view mercurial/profiling.py @ 39763:5ccd791344f3

localrepo: pass root manifest into manifestlog.__init__ Today, localrepository has a method that can be overloaded which returns an instance of the root manifest storage object. When a manifestlog is created, it calls this private method and stores the root manifest object on it. This "hook" on localrepository isn't part of the documented interface. It isn't compatible with our desire to make repo storage determined before the repo object is constructed. This commit changes manifestlog.__init__ to accept the root storage object instead of calling into the repo to construct it. By doing things this way, the repo instance is responsible for constructing the manifest storage object directly. This does mean that other derived repo types need to overload manifestlog(). But they should have been doing this already, as manifestlog() is typically decorated in a storage-specific way. e.g. localrepository.manifestlog() is decorated as @storecache('00manifest.i'). And this assumes that a 00manifest.i file exists in the store vfs. This condition may not hold for repository types using non-revlog storage. So it is important for special repo types to override manifestlog() to remove this file association. The code changed in perf is wrong because it isn't compatible with older Mercurial versions. But I'm pretty sure the code was broken on older versions before this commit. It only affects `hg perftags`. I don't care enough to fix that at this time. .. api:: ``manifest.manifestlog.__init__()`` now receives the root manifest storage instance instead of calling into a private method on the repo object to obtain it. Differential Revision: https://phab.mercurial-scm.org/D4641
author Gregory Szorc <gregory.szorc@gmail.com>
date Tue, 18 Sep 2018 15:15:24 -0700
parents 15a1e37f80bd
children b8f6a99ad89b
line wrap: on
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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,
    pycompat,
    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')
    field = ui.config('profiling', 'sort')
    limit = ui.configint('profiling', 'limit')
    climit = ui.configint('profiling', 'nested')

    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')
    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')
    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)

    track = ui.config('profiling', 'time-track')
    statprof.start(mechanism='thread', track=track)

    try:
        yield
    finally:
        data = statprof.stop()

        profformat = ui.config('profiling', 'statformat')

        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')
            kwargs.update(minthreshold=showmin, maxthreshold=showmax)
        elif profformat == 'hotpath':
            # inconsistent config: profiling.showmin
            limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05)
            kwargs[r'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')
        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')
            elif pycompat.iswindows:
                # parse escape sequence by win32print()
                class uifp(object):
                    def __init__(self, ui):
                        self._ui = ui
                    def write(self, data):
                        self._ui.write_err(data)
                    def flush(self):
                        self._ui.flush()
                self._fpdoclose = False
                self._fp = uifp(self._ui)
            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()