| #! /usr/bin/env python | |
| # | |
| # Class for profiling python code. rev 1.0 6/2/94 | |
| # | |
| # Based on prior profile module by Sjoerd Mullender... | |
| # which was hacked somewhat by: Guido van Rossum | |
| """Class for profiling Python code.""" | |
| # Copyright 1994, by InfoSeek Corporation, all rights reserved. | |
| # Written by James Roskind | |
| # | |
| # Permission to use, copy, modify, and distribute this Python software | |
| # and its associated documentation for any purpose (subject to the | |
| # restriction in the following sentence) without fee is hereby granted, | |
| # provided that the above copyright notice appears in all copies, and | |
| # that both that copyright notice and this permission notice appear in | |
| # supporting documentation, and that the name of InfoSeek not be used in | |
| # advertising or publicity pertaining to distribution of the software | |
| # without specific, written prior permission. This permission is | |
| # explicitly restricted to the copying and modification of the software | |
| # to remain in Python, compiled Python, or other languages (such as C) | |
| # wherein the modified or derived code is exclusively imported into a | |
| # Python module. | |
| # | |
| # INFOSEEK CORPORATION DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS | |
| # SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND | |
| # FITNESS. IN NO EVENT SHALL INFOSEEK CORPORATION BE LIABLE FOR ANY | |
| # SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER | |
| # RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF | |
| # CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN | |
| # CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. | |
| import sys | |
| import os | |
| import time | |
| import marshal | |
| from optparse import OptionParser | |
| __all__ = ["run", "runctx", "help", "Profile"] | |
| # Sample timer for use with | |
| #i_count = 0 | |
| #def integer_timer(): | |
| # global i_count | |
| # i_count = i_count + 1 | |
| # return i_count | |
| #itimes = integer_timer # replace with C coded timer returning integers | |
| #************************************************************************** | |
| # The following are the static member functions for the profiler class | |
| # Note that an instance of Profile() is *not* needed to call them. | |
| #************************************************************************** | |
| 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() | |
| try: | |
| prof = prof.run(statement) | |
| except SystemExit: | |
| pass | |
| if filename is not None: | |
| prof.dump_stats(filename) | |
| else: | |
| return 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 = Profile() | |
| try: | |
| prof = prof.runctx(statement, globals, locals) | |
| except SystemExit: | |
| pass | |
| if filename is not None: | |
| prof.dump_stats(filename) | |
| else: | |
| return prof.print_stats(sort) | |
| # Backwards compatibility. | |
| def help(): | |
| print "Documentation for the profile module can be found " | |
| print "in the Python Library Reference, section 'The Python Profiler'." | |
| if hasattr(os, "times"): | |
| def _get_time_times(timer=os.times): | |
| t = timer() | |
| return t[0] + t[1] | |
| # Using getrusage(3) is better than clock(3) if available: | |
| # on some systems (e.g. FreeBSD), getrusage has a higher resolution | |
| # Furthermore, on a POSIX system, returns microseconds, which | |
| # wrap around after 36min. | |
| _has_res = 0 | |
| try: | |
| import resource | |
| resgetrusage = lambda: resource.getrusage(resource.RUSAGE_SELF) | |
| def _get_time_resource(timer=resgetrusage): | |
| t = timer() | |
| return t[0] + t[1] | |
| _has_res = 1 | |
| except ImportError: | |
| pass | |
| class Profile: | |
| """Profiler class. | |
| self.cur is always a tuple. Each such tuple corresponds to a stack | |
| frame that is currently active (self.cur[-2]). The following are the | |
| definitions of its members. We use this external "parallel stack" to | |
| avoid contaminating the program that we are profiling. (old profiler | |
| used to write into the frames local dictionary!!) Derived classes | |
| can change the definition of some entries, as long as they leave | |
| [-2:] intact (frame and previous tuple). In case an internal error is | |
| detected, the -3 element is used as the function name. | |
| [ 0] = Time that needs to be charged to the parent frame's function. | |
| It is used so that a function call will not have to access the | |
| timing data for the parent frame. | |
| [ 1] = Total time spent in this frame's function, excluding time in | |
| subfunctions (this latter is tallied in cur[2]). | |
| [ 2] = Total time spent in subfunctions, excluding time executing the | |
| frame's function (this latter is tallied in cur[1]). | |
| [-3] = Name of the function that corresponds to this frame. | |
| [-2] = Actual frame that we correspond to (used to sync exception handling). | |
| [-1] = Our parent 6-tuple (corresponds to frame.f_back). | |
| Timing data for each function is stored as a 5-tuple in the dictionary | |
| self.timings[]. The index is always the name stored in self.cur[-3]. | |
| The following are the definitions of the members: | |
| [0] = The number of times this function was called, not counting direct | |
| or indirect recursion, | |
| [1] = Number of times this function appears on the stack, minus one | |
| [2] = Total time spent internal to this function | |
| [3] = Cumulative time that this function was present on the stack. In | |
| non-recursive functions, this is the total execution time from start | |
| to finish of each invocation of a function, including time spent in | |
| all subfunctions. | |
| [4] = A dictionary indicating for each function name, the number of times | |
| it was called by us. | |
| """ | |
| bias = 0 # calibration constant | |
| def __init__(self, timer=None, bias=None): | |
| self.timings = {} | |
| self.cur = None | |
| self.cmd = "" | |
| self.c_func_name = "" | |
| if bias is None: | |
| bias = self.bias | |
| self.bias = bias # Materialize in local dict for lookup speed. | |
| if not timer: | |
| if _has_res: | |
| self.timer = resgetrusage | |
| self.dispatcher = self.trace_dispatch | |
| self.get_time = _get_time_resource | |
| elif hasattr(time, 'clock'): | |
| self.timer = self.get_time = time.clock | |
| self.dispatcher = self.trace_dispatch_i | |
| elif hasattr(os, 'times'): | |
| self.timer = os.times | |
| self.dispatcher = self.trace_dispatch | |
| self.get_time = _get_time_times | |
| else: | |
| self.timer = self.get_time = time.time | |
| self.dispatcher = self.trace_dispatch_i | |
| else: | |
| self.timer = timer | |
| t = self.timer() # test out timer function | |
| try: | |
| length = len(t) | |
| except TypeError: | |
| self.get_time = timer | |
| self.dispatcher = self.trace_dispatch_i | |
| else: | |
| if length == 2: | |
| self.dispatcher = self.trace_dispatch | |
| else: | |
| self.dispatcher = self.trace_dispatch_l | |
| # This get_time() implementation needs to be defined | |
| # here to capture the passed-in timer in the parameter | |
| # list (for performance). Note that we can't assume | |
| # the timer() result contains two values in all | |
| # cases. | |
| def get_time_timer(timer=timer, sum=sum): | |
| return sum(timer()) | |
| self.get_time = get_time_timer | |
| self.t = self.get_time() | |
| self.simulate_call('profiler') | |
| # Heavily optimized dispatch routine for os.times() timer | |
| def trace_dispatch(self, frame, event, arg): | |
| timer = self.timer | |
| t = timer() | |
| t = t[0] + t[1] - self.t - self.bias | |
| if event == "c_call": | |
| self.c_func_name = arg.__name__ | |
| if self.dispatch[event](self, frame,t): | |
| t = timer() | |
| self.t = t[0] + t[1] | |
| else: | |
| r = timer() | |
| self.t = r[0] + r[1] - t # put back unrecorded delta | |
| # Dispatch routine for best timer program (return = scalar, fastest if | |
| # an integer but float works too -- and time.clock() relies on that). | |
| def trace_dispatch_i(self, frame, event, arg): | |
| timer = self.timer | |
| t = timer() - self.t - self.bias | |
| if event == "c_call": | |
| self.c_func_name = arg.__name__ | |
| if self.dispatch[event](self, frame, t): | |
| self.t = timer() | |
| else: | |
| self.t = timer() - t # put back unrecorded delta | |
| # Dispatch routine for macintosh (timer returns time in ticks of | |
| # 1/60th second) | |
| def trace_dispatch_mac(self, frame, event, arg): | |
| timer = self.timer | |
| t = timer()/60.0 - self.t - self.bias | |
| if event == "c_call": | |
| self.c_func_name = arg.__name__ | |
| if self.dispatch[event](self, frame, t): | |
| self.t = timer()/60.0 | |
| else: | |
| self.t = timer()/60.0 - t # put back unrecorded delta | |
| # SLOW generic dispatch routine for timer returning lists of numbers | |
| def trace_dispatch_l(self, frame, event, arg): | |
| get_time = self.get_time | |
| t = get_time() - self.t - self.bias | |
| if event == "c_call": | |
| self.c_func_name = arg.__name__ | |
| if self.dispatch[event](self, frame, t): | |
| self.t = get_time() | |
| else: | |
| self.t = get_time() - t # put back unrecorded delta | |
| # In the event handlers, the first 3 elements of self.cur are unpacked | |
| # into vrbls w/ 3-letter names. The last two characters are meant to be | |
| # mnemonic: | |
| # _pt self.cur[0] "parent time" time to be charged to parent frame | |
| # _it self.cur[1] "internal time" time spent directly in the function | |
| # _et self.cur[2] "external time" time spent in subfunctions | |
| def trace_dispatch_exception(self, frame, t): | |
| rpt, rit, ret, rfn, rframe, rcur = self.cur | |
| if (rframe is not frame) and rcur: | |
| return self.trace_dispatch_return(rframe, t) | |
| self.cur = rpt, rit+t, ret, rfn, rframe, rcur | |
| return 1 | |
| def trace_dispatch_call(self, frame, t): | |
| if self.cur and frame.f_back is not self.cur[-2]: | |
| rpt, rit, ret, rfn, rframe, rcur = self.cur | |
| if not isinstance(rframe, Profile.fake_frame): | |
| assert rframe.f_back is frame.f_back, ("Bad call", rfn, | |
| rframe, rframe.f_back, | |
| frame, frame.f_back) | |
| self.trace_dispatch_return(rframe, 0) | |
| assert (self.cur is None or \ | |
| frame.f_back is self.cur[-2]), ("Bad call", | |
| self.cur[-3]) | |
| fcode = frame.f_code | |
| fn = (fcode.co_filename, fcode.co_firstlineno, fcode.co_name) | |
| self.cur = (t, 0, 0, fn, frame, self.cur) | |
| timings = self.timings | |
| if fn in timings: | |
| cc, ns, tt, ct, callers = timings[fn] | |
| timings[fn] = cc, ns + 1, tt, ct, callers | |
| else: | |
| timings[fn] = 0, 0, 0, 0, {} | |
| return 1 | |
| def trace_dispatch_c_call (self, frame, t): | |
| fn = ("", 0, self.c_func_name) | |
| self.cur = (t, 0, 0, fn, frame, self.cur) | |
| timings = self.timings | |
| if fn in timings: | |
| cc, ns, tt, ct, callers = timings[fn] | |
| timings[fn] = cc, ns+1, tt, ct, callers | |
| else: | |
| timings[fn] = 0, 0, 0, 0, {} | |
| return 1 | |
| def trace_dispatch_return(self, frame, t): | |
| if frame is not self.cur[-2]: | |
| assert frame is self.cur[-2].f_back, ("Bad return", self.cur[-3]) | |
| self.trace_dispatch_return(self.cur[-2], 0) | |
| # Prefix "r" means part of the Returning or exiting frame. | |
| # Prefix "p" means part of the Previous or Parent or older frame. | |
| rpt, rit, ret, rfn, frame, rcur = self.cur | |
| rit = rit + t | |
| frame_total = rit + ret | |
| ppt, pit, pet, pfn, pframe, pcur = rcur | |
| self.cur = ppt, pit + rpt, pet + frame_total, pfn, pframe, pcur | |
| timings = self.timings | |
| cc, ns, tt, ct, callers = timings[rfn] | |
| if not ns: | |
| # This is the only occurrence of the function on the stack. | |
| # Else this is a (directly or indirectly) recursive call, and | |
| # its cumulative time will get updated when the topmost call to | |
| # it returns. | |
| ct = ct + frame_total | |
| cc = cc + 1 | |
| if pfn in callers: | |
| callers[pfn] = callers[pfn] + 1 # hack: gather more | |
| # stats such as the amount of time added to ct courtesy | |
| # of this specific call, and the contribution to cc | |
| # courtesy of this call. | |
| else: | |
| callers[pfn] = 1 | |
| timings[rfn] = cc, ns - 1, tt + rit, ct, callers | |
| return 1 | |
| dispatch = { | |
| "call": trace_dispatch_call, | |
| "exception": trace_dispatch_exception, | |
| "return": trace_dispatch_return, | |
| "c_call": trace_dispatch_c_call, | |
| "c_exception": trace_dispatch_return, # the C function returned | |
| "c_return": trace_dispatch_return, | |
| } | |
| # The next few functions play with self.cmd. By carefully preloading | |
| # our parallel stack, we can force the profiled result to include | |
| # an arbitrary string as the name of the calling function. | |
| # We use self.cmd as that string, and the resulting stats look | |
| # very nice :-). | |
| def set_cmd(self, cmd): | |
| if self.cur[-1]: return # already set | |
| self.cmd = cmd | |
| self.simulate_call(cmd) | |
| class fake_code: | |
| def __init__(self, filename, line, name): | |
| self.co_filename = filename | |
| self.co_line = line | |
| self.co_name = name | |
| self.co_firstlineno = 0 | |
| def __repr__(self): | |
| return repr((self.co_filename, self.co_line, self.co_name)) | |
| class fake_frame: | |
| def __init__(self, code, prior): | |
| self.f_code = code | |
| self.f_back = prior | |
| def simulate_call(self, name): | |
| code = self.fake_code('profile', 0, name) | |
| if self.cur: | |
| pframe = self.cur[-2] | |
| else: | |
| pframe = None | |
| frame = self.fake_frame(code, pframe) | |
| self.dispatch['call'](self, frame, 0) | |
| # collect stats from pending stack, including getting final | |
| # timings for self.cmd frame. | |
| def simulate_cmd_complete(self): | |
| get_time = self.get_time | |
| t = get_time() - self.t | |
| while self.cur[-1]: | |
| # We *can* cause assertion errors here if | |
| # dispatch_trace_return checks for a frame match! | |
| self.dispatch['return'](self, self.cur[-2], t) | |
| t = 0 | |
| self.t = get_time() - t | |
| def print_stats(self, sort=-1): | |
| import pstats | |
| pstats.Stats(self).strip_dirs().sort_stats(sort). \ | |
| print_stats() | |
| def dump_stats(self, file): | |
| f = open(file, 'wb') | |
| self.create_stats() | |
| marshal.dump(self.stats, f) | |
| f.close() | |
| def create_stats(self): | |
| self.simulate_cmd_complete() | |
| self.snapshot_stats() | |
| def snapshot_stats(self): | |
| self.stats = {} | |
| for func, (cc, ns, tt, ct, callers) in self.timings.iteritems(): | |
| callers = callers.copy() | |
| nc = 0 | |
| for callcnt in callers.itervalues(): | |
| nc += callcnt | |
| self.stats[func] = cc, nc, tt, ct, callers | |
| # 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.set_cmd(cmd) | |
| sys.setprofile(self.dispatcher) | |
| try: | |
| exec cmd in globals, locals | |
| finally: | |
| sys.setprofile(None) | |
| return self | |
| # This method is more useful to profile a single function call. | |
| def runcall(self, func, *args, **kw): | |
| self.set_cmd(repr(func)) | |
| sys.setprofile(self.dispatcher) | |
| try: | |
| return func(*args, **kw) | |
| finally: | |
| sys.setprofile(None) | |
| #****************************************************************** | |
| # The following calculates the overhead for using a profiler. The | |
| # problem is that it takes a fair amount of time for the profiler | |
| # to stop the stopwatch (from the time it receives an event). | |
| # Similarly, there is a delay from the time that the profiler | |
| # re-starts the stopwatch before the user's code really gets to | |
| # continue. The following code tries to measure the difference on | |
| # a per-event basis. | |
| # | |
| # Note that this difference is only significant if there are a lot of | |
| # events, and relatively little user code per event. For example, | |
| # code with small functions will typically benefit from having the | |
| # profiler calibrated for the current platform. This *could* be | |
| # done on the fly during init() time, but it is not worth the | |
| # effort. Also note that if too large a value specified, then | |
| # execution time on some functions will actually appear as a | |
| # negative number. It is *normal* for some functions (with very | |
| # low call counts) to have such negative stats, even if the | |
| # calibration figure is "correct." | |
| # | |
| # One alternative to profile-time calibration adjustments (i.e., | |
| # adding in the magic little delta during each event) is to track | |
| # more carefully the number of events (and cumulatively, the number | |
| # of events during sub functions) that are seen. If this were | |
| # done, then the arithmetic could be done after the fact (i.e., at | |
| # display time). Currently, we track only call/return events. | |
| # These values can be deduced by examining the callees and callers | |
| # vectors for each functions. Hence we *can* almost correct the | |
| # internal time figure at print time (note that we currently don't | |
| # track exception event processing counts). Unfortunately, there | |
| # is currently no similar information for cumulative sub-function | |
| # time. It would not be hard to "get all this info" at profiler | |
| # time. Specifically, we would have to extend the tuples to keep | |
| # counts of this in each frame, and then extend the defs of timing | |
| # tuples to include the significant two figures. I'm a bit fearful | |
| # that this additional feature will slow the heavily optimized | |
| # event/time ratio (i.e., the profiler would run slower, fur a very | |
| # low "value added" feature.) | |
| #************************************************************** | |
| def calibrate(self, m, verbose=0): | |
| if self.__class__ is not Profile: | |
| raise TypeError("Subclasses must override .calibrate().") | |
| saved_bias = self.bias | |
| self.bias = 0 | |
| try: | |
| return self._calibrate_inner(m, verbose) | |
| finally: | |
| self.bias = saved_bias | |
| def _calibrate_inner(self, m, verbose): | |
| get_time = self.get_time | |
| # Set up a test case to be run with and without profiling. Include | |
| # lots of calls, because we're trying to quantify stopwatch overhead. | |
| # Do not raise any exceptions, though, because we want to know | |
| # exactly how many profile events are generated (one call event, + | |
| # one return event, per Python-level call). | |
| def f1(n): | |
| for i in range(n): | |
| x = 1 | |
| def f(m, f1=f1): | |
| for i in range(m): | |
| f1(100) | |
| f(m) # warm up the cache | |
| # elapsed_noprofile <- time f(m) takes without profiling. | |
| t0 = get_time() | |
| f(m) | |
| t1 = get_time() | |
| elapsed_noprofile = t1 - t0 | |
| if verbose: | |
| print "elapsed time without profiling =", elapsed_noprofile | |
| # elapsed_profile <- time f(m) takes with profiling. The difference | |
| # is profiling overhead, only some of which the profiler subtracts | |
| # out on its own. | |
| p = Profile() | |
| t0 = get_time() | |
| p.runctx('f(m)', globals(), locals()) | |
| t1 = get_time() | |
| elapsed_profile = t1 - t0 | |
| if verbose: | |
| print "elapsed time with profiling =", elapsed_profile | |
| # reported_time <- "CPU seconds" the profiler charged to f and f1. | |
| total_calls = 0.0 | |
| reported_time = 0.0 | |
| for (filename, line, funcname), (cc, ns, tt, ct, callers) in \ | |
| p.timings.items(): | |
| if funcname in ("f", "f1"): | |
| total_calls += cc | |
| reported_time += tt | |
| if verbose: | |
| print "'CPU seconds' profiler reported =", reported_time | |
| print "total # calls =", total_calls | |
| if total_calls != m + 1: | |
| raise ValueError("internal error: total calls = %d" % total_calls) | |
| # reported_time - elapsed_noprofile = overhead the profiler wasn't | |
| # able to measure. Divide by twice the number of calls (since there | |
| # are two profiler events per call in this test) to get the hidden | |
| # overhead per event. | |
| mean = (reported_time - elapsed_noprofile) / 2.0 / total_calls | |
| if verbose: | |
| print "mean stopwatch overhead per profile event =", mean | |
| return mean | |
| #**************************************************************************** | |
| def Stats(*args): | |
| print 'Report generating functions are in the "pstats" module\a' | |
| def main(): | |
| usage = "profile.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, | |
| } | |
| 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() |