Mercurial > hg
view mercurial/profiling.py @ 31072:80f04ba7f4d1
color: set initial default value for 'colormode' to None
This should not introduce any behavior changes when using the color extension.
In practive, the colormode will be setup at early at run time to the proper
value (from config and environment).
We do this change as this gets us closer of a state were we can have all the
mechanisms associated to color in core with the feature disabled by default.
author | Pierre-Yves David <pierre-yves.david@ens-lyon.org> |
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date | Thu, 22 Dec 2016 06:18:45 +0100 |
parents | 22fbca1d11ed |
children | f40dc6f7c12f |
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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, 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 = 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') 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