##// END OF EJS Templates
aggressivemergedelta: document rename and move to `revlog` section...
aggressivemergedelta: document rename and move to `revlog` section The config does not follow our naming guideline and "Aggressive" is probably a word to keep away from users. The option does not truly fit in the `format` section. It can be turned on and off for existing repository without much consequence regarding compatibility. A new `revlog` option is created to control behavior related to revlog writing and reading. We can see multiple other config options that could be migrated there. * format.maxchainlen * experimental.mmapindexthreshold * experimental.sparse-read.density-threshold (in an updated form) * experimental.sparse-read.min-gap-size (in an updated form) In addition, we can foresee at least a couple of sparse-revlog related option coming too (to reduce delta chain length and increase snapshot reuse) These two extra options might fit there too. Unless we want to create a section dedicated to caches and performance. * format.chunkcachesize * format.manifestcachesize For now, we only migrate `optimize-delta-parent-choice` since it is getting out of experimental. It is too close to the release to move the other one. In addition, we still lack proper the prioritization of alias that would help renaming them without bad consequence for users. (Not fully happy about the `revlog` name but could not find better).

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profiling.py
251 lines | 7.9 KiB | text/x-python | PythonLexer
# 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
import contextlib
from .i18n import _
from . import (
encoding,
error,
extensions,
pycompat,
util,
)
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)
@contextlib.contextmanager
def lsprofile(ui, fp):
format = ui.config('profiling', 'format')
field = ui.config('profiling', 'sort')
limit = ui.configint('profiling', 'limit')
climit = ui.configint('profiling', 'nested')
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:
yield
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)
@contextlib.contextmanager
def flameprofile(ui, fp):
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')
filter_ = None
collapse_recursion = True
thread = flamegraph.ProfileThread(fp, 1.0 / freq,
filter_, collapse_recursion)
start_time = util.timer()
try:
thread.start()
yield
finally:
thread.stop()
thread.join()
print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
util.timer() - start_time, thread.num_frames(),
thread.num_frames(unique=True)))
@contextlib.contextmanager
def statprofile(ui, fp):
from . import statprof
freq = ui.configint('profiling', 'freq')
if freq > 0:
# Cannot reset when profiler is already active. So silently no-op.
if statprof.state.profile_level == 0:
statprof.reset(freq)
else:
ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)
track = ui.config('profiling', 'time-track')
statprof.start(mechanism='thread', track=track)
try:
yield
finally:
data = statprof.stop()
profformat = ui.config('profiling', 'statformat')
formats = {
'byline': statprof.DisplayFormats.ByLine,
'bymethod': statprof.DisplayFormats.ByMethod,
'hotpath': statprof.DisplayFormats.Hotpath,
'json': statprof.DisplayFormats.Json,
'chrome': statprof.DisplayFormats.Chrome,
}
if profformat in formats:
displayformat = formats[profformat]
else:
ui.warn(_('unknown profiler output format: %s\n') % profformat)
displayformat = statprof.DisplayFormats.Hotpath
kwargs = {}
def fraction(s):
if isinstance(s, (float, int)):
return float(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')
kwargs.update(minthreshold=showmin, maxthreshold=showmax)
elif profformat == 'hotpath':
# inconsistent config: profiling.showmin
limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05)
kwargs[r'limit'] = limit
statprof.display(fp, data=data, format=displayformat, **kwargs)
class profile(object):
"""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.
"""
def __init__(self, ui, enabled=True):
self._ui = ui
self._output = None
self._fp = None
self._fpdoclose = True
self._profiler = None
self._enabled = enabled
self._entered = False
self._started = False
def __enter__(self):
self._entered = True
if self._enabled:
self.start()
return self
def start(self):
"""Start profiling.
The profiling will stop at the context exit.
If the profiler was already started, this has no effect."""
if not self._entered:
raise error.ProgrammingError()
if self._started:
return
self._started = True
profiler = encoding.environ.get('HGPROF')
proffn = None
if profiler is None:
profiler = self._ui.config('profiling', 'type')
if profiler not in ('ls', 'stat', 'flame'):
# try load profiler from extension with the same name
proffn = _loadprofiler(self._ui, profiler)
if proffn is None:
self._ui.warn(_("unrecognized profiler '%s' - ignored\n")
% profiler)
profiler = 'stat'
self._output = self._ui.config('profiling', 'output')
try:
if self._output == 'blackbox':
self._fp = util.stringio()
elif self._output:
path = self._ui.expandpath(self._output)
self._fp = open(path, 'wb')
elif pycompat.iswindows:
# parse escape sequence by win32print()
class uifp(object):
def __init__(self, ui):
self._ui = ui
def write(self, data):
self._ui.write_err(data)
def flush(self):
self._ui.flush()
self._fpdoclose = False
self._fp = uifp(self._ui)
else:
self._fpdoclose = False
self._fp = self._ui.ferr
if proffn is not None:
pass
elif profiler == 'ls':
proffn = lsprofile
elif profiler == 'flame':
proffn = flameprofile
else:
proffn = statprofile
self._profiler = proffn(self._ui, self._fp)
self._profiler.__enter__()
except: # re-raises
self._closefp()
raise
def __exit__(self, exception_type, exception_value, traceback):
propagate = None
if self._profiler is not None:
propagate = self._profiler.__exit__(exception_type, exception_value,
traceback)
if self._output == 'blackbox':
val = 'Profile:\n%s' % self._fp.getvalue()
# ui.log treats the input as a format string,
# so we need to escape any % signs.
val = val.replace('%', '%%')
self._ui.log('profile', val)
self._closefp()
return propagate
def _closefp(self):
if self._fpdoclose and self._fp is not None:
self._fp.close()