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1 1 # profiling.py - profiling functions
2 2 #
3 3 # Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
4 4 #
5 5 # This software may be used and distributed according to the terms of the
6 6 # GNU General Public License version 2 or any later version.
7 7
8 8 from __future__ import absolute_import, print_function
9 9
10 10 import contextlib
11 11
12 12 from .i18n import _
13 13 from . import (
14 14 encoding,
15 15 error,
16 16 extensions,
17 17 util,
18 18 )
19 19
20 20 def _loadprofiler(ui, profiler):
21 21 """load profiler extension. return profile method, or None on failure"""
22 22 extname = profiler
23 23 extensions.loadall(ui, whitelist=[extname])
24 24 try:
25 25 mod = extensions.find(extname)
26 26 except KeyError:
27 27 return None
28 28 else:
29 29 return getattr(mod, 'profile', None)
30 30
31 31 @contextlib.contextmanager
32 32 def lsprofile(ui, fp):
33 33 format = ui.config('profiling', 'format', default='text')
34 34 field = ui.config('profiling', 'sort', default='inlinetime')
35 35 limit = ui.configint('profiling', 'limit', default=30)
36 36 climit = ui.configint('profiling', 'nested', default=0)
37 37
38 38 if format not in ['text', 'kcachegrind']:
39 39 ui.warn(_("unrecognized profiling format '%s'"
40 40 " - Ignored\n") % format)
41 41 format = 'text'
42 42
43 43 try:
44 44 from . import lsprof
45 45 except ImportError:
46 46 raise error.Abort(_(
47 47 'lsprof not available - install from '
48 48 'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
49 49 p = lsprof.Profiler()
50 50 p.enable(subcalls=True)
51 51 try:
52 52 yield
53 53 finally:
54 54 p.disable()
55 55
56 56 if format == 'kcachegrind':
57 57 from . import lsprofcalltree
58 58 calltree = lsprofcalltree.KCacheGrind(p)
59 59 calltree.output(fp)
60 60 else:
61 61 # format == 'text'
62 62 stats = lsprof.Stats(p.getstats())
63 63 stats.sort(field)
64 64 stats.pprint(limit=limit, file=fp, climit=climit)
65 65
66 66 @contextlib.contextmanager
67 67 def flameprofile(ui, fp):
68 68 try:
69 69 from flamegraph import flamegraph
70 70 except ImportError:
71 71 raise error.Abort(_(
72 72 'flamegraph not available - install from '
73 73 'https://github.com/evanhempel/python-flamegraph'))
74 74 # developer config: profiling.freq
75 75 freq = ui.configint('profiling', 'freq', default=1000)
76 76 filter_ = None
77 77 collapse_recursion = True
78 78 thread = flamegraph.ProfileThread(fp, 1.0 / freq,
79 79 filter_, collapse_recursion)
80 80 start_time = util.timer()
81 81 try:
82 82 thread.start()
83 83 yield
84 84 finally:
85 85 thread.stop()
86 86 thread.join()
87 87 print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
88 88 util.timer() - start_time, thread.num_frames(),
89 89 thread.num_frames(unique=True)))
90 90
91 91 @contextlib.contextmanager
92 92 def statprofile(ui, fp):
93 93 from . import statprof
94 94
95 95 freq = ui.configint('profiling', 'freq', default=1000)
96 96 if freq > 0:
97 97 # Cannot reset when profiler is already active. So silently no-op.
98 98 if statprof.state.profile_level == 0:
99 99 statprof.reset(freq)
100 100 else:
101 101 ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)
102 102
103 103 statprof.start(mechanism='thread')
104 104
105 105 try:
106 106 yield
107 107 finally:
108 108 data = statprof.stop()
109 109
110 110 profformat = ui.config('profiling', 'statformat', 'hotpath')
111 111
112 112 formats = {
113 113 'byline': statprof.DisplayFormats.ByLine,
114 114 'bymethod': statprof.DisplayFormats.ByMethod,
115 115 'hotpath': statprof.DisplayFormats.Hotpath,
116 116 'json': statprof.DisplayFormats.Json,
117 117 'chrome': statprof.DisplayFormats.Chrome,
118 118 }
119 119
120 120 if profformat in formats:
121 121 displayformat = formats[profformat]
122 122 else:
123 123 ui.warn(_('unknown profiler output format: %s\n') % profformat)
124 124 displayformat = statprof.DisplayFormats.Hotpath
125 125
126 126 kwargs = {}
127 127
128 128 def fraction(s):
129 129 if s.endswith('%'):
130 130 v = float(s[:-1]) / 100
131 131 else:
132 132 v = float(s)
133 133 if 0 <= v <= 1:
134 134 return v
135 135 raise ValueError(s)
136 136
137 137 if profformat == 'chrome':
138 138 showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
139 139 showmax = ui.configwith(fraction, 'profiling', 'showmax', 0.999)
140 140 kwargs.update(minthreshold=showmin, maxthreshold=showmax)
141 141
142 142 statprof.display(fp, data=data, format=displayformat, **kwargs)
143 143
144 144 class profile(object):
145 145 """Start profiling.
146 146
147 147 Profiling is active when the context manager is active. When the context
148 148 manager exits, profiling results will be written to the configured output.
149 149 """
150 150 def __init__(self, ui, enabled=True):
151 151 self._ui = ui
152 152 self._output = None
153 153 self._fp = None
154 154 self._fpdoclose = True
155 155 self._profiler = None
156 156 self._enabled = enabled
157 157 self._entered = False
158 158 self._started = False
159 159
160 160 def __enter__(self):
161 161 self._entered = True
162 162 if self._enabled:
163 163 self.start()
164 164 return self
165 165
166 166 def start(self):
167 167 """Start profiling.
168 168
169 169 The profiling will stop at the context exit.
170 170
171 171 If the profiler was already started, this has no effect."""
172 172 if not self._entered:
173 173 raise error.ProgrammingError()
174 174 if self._started:
175 175 return
176 176 self._started = True
177 177 profiler = encoding.environ.get('HGPROF')
178 178 proffn = None
179 179 if profiler is None:
180 180 profiler = self._ui.config('profiling', 'type', default='stat')
181 181 if profiler not in ('ls', 'stat', 'flame'):
182 182 # try load profiler from extension with the same name
183 183 proffn = _loadprofiler(self._ui, profiler)
184 184 if proffn is None:
185 185 self._ui.warn(_("unrecognized profiler '%s' - ignored\n")
186 186 % profiler)
187 187 profiler = 'stat'
188 188
189 189 self._output = self._ui.config('profiling', 'output')
190 190
191 if True:
191 192 if self._output == 'blackbox':
192 193 self._fp = util.stringio()
193 194 elif self._output:
194 195 path = self._ui.expandpath(self._output)
195 196 self._fp = open(path, 'wb')
196 197 else:
197 198 self._fpdoclose = False
198 199 self._fp = self._ui.ferr
199 200
200 201 if proffn is not None:
201 202 pass
202 203 elif profiler == 'ls':
203 204 proffn = lsprofile
204 205 elif profiler == 'flame':
205 206 proffn = flameprofile
206 207 else:
207 208 proffn = statprofile
208 209
209 210 self._profiler = proffn(self._ui, self._fp)
210 211 self._profiler.__enter__()
211 212
212 213 def __exit__(self, exception_type, exception_value, traceback):
213 214 if self._profiler is None:
214 215 return
215 216 self._profiler.__exit__(exception_type, exception_value, traceback)
216 217 if self._output == 'blackbox':
217 218 val = 'Profile:\n%s' % self._fp.getvalue()
218 219 # ui.log treats the input as a format string,
219 220 # so we need to escape any % signs.
220 221 val = val.replace('%', '%%')
221 222 self._ui.log('profile', val)
222 223 self._closefp()
223 224
224 225 def _closefp(self):
225 226 if self._fpdoclose and self._fp is not None:
226 227 self._fp.close()
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