annotate mercurial/profiling.py @ 32983:0d757af1ea67

configitems: add a basic class to hold config item information The goal of this class is allow explicit declaration for the available config option. This class will hold the data for one specific config item. To keep it simple we start centralizing the handling of the default config value. In the future we can expect more data to be carried on this class. For example: - documentation, - status (experimental, advanced, normal, deprecated), - aliases, - expected type, - etc...
author Pierre-Yves David <pierre-yves.david@octobus.net>
date Sat, 17 Jun 2017 18:41:55 +0200
parents 41b081ac2145
children 5d8942dbe49e
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1 # profiling.py - profiling functions
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2 #
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3 # Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
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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, print_function
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9
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10 import contextlib
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11
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12 from .i18n import _
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13 from . import (
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14 encoding,
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15 error,
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16 extensions,
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17 util,
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18 )
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19
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20 def _loadprofiler(ui, profiler):
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21 """load profiler extension. return profile method, or None on failure"""
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22 extname = profiler
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23 extensions.loadall(ui, whitelist=[extname])
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24 try:
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25 mod = extensions.find(extname)
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26 except KeyError:
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27 return None
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28 else:
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29 return getattr(mod, 'profile', None)
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30
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31 @contextlib.contextmanager
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32 def lsprofile(ui, fp):
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33 format = ui.config('profiling', 'format', default='text')
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34 field = ui.config('profiling', 'sort', default='inlinetime')
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35 limit = ui.configint('profiling', 'limit', default=30)
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36 climit = ui.configint('profiling', 'nested', default=0)
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37
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38 if format not in ['text', 'kcachegrind']:
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39 ui.warn(_("unrecognized profiling format '%s'"
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40 " - Ignored\n") % format)
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41 format = 'text'
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42
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43 try:
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44 from . import lsprof
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45 except ImportError:
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46 raise error.Abort(_(
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47 'lsprof not available - install from '
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48 'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
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49 p = lsprof.Profiler()
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50 p.enable(subcalls=True)
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51 try:
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52 yield
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53 finally:
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54 p.disable()
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55
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56 if format == 'kcachegrind':
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57 from . import lsprofcalltree
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58 calltree = lsprofcalltree.KCacheGrind(p)
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59 calltree.output(fp)
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60 else:
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61 # format == 'text'
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62 stats = lsprof.Stats(p.getstats())
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63 stats.sort(field)
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64 stats.pprint(limit=limit, file=fp, climit=climit)
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65
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66 @contextlib.contextmanager
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67 def flameprofile(ui, fp):
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68 try:
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69 from flamegraph import flamegraph
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70 except ImportError:
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71 raise error.Abort(_(
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72 'flamegraph not available - install from '
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73 'https://github.com/evanhempel/python-flamegraph'))
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74 # developer config: profiling.freq
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75 freq = ui.configint('profiling', 'freq', default=1000)
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76 filter_ = None
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77 collapse_recursion = True
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78 thread = flamegraph.ProfileThread(fp, 1.0 / freq,
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79 filter_, collapse_recursion)
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80 start_time = util.timer()
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81 try:
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82 thread.start()
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83 yield
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84 finally:
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85 thread.stop()
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86 thread.join()
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87 print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
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88 util.timer() - start_time, thread.num_frames(),
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89 thread.num_frames(unique=True)))
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90
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91 @contextlib.contextmanager
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92 def statprofile(ui, fp):
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93 from . import statprof
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94
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95 freq = ui.configint('profiling', 'freq', default=1000)
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96 if freq > 0:
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97 # Cannot reset when profiler is already active. So silently no-op.
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98 if statprof.state.profile_level == 0:
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99 statprof.reset(freq)
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100 else:
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101 ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)
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102
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103 statprof.start(mechanism='thread')
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104
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105 try:
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106 yield
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107 finally:
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108 data = statprof.stop()
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109
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110 profformat = ui.config('profiling', 'statformat', 'hotpath')
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111
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112 formats = {
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113 'byline': statprof.DisplayFormats.ByLine,
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114 'bymethod': statprof.DisplayFormats.ByMethod,
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115 'hotpath': statprof.DisplayFormats.Hotpath,
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116 'json': statprof.DisplayFormats.Json,
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117 'chrome': statprof.DisplayFormats.Chrome,
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118 }
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119
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120 if profformat in formats:
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121 displayformat = formats[profformat]
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122 else:
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123 ui.warn(_('unknown profiler output format: %s\n') % profformat)
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124 displayformat = statprof.DisplayFormats.Hotpath
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125
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126 kwargs = {}
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127
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128 def fraction(s):
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129 if isinstance(s, (float, int)):
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130 return float(s)
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131 if s.endswith('%'):
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132 v = float(s[:-1]) / 100
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133 else:
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134 v = float(s)
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135 if 0 <= v <= 1:
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136 return v
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137 raise ValueError(s)
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138
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139 if profformat == 'chrome':
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140 showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
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141 showmax = ui.configwith(fraction, 'profiling', 'showmax', 0.999)
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142 kwargs.update(minthreshold=showmin, maxthreshold=showmax)
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143 elif profformat == 'hotpath':
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144 limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05)
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145 kwargs['limit'] = limit
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146
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147 statprof.display(fp, data=data, format=displayformat, **kwargs)
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148
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149 class profile(object):
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150 """Start profiling.
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151
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152 Profiling is active when the context manager is active. When the context
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153 manager exits, profiling results will be written to the configured output.
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154 """
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155 def __init__(self, ui, enabled=True):
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156 self._ui = ui
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157 self._output = None
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158 self._fp = None
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159 self._fpdoclose = True
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160 self._profiler = None
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161 self._enabled = enabled
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162 self._entered = False
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163 self._started = False
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164
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165 def __enter__(self):
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166 self._entered = True
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167 if self._enabled:
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168 self.start()
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169 return self
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170
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171 def start(self):
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172 """Start profiling.
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173
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174 The profiling will stop at the context exit.
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175
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176 If the profiler was already started, this has no effect."""
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177 if not self._entered:
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178 raise error.ProgrammingError()
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179 if self._started:
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180 return
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181 self._started = True
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182 profiler = encoding.environ.get('HGPROF')
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183 proffn = None
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184 if profiler is None:
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185 profiler = self._ui.config('profiling', 'type', default='stat')
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186 if profiler not in ('ls', 'stat', 'flame'):
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187 # try load profiler from extension with the same name
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188 proffn = _loadprofiler(self._ui, profiler)
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189 if proffn is None:
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190 self._ui.warn(_("unrecognized profiler '%s' - ignored\n")
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191 % profiler)
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192 profiler = 'stat'
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193
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194 self._output = self._ui.config('profiling', 'output')
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195
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196 try:
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197 if self._output == 'blackbox':
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198 self._fp = util.stringio()
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199 elif self._output:
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200 path = self._ui.expandpath(self._output)
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201 self._fp = open(path, 'wb')
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202 else:
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203 self._fpdoclose = False
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204 self._fp = self._ui.ferr
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205
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206 if proffn is not None:
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207 pass
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208 elif profiler == 'ls':
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209 proffn = lsprofile
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210 elif profiler == 'flame':
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211 proffn = flameprofile
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212 else:
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213 proffn = statprofile
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214
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215 self._profiler = proffn(self._ui, self._fp)
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216 self._profiler.__enter__()
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217 except: # re-raises
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218 self._closefp()
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219 raise
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220
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221 def __exit__(self, exception_type, exception_value, traceback):
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222 propagate = None
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223 if self._profiler is not None:
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224 propagate = self._profiler.__exit__(exception_type, exception_value,
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225 traceback)
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226 if self._output == 'blackbox':
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227 val = 'Profile:\n%s' % self._fp.getvalue()
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228 # ui.log treats the input as a format string,
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229 # so we need to escape any % signs.
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230 val = val.replace('%', '%%')
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231 self._ui.log('profile', val)
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232 self._closefp()
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233 return propagate
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234
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235 def _closefp(self):
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236 if self._fpdoclose and self._fp is not None:
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237 self._fp.close()