/usr/lib/python2.7/dist-packages/pprofile.py is in python-pprofile 1.11.0-1.
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# Copyright (C) 2013-2016 Vincent Pelletier <plr.vincent@gmail.com>
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""
pprofile - Line-granularity, thread-aware deterministic and statistic
pure-python profiler
Usage as a command line:
$ pprofile --exclude-syspath some_python_executable arg1 ...
$ pprofile --exclude-syspath -m some_python_module -- arg1 ...
$ python -m pprofile --exclude-syspath some_python_executable arg1 ...
$ python -m pprofile -m some_python_module -- arg1 ...
See --help for all options.
Usage as a python module:
Deterministic profiling:
>>> prof = pprofile.Profile()
>>> with prof():
>>> # Code to profile
>>> prof.print_stats()
Statistic profiling:
>>> prof = StatisticalProfile()
>>> with prof():
>>> # Code to profile
>>> prof.print_stats()
"""
from __future__ import print_function
from collections import defaultdict, deque
from functools import partial, wraps
# Note: use time, not clock.
# Clock, at least on linux, ignores time not spent executing code
# (ex: time.sleep()). The goal of pprofile is not to profile python code
# execution as such (ie, to improve python interpreter), but to profile a
# possibly complex application, with its (IO) waits, sleeps, (...) so a
# developper can understand what is slow rather than what keeps the cpu busy.
# So using the wall-clock as a way to measure time spent is more meaningful.
# XXX: This said, if time() lacks precision, a better but likely
# platform-dependent wall-clock time source must be identified and used.
from time import time
from warnings import warn
import argparse
import cStringIO
import inspect
import linecache
import os
import re
import runpy
import shlex
import sys
import threading
import zipfile
try:
from IPython.core.magic import register_line_cell_magic
except ImportError:
register_line_cell_magic = lambda x: x
__all__ = (
'ProfileBase', 'ProfileRunnerBase', 'Profile', 'ThreadProfile',
'StatisticProfile', 'StatisticThread', 'run', 'runctx', 'runfile',
'runpath',
)
if sys.version_info < (3, ):
# Python 2.x linecache returns non-decoded strings, which cause errors when
# mixing source code of different encodings and writing to a fixed-encoding
# output. So instead of writing a lot of code to properly handle this, just
# emit text the Python 2 way: don't specify encoding.
def _open(name, mode, errors):
return open(name, mode)
def _reopen(stream, encoding=None, errors='strict'):
return stream
else:
import codecs
_open = open
def _reopen(stream, encoding=None, errors='strict'):
"""
Reopen given stream, optionally changing the encoding and error handler.
"""
if encoding is None:
encoding = stream.encoding
# XXX: Python3 < 3.2 and ipykernel.iostream.OutStream at least up to
# 4.5.0 do not have stream.buffer.
# I do not see a way to change errors without also potentially changing
# the encoding, and there does not seem to be a way to change encoding
# without having to access the binary stream.
try:
buf = stream.buffer
except AttributeError:
warn(
'Cannot access "%r.buffer", invalid entities from source '
'files will cause errors when annotating.' % (stream, )
)
return stream
return codecs.getwriter(encoding)(buf, errors=errors)
def _getFuncOrFile(func, module, line):
if func == '<module>' or func is None:
return module
else:
return '%s:%s' % (func, line)
def _isCallgrindName(filepath):
return os.path.basename(filepath).startswith('cachegrind.out.')
class _FileTiming(object):
"""
Accumulation of profiling statistics (line and call durations) for a given
source "file" (unique global dict).
Subclasses should be aware that:
- this classes uses __slots__, mainly for cpu efficiency (property lookup
is in a list instead of a dict)
- it can access the BaseProfile instance which created any instace using
the "profiler" property, should they share some state across source
files.
- methods on this class are profiling choke-point - keep customisations
as cheap in CPU as you can !
"""
__slots__ = ('line_dict', 'call_dict', 'filename', 'global_dict',
'raw_filename', 'profiler')
def __init__(self, raw_filename, filename, global_dict, profiler):
self.raw_filename = raw_filename
self.filename = filename
self.global_dict = global_dict
self.line_dict = {}
self.call_dict = {}
# Note: not used in this implementation, may be used by subclasses.
self.profiler = profiler
def hit(self, code, line, duration):
"""
A line has finished executing.
code (code)
container function's code object
line (int)
line number of just executed line
duration (float)
duration of the line, in seconds
"""
try:
entry = self.line_dict[line]
except KeyError:
self.line_dict[line] = [code, 1, duration]
else:
entry[1] += 1
entry[2] += duration
def call(self, code, line, callee_file_timing, callee, duration, frame):
"""
A call originating from this file returned.
code (code)
caller's code object
line (int)
caller's line number
callee_file_timing (FileTiming)
callee's FileTiming
callee (code)
callee's code object
duration (float)
duration of the call, in seconds
frame (frame)
calle's entire frame as of its return
"""
key = (line, callee_file_timing.filename, callee)
try:
entry = self.call_dict[key]
except KeyError:
self.call_dict[key] = [code, 1, duration]
else:
entry[1] += 1
entry[2] += duration
def getHitStatsFor(self, line):
code, line, duration = self.line_dict.get(line, (None, 0, 0))
if code is None:
firstlineno = None
else:
firstlineno = code.co_firstlineno
code = code.co_name
return code, firstlineno, line, duration
def getCallListByLine(self):
result = defaultdict(list)
for (line, name, callee), (code, hit, duration) in \
self.call_dict.iteritems():
result[line].append((
code.co_name, code.co_firstlineno,
hit, duration,
name, callee.co_firstlineno, callee.co_name,
))
return result
def getTotalTime(self):
return sum(x[2] for x in self.line_dict.itervalues())
def getTotalHitCount(self):
return sum(x[1] for x in self.line_dict.itervalues())
def getSortKey(self):
# total duration first, then total hit count for statistical profiling
result = [0, 0]
for _, hit, duration in self.line_dict.itervalues():
result[0] += duration
result[1] += hit
return result
FileTiming = _FileTiming
class LocalDescriptor(threading.local):
"""
Implementation of descriptor API for thread-local properties.
"""
def __init__(self, func=None):
"""
func (callable)
If provided, called when a missing property is accessed
(ex: accessing thread never initialised that property).
If None, AttributeError is raised.
"""
super(LocalDescriptor, self).__init__()
if func is not None:
self.func = func
def __get__(self, instance, owner):
try:
return getattr(self, str(id(instance)))
except AttributeError:
# Raises AttributeError if func was not provided.
value = self.func()
setattr(self, str(id(instance)), value)
return value
def __set__(self, instance, value):
setattr(self, str(id(instance)), value)
def __delete__(self, instance):
try:
delattr(self, str(id(instance)))
except AttributeError:
pass
_ANNOTATE_HEADER = \
'%6s|%10s|' \
'%13s|%13s|%7s|' \
'Source code' % (
'Line #', 'Hits',
'Time', 'Time per hit', '%',
)
_ANNOTATE_HORIZONTAL_LINE = ''.join(x == '|' and '+' or '-'
for x in _ANNOTATE_HEADER)
_ANNOTATE_FORMAT = \
'%(lineno)6i|%(hits)10i|' \
'%(time)13g|%(time_per_hit)13g|%(percent)6.2f%%|' \
'%(line)s'
_ANNOTATE_CALL_FORMAT = \
'(call)|%(hits)10i|' \
'%(time)13g|%(time_per_hit)13g|%(percent)6.2f%%|' \
'# %(callee_file)s:%(callee_line)s %(callee_name)s'
def _initStack():
return deque([[time(), None, None]])
def _verboseProfileDecorator(self):
def decorator(func):
@wraps(func)
def wrapper(frame, event, arg):
self._traceEvent(frame, event)
return func(frame, event, arg)
return wrapper
return decorator
class ProfileBase(object):
"""
Methods common to deterministic and statistic profiling.
Subclasses can override the "FileTiming" property to use a different class.
"""
FileTiming = _FileTiming
def __init__(self):
self.file_dict = {}
self.global_dict = {}
self.total_time = 0
def _getFileTiming(self, frame):
try:
return self.global_dict[(id(frame.f_globals), frame.f_code.co_filename)]
except KeyError:
f_globals = frame.f_globals
name = self._getFilename(frame.f_code.co_filename, f_globals)
try:
file_timing = self.file_dict[name]
except KeyError:
self.file_dict[name] = file_timing = self.FileTiming(
frame.f_code.co_filename,
name,
f_globals,
self,
)
self.global_dict[id(f_globals)] = file_timing
return file_timing
def _getFilename(self, filename, f_globals):
"""
Overload in subclasses to customise filename generation.
"""
return filename
def getFilenameSet(self):
"""
Returns a set of profiled file names.
Note: "file name" is used loosely here. See python documentation for
co_filename, linecache module and PEP302. It may not be a valid
filesystem path.
"""
result = set(self.file_dict)
# Ignore profiling code. __file__ does not always provide consistent
# results with f_code.co_filename (ex: easy_install with zipped egg),
# so inspect current frame instead.
# Get current file from one of pprofile methods. Compatible with
# implementations that do not have the inspect.currentframe() method
# (e.g. IronPython).
# XXX: Assumes that all of pprofile code is in a single file.
# XXX: Assumes that _initStack exists in pprofile module.
result.discard(inspect.getsourcefile(_initStack))
return result
def _getFileNameList(self, filename, may_sort=True):
if filename is None:
filename = self.getFilenameSet()
elif isinstance(filename, basestring):
return [filename]
if may_sort:
try:
# Detect if filename is an ordered data type.
filename[:0]
except TypeError:
# Not ordered, sort.
file_dict = self.file_dict
filename = sorted(filename, reverse=True,
key=lambda x: file_dict[x].getSortKey()
)
return filename
def _iterFile(self, name, call_list_by_line):
lineno = 0
if call_list_by_line:
last_call_line = max(call_list_by_line)
else:
last_call_line = 0
file_timing = self.file_dict[name]
while True:
lineno += 1
line = linecache.getline(file_timing.raw_filename, lineno,
file_timing.global_dict)
func, firstlineno, hits, duration = file_timing.getHitStatsFor(
lineno)
if func is None:
# In case the line has no hit but has a call (happens in
# statistical profiling, as hits are on leaves only).
# func & firstlineno are expected to be constant on a
# given line (accumulated data is redundant)
call_list = call_list_by_line.get(lineno)
if call_list:
func, firstlineno = call_list[0][:2]
if not line and lineno > last_call_line:
if hits == 0:
break
# Line exists in stats, but not in file. Happens on 1st
# line of empty files (ex: __init__.py). Fake the presence
# of an empty line.
line = os.linesep
yield lineno, func, firstlineno, hits, duration, line
def callgrind(self, out, filename=None, commandline=None, relative_path=False):
"""
Dump statistics in callgrind format.
Contains:
- per-line hit count, time and time-per-hit
- call associations (call tree)
Note: hit count is not inclusive, in that it is not the sum of all
hits inside that call.
Time unit: microsecond (1e-6 second).
out (file-ish opened for writing)
Destination of callgrind profiling data.
filename (str, collection of str)
If provided, dump stats for given source file(s) only.
By default, list for all known files.
commandline (anything with __str__)
If provided, will be output as the command line used to generate
this profiling data.
relative_path (bool)
When True, absolute elements are stripped from path. Useful when
maintaining several copies of source trees with their own
profiling result, so kcachegrind does not look in system-wide
files which may not match with profiled code.
"""
print('version: 1', file=out)
print('creator: pprofile', file=out)
print('event: usphit :us/hit', file=out)
print('events: hits us usphit', file=out)
if commandline is not None:
print('cmd:', commandline, file=out)
file_dict = self.file_dict
if relative_path:
convertPath = _relpath
else:
convertPath = lambda x: x
if os.path.sep != "/":
# qCacheGrind (windows build) needs at least one UNIX separator
# in path to find the file. Adapt here even if this is probably
# more of a qCacheGrind issue...
convertPath = lambda x, cascade=convertPath: cascade(
'/'.join(x.split(os.path.sep))
)
for name in self._getFileNameList(filename, may_sort=False):
printable_name = convertPath(name)
print('fl=%s' % printable_name, file=out)
funcname = False
call_list_by_line = file_dict[name].getCallListByLine()
for lineno, func, firstlineno, hits, duration, _ in self._iterFile(
name, call_list_by_line):
call_list = call_list_by_line.get(lineno, ())
if not hits and not call_list:
continue
if func is None:
func, firstlineno = call_list[0][:2]
if funcname != func:
funcname = func
print('fn=%s' % _getFuncOrFile(func,
printable_name, firstlineno), file=out)
ticks = int(duration * 1000000)
if hits == 0:
ticksperhit = 0
else:
ticksperhit = ticks / hits
print(lineno, hits, ticks, int(ticksperhit), file=out)
for _, _, hits, duration, callee_file, callee_line, \
callee_name in sorted(call_list, key=lambda x: x[2:4]):
callee_file = convertPath(callee_file)
print('cfl=%s' % callee_file, file=out)
print('cfn=%s' % _getFuncOrFile(callee_name,
callee_file, callee_line), file=out)
print('calls=%s' % hits, callee_line, file=out)
duration *= 1000000
print(lineno, hits, int(duration), int(duration / hits), file=out)
def annotate(self, out, filename=None, commandline=None, relative_path=False):
"""
Dump annotated source code with current profiling statistics to "out"
file.
Time unit: second.
out (file-ish opened for writing)
Destination of annotated sources.
filename (str, collection of str)
If provided, dump stats for given source file(s) only.
If unordered collection, it will get sorted by decreasing total
file score (total time if available, then total hit count).
By default, list for all known files.
commandline (anything with __str__)
If provided, will be output as the command line used to generate
this annotation.
relative_path (bool)
For compatibility with callgrind. Ignored.
"""
file_dict = self.file_dict
total_time = self.total_time
if commandline is not None:
print('Command line:', commandline, file=out)
print('Total duration: %gs' % total_time, file=out)
if not total_time:
return
def percent(value, scale):
if scale == 0:
return 0
return value * 100 / float(scale)
for name in self._getFileNameList(filename):
file_timing = file_dict[name]
file_total_time = file_timing.getTotalTime()
call_list_by_line = file_timing.getCallListByLine()
print('File:', name, file=out)
print('File duration: %gs (%.2f%%)' % (file_total_time,
percent(file_total_time, total_time)), file=out)
print(_ANNOTATE_HEADER, file=out)
print(_ANNOTATE_HORIZONTAL_LINE, file=out)
for lineno, _, _, hits, duration, line in self._iterFile(name,
call_list_by_line):
if hits:
time_per_hit = duration / hits
else:
time_per_hit = 0
print(_ANNOTATE_FORMAT % {
'lineno': lineno,
'hits': hits,
'time': duration,
'time_per_hit': time_per_hit,
'percent': percent(duration, total_time),
'line': line.rstrip(),
}, file=out)
for _, _, hits, duration, callee_file, callee_line, \
callee_name in call_list_by_line.get(lineno, ()):
print(_ANNOTATE_CALL_FORMAT % {
'hits': hits,
'time': duration,
'time_per_hit': duration / hits,
'percent': percent(duration, total_time),
'callee_file': callee_file,
'callee_line': callee_line,
'callee_name': callee_name,
}, file=out)
def _iterRawFile(self, name):
lineno = 0
file_timing = self.file_dict[name]
while True:
lineno += 1
line = linecache.getline(file_timing.raw_filename, lineno,
file_timing.global_dict)
if not line:
break
yield line
def iterSource(self):
"""
Iterator over all involved files.
Yields 2-tuple composed of file path and an iterator over
(non-annotated) source lines.
Can be used to generate a file tree for use with kcachegrind, for
example.
"""
for name in self._getFileNameList(None):
yield name, self._iterRawFile(name)
# profile/cProfile-like API
def dump_stats(self, filename):
"""
Similar to profile.Profile.dump_stats - but different output format !
"""
if _isCallgrindName(filename):
with open(filename, 'w') as out:
self.callgrind(out)
else:
with _open(filename, 'w', errors='replace') as out:
self.annotate(out)
def print_stats(self):
"""
Similar to profile.Profile.print_stats .
Returns None.
"""
self.annotate(_reopen(sys.stdout, errors='replace'))
class ProfileRunnerBase(object):
def __call__(self):
return self
def __enter__(self):
raise NotImplementedError
def __exit__(self, exc_type, exc_val, exc_tb):
raise NotImplementedError
# profile/cProfile-like API
def runctx(self, cmd, globals, locals):
"""Similar to profile.Profile.runctx ."""
with self():
exec(cmd, globals, locals)
return self
def runcall(self, func, *args, **kw):
"""Similar to profile.Profile.runcall ."""
with self():
return func(*args, **kw)
def runfile(self, fd, argv, fd_name='<unknown>', compile_flags=0,
dont_inherit=1, globals={}):
with fd:
code = compile(fd.read(), fd_name, 'exec', flags=compile_flags,
dont_inherit=dont_inherit)
original_sys_argv = list(sys.argv)
ctx_globals = globals.copy()
ctx_globals['__file__'] = fd_name
ctx_globals['__name__'] = '__main__'
ctx_globals['__package__'] = None
try:
sys.argv[:] = argv
return self.runctx(code, ctx_globals, None)
finally:
sys.argv[:] = original_sys_argv
def runpath(self, path, argv):
original_sys_path = list(sys.path)
try:
sys.path.insert(0, os.path.dirname(path))
return self.runfile(open(path, 'rb'), argv, fd_name=path)
finally:
sys.path[:] = original_sys_path
def runmodule(self, module, argv):
original_sys_argv = list(sys.argv)
original_sys_path0 = sys.path[0]
try:
sys.path[0] = os.getcwd()
sys.argv[:] = argv
with self():
runpy.run_module(module, run_name='__main__', alter_sys=True)
finally:
sys.argv[:] = original_sys_argv
sys.path[0] = original_sys_path0
return self
class Profile(ProfileBase, ProfileRunnerBase):
"""
Deterministic, recursive, line-granularity, profiling class.
Does not require any source code change to work.
If the performance hit is too large, it can benefit from some
integration (calling enable/disable around selected code chunks).
The sum of time spent in all profiled lines is less than the total
profiled time reported. This is (part of) profiling overhead.
This also mans that sum of time-spent-on-line percentage is less than 100%.
All times are "internal time", ie they do not count time spent inside
called (profilable, so python) functions.
"""
stack = LocalDescriptor(_initStack)
enabled_start = LocalDescriptor(float)
discount_stack = LocalDescriptor(partial(deque, [0]))
def __init__(self, verbose=False):
super(Profile, self).__init__()
if verbose:
self._global_trace = _verboseProfileDecorator(self)(
self._global_trace)
self._local_trace = _verboseProfileDecorator(self)(
self._local_trace)
def _enable(self):
"""
Overload this method when subclassing. Called before actually
enabling trace.
"""
self.enabled_start = time()
def enable(self):
"""
Enable profiling.
"""
if self.enabled_start:
warn('Duplicate "enable" call')
else:
self._enable()
sys.settrace(self._global_trace)
def _disable(self):
"""
Overload this method when subclassing. Called after actually disabling
trace.
"""
self.total_time += time() - self.enabled_start
del self.enabled_start
del self.stack
del self.discount_stack
def disable(self, threads=True):
"""
Disable profiling.
"""
if self.enabled_start:
sys.settrace(None)
self._disable()
else:
warn('Duplicate "disable" call')
def __enter__(self):
"""
__enter__() -> self
"""
self.enable()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""
__exit__(*excinfo) -> None. Disables profiling.
"""
self.disable()
def _traceEvent(self, frame, event):
f_code = frame.f_code
lineno = frame.f_lineno
print('%10.6f%s%s %s:%s %s+%s %s' % (
time() - self.enabled_start,
' ' * len(self.stack),
event,
f_code.co_filename,
lineno,
f_code.co_name,
lineno - f_code.co_firstlineno,
self.discount_stack[-1],
), file=sys.stderr)
def _global_trace(self, frame, event, arg):
local_trace = self._local_trace
if local_trace is not None:
now = time()
self.stack.append([now, frame.f_lineno, now])
self.discount_stack.append(0)
return local_trace
def _local_trace(self, frame, event, arg):
if event == 'line' or event == 'return':
event_time = time()
stack = self.stack
try:
stack_entry = stack[-1]
except IndexError:
warn('Profiling stack underflow, disabling.')
self.disable()
return
call_time, old_line, old_time = stack_entry
try:
duration = event_time - old_time
except TypeError:
pass
else:
discount_time = self.discount_stack[-1]
if discount_time:
duration -= discount_time
self.discount_stack[-1] = 0
self._getFileTiming(frame).hit(frame.f_code, old_line,
duration)
if event == 'line':
stack_entry[1] = frame.f_lineno
stack_entry[2] = event_time
else:
stack.pop()
self.discount_stack.pop()
inclusive_duration = event_time - call_time
self.discount_stack[-1] += inclusive_duration
caller_frame = frame.f_back
self._getFileTiming(caller_frame).call(
caller_frame.f_code, caller_frame.f_lineno,
self._getFileTiming(frame),
frame.f_code, inclusive_duration,
frame,
)
return self._local_trace
# profile/cProfile-like API
def run(self, cmd):
"""Similar to profile.Profile.run ."""
import __main__
dict = __main__.__dict__
return self.runctx(cmd, dict, dict)
class ThreadProfile(Profile):
"""
threading.Thread-aware version of Profile class.
Threads started after enable() call will be profiled.
After disable() call, threads will need to be switched into and trigger a
trace event (typically a "line" event) before they can notice the
disabling.
"""
def __init__(self, **kw):
super(ThreadProfile, self).__init__(**kw)
self._local_trace_backup = self._local_trace
def _enable(self):
self._local_trace = self._local_trace_backup
threading.settrace(self._global_trace)
super(ThreadProfile, self)._enable()
def _disable(self):
super(ThreadProfile, self)._disable()
threading.settrace(None)
self._local_trace = None
class StatisticProfile(ProfileBase, ProfileRunnerBase):
"""
Statistic profiling class.
This class does not gather its own samples by itself.
Instead, it must be provided with call stacks (as returned by
sys._getframe() or sys._current_frames()).
"""
def __init__(self):
super(StatisticProfile, self).__init__()
self.total_time = 1
def sample(self, frame):
getFileTiming = self._getFileTiming
called_timing = getFileTiming(frame)
called_code = frame.f_code
called_timing.hit(called_code, frame.f_lineno, 0)
while True:
caller = frame.f_back
if caller is None:
break
caller_timing = getFileTiming(caller)
caller_code = caller.f_code
caller_timing.call(caller_code, caller.f_lineno,
called_timing, called_code, 0, frame)
called_timing = caller_timing
frame = caller
called_code = caller_code
def __call__(self, period=.001, single=True, group=None, name=None):
"""
Instanciate StatisticThread.
>>> s_profile = StatisticProfile()
>>> with s_profile(single=False):
>>> # Code to profile
Is equivalent to:
>>> s_profile = StatisticProfile()
>>> s_thread = StatisticThread(profiler=s_profile, single=False)
>>> with s_thread:
>>> # Code to profile
"""
return StatisticThread(
profiler=self, period=period, single=single, group=group,
name=name,
)
# BBB
StatisticalProfile = StatisticProfile
class StatisticThread(threading.Thread, ProfileRunnerBase):
"""
Usage in a nutshell:
profiler = StatisticProfile()
pt = StatisticThread(profiler)
with pt:
# do stuff
profiler.print_stats()
"""
_test = None
_start_time = None
clean_exit = False
def __init__(self, profiler, period=.001, single=True, group=None, name=None):
"""
period (float)
How many seconds to wait between consecutive samples.
The smaller, the more profiling overhead, but the faster results
become meaningful.
The larger, the less profiling overhead, but requires long profiling
session to get meaningful results.
Available on instances as the "profiler" read-only property.
single (bool)
Profile only the thread which created this instance.
group, name
See Python's threading.Thread API.
"""
if single:
self._test = lambda x, ident=threading.current_thread().ident: ident == x
super(StatisticThread, self).__init__(
group=group,
name=name,
)
self._stop_event = threading.Event()
self._period = period
self._profiler = profiler
profiler.total_time = 0
self.daemon = True
@property
def profiler(self):
return self._profiler
def start(self):
self._start_time = time()
self._can_run = True
super(StatisticThread, self).start()
def stop(self):
"""
Request thread to stop.
Does not wait for actual termination (use join() method).
"""
if self.is_alive():
self._can_run = False
self._stop_event.set()
self._profiler.total_time += time() - self._start_time
self._start_time = None
def __enter__(self):
"""
__enter__() -> self
"""
self.start()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""
__exit__(*excinfo) -> None. Stops and joins profiling thread.
"""
self.stop()
self.join()
def run(self):
current_frames = sys._current_frames
test = self._test
if test is None:
test = lambda x, ident=self.ident: ident != x
sample = self._profiler.sample
stop_event = self._stop_event
wait = partial(stop_event.wait, self._period)
while self._can_run:
for ident, frame in current_frames().iteritems():
if test(ident):
sample(frame)
frame = None
wait()
stop_event.clear()
self.clean_exit = True
def callgrind(self, *args, **kw):
warn('deprecated', DeprecationWarning)
return self._profiler.callgrind(*args, **kw)
def annotate(self, *args, **kw):
warn('deprecated', DeprecationWarning)
return self._profiler.annotate(*args, **kw)
def dump_stats(self, *args, **kw):
warn('deprecated', DeprecationWarning)
return self._profiler.dump_stats(*args, **kw)
def print_stats(self, *args, **kw):
warn('deprecated', DeprecationWarning)
return self._profiler.print_stats(*args, **kw)
def iterSource(self, *args, **kw):
warn('deprecated', DeprecationWarning)
return self._profiler.iterSource(*args, **kw)
# BBB
StatisticalThread = StatisticThread
# profile/cProfile-like API (no sort parameter !)
def _run(threads, verbose, func_name, filename, *args, **kw):
if threads:
klass = ThreadProfile
else:
klass = Profile
prof = klass(verbose=verbose)
try:
try:
getattr(prof, func_name)(*args, **kw)
except SystemExit:
pass
finally:
if filename is None:
prof.print_stats()
else:
prof.dump_stats(filename)
def run(cmd, filename=None, threads=True, verbose=False):
"""Similar to profile.run ."""
_run(threads, verbose, 'run', filename, cmd)
def runctx(cmd, globals, locals, filename=None, threads=True, verbose=False):
"""Similar to profile.runctx ."""
_run(threads, verbose, 'runctx', filename, cmd, globals, locals)
def runfile(fd, argv, fd_name='<unknown>', compile_flags=0, dont_inherit=1,
filename=None, threads=True, verbose=False):
"""
Run code from given file descriptor with profiling enabled.
Closes fd before executing contained code.
"""
_run(threads, verbose, 'runfile', filename, fd, argv, fd_name,
compile_flags, dont_inherit)
def runpath(path, argv, filename=None, threads=True, verbose=False):
"""
Run code from open-accessible file path with profiling enabled.
"""
_run(threads, verbose, 'runpath', filename, path, argv)
_allsep = os.sep + (os.altsep or '')
def _relpath(name):
"""
Strip absolute components from path.
Inspired from zipfile.write().
"""
return os.path.normpath(os.path.splitdrive(name)[1]).lstrip(_allsep)
def _main(argv, stdin=None):
format_dict = {
'text': 'annotate',
'callgrind': 'callgrind',
}
parser = argparse.ArgumentParser(argv[0])
parser.add_argument('script', help='Python script to execute (optionaly '
'followed by its arguments)', nargs='?')
parser.add_argument('argv', nargs=argparse.REMAINDER)
parser.add_argument('-o', '--out', default='-',
help='Write annotated sources to this file. Defaults to stdout.')
parser.add_argument('-z', '--zipfile',
help='Name of a zip file to generate from all involved source files. '
'Useful with callgrind output.')
parser.add_argument('-t', '--threads', default=1, type=int, help='If '
'non-zero, trace threads spawned by program. Default: %(default)s')
parser.add_argument('-f', '--format', choices=format_dict,
help='Format in which output is generated. If not set, auto-detected '
'from filename if provided, falling back to "text".')
parser.add_argument('-v', '--verbose', action='store_true',
help='Enable profiler internal tracing output. Cryptic and verbose.')
parser.add_argument('-s', '--statistic', default=0, type=float,
help='Use this period for statistic profiling, or use deterministic '
'profiling when 0.')
parser.add_argument('-m', dest='module',
help='Searches sys.path for the named module and runs the '
'corresponding .py file as a script. When given, positional arguments '
'become sys.argv[1:]')
group = parser.add_argument_group(
title='Filtering',
description='Allows excluding (and re-including) code from '
'"file names" matching regular expressions. '
'"file name" follows the semantics of python\'s "co_filename": '
'it may be a valid path, of an existing or non-existing file, '
'but it may be some arbitrary string too.'
)
group.add_argument('--exclude-syspath', action='store_true',
help='Exclude all from default "sys.path". Beware: this will also '
'exclude properly-installed non-standard modules, which may not be '
'what you want.')
group.add_argument('--exclude', action='append', default=[],
help='Exclude files whose name starts with any pattern.')
group.add_argument('--include', action='append', default=[],
help='Include files whose name would have otherwise excluded. '
'If no exclusion was specified, all paths are excluded first.')
options = parser.parse_args(argv[1:])
if options.exclude_syspath:
options.exclude.extend('^' + re.escape(x) for x in sys.path)
if options.include and not options.exclude:
options.exclude.append('') # All-matching regex
if options.verbose:
if options.exclude:
print('Excluding:', file=sys.stderr)
for regex in options.exclude:
print('\t' + regex, file=sys.stderr)
if options.include:
print('But including:', file=sys.stderr)
for regex in options.include:
print('\t' + regex, file=sys.stderr)
if options.module is None:
if options.script is None:
parser.error('too few arguments')
args = [options.script] + options.argv
runner_method_kw = {
'path': args[0],
'argv': args,
}
runner_method_id = 'runpath'
elif stdin is not None and options.module == '-':
# Undocumented way of using -m, used internaly by %%pprofile
args = ['<stdin>']
if options.script is not None:
args.append(options.script)
args.extend(options.argv)
import __main__
runner_method_kw = {
'fd': stdin,
'argv': args,
'fd_name': '<stdin>',
'globals': __main__.__dict__,
}
runner_method_id = 'runfile'
else:
args = [options.module]
if options.script is not None:
args.append(options.script)
args.extend(options.argv)
runner_method_kw = {
'module': options.module,
'argv': args,
}
runner_method_id = 'runmodule'
if options.format is None:
if _isCallgrindName(options.out):
options.format = 'callgrind'
else:
options.format = 'text'
relative_path = options.format == 'callgrind' and options.zipfile
if options.statistic:
prof = StatisticalProfile()
runner = StatisticalThread(
profiler=prof,
period=options.statistic,
single=not options.threads,
)
else:
if options.threads:
klass = ThreadProfile
else:
klass = Profile
prof = runner = klass(verbose=options.verbose)
try:
getattr(runner, runner_method_id)(**runner_method_kw)
finally:
if options.out == '-':
out = _reopen(sys.stdout, errors='replace')
close = lambda: None
else:
out = _open(options.out, 'w', errors='replace')
close = out.close
if options.exclude:
exclusion_search_list = [
re.compile(x).search for x in options.exclude
]
include_search_list = [
re.compile(x).search for x in options.include
]
filename_set = {
x for x in prof.getFilenameSet()
if not (
any(y(x) for y in exclusion_search_list) and
not any(y(x) for y in include_search_list)
)
}
else:
filename_set = None
getattr(prof, format_dict[options.format])(
out,
filename=filename_set,
commandline=repr(args),
relative_path=relative_path,
)
close()
zip_path = options.zipfile
if zip_path:
if relative_path:
convertPath = _relpath
else:
convertPath = lambda x: x
with zipfile.ZipFile(
zip_path,
mode='w',
compression=zipfile.ZIP_DEFLATED,
) as zip_file:
for name, lines in prof.iterSource():
zip_file.writestr(
convertPath(name),
''.join(lines)
)
if options.statistic and not runner.clean_exit:
# Mostly useful for regresion testing, as exceptions raised in threads
# do not change exit status.
sys.exit(1)
def pprofile(line, cell=None):
"""
Profile line execution.
"""
if cell is None:
# TODO: detect and use arguments (statistical profiling, ...) ?
return run(line)
else:
return _main(['%%pprofile', '-m', '-'] + shlex.split(line), cStringIO.StringIO(cell))
try:
register_line_cell_magic(pprofile)
except Exception:
# ipython can be imported, but may not be currently running.
pass
del pprofile
def main():
_main(sys.argv)
if __name__ == '__main__':
main()
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