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#!/usr/bin/env python
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## statprof.py
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## Copyright (C) 2012 Bryan O'Sullivan <bos@serpentine.com>
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## Copyright (C) 2011 Alex Fraser <alex at phatcore dot com>
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## Copyright (C) 2004,2005 Andy Wingo <wingo at pobox dot com>
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## Copyright (C) 2001 Rob Browning <rlb at defaultvalue dot org>
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## This library is free software; you can redistribute it and/or
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## modify it under the terms of the GNU Lesser General Public
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## License as published by the Free Software Foundation; either
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## version 2.1 of the License, or (at your option) any later version.
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##
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## This library is distributed in the hope that it will be useful,
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## but WITHOUT ANY WARRANTY; without even the implied warranty of
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## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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## Lesser General Public License for more details.
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##
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## You should have received a copy of the GNU Lesser General Public
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## License along with this program; if not, contact:
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##
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## Free Software Foundation Voice: +1-617-542-5942
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## 59 Temple Place - Suite 330 Fax: +1-617-542-2652
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## Boston, MA 02111-1307, USA gnu@gnu.org
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"""
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statprof is intended to be a fairly simple statistical profiler for
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python. It was ported directly from a statistical profiler for guile,
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also named statprof, available from guile-lib [0].
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[0] http://wingolog.org/software/guile-lib/statprof/
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To start profiling, call statprof.start():
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>>> start()
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Then run whatever it is that you want to profile, for example:
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>>> import test.pystone; test.pystone.pystones()
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Then stop the profiling and print out the results:
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>>> stop()
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>>> display()
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% cumulative self
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time seconds seconds name
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26.72 1.40 0.37 pystone.py:79:Proc0
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13.79 0.56 0.19 pystone.py:133:Proc1
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13.79 0.19 0.19 pystone.py:208:Proc8
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10.34 0.16 0.14 pystone.py:229:Func2
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6.90 0.10 0.10 pystone.py:45:__init__
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4.31 0.16 0.06 pystone.py:53:copy
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...
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All of the numerical data is statistically approximate. In the
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following column descriptions, and in all of statprof, "time" refers
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to execution time (both user and system), not wall clock time.
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% time
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The percent of the time spent inside the procedure itself (not
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counting children).
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cumulative seconds
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The total number of seconds spent in the procedure, including
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children.
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self seconds
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The total number of seconds spent in the procedure itself (not
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counting children).
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name
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The name of the procedure.
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By default statprof keeps the data collected from previous runs. If you
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want to clear the collected data, call reset():
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>>> reset()
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reset() can also be used to change the sampling frequency from the
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default of 1000 Hz. For example, to tell statprof to sample 50 times a
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second:
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>>> reset(50)
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This means that statprof will sample the call stack after every 1/50 of
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a second of user + system time spent running on behalf of the python
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process. When your process is idle (for example, blocking in a read(),
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as is the case at the listener), the clock does not advance. For this
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reason statprof is not currently not suitable for profiling io-bound
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operations.
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The profiler uses the hash of the code object itself to identify the
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procedures, so it won't confuse different procedures with the same name.
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They will show up as two different rows in the output.
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Right now the profiler is quite simplistic. I cannot provide
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call-graphs or other higher level information. What you see in the
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table is pretty much all there is. Patches are welcome :-)
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Threading
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---------
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Because signals only get delivered to the main thread in Python,
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statprof only profiles the main thread. However because the time
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reporting function uses per-process timers, the results can be
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significantly off if other threads' work patterns are not similar to the
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main thread's work patterns.
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"""
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# no-check-code
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from __future__ import absolute_import, division, print_function
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import collections
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import contextlib
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import getopt
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import inspect
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import json
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import os
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import signal
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import sys
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import threading
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import time
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from . import (
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encoding,
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pycompat,
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)
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defaultdict = collections.defaultdict
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contextmanager = contextlib.contextmanager
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__all__ = ['start', 'stop', 'reset', 'display', 'profile']
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skips = {
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r"util.py:check",
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r"extensions.py:closure",
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r"color.py:colorcmd",
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r"dispatch.py:checkargs",
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r"dispatch.py:<lambda>",
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r"dispatch.py:_runcatch",
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r"dispatch.py:_dispatch",
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r"dispatch.py:_runcommand",
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r"pager.py:pagecmd",
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r"dispatch.py:run",
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r"dispatch.py:dispatch",
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r"dispatch.py:runcommand",
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r"hg.py:<module>",
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r"evolve.py:warnobserrors",
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}
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###########################################################################
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## Utils
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def clock():
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times = os.times()
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return (times[0] + times[1], times[4])
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###########################################################################
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## Collection data structures
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class ProfileState(object):
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def __init__(self, frequency=None):
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self.reset(frequency)
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self.track = 'cpu'
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def reset(self, frequency=None):
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# total so far
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self.accumulated_time = (0.0, 0.0)
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# start_time when timer is active
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self.last_start_time = None
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# a float
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if frequency:
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self.sample_interval = 1.0 / frequency
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elif not hasattr(self, 'sample_interval'):
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# default to 1000 Hz
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self.sample_interval = 1.0 / 1000.0
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else:
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# leave the frequency as it was
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pass
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self.remaining_prof_time = None
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# for user start/stop nesting
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self.profile_level = 0
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self.samples = []
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def accumulate_time(self, stop_time):
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increment = (
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stop_time[0] - self.last_start_time[0],
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stop_time[1] - self.last_start_time[1],
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)
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self.accumulated_time = (
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self.accumulated_time[0] + increment[0],
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self.accumulated_time[1] + increment[1],
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)
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def seconds_per_sample(self):
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return self.accumulated_time[self.timeidx] / len(self.samples)
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@property
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def timeidx(self):
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if self.track == 'real':
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return 1
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return 0
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state = ProfileState()
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class CodeSite(object):
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cache = {}
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__slots__ = (u'path', u'lineno', u'function', u'source')
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def __init__(self, path, lineno, function):
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self.path = path
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self.lineno = lineno
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self.function = function
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self.source = None
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def __eq__(self, other):
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try:
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return (self.lineno == other.lineno and
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self.path == other.path)
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except:
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return False
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def __hash__(self):
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return hash((self.lineno, self.path))
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@classmethod
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def get(cls, path, lineno, function):
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k = (path, lineno)
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try:
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return cls.cache[k]
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except KeyError:
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v = cls(path, lineno, function)
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cls.cache[k] = v
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return v
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def getsource(self, length):
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if self.source is None:
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lineno = self.lineno - 1
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fp = None
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try:
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fp = open(self.path)
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for i, line in enumerate(fp):
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if i == lineno:
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self.source = line.strip()
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break
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except:
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pass
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finally:
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if fp:
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fp.close()
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if self.source is None:
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self.source = ''
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source = self.source
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if len(source) > length:
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source = source[:(length - 3)] + "..."
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return source
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def filename(self):
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return os.path.basename(self.path)
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class Sample(object):
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__slots__ = (u'stack', u'time')
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def __init__(self, stack, time):
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self.stack = stack
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self.time = time
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@classmethod
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def from_frame(cls, frame, time):
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stack = []
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while frame:
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stack.append(CodeSite.get(frame.f_code.co_filename, frame.f_lineno,
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frame.f_code.co_name))
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frame = frame.f_back
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return Sample(stack, time)
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###########################################################################
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## SIGPROF handler
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def profile_signal_handler(signum, frame):
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if state.profile_level > 0:
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now = clock()
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state.accumulate_time(now)
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timestamp = state.accumulated_time[state.timeidx]
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state.samples.append(Sample.from_frame(frame, timestamp))
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signal.setitimer(signal.ITIMER_PROF,
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state.sample_interval, 0.0)
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state.last_start_time = now
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stopthread = threading.Event()
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def samplerthread(tid):
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while not stopthread.is_set():
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now = clock()
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state.accumulate_time(now)
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frame = sys._current_frames()[tid]
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timestamp = state.accumulated_time[state.timeidx]
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state.samples.append(Sample.from_frame(frame, timestamp))
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state.last_start_time = now
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time.sleep(state.sample_interval)
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stopthread.clear()
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###########################################################################
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## Profiling API
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def is_active():
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return state.profile_level > 0
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lastmechanism = None
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def start(mechanism='thread', track='cpu'):
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'''Install the profiling signal handler, and start profiling.'''
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state.track = track # note: nesting different mode won't work
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state.profile_level += 1
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if state.profile_level == 1:
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state.last_start_time = clock()
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rpt = state.remaining_prof_time
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state.remaining_prof_time = None
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global lastmechanism
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lastmechanism = mechanism
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if mechanism == 'signal':
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signal.signal(signal.SIGPROF, profile_signal_handler)
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signal.setitimer(signal.ITIMER_PROF,
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rpt or state.sample_interval, 0.0)
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elif mechanism == 'thread':
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frame = inspect.currentframe()
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tid = [k for k, f in sys._current_frames().items() if f == frame][0]
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state.thread = threading.Thread(target=samplerthread,
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args=(tid,), name="samplerthread")
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state.thread.start()
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def stop():
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'''Stop profiling, and uninstall the profiling signal handler.'''
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state.profile_level -= 1
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if state.profile_level == 0:
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if lastmechanism == 'signal':
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rpt = signal.setitimer(signal.ITIMER_PROF, 0.0, 0.0)
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signal.signal(signal.SIGPROF, signal.SIG_IGN)
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state.remaining_prof_time = rpt[0]
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elif lastmechanism == 'thread':
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stopthread.set()
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state.thread.join()
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state.accumulate_time(clock())
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state.last_start_time = None
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statprofpath = encoding.environ.get('STATPROF_DEST')
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if statprofpath:
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save_data(statprofpath)
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return state
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def save_data(path):
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with open(path, 'w+') as file:
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file.write("%f %f\n" % state.accumulated_time)
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for sample in state.samples:
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time = sample.time
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stack = sample.stack
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sites = ['\1'.join([s.path, str(s.lineno), s.function])
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for s in stack]
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file.write("%d\0%s\n" % (time, '\0'.join(sites)))
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def load_data(path):
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lines = open(path, 'r').read().splitlines()
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state.accumulated_time = [float(value) for value in lines[0].split()]
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state.samples = []
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for line in lines[1:]:
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parts = line.split('\0')
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time = float(parts[0])
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rawsites = parts[1:]
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sites = []
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for rawsite in rawsites:
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siteparts = rawsite.split('\1')
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sites.append(CodeSite.get(siteparts[0], int(siteparts[1]),
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siteparts[2]))
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state.samples.append(Sample(sites, time))
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def reset(frequency=None):
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'''Clear out the state of the profiler. Do not call while the
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profiler is running.
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The optional frequency argument specifies the number of samples to
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collect per second.'''
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assert state.profile_level == 0, "Can't reset() while statprof is running"
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CodeSite.cache.clear()
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state.reset(frequency)
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@contextmanager
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def profile():
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start()
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try:
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yield
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finally:
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stop()
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display()
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###########################################################################
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## Reporting API
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class SiteStats(object):
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def __init__(self, site):
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self.site = site
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self.selfcount = 0
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self.totalcount = 0
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def addself(self):
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self.selfcount += 1
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def addtotal(self):
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self.totalcount += 1
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def selfpercent(self):
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return self.selfcount / len(state.samples) * 100
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def totalpercent(self):
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return self.totalcount / len(state.samples) * 100
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def selfseconds(self):
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return self.selfcount * state.seconds_per_sample()
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def totalseconds(self):
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return self.totalcount * state.seconds_per_sample()
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@classmethod
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def buildstats(cls, samples):
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stats = {}
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for sample in samples:
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for i, site in enumerate(sample.stack):
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sitestat = stats.get(site)
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if not sitestat:
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sitestat = SiteStats(site)
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stats[site] = sitestat
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sitestat.addtotal()
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if i == 0:
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sitestat.addself()
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return [s for s in stats.itervalues()]
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class DisplayFormats:
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ByLine = 0
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ByMethod = 1
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AboutMethod = 2
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Hotpath = 3
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FlameGraph = 4
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Json = 5
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Chrome = 6
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def display(fp=None, format=3, data=None, **kwargs):
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'''Print statistics, either to stdout or the given file object.'''
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if data is None:
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data = state
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if fp is None:
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import sys
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fp = sys.stdout
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if len(data.samples) == 0:
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fp.write(b'No samples recorded.\n')
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|
|
return
|
|
|
|
|
|
if format == DisplayFormats.ByLine:
|
|
|
display_by_line(data, fp)
|
|
|
elif format == DisplayFormats.ByMethod:
|
|
|
display_by_method(data, fp)
|
|
|
elif format == DisplayFormats.AboutMethod:
|
|
|
display_about_method(data, fp, **kwargs)
|
|
|
elif format == DisplayFormats.Hotpath:
|
|
|
display_hotpath(data, fp, **kwargs)
|
|
|
elif format == DisplayFormats.FlameGraph:
|
|
|
write_to_flame(data, fp, **kwargs)
|
|
|
elif format == DisplayFormats.Json:
|
|
|
write_to_json(data, fp)
|
|
|
elif format == DisplayFormats.Chrome:
|
|
|
write_to_chrome(data, fp, **kwargs)
|
|
|
else:
|
|
|
raise Exception("Invalid display format")
|
|
|
|
|
|
if format not in (DisplayFormats.Json, DisplayFormats.Chrome):
|
|
|
fp.write(b'---\n')
|
|
|
fp.write(b'Sample count: %d\n' % len(data.samples))
|
|
|
fp.write(b'Total time: %f seconds (%f wall)\n' % data.accumulated_time)
|
|
|
|
|
|
def display_by_line(data, fp):
|
|
|
'''Print the profiler data with each sample line represented
|
|
|
as one row in a table. Sorted by self-time per line.'''
|
|
|
stats = SiteStats.buildstats(data.samples)
|
|
|
stats.sort(reverse=True, key=lambda x: x.selfseconds())
|
|
|
|
|
|
fp.write(b'%5.5s %10.10s %7.7s %-8.8s\n' % (
|
|
|
b'% ', b'cumulative', b'self', b''))
|
|
|
fp.write(b'%5.5s %9.9s %8.8s %-8.8s\n' % (
|
|
|
b"time", b"seconds", b"seconds", b"name"))
|
|
|
|
|
|
for stat in stats:
|
|
|
site = stat.site
|
|
|
sitelabel = '%s:%d:%s' % (site.filename(), site.lineno, site.function)
|
|
|
fp.write(b'%6.2f %9.2f %9.2f %s\n' % (
|
|
|
stat.selfpercent(), stat.totalseconds(),
|
|
|
stat.selfseconds(), sitelabel))
|
|
|
|
|
|
def display_by_method(data, fp):
|
|
|
'''Print the profiler data with each sample function represented
|
|
|
as one row in a table. Important lines within that function are
|
|
|
output as nested rows. Sorted by self-time per line.'''
|
|
|
fp.write(b'%5.5s %10.10s %7.7s %-8.8s\n' %
|
|
|
('% ', 'cumulative', 'self', ''))
|
|
|
fp.write(b'%5.5s %9.9s %8.8s %-8.8s\n' %
|
|
|
("time", "seconds", "seconds", "name"))
|
|
|
|
|
|
stats = SiteStats.buildstats(data.samples)
|
|
|
|
|
|
grouped = defaultdict(list)
|
|
|
for stat in stats:
|
|
|
grouped[stat.site.filename() + ":" + stat.site.function].append(stat)
|
|
|
|
|
|
# compute sums for each function
|
|
|
functiondata = []
|
|
|
for fname, sitestats in grouped.iteritems():
|
|
|
total_cum_sec = 0
|
|
|
total_self_sec = 0
|
|
|
total_percent = 0
|
|
|
for stat in sitestats:
|
|
|
total_cum_sec += stat.totalseconds()
|
|
|
total_self_sec += stat.selfseconds()
|
|
|
total_percent += stat.selfpercent()
|
|
|
|
|
|
functiondata.append((fname,
|
|
|
total_cum_sec,
|
|
|
total_self_sec,
|
|
|
total_percent,
|
|
|
sitestats))
|
|
|
|
|
|
# sort by total self sec
|
|
|
functiondata.sort(reverse=True, key=lambda x: x[2])
|
|
|
|
|
|
for function in functiondata:
|
|
|
if function[3] < 0.05:
|
|
|
continue
|
|
|
fp.write(b'%6.2f %9.2f %9.2f %s\n' % (
|
|
|
function[3], # total percent
|
|
|
function[1], # total cum sec
|
|
|
function[2], # total self sec
|
|
|
function[0])) # file:function
|
|
|
|
|
|
function[4].sort(reverse=True, key=lambda i: i.selfseconds())
|
|
|
for stat in function[4]:
|
|
|
# only show line numbers for significant locations (>1% time spent)
|
|
|
if stat.selfpercent() > 1:
|
|
|
source = stat.site.getsource(25)
|
|
|
stattuple = (stat.selfpercent(), stat.selfseconds(),
|
|
|
stat.site.lineno, source)
|
|
|
|
|
|
fp.write(b'%33.0f%% %6.2f line %d: %s\n' % stattuple)
|
|
|
|
|
|
def display_about_method(data, fp, function=None, **kwargs):
|
|
|
if function is None:
|
|
|
raise Exception("Invalid function")
|
|
|
|
|
|
filename = None
|
|
|
if ':' in function:
|
|
|
filename, function = function.split(':')
|
|
|
|
|
|
relevant_samples = 0
|
|
|
parents = {}
|
|
|
children = {}
|
|
|
|
|
|
for sample in data.samples:
|
|
|
for i, site in enumerate(sample.stack):
|
|
|
if site.function == function and (not filename
|
|
|
or site.filename() == filename):
|
|
|
relevant_samples += 1
|
|
|
if i != len(sample.stack) - 1:
|
|
|
parent = sample.stack[i + 1]
|
|
|
if parent in parents:
|
|
|
parents[parent] = parents[parent] + 1
|
|
|
else:
|
|
|
parents[parent] = 1
|
|
|
|
|
|
if site in children:
|
|
|
children[site] = children[site] + 1
|
|
|
else:
|
|
|
children[site] = 1
|
|
|
|
|
|
parents = [(parent, count) for parent, count in parents.iteritems()]
|
|
|
parents.sort(reverse=True, key=lambda x: x[1])
|
|
|
for parent, count in parents:
|
|
|
fp.write(b'%6.2f%% %s:%s line %s: %s\n' %
|
|
|
(count / relevant_samples * 100, parent.filename(),
|
|
|
parent.function, parent.lineno, parent.getsource(50)))
|
|
|
|
|
|
stats = SiteStats.buildstats(data.samples)
|
|
|
stats = [s for s in stats
|
|
|
if s.site.function == function and
|
|
|
(not filename or s.site.filename() == filename)]
|
|
|
|
|
|
total_cum_sec = 0
|
|
|
total_self_sec = 0
|
|
|
total_self_percent = 0
|
|
|
total_cum_percent = 0
|
|
|
for stat in stats:
|
|
|
total_cum_sec += stat.totalseconds()
|
|
|
total_self_sec += stat.selfseconds()
|
|
|
total_self_percent += stat.selfpercent()
|
|
|
total_cum_percent += stat.totalpercent()
|
|
|
|
|
|
fp.write(
|
|
|
b'\n %s:%s Total: %0.2fs (%0.2f%%) Self: %0.2fs (%0.2f%%)\n\n'
|
|
|
% (
|
|
|
filename or '___',
|
|
|
function,
|
|
|
total_cum_sec,
|
|
|
total_cum_percent,
|
|
|
total_self_sec,
|
|
|
total_self_percent
|
|
|
))
|
|
|
|
|
|
children = [(child, count) for child, count in children.iteritems()]
|
|
|
children.sort(reverse=True, key=lambda x: x[1])
|
|
|
for child, count in children:
|
|
|
fp.write(b' %6.2f%% line %s: %s\n' %
|
|
|
(count / relevant_samples * 100, child.lineno,
|
|
|
child.getsource(50)))
|
|
|
|
|
|
def display_hotpath(data, fp, limit=0.05, **kwargs):
|
|
|
class HotNode(object):
|
|
|
def __init__(self, site):
|
|
|
self.site = site
|
|
|
self.count = 0
|
|
|
self.children = {}
|
|
|
|
|
|
def add(self, stack, time):
|
|
|
self.count += time
|
|
|
site = stack[0]
|
|
|
child = self.children.get(site)
|
|
|
if not child:
|
|
|
child = HotNode(site)
|
|
|
self.children[site] = child
|
|
|
|
|
|
if len(stack) > 1:
|
|
|
i = 1
|
|
|
# Skip boiler plate parts of the stack
|
|
|
name = r'%s:%s' % (stack[i].filename(), stack[i].function)
|
|
|
while i < len(stack) and name in skips:
|
|
|
i += 1
|
|
|
if i < len(stack):
|
|
|
child.add(stack[i:], time)
|
|
|
|
|
|
root = HotNode(None)
|
|
|
lasttime = data.samples[0].time
|
|
|
for sample in data.samples:
|
|
|
root.add(sample.stack[::-1], sample.time - lasttime)
|
|
|
lasttime = sample.time
|
|
|
|
|
|
def _write(node, depth, multiple_siblings):
|
|
|
site = node.site
|
|
|
visiblechildren = [c for c in node.children.itervalues()
|
|
|
if c.count >= (limit * root.count)]
|
|
|
if site:
|
|
|
indent = depth * 2 - 1
|
|
|
filename = ''
|
|
|
function = ''
|
|
|
if len(node.children) > 0:
|
|
|
childsite = list(node.children.itervalues())[0].site
|
|
|
filename = (childsite.filename() + ':').ljust(15)
|
|
|
function = childsite.function
|
|
|
|
|
|
# lots of string formatting
|
|
|
listpattern = ''.ljust(indent) +\
|
|
|
('\\' if multiple_siblings else '|') +\
|
|
|
' %4.1f%% %s %s'
|
|
|
liststring = listpattern % (node.count / root.count * 100,
|
|
|
filename, function)
|
|
|
codepattern = '%' + str(55 - len(liststring)) + 's %s: %s'
|
|
|
codestring = codepattern % ('line', site.lineno, site.getsource(30))
|
|
|
|
|
|
finalstring = liststring + codestring
|
|
|
childrensamples = sum([c.count for c in node.children.itervalues()])
|
|
|
# Make frames that performed more than 10% of the operation red
|
|
|
if node.count - childrensamples > (0.1 * root.count):
|
|
|
finalstring = '\033[91m' + finalstring + '\033[0m'
|
|
|
# Make frames that didn't actually perform work dark grey
|
|
|
elif node.count - childrensamples == 0:
|
|
|
finalstring = '\033[90m' + finalstring + '\033[0m'
|
|
|
fp.write(finalstring + b'\n')
|
|
|
|
|
|
newdepth = depth
|
|
|
if len(visiblechildren) > 1 or multiple_siblings:
|
|
|
newdepth += 1
|
|
|
|
|
|
visiblechildren.sort(reverse=True, key=lambda x: x.count)
|
|
|
for child in visiblechildren:
|
|
|
_write(child, newdepth, len(visiblechildren) > 1)
|
|
|
|
|
|
if root.count > 0:
|
|
|
_write(root, 0, False)
|
|
|
|
|
|
def write_to_flame(data, fp, scriptpath=None, outputfile=None, **kwargs):
|
|
|
if scriptpath is None:
|
|
|
scriptpath = encoding.environ['HOME'] + '/flamegraph.pl'
|
|
|
if not os.path.exists(scriptpath):
|
|
|
fp.write(b'error: missing %s\n' % scriptpath)
|
|
|
fp.write(b'get it here: https://github.com/brendangregg/FlameGraph\n')
|
|
|
return
|
|
|
|
|
|
fd, path = pycompat.mkstemp()
|
|
|
|
|
|
file = open(path, "w+")
|
|
|
|
|
|
lines = {}
|
|
|
for sample in data.samples:
|
|
|
sites = [s.function for s in sample.stack]
|
|
|
sites.reverse()
|
|
|
line = ';'.join(sites)
|
|
|
if line in lines:
|
|
|
lines[line] = lines[line] + 1
|
|
|
else:
|
|
|
lines[line] = 1
|
|
|
|
|
|
for line, count in lines.iteritems():
|
|
|
file.write("%s %d\n" % (line, count))
|
|
|
|
|
|
file.close()
|
|
|
|
|
|
if outputfile is None:
|
|
|
outputfile = '~/flamegraph.svg'
|
|
|
|
|
|
os.system("perl ~/flamegraph.pl %s > %s" % (path, outputfile))
|
|
|
fp.write(b'Written to %s\n' % outputfile)
|
|
|
|
|
|
_pathcache = {}
|
|
|
def simplifypath(path):
|
|
|
'''Attempt to make the path to a Python module easier to read by
|
|
|
removing whatever part of the Python search path it was found
|
|
|
on.'''
|
|
|
|
|
|
if path in _pathcache:
|
|
|
return _pathcache[path]
|
|
|
hgpath = pycompat.fsencode(encoding.__file__).rsplit(os.sep, 2)[0]
|
|
|
for p in [hgpath] + sys.path:
|
|
|
prefix = p + os.sep
|
|
|
if path.startswith(prefix):
|
|
|
path = path[len(prefix):]
|
|
|
break
|
|
|
_pathcache[path] = path
|
|
|
return path
|
|
|
|
|
|
def write_to_json(data, fp):
|
|
|
samples = []
|
|
|
|
|
|
for sample in data.samples:
|
|
|
stack = []
|
|
|
|
|
|
for frame in sample.stack:
|
|
|
stack.append((frame.path, frame.lineno, frame.function))
|
|
|
|
|
|
samples.append((sample.time, stack))
|
|
|
|
|
|
data = json.dumps(samples)
|
|
|
if not isinstance(data, bytes):
|
|
|
data = data.encode('utf-8')
|
|
|
|
|
|
fp.write(data)
|
|
|
|
|
|
def write_to_chrome(data, fp, minthreshold=0.005, maxthreshold=0.999):
|
|
|
samples = []
|
|
|
laststack = collections.deque()
|
|
|
lastseen = collections.deque()
|
|
|
|
|
|
# The Chrome tracing format allows us to use a compact stack
|
|
|
# representation to save space. It's fiddly but worth it.
|
|
|
# We maintain a bijection between stack and ID.
|
|
|
stack2id = {}
|
|
|
id2stack = [] # will eventually be rendered
|
|
|
|
|
|
def stackid(stack):
|
|
|
if not stack:
|
|
|
return
|
|
|
if stack in stack2id:
|
|
|
return stack2id[stack]
|
|
|
parent = stackid(stack[1:])
|
|
|
myid = len(stack2id)
|
|
|
stack2id[stack] = myid
|
|
|
id2stack.append(dict(category=stack[0][0], name='%s %s' % stack[0]))
|
|
|
if parent is not None:
|
|
|
id2stack[-1].update(parent=parent)
|
|
|
return myid
|
|
|
|
|
|
def endswith(a, b):
|
|
|
return list(a)[-len(b):] == list(b)
|
|
|
|
|
|
# The sampling profiler can sample multiple times without
|
|
|
# advancing the clock, potentially causing the Chrome trace viewer
|
|
|
# to render single-pixel columns that we cannot zoom in on. We
|
|
|
# work around this by pretending that zero-duration samples are a
|
|
|
# millisecond in length.
|
|
|
|
|
|
clamp = 0.001
|
|
|
|
|
|
# We provide knobs that by default attempt to filter out stack
|
|
|
# frames that are too noisy:
|
|
|
#
|
|
|
# * A few take almost all execution time. These are usually boring
|
|
|
# setup functions, giving a stack that is deep but uninformative.
|
|
|
#
|
|
|
# * Numerous samples take almost no time, but introduce lots of
|
|
|
# noisy, oft-deep "spines" into a rendered profile.
|
|
|
|
|
|
blacklist = set()
|
|
|
totaltime = data.samples[-1].time - data.samples[0].time
|
|
|
minthreshold = totaltime * minthreshold
|
|
|
maxthreshold = max(totaltime * maxthreshold, clamp)
|
|
|
|
|
|
def poplast():
|
|
|
oldsid = stackid(tuple(laststack))
|
|
|
oldcat, oldfunc = laststack.popleft()
|
|
|
oldtime, oldidx = lastseen.popleft()
|
|
|
duration = sample.time - oldtime
|
|
|
if minthreshold <= duration <= maxthreshold:
|
|
|
# ensure no zero-duration events
|
|
|
sampletime = max(oldtime + clamp, sample.time)
|
|
|
samples.append(dict(ph='E', name=oldfunc, cat=oldcat, sf=oldsid,
|
|
|
ts=sampletime*1e6, pid=0))
|
|
|
else:
|
|
|
blacklist.add(oldidx)
|
|
|
|
|
|
# Much fiddling to synthesize correctly(ish) nested begin/end
|
|
|
# events given only stack snapshots.
|
|
|
|
|
|
for sample in data.samples:
|
|
|
tos = sample.stack[0]
|
|
|
name = tos.function
|
|
|
path = simplifypath(tos.path)
|
|
|
stack = tuple((('%s:%d' % (simplifypath(frame.path), frame.lineno),
|
|
|
frame.function) for frame in sample.stack))
|
|
|
qstack = collections.deque(stack)
|
|
|
if laststack == qstack:
|
|
|
continue
|
|
|
while laststack and qstack and laststack[-1] == qstack[-1]:
|
|
|
laststack.pop()
|
|
|
qstack.pop()
|
|
|
while laststack:
|
|
|
poplast()
|
|
|
for f in reversed(qstack):
|
|
|
lastseen.appendleft((sample.time, len(samples)))
|
|
|
laststack.appendleft(f)
|
|
|
path, name = f
|
|
|
sid = stackid(tuple(laststack))
|
|
|
samples.append(dict(ph='B', name=name, cat=path, ts=sample.time*1e6,
|
|
|
sf=sid, pid=0))
|
|
|
laststack = collections.deque(stack)
|
|
|
while laststack:
|
|
|
poplast()
|
|
|
events = [s[1] for s in enumerate(samples) if s[0] not in blacklist]
|
|
|
frames = collections.OrderedDict((str(k), v)
|
|
|
for (k,v) in enumerate(id2stack))
|
|
|
json.dump(dict(traceEvents=events, stackFrames=frames), fp, indent=1)
|
|
|
fp.write('\n')
|
|
|
|
|
|
def printusage():
|
|
|
print(r"""
|
|
|
The statprof command line allows you to inspect the last profile's results in
|
|
|
the following forms:
|
|
|
|
|
|
usage:
|
|
|
hotpath [-l --limit percent]
|
|
|
Shows a graph of calls with the percent of time each takes.
|
|
|
Red calls take over 10%% of the total time themselves.
|
|
|
lines
|
|
|
Shows the actual sampled lines.
|
|
|
functions
|
|
|
Shows the samples grouped by function.
|
|
|
function [filename:]functionname
|
|
|
Shows the callers and callees of a particular function.
|
|
|
flame [-s --script-path] [-o --output-file path]
|
|
|
Writes out a flamegraph to output-file (defaults to ~/flamegraph.svg)
|
|
|
Requires that ~/flamegraph.pl exist.
|
|
|
(Specify alternate script path with --script-path.)""")
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def main(argv=None):
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if argv is None:
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argv = sys.argv
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|
|
|
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if len(argv) == 1:
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|
printusage()
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return 0
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displayargs = {}
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optstart = 2
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displayargs['function'] = None
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if argv[1] == 'hotpath':
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|
displayargs['format'] = DisplayFormats.Hotpath
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|
elif argv[1] == 'lines':
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displayargs['format'] = DisplayFormats.ByLine
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elif argv[1] == 'functions':
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|
displayargs['format'] = DisplayFormats.ByMethod
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|
elif argv[1] == 'function':
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|
displayargs['format'] = DisplayFormats.AboutMethod
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|
displayargs['function'] = argv[2]
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optstart = 3
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|
elif argv[1] == 'flame':
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|
displayargs['format'] = DisplayFormats.FlameGraph
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else:
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|
printusage()
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|
return 0
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|
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|
|
# process options
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|
try:
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|
|
opts, args = pycompat.getoptb(sys.argv[optstart:], "hl:f:o:p:",
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|
|
["help", "limit=", "file=", "output-file=", "script-path="])
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|
|
except getopt.error as msg:
|
|
|
print(msg)
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|
|
printusage()
|
|
|
return 2
|
|
|
|
|
|
displayargs['limit'] = 0.05
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|
|
path = None
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|
|
for o, value in opts:
|
|
|
if o in ("-l", "--limit"):
|
|
|
displayargs['limit'] = float(value)
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|
|
elif o in ("-f", "--file"):
|
|
|
path = value
|
|
|
elif o in ("-o", "--output-file"):
|
|
|
displayargs['outputfile'] = value
|
|
|
elif o in ("-p", "--script-path"):
|
|
|
displayargs['scriptpath'] = value
|
|
|
elif o in ("-h", "help"):
|
|
|
printusage()
|
|
|
return 0
|
|
|
else:
|
|
|
assert False, "unhandled option %s" % o
|
|
|
|
|
|
if not path:
|
|
|
print('must specify --file to load')
|
|
|
return 1
|
|
|
|
|
|
load_data(path=path)
|
|
|
|
|
|
display(**pycompat.strkwargs(displayargs))
|
|
|
|
|
|
return 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
sys.exit(main())
|
|
|
|