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cProfile.py
#! /usr/libexec/platform-python """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(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 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, 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, '__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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