SickRage/lib/profilehooks.py

734 lines
24 KiB
Python

"""
Profiling hooks
This module contains a couple of decorators (`profile` and `coverage`) that
can be used to wrap functions and/or methods to produce profiles and line
coverage reports. There's a third convenient decorator (`timecall`) that
measures the duration of function execution without the extra profiling
overhead.
Usage example (Python 2.4 or newer)::
from profilehooks import profile, coverage
@profile # or @coverage
def fn(n):
if n < 2: return 1
else: return n * fn(n-1)
print fn(42)
Usage example (Python 2.3 or older)::
from profilehooks import profile, coverage
def fn(n):
if n < 2: return 1
else: return n * fn(n-1)
# Now wrap that function in a decorator
fn = profile(fn) # or coverage(fn)
print fn(42)
Reports for all thusly decorated functions will be printed to sys.stdout
on program termination. You can alternatively request for immediate
reports for each call by passing immediate=True to the profile decorator.
There's also a @timecall decorator for printing the time to sys.stderr
every time a function is called, when you just want to get a rough measure
instead of a detailed (but costly) profile.
Caveats
A thread on python-dev convinced me that hotshot produces bogus numbers.
See http://mail.python.org/pipermail/python-dev/2005-November/058264.html
I don't know what will happen if a decorated function will try to call
another decorated function. All decorators probably need to explicitly
support nested profiling (currently TraceFuncCoverage is the only one
that supports this, while HotShotFuncProfile has support for recursive
functions.)
Profiling with hotshot creates temporary files (*.prof for profiling,
*.cprof for coverage) in the current directory. These files are not
cleaned up. Exception: when you specify a filename to the profile
decorator (to store the pstats.Stats object for later inspection),
the temporary file will be the filename you specified with '.raw'
appended at the end.
Coverage analysis with hotshot seems to miss some executions resulting
in lower line counts and some lines errorneously marked as never
executed. For this reason coverage analysis now uses trace.py which is
slower, but more accurate.
Copyright (c) 2004--2008 Marius Gedminas <marius@pov.lt>
Copyright (c) 2007 Hanno Schlichting
Copyright (c) 2008 Florian Schulze
Released under the MIT licence since December 2006:
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the "Software"),
to deal in the Software without restriction, including without limitation
the rights to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.
(Previously it was distributed under the GNU General Public Licence.)
"""
# $Id: profilehooks.py 29 2010-08-13 16:29:20Z mg $
__author__ = "Marius Gedminas (marius@gedmin.as)"
__copyright__ = "Copyright 2004-2009 Marius Gedminas"
__license__ = "MIT"
__version__ = "1.4"
__date__ = "2009-03-31"
import atexit
import inspect
import sys
import re
# For profiling
from profile import Profile
import pstats
# For hotshot profiling (inaccurate!)
try:
import hotshot
import hotshot.stats
except ImportError:
hotshot = None
# For trace.py coverage
import trace
# For hotshot coverage (inaccurate!; uses undocumented APIs; might break)
if hotshot is not None:
import _hotshot
import hotshot.log
# For cProfile profiling (best)
try:
import cProfile
except ImportError:
cProfile = None
# For timecall
import time
# registry of available profilers
AVAILABLE_PROFILERS = {}
def profile(fn=None, skip=0, filename=None, immediate=False, dirs=False,
sort=None, entries=40,
profiler=('cProfile', 'profile', 'hotshot')):
"""Mark `fn` for profiling.
If `skip` is > 0, first `skip` calls to `fn` will not be profiled.
If `immediate` is False, profiling results will be printed to
sys.stdout on program termination. Otherwise results will be printed
after each call.
If `dirs` is False only the name of the file will be printed.
Otherwise the full path is used.
`sort` can be a list of sort keys (defaulting to ['cumulative',
'time', 'calls']). The following ones are recognized::
'calls' -- call count
'cumulative' -- cumulative time
'file' -- file name
'line' -- line number
'module' -- file name
'name' -- function name
'nfl' -- name/file/line
'pcalls' -- call count
'stdname' -- standard name
'time' -- internal time
`entries` limits the output to the first N entries.
`profiler` can be used to select the preferred profiler, or specify a
sequence of them, in order of preference. The default is ('cProfile'.
'profile', 'hotshot').
If `filename` is specified, the profile stats will be stored in the
named file. You can load them pstats.Stats(filename).
Usage::
def fn(...):
...
fn = profile(fn, skip=1)
If you are using Python 2.4, you should be able to use the decorator
syntax::
@profile(skip=3)
def fn(...):
...
or just ::
@profile
def fn(...):
...
"""
if fn is None: # @profile() syntax -- we are a decorator maker
def decorator(fn):
return profile(fn, skip=skip, filename=filename,
immediate=immediate, dirs=dirs,
sort=sort, entries=entries,
profiler=profiler)
return decorator
# @profile syntax -- we are a decorator.
if isinstance(profiler, str):
profiler = [profiler]
for p in profiler:
if p in AVAILABLE_PROFILERS:
profiler_class = AVAILABLE_PROFILERS[p]
break
else:
raise ValueError('only these profilers are available: %s'
% ', '.join(AVAILABLE_PROFILERS))
fp = profiler_class(fn, skip=skip, filename=filename,
immediate=immediate, dirs=dirs,
sort=sort, entries=entries)
# fp = HotShotFuncProfile(fn, skip=skip, filename=filename, ...)
# or HotShotFuncProfile
# We cannot return fp or fp.__call__ directly as that would break method
# definitions, instead we need to return a plain function.
def new_fn(*args, **kw):
return fp(*args, **kw)
new_fn.__doc__ = fn.__doc__
new_fn.__name__ = fn.__name__
new_fn.__dict__ = fn.__dict__
new_fn.__module__ = fn.__module__
return new_fn
def coverage(fn):
"""Mark `fn` for line coverage analysis.
Results will be printed to sys.stdout on program termination.
Usage::
def fn(...):
...
fn = coverage(fn)
If you are using Python 2.4, you should be able to use the decorator
syntax::
@coverage
def fn(...):
...
"""
fp = TraceFuncCoverage(fn) # or HotShotFuncCoverage
# We cannot return fp or fp.__call__ directly as that would break method
# definitions, instead we need to return a plain function.
def new_fn(*args, **kw):
return fp(*args, **kw)
new_fn.__doc__ = fn.__doc__
new_fn.__name__ = fn.__name__
new_fn.__dict__ = fn.__dict__
new_fn.__module__ = fn.__module__
return new_fn
def coverage_with_hotshot(fn):
"""Mark `fn` for line coverage analysis.
Uses the 'hotshot' module for fast coverage analysis.
BUG: Produces inaccurate results.
See the docstring of `coverage` for usage examples.
"""
fp = HotShotFuncCoverage(fn)
# We cannot return fp or fp.__call__ directly as that would break method
# definitions, instead we need to return a plain function.
def new_fn(*args, **kw):
return fp(*args, **kw)
new_fn.__doc__ = fn.__doc__
new_fn.__name__ = fn.__name__
new_fn.__dict__ = fn.__dict__
new_fn.__module__ = fn.__module__
return new_fn
class FuncProfile(object):
"""Profiler for a function (uses profile)."""
# This flag is shared between all instances
in_profiler = False
Profile = Profile
def __init__(self, fn, skip=0, filename=None, immediate=False, dirs=False,
sort=None, entries=40):
"""Creates a profiler for a function.
Every profiler has its own log file (the name of which is derived
from the function name).
FuncProfile registers an atexit handler that prints profiling
information to sys.stderr when the program terminates.
"""
self.fn = fn
self.skip = skip
self.filename = filename
self.immediate = immediate
self.dirs = dirs
self.sort = sort or ('cumulative', 'time', 'calls')
if isinstance(self.sort, str):
self.sort = (self.sort, )
self.entries = entries
self.reset_stats()
atexit.register(self.atexit)
def __call__(self, *args, **kw):
"""Profile a singe call to the function."""
self.ncalls += 1
if self.skip > 0:
self.skip -= 1
self.skipped += 1
return self.fn(*args, **kw)
if FuncProfile.in_profiler:
# handle recursive calls
return self.fn(*args, **kw)
# You cannot reuse the same profiler for many calls and accumulate
# stats that way. :-/
profiler = self.Profile()
try:
FuncProfile.in_profiler = True
return profiler.runcall(self.fn, *args, **kw)
finally:
FuncProfile.in_profiler = False
self.stats.add(profiler)
if self.immediate:
self.print_stats()
self.reset_stats()
def print_stats(self):
"""Print profile information to sys.stdout."""
funcname = self.fn.__name__
filename = self.fn.func_code.co_filename
lineno = self.fn.func_code.co_firstlineno
print
print "*** PROFILER RESULTS ***"
print "%s (%s:%s)" % (funcname, filename, lineno)
print "function called %d times" % self.ncalls,
if self.skipped:
print "(%d calls not profiled)" % self.skipped
else:
print
print
stats = self.stats
if self.filename:
stats.dump_stats(self.filename)
if not self.dirs:
stats.strip_dirs()
stats.sort_stats(*self.sort)
stats.print_stats(self.entries)
def reset_stats(self):
"""Reset accumulated profiler statistics."""
# Note: not using self.Profile, since pstats.Stats() fails then
self.stats = pstats.Stats(Profile())
self.ncalls = 0
self.skipped = 0
def atexit(self):
"""Stop profiling and print profile information to sys.stdout.
This function is registered as an atexit hook.
"""
if not self.immediate:
self.print_stats()
AVAILABLE_PROFILERS['profile'] = FuncProfile
if cProfile is not None:
class CProfileFuncProfile(FuncProfile):
"""Profiler for a function (uses cProfile)."""
Profile = cProfile.Profile
AVAILABLE_PROFILERS['cProfile'] = CProfileFuncProfile
if hotshot is not None:
class HotShotFuncProfile(object):
"""Profiler for a function (uses hotshot)."""
# This flag is shared between all instances
in_profiler = False
def __init__(self, fn, skip=0, filename=None):
"""Creates a profiler for a function.
Every profiler has its own log file (the name of which is derived
from the function name).
HotShotFuncProfile registers an atexit handler that prints
profiling information to sys.stderr when the program terminates.
The log file is not removed and remains there to clutter the
current working directory.
"""
self.fn = fn
self.filename = filename
if self.filename:
self.logfilename = filename + ".raw"
else:
self.logfilename = fn.__name__ + ".prof"
self.profiler = hotshot.Profile(self.logfilename)
self.ncalls = 0
self.skip = skip
self.skipped = 0
atexit.register(self.atexit)
def __call__(self, *args, **kw):
"""Profile a singe call to the function."""
self.ncalls += 1
if self.skip > 0:
self.skip -= 1
self.skipped += 1
return self.fn(*args, **kw)
if HotShotFuncProfile.in_profiler:
# handle recursive calls
return self.fn(*args, **kw)
try:
HotShotFuncProfile.in_profiler = True
return self.profiler.runcall(self.fn, *args, **kw)
finally:
HotShotFuncProfile.in_profiler = False
def atexit(self):
"""Stop profiling and print profile information to sys.stderr.
This function is registered as an atexit hook.
"""
self.profiler.close()
funcname = self.fn.__name__
filename = self.fn.func_code.co_filename
lineno = self.fn.func_code.co_firstlineno
print
print "*** PROFILER RESULTS ***"
print "%s (%s:%s)" % (funcname, filename, lineno)
print "function called %d times" % self.ncalls,
if self.skipped:
print "(%d calls not profiled)" % self.skipped
else:
print
print
stats = hotshot.stats.load(self.logfilename)
# hotshot.stats.load takes ages, and the .prof file eats megabytes, but
# a saved stats object is small and fast
if self.filename:
stats.dump_stats(self.filename)
# it is best to save before strip_dirs
stats.strip_dirs()
stats.sort_stats('cumulative', 'time', 'calls')
stats.print_stats(40)
AVAILABLE_PROFILERS['hotshot'] = HotShotFuncProfile
class HotShotFuncCoverage:
"""Coverage analysis for a function (uses _hotshot).
HotShot coverage is reportedly faster than trace.py, but it appears to
have problems with exceptions; also line counts in coverage reports
are generally lower from line counts produced by TraceFuncCoverage.
Is this my bug, or is it a problem with _hotshot?
"""
def __init__(self, fn):
"""Creates a profiler for a function.
Every profiler has its own log file (the name of which is derived
from the function name).
HotShotFuncCoverage registers an atexit handler that prints
profiling information to sys.stderr when the program terminates.
The log file is not removed and remains there to clutter the
current working directory.
"""
self.fn = fn
self.logfilename = fn.__name__ + ".cprof"
self.profiler = _hotshot.coverage(self.logfilename)
self.ncalls = 0
atexit.register(self.atexit)
def __call__(self, *args, **kw):
"""Profile a singe call to the function."""
self.ncalls += 1
return self.profiler.runcall(self.fn, args, kw)
def atexit(self):
"""Stop profiling and print profile information to sys.stderr.
This function is registered as an atexit hook.
"""
self.profiler.close()
funcname = self.fn.__name__
filename = self.fn.func_code.co_filename
lineno = self.fn.func_code.co_firstlineno
print
print "*** COVERAGE RESULTS ***"
print "%s (%s:%s)" % (funcname, filename, lineno)
print "function called %d times" % self.ncalls
print
fs = FuncSource(self.fn)
reader = hotshot.log.LogReader(self.logfilename)
for what, (filename, lineno, funcname), tdelta in reader:
if filename != fs.filename:
continue
if what == hotshot.log.LINE:
fs.mark(lineno)
if what == hotshot.log.ENTER:
# hotshot gives us the line number of the function definition
# and never gives us a LINE event for the first statement in
# a function, so if we didn't perform this mapping, the first
# statement would be marked as never executed
if lineno == fs.firstlineno:
lineno = fs.firstcodelineno
fs.mark(lineno)
reader.close()
print fs
class TraceFuncCoverage:
"""Coverage analysis for a function (uses trace module).
HotShot coverage analysis is reportedly faster, but it appears to have
problems with exceptions.
"""
# Shared between all instances so that nested calls work
tracer = trace.Trace(count=True, trace=False,
ignoredirs=[sys.prefix, sys.exec_prefix])
# This flag is also shared between all instances
tracing = False
def __init__(self, fn):
"""Creates a profiler for a function.
Every profiler has its own log file (the name of which is derived
from the function name).
TraceFuncCoverage registers an atexit handler that prints
profiling information to sys.stderr when the program terminates.
The log file is not removed and remains there to clutter the
current working directory.
"""
self.fn = fn
self.logfilename = fn.__name__ + ".cprof"
self.ncalls = 0
atexit.register(self.atexit)
def __call__(self, *args, **kw):
"""Profile a singe call to the function."""
self.ncalls += 1
if TraceFuncCoverage.tracing:
return self.fn(*args, **kw)
try:
TraceFuncCoverage.tracing = True
return self.tracer.runfunc(self.fn, *args, **kw)
finally:
TraceFuncCoverage.tracing = False
def atexit(self):
"""Stop profiling and print profile information to sys.stderr.
This function is registered as an atexit hook.
"""
funcname = self.fn.__name__
filename = self.fn.func_code.co_filename
lineno = self.fn.func_code.co_firstlineno
print
print "*** COVERAGE RESULTS ***"
print "%s (%s:%s)" % (funcname, filename, lineno)
print "function called %d times" % self.ncalls
print
fs = FuncSource(self.fn)
for (filename, lineno), count in self.tracer.counts.items():
if filename != fs.filename:
continue
fs.mark(lineno, count)
print fs
never_executed = fs.count_never_executed()
if never_executed:
print "%d lines were not executed." % never_executed
class FuncSource:
"""Source code annotator for a function."""
blank_rx = re.compile(r"^\s*finally:\s*(#.*)?$")
def __init__(self, fn):
self.fn = fn
self.filename = inspect.getsourcefile(fn)
self.source, self.firstlineno = inspect.getsourcelines(fn)
self.sourcelines = {}
self.firstcodelineno = self.firstlineno
self.find_source_lines()
def find_source_lines(self):
"""Mark all executable source lines in fn as executed 0 times."""
strs = trace.find_strings(self.filename)
lines = trace.find_lines_from_code(self.fn.func_code, strs)
self.firstcodelineno = sys.maxint
for lineno in lines:
self.firstcodelineno = min(self.firstcodelineno, lineno)
self.sourcelines.setdefault(lineno, 0)
if self.firstcodelineno == sys.maxint:
self.firstcodelineno = self.firstlineno
def mark(self, lineno, count=1):
"""Mark a given source line as executed count times.
Multiple calls to mark for the same lineno add up.
"""
self.sourcelines[lineno] = self.sourcelines.get(lineno, 0) + count
def count_never_executed(self):
"""Count statements that were never executed."""
lineno = self.firstlineno
counter = 0
for line in self.source:
if self.sourcelines.get(lineno) == 0:
if not self.blank_rx.match(line):
counter += 1
lineno += 1
return counter
def __str__(self):
"""Return annotated source code for the function."""
lines = []
lineno = self.firstlineno
for line in self.source:
counter = self.sourcelines.get(lineno)
if counter is None:
prefix = ' ' * 7
elif counter == 0:
if self.blank_rx.match(line):
prefix = ' ' * 7
else:
prefix = '>' * 6 + ' '
else:
prefix = '%5d: ' % counter
lines.append(prefix + line)
lineno += 1
return ''.join(lines)
def timecall(fn=None, immediate=True, timer=time.time):
"""Wrap `fn` and print its execution time.
Example::
@timecall
def somefunc(x, y):
time.sleep(x * y)
somefunc(2, 3)
will print the time taken by somefunc on every call. If you want just
a summary at program termination, use
@timecall(immediate=False)
You can also choose a timing method other than the default ``time.time()``,
e.g.:
@timecall(timer=time.clock)
"""
if fn is None: # @timecall() syntax -- we are a decorator maker
def decorator(fn):
return timecall(fn, immediate=immediate, timer=timer)
return decorator
# @timecall syntax -- we are a decorator.
fp = FuncTimer(fn, immediate=immediate, timer=timer)
# We cannot return fp or fp.__call__ directly as that would break method
# definitions, instead we need to return a plain function.
def new_fn(*args, **kw):
return fp(*args, **kw)
new_fn.__doc__ = fn.__doc__
new_fn.__name__ = fn.__name__
new_fn.__dict__ = fn.__dict__
new_fn.__module__ = fn.__module__
return new_fn
class FuncTimer(object):
def __init__(self, fn, immediate, timer):
self.fn = fn
self.ncalls = 0
self.totaltime = 0
self.immediate = immediate
self.timer = timer
if not immediate:
atexit.register(self.atexit)
def __call__(self, *args, **kw):
"""Profile a singe call to the function."""
fn = self.fn
timer = self.timer
self.ncalls += 1
try:
start = timer()
return fn(*args, **kw)
finally:
duration = timer() - start
self.totaltime += duration
if self.immediate:
funcname = fn.__name__
filename = fn.func_code.co_filename
lineno = fn.func_code.co_firstlineno
print >> sys.stderr, "\n %s (%s:%s):\n %.3f seconds\n" % (
funcname, filename, lineno, duration)
def atexit(self):
if not self.ncalls:
return
funcname = self.fn.__name__
filename = self.fn.func_code.co_filename
lineno = self.fn.func_code.co_firstlineno
print ("\n %s (%s:%s):\n"
" %d calls, %.3f seconds (%.3f seconds per call)\n" % (
funcname, filename, lineno, self.ncalls,
self.totaltime, self.totaltime / self.ncalls))