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profiling.py
210 lines | 6.3 KiB | text/x-python | PythonLexer
Gregory Szorc
profiling: move profiling code from dispatch.py (API)...
r29781 # profiling.py - profiling functions
#
# Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
from __future__ import absolute_import, print_function
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r29783 import contextlib
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r29781
from .i18n import _
from . import (
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r30820 encoding,
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r29781 error,
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r32417 extensions,
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r29781 util,
)
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r32417 def _loadprofiler(ui, profiler):
"""load profiler extension. return profile method, or None on failure"""
extname = profiler
extensions.loadall(ui, whitelist=[extname])
try:
mod = extensions.find(extname)
except KeyError:
return None
else:
return getattr(mod, 'profile', None)
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r29783 @contextlib.contextmanager
def lsprofile(ui, fp):
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r29781 format = ui.config('profiling', 'format', default='text')
field = ui.config('profiling', 'sort', default='inlinetime')
limit = ui.configint('profiling', 'limit', default=30)
climit = ui.configint('profiling', 'nested', default=0)
if format not in ['text', 'kcachegrind']:
ui.warn(_("unrecognized profiling format '%s'"
" - Ignored\n") % format)
format = 'text'
try:
from . import lsprof
except ImportError:
raise error.Abort(_(
'lsprof not available - install from '
'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
p = lsprof.Profiler()
p.enable(subcalls=True)
try:
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r29783 yield
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r29781 finally:
p.disable()
if format == 'kcachegrind':
from . import lsprofcalltree
calltree = lsprofcalltree.KCacheGrind(p)
calltree.output(fp)
else:
# format == 'text'
stats = lsprof.Stats(p.getstats())
stats.sort(field)
stats.pprint(limit=limit, file=fp, climit=climit)
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r29783 @contextlib.contextmanager
def flameprofile(ui, fp):
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r29781 try:
from flamegraph import flamegraph
except ImportError:
raise error.Abort(_(
'flamegraph not available - install from '
'https://github.com/evanhempel/python-flamegraph'))
# developer config: profiling.freq
freq = ui.configint('profiling', 'freq', default=1000)
filter_ = None
collapse_recursion = True
thread = flamegraph.ProfileThread(fp, 1.0 / freq,
filter_, collapse_recursion)
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r30975 start_time = util.timer()
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r29781 try:
thread.start()
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r29783 yield
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r29781 finally:
thread.stop()
thread.join()
print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
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r30975 util.timer() - start_time, thread.num_frames(),
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r29781 thread.num_frames(unique=True)))
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r29783 @contextlib.contextmanager
def statprofile(ui, fp):
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r30316 from . import statprof
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r29781
freq = ui.configint('profiling', 'freq', default=1000)
if freq > 0:
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r29785 # Cannot reset when profiler is already active. So silently no-op.
if statprof.state.profile_level == 0:
statprof.reset(freq)
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r29781 else:
ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)
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r30316 statprof.start(mechanism='thread')
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r29781 try:
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r29783 yield
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r29781 finally:
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r30316 data = statprof.stop()
profformat = ui.config('profiling', 'statformat', 'hotpath')
formats = {
'byline': statprof.DisplayFormats.ByLine,
'bymethod': statprof.DisplayFormats.ByMethod,
'hotpath': statprof.DisplayFormats.Hotpath,
'json': statprof.DisplayFormats.Json,
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r30930 'chrome': statprof.DisplayFormats.Chrome,
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r30316 }
if profformat in formats:
displayformat = formats[profformat]
else:
ui.warn(_('unknown profiler output format: %s\n') % profformat)
displayformat = statprof.DisplayFormats.Hotpath
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r30930 kwargs = {}
def fraction(s):
if s.endswith('%'):
v = float(s[:-1]) / 100
else:
v = float(s)
if 0 <= v <= 1:
return v
raise ValueError(s)
if profformat == 'chrome':
showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
showmax = ui.configwith(fraction, 'profiling', 'showmax', 0.999)
kwargs.update(minthreshold=showmin, maxthreshold=showmax)
statprof.display(fp, data=data, format=displayformat, **kwargs)
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r29781
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r29783 @contextlib.contextmanager
def profile(ui):
"""Start profiling.
Profiling is active when the context manager is active. When the context
manager exits, profiling results will be written to the configured output.
"""
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r30820 profiler = encoding.environ.get('HGPROF')
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r32417 proffn = None
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r29781 if profiler is None:
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r30317 profiler = ui.config('profiling', 'type', default='stat')
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r29781 if profiler not in ('ls', 'stat', 'flame'):
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r32417 # try load profiler from extension with the same name
proffn = _loadprofiler(ui, profiler)
if proffn is None:
ui.warn(_("unrecognized profiler '%s' - ignored\n") % profiler)
profiler = 'stat'
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r29781
output = ui.config('profiling', 'output')
if output == 'blackbox':
fp = util.stringio()
elif output:
path = ui.expandpath(output)
fp = open(path, 'wb')
else:
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r30322 fp = ui.ferr
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r29781
try:
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r32417 if proffn is not None:
pass
elif profiler == 'ls':
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r29783 proffn = lsprofile
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r29781 elif profiler == 'flame':
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r29783 proffn = flameprofile
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r29781 else:
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r29783 proffn = statprofile
with proffn(ui, fp):
yield
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r29781 finally:
if output:
if output == 'blackbox':
val = 'Profile:\n%s' % fp.getvalue()
# ui.log treats the input as a format string,
# so we need to escape any % signs.
val = val.replace('%', '%%')
ui.log('profile', val)
fp.close()
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r29784
@contextlib.contextmanager
def maybeprofile(ui):
"""Profile if enabled, else do nothing.
This context manager can be used to optionally profile if profiling
is enabled. Otherwise, it does nothing.
The purpose of this context manager is to make calling code simpler:
just use a single code path for calling into code you may want to profile
and this function determines whether to start profiling.
"""
if ui.configbool('profiling', 'enabled'):
with profile(ui):
yield
else:
yield