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#! /usr/bin/env python3
"""Python interface for the 'lsprof' profiler.
Compatible with the 'profile' module.
"""
__all__ = ["run", "runctx", "Profile"]
import _lsprof
import profile as _pyprofile
# ____________________________________________________________
# Simple interface
def run(statement, filename=None, sort=-1):
return _pyprofile._Utils(Profile).run(statement, filename, sort)
def runctx(statement, globals, locals, filename=None, sort=-1):
return _pyprofile._Utils(Profile).runctx(statement, globals, locals,
filename, sort)
run.__doc__ = _pyprofile.run.__doc__
runctx.__doc__ = _pyprofile.runctx.__doc__
# ____________________________________________________________
class Profile(_lsprof.Profiler):
"""Profile(custom_timer=None, time_unit=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, time_unit 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
with open(file, 'wb') as f:
self.create_stats()
marshal.dump(self.stats, f)
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, 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
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)
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,
'__cached__': 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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