Mercurial > public > mercurial-scm > hg-stable
view mercurial/profiling.py @ 30330:3fd53cc1aad8
profiling: make statprof the default profiler (BC)
The statprof sampling profiler runs with significantly less overhead.
Its data is therefore more useful. Furthermore, its default output
shows the hotpath by default, which I've found to be way more useful
than the default profiler's function time table.
There is one behavioral regression with this change worth noting:
the statprof profiler currently doesn't profile individual hgweb
requests like lsprof does. This is because the current implementation
of statprof only profiles the thread that started profiling.
The ability for lsprof to profile individual hgweb requests is
relatively new and likely not widely used. Furthermore, I have plans
to modify statprof to support profiling multiple threads. I expect
that change to go through several iterations. I'm submitting this
patch first so there is more time to test statprof. Perfect is the
enemy of good.
author | Gregory Szorc <gregory.szorc@gmail.com> |
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date | Fri, 04 Nov 2016 21:44:25 -0700 |
parents | faf1b8923da2 |
children | 189a1030affb |
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# 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 sys 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 = sys.stderr 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