annotate mercurial/worker.py @ 26551:5b8faea8b509

extract: move 'branch' assignment where it is parsed There is one setter and no consumer, we can move it there directly.
author Pierre-Yves David <pierre-yves.david@fb.com>
date Tue, 06 Oct 2015 02:06:36 -0700
parents d29859cfcfc2
children c0501c26b05c
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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1 # worker.py - master-slave parallelism support
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2 #
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3 # Copyright 2013 Facebook, Inc.
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4 #
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5 # This software may be used and distributed according to the terms of the
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6 # GNU General Public License version 2 or any later version.
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7
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8 from __future__ import absolute_import
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9
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10 import errno
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11 import multiprocessing
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12 import os
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13 import signal
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14 import sys
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15 import threading
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16
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17 from .i18n import _
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18 from . import util
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19
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20 def countcpus():
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21 '''try to count the number of CPUs on the system'''
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22 try:
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23 return multiprocessing.cpu_count()
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24 except NotImplementedError:
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25 return 1
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26
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27 def _numworkers(ui):
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28 s = ui.config('worker', 'numcpus')
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29 if s:
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30 try:
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31 n = int(s)
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32 if n >= 1:
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33 return n
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34 except ValueError:
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35 raise util.Abort(_('number of cpus must be an integer'))
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36 return min(max(countcpus(), 4), 32)
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37
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38 if os.name == 'posix':
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39 _startupcost = 0.01
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40 else:
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41 _startupcost = 1e30
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42
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43 def worthwhile(ui, costperop, nops):
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44 '''try to determine whether the benefit of multiple processes can
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45 outweigh the cost of starting them'''
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46 linear = costperop * nops
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47 workers = _numworkers(ui)
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48 benefit = linear - (_startupcost * workers + linear / workers)
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49 return benefit >= 0.15
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50
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51 def worker(ui, costperarg, func, staticargs, args):
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52 '''run a function, possibly in parallel in multiple worker
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53 processes.
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54
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55 returns a progress iterator
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56
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57 costperarg - cost of a single task
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58
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59 func - function to run
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60
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61 staticargs - arguments to pass to every invocation of the function
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62
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63 args - arguments to split into chunks, to pass to individual
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64 workers
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65 '''
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66 if worthwhile(ui, costperarg, len(args)):
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67 return _platformworker(ui, func, staticargs, args)
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68 return func(*staticargs + (args,))
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69
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70 def _posixworker(ui, func, staticargs, args):
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71 rfd, wfd = os.pipe()
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72 workers = _numworkers(ui)
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73 oldhandler = signal.getsignal(signal.SIGINT)
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74 signal.signal(signal.SIGINT, signal.SIG_IGN)
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75 pids, problem = [], [0]
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76 for pargs in partition(args, workers):
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77 pid = os.fork()
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78 if pid == 0:
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79 signal.signal(signal.SIGINT, oldhandler)
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80 try:
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81 os.close(rfd)
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82 for i, item in func(*(staticargs + (pargs,))):
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83 os.write(wfd, '%d %s\n' % (i, item))
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84 os._exit(0)
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85 except KeyboardInterrupt:
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86 os._exit(255)
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87 # other exceptions are allowed to propagate, we rely
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88 # on lock.py's pid checks to avoid release callbacks
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89 pids.append(pid)
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90 pids.reverse()
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91 os.close(wfd)
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92 fp = os.fdopen(rfd, 'rb', 0)
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93 def killworkers():
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94 # if one worker bails, there's no good reason to wait for the rest
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95 for p in pids:
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96 try:
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97 os.kill(p, signal.SIGTERM)
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98 except OSError as err:
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99 if err.errno != errno.ESRCH:
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100 raise
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101 def waitforworkers():
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102 for _pid in pids:
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103 st = _exitstatus(os.wait()[1])
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104 if st and not problem[0]:
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105 problem[0] = st
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106 killworkers()
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107 t = threading.Thread(target=waitforworkers)
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108 t.start()
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109 def cleanup():
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110 signal.signal(signal.SIGINT, oldhandler)
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111 t.join()
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112 status = problem[0]
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113 if status:
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114 if status < 0:
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115 os.kill(os.getpid(), -status)
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116 sys.exit(status)
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117 try:
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118 for line in fp:
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119 l = line.split(' ', 1)
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120 yield int(l[0]), l[1][:-1]
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121 except: # re-raises
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122 killworkers()
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123 cleanup()
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124 raise
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125 cleanup()
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126
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127 def _posixexitstatus(code):
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128 '''convert a posix exit status into the same form returned by
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129 os.spawnv
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130
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131 returns None if the process was stopped instead of exiting'''
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132 if os.WIFEXITED(code):
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133 return os.WEXITSTATUS(code)
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134 elif os.WIFSIGNALED(code):
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135 return -os.WTERMSIG(code)
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136
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137 if os.name != 'nt':
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138 _platformworker = _posixworker
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139 _exitstatus = _posixexitstatus
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140
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141 def partition(lst, nslices):
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142 '''partition a list into N slices of equal size'''
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143 n = len(lst)
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144 chunk, slop = n / nslices, n % nslices
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145 end = 0
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146 for i in xrange(nslices):
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147 start = end
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148 end = start + chunk
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149 if slop:
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150 end += 1
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151 slop -= 1
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152 yield lst[start:end]