Mercurial > hg
view mercurial/profiling.py @ 30758:76104a4899ad
commands: config option to control bundle compression level
Currently, bundle compression uses the default compression level
for the active compression engine. The default compression level
is tuned as a compromise between speed and size.
Some scenarios may call for a different compression level. For
example, with clone bundles, bundles are generated once and used
several times. Since the cost to generate is paid infrequently,
server operators may wish to trade extra CPU time for better
compression ratios.
This patch introduces an experimental and undocumented config
option to control the bundle compression level. As the inline
comment says, this approach is a bit hacky. I'd prefer for
the compression level to be encoded in the bundle spec. e.g.
"zstd-v2;complevel=15." However, given that the 4.1 freeze is
imminent, I'm not comfortable implementing this user-facing
change without much time to test and consider the implications.
So, we're going with the quick and dirty solution for now.
Having this option in the 4.1 release will enable Mozilla to
easily produce and test zlib and zstd bundles with non-default
compression levels in production. This will help drive future
development of the feature and zstd integration with Mercurial.
author | Gregory Szorc <gregory.szorc@gmail.com> |
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date | Tue, 10 Jan 2017 11:20:32 -0800 |
parents | 69acfd2ca11e |
children | 6a70cf94d1b5 |
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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 import time from .i18n import _ from . import ( error, pycompat, 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 = time.clock() try: thread.start() yield finally: thread.stop() thread.join() print('Collected %d stack frames (%d unique) in %2.2f seconds.' % ( time.clock() - 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, } if profformat in formats: displayformat = formats[profformat] else: ui.warn(_('unknown profiler output format: %s\n') % profformat) displayformat = statprof.DisplayFormats.Hotpath statprof.display(fp, data=data, format=displayformat) @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 = pycompat.osgetenv('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