Mercurial > hg
view mercurial/profiling.py @ 33475:f501322512b6
parsers: fix invariant bug in find_deepest (issue5623)
find_deepest is used to find the "best" ancestors given a list. In the main
loop it keeps an invariant called 'ninteresting' which is supposed to contain
the number of non-zero entries in the 'interesting' array. This invariant is
incorrectly maintained, however, which leads the the algorithm returning an
empty result for certain graphs. This has been fixed.
Also, the 'interesting' array is supposed to fit 2^ancestors values, but is
incorrectly allocated to twice that size. This has been fixed as well.
The tests in test-ancestor.py compare the Python and C versions of the code,
and report the error correctly, since the Python version works correct. Even
so, I have added an additional test against the expected result, in the event
that both algorithms have an identical error in the future.
This fixes issue5623.
author | Sune Foldager <cryo@cyanite.org> |
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date | Fri, 14 Jul 2017 13:48:17 +0200 |
parents | 5d8942dbe49e |
children | 0407a51b9d8c |
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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 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', 0.999) kwargs.update(minthreshold=showmin, maxthreshold=showmax) elif profformat == 'hotpath': # inconsistent config: profiling.showmin limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05) kwargs['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', default='stat') 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') 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()