Mercurial > hg
annotate mercurial/profiling.py @ 40324:6637b079ae45
lfs: autoload the extension when cloning from repo with lfs enabled
This is based on a patch by Gregory Szorc. I made small adjustments to
clean up the messaging when the server has the extension enabled, but the
client has it disabled (to prevent autoloading). Additionally, I added
a second server capability to distinguish between the server having the
extension enabled, and the server having LFS commits. This helps prevent
unnecessary requirement propagation- the client shouldn't add a requirement
that the server doesn't have, just because the server had the extension
loaded. The TODO I had about advertising a capability when the server can
natively serve up blobs isn't relevant anymore (we've had 2 releases that
support this), so I dropped it.
Currently, we lazily add the "lfs" requirement to a repo when we first
encounter LFS data. Due to a pretxnchangegroup hook that looks for LFS
data, this can happen at the end of clone.
Now that we have more control over how repositories are created, we can
do better.
This commit adds a repo creation option to add the "lfs" requirement.
hg.clone() sets this creation option if the remote peer is advertising
lfs usage (as opposed to just support needed to push).
So, what this change effectively does is have cloned repos
automatically inherit the "lfs" requirement.
Differential Revision: https://phab.mercurial-scm.org/D5130
author | Matt Harbison <matt_harbison@yahoo.com> |
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date | Thu, 20 Sep 2018 17:27:01 -0700 |
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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 pycompat, |
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18 util, |
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19 ) |
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20 |
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21 def _loadprofiler(ui, profiler): |
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22 """load profiler extension. return profile method, or None on failure""" |
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23 extname = profiler |
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24 extensions.loadall(ui, whitelist=[extname]) |
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25 try: |
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26 mod = extensions.find(extname) |
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27 except KeyError: |
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28 return None |
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29 else: |
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30 return getattr(mod, 'profile', None) |
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31 |
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32 @contextlib.contextmanager |
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33 def lsprofile(ui, fp): |
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34 format = ui.config('profiling', 'format') |
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35 field = ui.config('profiling', 'sort') |
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36 limit = ui.configint('profiling', 'limit') |
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37 climit = ui.configint('profiling', 'nested') |
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38 |
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39 if format not in ['text', 'kcachegrind']: |
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40 ui.warn(_("unrecognized profiling format '%s'" |
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41 " - Ignored\n") % format) |
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42 format = 'text' |
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43 |
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44 try: |
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45 from . import lsprof |
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46 except ImportError: |
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47 raise error.Abort(_( |
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48 'lsprof not available - install from ' |
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49 'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/')) |
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50 p = lsprof.Profiler() |
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51 p.enable(subcalls=True) |
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52 try: |
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53 yield |
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54 finally: |
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55 p.disable() |
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56 |
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57 if format == 'kcachegrind': |
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58 from . import lsprofcalltree |
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59 calltree = lsprofcalltree.KCacheGrind(p) |
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60 calltree.output(fp) |
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61 else: |
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62 # format == 'text' |
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63 stats = lsprof.Stats(p.getstats()) |
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64 stats.sort(pycompat.sysstr(field)) |
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65 stats.pprint(limit=limit, file=fp, climit=climit) |
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66 |
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67 @contextlib.contextmanager |
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68 def flameprofile(ui, fp): |
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69 try: |
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70 from flamegraph import flamegraph |
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71 except ImportError: |
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72 raise error.Abort(_( |
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73 'flamegraph not available - install from ' |
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74 'https://github.com/evanhempel/python-flamegraph')) |
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75 # developer config: profiling.freq |
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76 freq = ui.configint('profiling', 'freq') |
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77 filter_ = None |
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78 collapse_recursion = True |
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79 thread = flamegraph.ProfileThread(fp, 1.0 / freq, |
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80 filter_, collapse_recursion) |
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81 start_time = util.timer() |
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82 try: |
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83 thread.start() |
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84 yield |
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85 finally: |
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86 thread.stop() |
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87 thread.join() |
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88 print('Collected %d stack frames (%d unique) in %2.2f seconds.' % ( |
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89 util.timer() - start_time, thread.num_frames(), |
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90 thread.num_frames(unique=True))) |
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91 |
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92 @contextlib.contextmanager |
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93 def statprofile(ui, fp): |
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94 from . import statprof |
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95 |
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96 freq = ui.configint('profiling', 'freq') |
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97 if freq > 0: |
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98 # Cannot reset when profiler is already active. So silently no-op. |
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99 if statprof.state.profile_level == 0: |
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100 statprof.reset(freq) |
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101 else: |
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102 ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq) |
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103 |
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104 track = ui.config('profiling', 'time-track') |
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105 statprof.start(mechanism='thread', track=track) |
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106 |
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107 try: |
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108 yield |
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109 finally: |
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110 data = statprof.stop() |
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111 |
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112 profformat = ui.config('profiling', 'statformat') |
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113 |
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114 formats = { |
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115 'byline': statprof.DisplayFormats.ByLine, |
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116 'bymethod': statprof.DisplayFormats.ByMethod, |
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117 'hotpath': statprof.DisplayFormats.Hotpath, |
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118 'json': statprof.DisplayFormats.Json, |
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119 'chrome': statprof.DisplayFormats.Chrome, |
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120 } |
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121 |
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122 if profformat in formats: |
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123 displayformat = formats[profformat] |
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124 else: |
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125 ui.warn(_('unknown profiler output format: %s\n') % profformat) |
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126 displayformat = statprof.DisplayFormats.Hotpath |
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127 |
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128 kwargs = {} |
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129 |
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130 def fraction(s): |
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131 if isinstance(s, (float, int)): |
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132 return float(s) |
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133 if s.endswith('%'): |
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134 v = float(s[:-1]) / 100 |
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135 else: |
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136 v = float(s) |
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137 if 0 <= v <= 1: |
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138 return v |
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139 raise ValueError(s) |
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140 |
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141 if profformat == 'chrome': |
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142 showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005) |
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143 showmax = ui.configwith(fraction, 'profiling', 'showmax') |
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144 kwargs.update(minthreshold=showmin, maxthreshold=showmax) |
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145 elif profformat == 'hotpath': |
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146 # inconsistent config: profiling.showmin |
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147 limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05) |
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148 kwargs[r'limit'] = limit |
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149 |
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150 statprof.display(fp, data=data, format=displayformat, **kwargs) |
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151 |
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152 class profile(object): |
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153 """Start profiling. |
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154 |
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155 Profiling is active when the context manager is active. When the context |
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156 manager exits, profiling results will be written to the configured output. |
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157 """ |
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158 def __init__(self, ui, enabled=True): |
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159 self._ui = ui |
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160 self._output = None |
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161 self._fp = None |
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162 self._fpdoclose = True |
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163 self._profiler = None |
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164 self._enabled = enabled |
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165 self._entered = False |
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166 self._started = False |
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167 |
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168 def __enter__(self): |
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169 self._entered = True |
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170 if self._enabled: |
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171 self.start() |
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172 return self |
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173 |
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174 def start(self): |
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175 """Start profiling. |
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176 |
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177 The profiling will stop at the context exit. |
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178 |
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179 If the profiler was already started, this has no effect.""" |
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180 if not self._entered: |
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181 raise error.ProgrammingError() |
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182 if self._started: |
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183 return |
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184 self._started = True |
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185 profiler = encoding.environ.get('HGPROF') |
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186 proffn = None |
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187 if profiler is None: |
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188 profiler = self._ui.config('profiling', 'type') |
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189 if profiler not in ('ls', 'stat', 'flame'): |
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190 # try load profiler from extension with the same name |
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191 proffn = _loadprofiler(self._ui, profiler) |
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192 if proffn is None: |
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193 self._ui.warn(_("unrecognized profiler '%s' - ignored\n") |
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194 % profiler) |
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195 profiler = 'stat' |
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196 |
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197 self._output = self._ui.config('profiling', 'output') |
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198 |
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199 try: |
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200 if self._output == 'blackbox': |
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201 self._fp = util.stringio() |
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202 elif self._output: |
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203 path = self._ui.expandpath(self._output) |
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204 self._fp = open(path, 'wb') |
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205 elif pycompat.iswindows: |
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206 # parse escape sequence by win32print() |
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207 class uifp(object): |
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208 def __init__(self, ui): |
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209 self._ui = ui |
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210 def write(self, data): |
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211 self._ui.write_err(data) |
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212 def flush(self): |
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213 self._ui.flush() |
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214 self._fpdoclose = False |
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215 self._fp = uifp(self._ui) |
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216 else: |
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217 self._fpdoclose = False |
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218 self._fp = self._ui.ferr |
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219 |
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220 if proffn is not None: |
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221 pass |
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222 elif profiler == 'ls': |
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223 proffn = lsprofile |
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224 elif profiler == 'flame': |
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225 proffn = flameprofile |
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226 else: |
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227 proffn = statprofile |
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228 |
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229 self._profiler = proffn(self._ui, self._fp) |
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230 self._profiler.__enter__() |
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231 except: # re-raises |
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232 self._closefp() |
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233 raise |
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234 |
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235 def __exit__(self, exception_type, exception_value, traceback): |
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236 propagate = None |
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237 if self._profiler is not None: |
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238 propagate = self._profiler.__exit__(exception_type, exception_value, |
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239 traceback) |
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240 if self._output == 'blackbox': |
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241 val = 'Profile:\n%s' % self._fp.getvalue() |
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242 # ui.log treats the input as a format string, |
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243 # so we need to escape any % signs. |
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244 val = val.replace('%', '%%') |
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245 self._ui.log('profile', val) |
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246 self._closefp() |
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247 return propagate |
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248 |
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249 def _closefp(self): |
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250 if self._fpdoclose and self._fp is not None: |
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251 self._fp.close() |