mercurial/profiling.py
author Wagner Bruna <wbruna@softwareexpress.com.br>
Wed, 31 May 2017 19:24:00 -0300
branchstable
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child 32417 f40dc6f7c12f
permissions -rw-r--r--
bugzilla: fix typo in help text
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# profiling.py - profiling functions
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#
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# Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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from __future__ import absolute_import, print_function
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import contextlib
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from .i18n import _
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from . import (
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    encoding,
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    error,
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    util,
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)
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@contextlib.contextmanager
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def lsprofile(ui, fp):
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    format = ui.config('profiling', 'format', default='text')
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    field = ui.config('profiling', 'sort', default='inlinetime')
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    limit = ui.configint('profiling', 'limit', default=30)
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    climit = ui.configint('profiling', 'nested', default=0)
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    if format not in ['text', 'kcachegrind']:
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        ui.warn(_("unrecognized profiling format '%s'"
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                    " - Ignored\n") % format)
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        format = 'text'
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    try:
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        from . import lsprof
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    except ImportError:
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        raise error.Abort(_(
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            'lsprof not available - install from '
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            'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
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    p = lsprof.Profiler()
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    p.enable(subcalls=True)
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    try:
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        yield
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    finally:
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        p.disable()
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        if format == 'kcachegrind':
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            from . import lsprofcalltree
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            calltree = lsprofcalltree.KCacheGrind(p)
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            calltree.output(fp)
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        else:
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            # format == 'text'
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            stats = lsprof.Stats(p.getstats())
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            stats.sort(field)
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            stats.pprint(limit=limit, file=fp, climit=climit)
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@contextlib.contextmanager
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def flameprofile(ui, fp):
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    try:
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        from flamegraph import flamegraph
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    except ImportError:
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        raise error.Abort(_(
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            'flamegraph not available - install from '
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            'https://github.com/evanhempel/python-flamegraph'))
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    # developer config: profiling.freq
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    freq = ui.configint('profiling', 'freq', default=1000)
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    filter_ = None
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    collapse_recursion = True
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    thread = flamegraph.ProfileThread(fp, 1.0 / freq,
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                                      filter_, collapse_recursion)
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    start_time = util.timer()
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    try:
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        thread.start()
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        yield
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    finally:
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        thread.stop()
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        thread.join()
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        print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
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            util.timer() - start_time, thread.num_frames(),
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            thread.num_frames(unique=True)))
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@contextlib.contextmanager
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def statprofile(ui, fp):
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    from . import statprof
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    freq = ui.configint('profiling', 'freq', default=1000)
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    if freq > 0:
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        # Cannot reset when profiler is already active. So silently no-op.
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        if statprof.state.profile_level == 0:
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            statprof.reset(freq)
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    else:
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        ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)
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    statprof.start(mechanism='thread')
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    try:
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        yield
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    finally:
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        data = statprof.stop()
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        profformat = ui.config('profiling', 'statformat', 'hotpath')
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        formats = {
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            'byline': statprof.DisplayFormats.ByLine,
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            'bymethod': statprof.DisplayFormats.ByMethod,
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            'hotpath': statprof.DisplayFormats.Hotpath,
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            'json': statprof.DisplayFormats.Json,
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            'chrome': statprof.DisplayFormats.Chrome,
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        }
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        if profformat in formats:
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            displayformat = formats[profformat]
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        else:
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            ui.warn(_('unknown profiler output format: %s\n') % profformat)
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            displayformat = statprof.DisplayFormats.Hotpath
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        kwargs = {}
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        def fraction(s):
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            if s.endswith('%'):
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                v = float(s[:-1]) / 100
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            else:
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                v = float(s)
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            if 0 <= v <= 1:
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                return v
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            raise ValueError(s)
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        if profformat == 'chrome':
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            showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
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            showmax = ui.configwith(fraction, 'profiling', 'showmax', 0.999)
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            kwargs.update(minthreshold=showmin, maxthreshold=showmax)
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        statprof.display(fp, data=data, format=displayformat, **kwargs)
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@contextlib.contextmanager
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def profile(ui):
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    """Start profiling.
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    Profiling is active when the context manager is active. When the context
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    manager exits, profiling results will be written to the configured output.
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    """
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    profiler = encoding.environ.get('HGPROF')
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    if profiler is None:
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        profiler = ui.config('profiling', 'type', default='stat')
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    if profiler not in ('ls', 'stat', 'flame'):
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        ui.warn(_("unrecognized profiler '%s' - ignored\n") % profiler)
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        profiler = 'stat'
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    output = ui.config('profiling', 'output')
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    if output == 'blackbox':
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        fp = util.stringio()
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    elif output:
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        path = ui.expandpath(output)
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        fp = open(path, 'wb')
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    else:
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        fp = ui.ferr
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    try:
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        if profiler == 'ls':
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            proffn = lsprofile
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        elif profiler == 'flame':
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            proffn = flameprofile
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        else:
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            proffn = statprofile
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        with proffn(ui, fp):
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            yield
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    finally:
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        if output:
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            if output == 'blackbox':
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                val = 'Profile:\n%s' % fp.getvalue()
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                # ui.log treats the input as a format string,
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                # so we need to escape any % signs.
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                val = val.replace('%', '%%')
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                ui.log('profile', val)
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            fp.close()
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@contextlib.contextmanager
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def maybeprofile(ui):
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    """Profile if enabled, else do nothing.
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    This context manager can be used to optionally profile if profiling
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    is enabled. Otherwise, it does nothing.
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    The purpose of this context manager is to make calling code simpler:
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    just use a single code path for calling into code you may want to profile
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    and this function determines whether to start profiling.
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    """
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    if ui.configbool('profiling', 'enabled'):
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        with profile(ui):
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            yield
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    else:
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        yield