Mercurial > hg
view mercurial/profiling.py @ 32460:f9445b528687
match: make subdirmatcher extend basematcher
This makes the subdirmatcher not depend on the main matcher, giving us
more freedom to modify that (specifically, it will lose it _always
field in a while).
author | Martin von Zweigbergk <martinvonz@google.com> |
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date | Wed, 17 May 2017 23:02:42 -0700 |
parents | f40dc6f7c12f |
children | 4483696dacee |
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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 from .i18n import _ from . import ( encoding, error, extensions, 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', 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 = 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', 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, '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 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) @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 = encoding.environ.get('HGPROF') proffn = None if profiler is None: profiler = ui.config('profiling', 'type', default='stat') if profiler not in ('ls', 'stat', 'flame'): # 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' 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 proffn is not None: pass elif 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