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Edit: /opt/alt/python33/lib64/python3.3/cProfile.py (6361B)
#! /opt/alt/python33/bin/python3.3 """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: 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: 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 ", 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()