#! /usr/bin/env python """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):    """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()    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(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 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    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(sys.argv) > 0):        sys.path.insert(0, os.path.dirname(sys.argv[0]))        run('execfile(%r)' % (sys.argv[0],), options.outfile, options.sort)    else:        parser.print_usage()    return parser # When invoked as main program, invoke the profiler on a scriptif __name__ == '__main__':    main()