Mercurial > hg
view mercurial/profiling.py @ 30446:b324b4e431e5
posix: give checkexec a fast path; keep the check files and test read only
Before, Mercurial would create a new temporary file every time, stat it, change
its exec mode, stat it again, and delete it. Most of this dance was done to
handle the rare and not-so-essential case of VFAT mounts on unix. The cost of
that was paid by the much more common and important case of using normal file
systems.
Instead, try to create and preserve .hg/cache/checkisexec and
.hg/cache/checknoexec with and without exec flag set. If the files exist and
have correct exec flags set, we can conclude that that file system supports the
exec flag. Best case, the whole exec check can thus be done with two stat
calls. Worst case, we delete the wrong files and check as usual. That will be
because temporary loss of exec bit or on file systems without support for the
exec bit. In that case we check as we did before, with the additional overhead
of one extra stat call.
It is possible that this different test algorithm in some cases on odd file
systems will give different behaviour. Again, I think it will be rare and
special cases and I think it is worth the risk.
test-clone.t happens to show the situation where checkisexec is left behind
from the old style check, while checknoexec only will be created next time a
exec check will be performed.
author | Mads Kiilerich <madski@unity3d.com> |
---|---|
date | Wed, 14 Jan 2015 01:15:26 +0100 |
parents | 189a1030affb |
children | 69acfd2ca11e |
line wrap: on
line source
# 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 import os import time from .i18n import _ from . import ( error, util, ) @contextlib.contextmanager def lsprofile(ui, fp): 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: 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', default=1000) filter_ = None collapse_recursion = True thread = flamegraph.ProfileThread(fp, 1.0 / freq, filter_, collapse_recursion) start_time = time.clock() try: thread.start() yield finally: thread.stop() thread.join() print('Collected %d stack frames (%d unique) in %2.2f seconds.' % ( time.clock() - start_time, thread.num_frames(), thread.num_frames(unique=True))) @contextlib.contextmanager def statprofile(ui, fp): from . import statprof freq = ui.configint('profiling', 'freq', default=1000) 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) statprof.start(mechanism='thread') try: yield finally: 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, } if profformat in formats: displayformat = formats[profformat] else: ui.warn(_('unknown profiler output format: %s\n') % profformat) displayformat = statprof.DisplayFormats.Hotpath statprof.display(fp, data=data, format=displayformat) @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. """ profiler = os.getenv('HGPROF') if profiler is None: profiler = ui.config('profiling', 'type', default='stat') if profiler not in ('ls', 'stat', 'flame'): ui.warn(_("unrecognized profiler '%s' - ignored\n") % profiler) profiler = 'stat' output = ui.config('profiling', 'output') if output == 'blackbox': fp = util.stringio() elif output: path = ui.expandpath(output) fp = open(path, 'wb') else: fp = ui.ferr try: if profiler == 'ls': proffn = lsprofile elif profiler == 'flame': proffn = flameprofile else: proffn = statprofile with proffn(ui, fp): yield 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() @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