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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

# ____________________________________________________________

# 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:

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:

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

# ____________________________________________________________

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

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, 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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