Current File : //proc/thread-self/root/proc/self/root/proc/thread-self/root/lib64/python2.7/cProfile.py
#! /usr/bin/python2.7
"""Python interface for the 'lsprof' profiler.
Compatible with the 'profile' module.
"""
__all__ = ["run", "runctx", "help", "Profile"]
import _lsprof
# ____________________________________________________________
# Simple interface
def run(statement, filename=None, sort=-1):
"""Run statement under profiler optionally saving results in filename
This function takes a single argument that can be passed to the
"exec" statement, and an optional file name. In all cases this
routine attempts to "exec" its first argument and gather profiling
statistics from the execution. If no file name is present, then this
function automatically prints a simple profiling report, sorted by the
standard name string (file/line/function-name) that is presented in
each line.
"""
prof = Profile()
result = None
try:
try:
prof = prof.run(statement)
except SystemExit:
pass
finally:
if filename is not None:
prof.dump_stats(filename)
else:
result = prof.print_stats(sort)
return result
def runctx(statement, globals, locals, filename=None, sort=-1):
"""Run statement under profiler, supplying your own globals and locals,
optionally saving results in filename.
statement and filename have the same semantics as profile.run
"""
prof = Profile()
result = None
try:
try:
prof = prof.runctx(statement, globals, locals)
except SystemExit:
pass
finally:
if filename is not None:
prof.dump_stats(filename)
else:
result = prof.print_stats(sort)
return result
# Backwards compatibility.
def help():
print "Documentation for the profile/cProfile modules can be found "
print "in the Python Library Reference, section 'The Python Profiler'."
# ____________________________________________________________
class Profile(_lsprof.Profiler):
"""Profile(timer=None, timeunit=None, subcalls=True, builtins=True)
Builds a profiler object using the specified timer function.
The default timer is a fast built-in one based on real time.
For custom timer functions returning integers, timeunit can
be a float specifying a scale (i.e. how long each integer unit
is, in seconds).
"""
# Most of the functionality is in the base class.
# This subclass only adds convenient and backward-compatible methods.
def print_stats(self, sort=-1):
import pstats
pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()
def dump_stats(self, file):
import marshal
f = open(file, 'wb')
self.create_stats()
marshal.dump(self.stats, f)
f.close()
def create_stats(self):
self.disable()
self.snapshot_stats()
def snapshot_stats(self):
entries = self.getstats()
self.stats = {}
callersdicts = {}
# call information
for entry in entries:
func = label(entry.code)
nc = entry.callcount # ncalls column of pstats (before '/')
cc = nc - entry.reccallcount # ncalls column of pstats (after '/')
tt = entry.inlinetime # tottime column of pstats
ct = entry.totaltime # cumtime column of pstats
callers = {}
callersdicts[id(entry.code)] = callers
self.stats[func] = cc, nc, tt, ct, callers
# subcall information
for entry in entries:
if entry.calls:
func = label(entry.code)
for subentry in entry.calls:
try:
callers = callersdicts[id(subentry.code)]
except KeyError:
continue
nc = subentry.callcount
cc = nc - subentry.reccallcount
tt = subentry.inlinetime
ct = subentry.totaltime
if func in callers:
prev = callers[func]
nc += prev[0]
cc += prev[1]
tt += prev[2]
ct += prev[3]
callers[func] = nc, cc, tt, ct
# The following two methods can be called by clients to use
# a profiler to profile a statement, given as a string.
def run(self, cmd):
import __main__
dict = __main__.__dict__
return self.runctx(cmd, dict, dict)
def runctx(self, cmd, globals, locals):
self.enable()
try:
exec cmd in globals, locals
finally:
self.disable()
return self
# This method is more useful to profile a single function call.
def runcall(self, func, *args, **kw):
self.enable()
try:
return func(*args, **kw)
finally:
self.disable()
# ____________________________________________________________
def label(code):
if isinstance(code, str):
return ('~', 0, code) # built-in functions ('~' sorts at the end)
else:
return (code.co_filename, code.co_firstlineno, code.co_name)
# ____________________________________________________________
def main():
import os, sys, pstats
from optparse import OptionParser
usage = "cProfile.py [-o output_file_path] [-s sort] scriptfile [arg] ..."
parser = OptionParser(usage=usage)
parser.allow_interspersed_args = False
parser.add_option('-o', '--outfile', dest="outfile",
help="Save stats to <outfile>", default=None)
parser.add_option('-s', '--sort', dest="sort",
help="Sort order when printing to stdout, based on pstats.Stats class",
default=-1,
choices=sorted(pstats.Stats.sort_arg_dict_default))
if not sys.argv[1:]:
parser.print_usage()
sys.exit(2)
(options, args) = parser.parse_args()
sys.argv[:] = args
if len(args) > 0:
progname = args[0]
sys.path.insert(0, os.path.dirname(progname))
with open(progname, 'rb') as fp:
code = compile(fp.read(), progname, 'exec')
globs = {
'__file__': progname,
'__name__': '__main__',
'__package__': None,
}
runctx(code, globs, None, options.outfile, options.sort)
else:
parser.print_usage()
return parser
# When invoked as main program, invoke the profiler on a script
if __name__ == '__main__':
main()
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