"""Python interface for the 'lsprof' profiler.
Compatible with the 'profile' module.
__all__ = ["run", "runctx", "help", "Profile"]
# ____________________________________________________________
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
prof = prof.run(statement)
prof.dump_stats(filename)
result = prof.print_stats(sort)
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 = prof.runctx(statement, globals, locals)
prof.dump_stats(filename)
result = prof.print_stats(sort)
# Backwards compatibility.
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
# Most of the functionality is in the base class.
# This subclass only adds convenient and backward-compatible methods.
def print_stats(self, sort=-1):
pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()
def dump_stats(self, file):
marshal.dump(self.stats, f)
def snapshot_stats(self):
entries = self.getstats()
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
callersdicts[id(entry.code)] = callers
self.stats[func] = cc, nc, tt, ct, callers
for subentry in entry.calls:
callers = callersdicts[id(subentry.code)]
cc = nc - subentry.reccallcount
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.
return self.runctx(cmd, dict, dict)
def runctx(self, cmd, globals, locals):
exec cmd in globals, locals
# This method is more useful to profile a single function call.
def runcall(self, func, *args, **kw):
# ____________________________________________________________
if isinstance(code, str):
return ('~', 0, code) # built-in functions ('~' sorts at the end)
return (code.co_filename, code.co_firstlineno, code.co_name)
# ____________________________________________________________
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",
choices=sorted(pstats.Stats.sort_arg_dict_default))
(options, args) = parser.parse_args()
sys.path.insert(0, os.path.dirname(progname))
with open(progname, 'rb') as fp:
code = compile(fp.read(), progname, 'exec')
runctx(code, globs, None, options.outfile, options.sort)
# When invoked as main program, invoke the profiler on a script
if __name__ == '__main__':