = min(lognormrandom(mu, sigma), len(nodes)) |
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93 return rng.sample(nodes, count) |
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94 |
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95 def err(seed, graph, bases, seq, output, expected): |
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96 if nerrs[0] == 0: |
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97 print('seed:', hex(seed)[:-1], file=sys.stderr) |
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98 if gerrs[0] == 0: |
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99 print('graph:', graph, file=sys.stderr) |
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100 print('* bases:', bases, file=sys.stderr) |
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101 print('* seq: ', seq, file=sys.stderr) |
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102 print('* output: ', output, file=sys.stderr) |
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103 print('* expected:', expected, file=sys.stderr) |
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104 nerrs[0] += 1 |
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105 gerrs[0] += 1 |
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106 |
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107 for g in xrange(graphcount): |
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108 graph = buildgraph(rng) |
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109 ancs = buildancestorsets(graph) |
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110 gerrs = [0] |
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111 for _ in xrange(testcount): |
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112 # start from nullrev to include it as a possibility |
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113 graphnodes = range(nullrev, len(graph)) |
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114 bases = samplerevs(graphnodes) |
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115 |
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116 # fast algorithm |
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117 inc = ancestor.incrementalmissingancestors(graph.__getitem__, bases) |
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118 # reference slow algorithm |
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119 naiveinc = naiveincrementalmissingancestors(ancs, bases) |
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120 seq = [] |
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121 revs = [] |
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122 for _ in xrange(inccount): |
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123 if rng.random() < 0.2: |
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124 newbases = samplerevs(graphnodes) |
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125 seq.append(('addbases', newbases)) |
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126 inc.addbases(newbases) |
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127 naiveinc.addbases(newbases) |
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128 if rng.random() < 0.4: |
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129 # larger set so that there are more revs to remove from |
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130 revs = samplerevs(graphnodes, mu=1.5) |
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131 seq.append(('removeancestorsfrom', revs)) |
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132 hrevs = set(revs) |
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133 rrevs = set(revs) |
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134 inc.removeancestorsfrom(hrevs) |
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135 naiveinc.removeancestorsfrom(rrevs) |
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136 if hrevs != rrevs: |
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137 err(seed, graph, bases, seq, sorted(hrevs), |
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138 sorted(rrevs)) |
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139 else: |
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140 revs = samplerevs(graphnodes) |
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141 seq.append(('missingancestors', revs)) |
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142 h = inc.missingancestors(revs) |
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143 r = naiveinc.missingancestors(revs) |
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144 if h != r: |
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145 err(seed, graph, bases, seq, h, r) |
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146 |
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147 # graph is a dict of child->parent adjacency lists for this graph: |
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148 # o 13 |
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149 # | |
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150 # | o 12 |
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151 # | | |
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152 # | | o 11 |
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153 # | | |\ |
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154 # | | | | o 10 |
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155 # | | | | | |
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156 # | o---+ | 9 |
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157 # | | | | | |
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158 # o | | | | 8 |
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159 # / / / / |
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160 # | | o | 7 |
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161 # | | | | |
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162 # o---+ | 6 |
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163 # / / / |
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164 # | | o 5 |
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165 # | |/ |
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166 # | o 4 |
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167 # | | |
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168 # o | 3 |
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169 # | | |
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170 # | o 2 |
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171 # |/ |
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172 # o 1 |
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173 # | |
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174 # o 0 |
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175 |
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176 graph = {0: [-1], 1: [0], 2: [1], 3: [1], 4: [2], 5: [4], 6: [4], |
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177 7: [4], 8: [-1], 9: [6, 7], 10: [5], 11: [3, 7], 12: [9], |
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178 13: [8]} |
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179 |
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180 def genlazyancestors(revs, stoprev=0, inclusive=False): |
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181 print(("%% lazy ancestor set for %s, stoprev = %s, inclusive = %s" % |
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182 (revs, stoprev, inclusive))) |
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183 return ancestor.lazyancestors(graph.get, revs, stoprev=stoprev, |
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184 inclusive=inclusive) |
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185 |
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186 def printlazyancestors(s, l): |
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187 print('membership: %r' % [n for n in l if n in s]) |
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188 print('iteration: %r' % list(s)) |
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189 |
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190 def test_lazyancestors(): |
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191 # Empty revs |
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192 s = genlazyancestors([]) |
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193 printlazyancestors(s, [3, 0, -1]) |
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194 |
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195 # Standard example |
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196 s = genlazyancestors([11, 13]) |
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197 printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) |
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198 |
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199 # Standard with ancestry in the initial set (1 is ancestor of 3) |
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200 s = genlazyancestors([1, 3]) |
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201 printlazyancestors(s, [1, -1, 0]) |
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202 |
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203 # Including revs |
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204 s = genlazyancestors([11, 13], inclusive=True) |
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205 printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) |
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206 |
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207 # Test with stoprev |
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208 s = genlazyancestors([11, 13], stoprev=6) |
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209 printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) |
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210 s = genlazyancestors([11, 13], stoprev=6, inclusive=True) |
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211 printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) |
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212 |
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213 |
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214 # The C gca algorithm requires a real repo. These are textual descriptions of |
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215 # DAGs that have been known to be problematic. |
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216 dagtests = [ |
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217 '+2*2*2/*3/2', |
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218 '+3*3/*2*2/*4*4/*4/2*4/2*2', |
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219 ] |
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220 def test_gca(): |
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221 u = uimod.ui() |
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222 for i, dag in enumerate(dagtests): |
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223 repo = hg.repository(u, 'gca%d' % i, create=1) |
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224 cl = repo.changelog |
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225 if not util.safehasattr(cl.index, 'ancestors'): |
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226 # C version not available |
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227 return |
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228 |
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229 commands.debugbuilddag(u, repo, dag) |
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230 # Compare the results of the Python and C versions. This does not |
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231 # include choosing a winner when more than one gca exists -- we make |
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232 # sure both return exactly the same set of gcas. |
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233 for a in cl: |
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234 for b in cl: |
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235 cgcas = sorted(cl.index.ancestors(a, b)) |
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236 pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b)) |
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237 if cgcas != pygcas: |
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238 print("test_gca: for dag %s, gcas for %d, %d:" |
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239 % (dag, a, b)) |
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240 print(" C returned: %s" % cgcas) |
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241 print(" Python returned: %s" % pygcas) |
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242 |
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243 def main(): |
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244 seed = None |
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245 opts, args = getopt.getopt(sys.argv[1:], 's:', ['seed=']) |
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246 for o, a in opts: |
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247 if o in ('-s', '--seed'): |
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248 seed = long(a, base=0) # accepts base 10 or 16 strings |
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249 |
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250 if seed is None: |
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251 try: |
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252 seed = long(binascii.hexlify(os.urandom(16)), 16) |
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253 except AttributeError: |
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254 seed = long(time.time() * 1000) |
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255 |
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256 rng = random.Random(seed) |
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257 test_missingancestors(seed, rng) |
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258 test_lazyancestors() |
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259 test_gca() |
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260 |
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261 if __name__ == '__main__': |
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262 main() |