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- #! /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
- #
- # See profile.doc for more information
-
-
- # 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 string
- import marshal
-
-
- # 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.
- #**************************************************************************
-
-
- # simplified user interface
- def run(statement, *args):
- prof = Profile()
- try:
- prof = prof.run(statement)
- except SystemExit:
- pass
- if args:
- prof.dump_stats(args[0])
- else:
- return prof.print_stats()
-
- # print help
- def help():
- for dirname in sys.path:
- fullname = os.path.join(dirname, 'profile.doc')
- if os.path.exists(fullname):
- sts = os.system('${PAGER-more} '+fullname)
- if sts: print '*** Pager exit status:', sts
- break
- else:
- print 'Sorry, can\'t find the help file "profile.doc"',
- print 'along the Python search path'
-
-
- #**************************************************************************
- # class Profile documentation:
- #**************************************************************************
- # 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.
- #
- # [ 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 parents frame.
- # [ 1] = Total time spent in this frame's function, excluding time in
- # subfunctions
- # [ 2] = Cumulative time spent in this frame's function, including time in
- # all subfunctions to this frame.
- # [-3] = Name of the function that corresonds to this frame.
- # [-2] = Actual frame that we correspond to (used to sync exception handling)
- # [-1] = Our parent 6-tuple (corresonds 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[4].
- # 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.
- # [5] = A dictionary indicating for each function name, the number of times
- # it was called by us.
- #**************************************************************************
- class Profile:
-
- def __init__(self, timer=None):
- self.timings = {}
- self.cur = None
- self.cmd = ""
-
- self.dispatch = { \
- 'call' : self.trace_dispatch_call, \
- 'return' : self.trace_dispatch_return, \
- 'exception': self.trace_dispatch_exception, \
- }
-
- if not timer:
- if os.name == 'mac':
- import MacOS
- self.timer = MacOS.GetTicks
- self.dispatcher = self.trace_dispatch_mac
- self.get_time = self.get_time_mac
- elif hasattr(time, 'clock'):
- self.timer = time.clock
- self.dispatcher = self.trace_dispatch_i
- elif hasattr(os, 'times'):
- self.timer = os.times
- self.dispatcher = self.trace_dispatch
- else:
- self.timer = time.time
- self.dispatcher = self.trace_dispatch_i
- else:
- self.timer = timer
- t = self.timer() # test out timer function
- try:
- if len(t) == 2:
- self.dispatcher = self.trace_dispatch
- else:
- self.dispatcher = self.trace_dispatch_l
- except TypeError:
- self.dispatcher = self.trace_dispatch_i
- self.t = self.get_time()
- self.simulate_call('profiler')
-
-
- def get_time(self): # slow simulation of method to acquire time
- t = self.timer()
- if type(t) == type(()) or type(t) == type([]):
- t = reduce(lambda x,y: x+y, t, 0)
- return t
-
- def get_time_mac(self):
- return self.timer()/60.0
-
- # Heavily optimized dispatch routine for os.times() timer
-
- def trace_dispatch(self, frame, event, arg):
- t = self.timer()
- t = t[0] + t[1] - self.t # No Calibration constant
- # t = t[0] + t[1] - self.t - .00053 # Calibration constant
-
- if self.dispatch[event](frame,t):
- t = self.timer()
- self.t = t[0] + t[1]
- else:
- r = self.timer()
- self.t = r[0] + r[1] - t # put back unrecorded delta
- return
-
-
-
- # Dispatch routine for best timer program (return = scalar integer)
-
- def trace_dispatch_i(self, frame, event, arg):
- t = self.timer() - self.t # - 1 # Integer calibration constant
- if self.dispatch[event](frame,t):
- self.t = self.timer()
- else:
- self.t = self.timer() - t # put back unrecorded delta
- return
-
- # Dispatch routine for macintosh (timer returns time in ticks of 1/60th second)
-
- def trace_dispatch_mac(self, frame, event, arg):
- t = self.timer()/60.0 - self.t # - 1 # Integer calibration constant
- if self.dispatch[event](frame,t):
- self.t = self.timer()/60.0
- else:
- self.t = self.timer()/60.0 - t # put back unrecorded delta
- return
-
-
- # SLOW generic dispatch rountine for timer returning lists of numbers
-
- def trace_dispatch_l(self, frame, event, arg):
- t = self.get_time() - self.t
-
- if self.dispatch[event](frame,t):
- self.t = self.get_time()
- else:
- self.t = self.get_time()-t # put back unrecorded delta
- return
-
-
- def trace_dispatch_exception(self, frame, t):
- rt, rtt, rct, rfn, rframe, rcur = self.cur
- if (not rframe is frame) and rcur:
- return self.trace_dispatch_return(rframe, t)
- return 0
-
-
- def trace_dispatch_call(self, frame, t):
- fcode = frame.f_code
- fn = (fcode.co_filename, fcode.co_firstlineno, fcode.co_name)
- self.cur = (t, 0, 0, fn, frame, self.cur)
- if self.timings.has_key(fn):
- cc, ns, tt, ct, callers = self.timings[fn]
- self.timings[fn] = cc, ns + 1, tt, ct, callers
- else:
- self.timings[fn] = 0, 0, 0, 0, {}
- return 1
-
- def trace_dispatch_return(self, frame, t):
- # if not frame is self.cur[-2]: raise "Bad return", self.cur[3]
-
- # Prefix "r" means part of the Returning or exiting frame
- # Prefix "p" means part of the Previous or older frame
-
- rt, rtt, rct, rfn, frame, rcur = self.cur
- rtt = rtt + t
- sft = rtt + rct
-
- pt, ptt, pct, pfn, pframe, pcur = rcur
- self.cur = pt, ptt+rt, pct+sft, pfn, pframe, pcur
-
- cc, ns, tt, ct, callers = self.timings[rfn]
- if not ns:
- ct = ct + sft
- cc = cc + 1
- if callers.has_key(pfn):
- 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
- self.timings[rfn] = cc, ns - 1, tt+rtt, ct, callers
-
- return 1
-
- # The next few function play with self.cmd. By carefully preloading
- # our paralell 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)
- a = self.dispatch['call'](frame, 0)
- return
-
- # collect stats from pending stack, including getting final
- # timings for self.cmd frame.
-
- def simulate_cmd_complete(self):
- t = self.get_time() - self.t
- while self.cur[-1]:
- # We *can* cause assertion errors here if
- # dispatch_trace_return checks for a frame match!
- a = self.dispatch['return'](self.cur[-2], t)
- t = 0
- self.t = self.get_time() - t
-
-
- def print_stats(self):
- import pstats
- pstats.Stats(self).strip_dirs().sort_stats(-1). \
- 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 in self.timings.keys():
- cc, ns, tt, ct, callers = self.timings[func]
- callers = callers.copy()
- nc = 0
- for func_caller in callers.keys():
- nc = nc + callers[func_caller]
- 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):
- self.set_cmd(`func`)
- sys.setprofile(self.dispatcher)
- try:
- return apply(func, args)
- 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 recieves 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. The result can the be placed in the
- # Profile.dispatch_event() routine for the given platform. 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). Currintly, 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.)
- #
- # Plugging in the calibration constant doesn't slow down the
- # profiler very much, and the accuracy goes way up.
- #**************************************************************
-
- def calibrate(self, m):
- # Modified by Tim Peters
- n = m
- s = self.get_time()
- while n:
- self.simple()
- n = n - 1
- f = self.get_time()
- my_simple = f - s
- #print "Simple =", my_simple,
-
- n = m
- s = self.get_time()
- while n:
- self.instrumented()
- n = n - 1
- f = self.get_time()
- my_inst = f - s
- # print "Instrumented =", my_inst
- avg_cost = (my_inst - my_simple)/m
- #print "Delta/call =", avg_cost, "(profiler fixup constant)"
- return avg_cost
-
- # simulate a program with no profiler activity
- def simple(self):
- a = 1
- pass
-
- # simulate a program with call/return event processing
- def instrumented(self):
- a = 1
- self.profiler_simulation(a, a, a)
-
- # simulate an event processing activity (from user's perspective)
- def profiler_simulation(self, x, y, z):
- t = self.timer()
- ## t = t[0] + t[1]
- self.ut = t
-
-
-
- #****************************************************************************
- # OldProfile class documentation
- #****************************************************************************
- #
- # The following derived profiler simulates the old style profile, providing
- # errant results on recursive functions. The reason for the usefulnes of this
- # profiler is that it runs faster (i.e., less overhead). It still creates
- # all the caller stats, and is quite useful when there is *no* recursion
- # in the user's code.
- #
- # This code also shows how easy it is to create a modified profiler.
- #****************************************************************************
- class OldProfile(Profile):
- def trace_dispatch_exception(self, frame, t):
- rt, rtt, rct, rfn, rframe, rcur = self.cur
- if rcur and not rframe is frame:
- return self.trace_dispatch_return(rframe, t)
- return 0
-
- def trace_dispatch_call(self, frame, t):
- fn = `frame.f_code`
-
- self.cur = (t, 0, 0, fn, frame, self.cur)
- if self.timings.has_key(fn):
- tt, ct, callers = self.timings[fn]
- self.timings[fn] = tt, ct, callers
- else:
- self.timings[fn] = 0, 0, {}
- return 1
-
- def trace_dispatch_return(self, frame, t):
- rt, rtt, rct, rfn, frame, rcur = self.cur
- rtt = rtt + t
- sft = rtt + rct
-
- pt, ptt, pct, pfn, pframe, pcur = rcur
- self.cur = pt, ptt+rt, pct+sft, pfn, pframe, pcur
-
- tt, ct, callers = self.timings[rfn]
- if callers.has_key(pfn):
- callers[pfn] = callers[pfn] + 1
- else:
- callers[pfn] = 1
- self.timings[rfn] = tt+rtt, ct + sft, callers
-
- return 1
-
-
- def snapshot_stats(self):
- self.stats = {}
- for func in self.timings.keys():
- tt, ct, callers = self.timings[func]
- callers = callers.copy()
- nc = 0
- for func_caller in callers.keys():
- nc = nc + callers[func_caller]
- self.stats[func] = nc, nc, tt, ct, callers
-
-
-
- #****************************************************************************
- # HotProfile class documentation
- #****************************************************************************
- #
- # This profiler is the fastest derived profile example. It does not
- # calculate caller-callee relationships, and does not calculate cumulative
- # time under a function. It only calculates time spent in a function, so
- # it runs very quickly (re: very low overhead)
- #****************************************************************************
- class HotProfile(Profile):
- def trace_dispatch_exception(self, frame, t):
- rt, rtt, rfn, rframe, rcur = self.cur
- if rcur and not rframe is frame:
- return self.trace_dispatch_return(rframe, t)
- return 0
-
- def trace_dispatch_call(self, frame, t):
- self.cur = (t, 0, frame, self.cur)
- return 1
-
- def trace_dispatch_return(self, frame, t):
- rt, rtt, frame, rcur = self.cur
-
- rfn = `frame.f_code`
-
- pt, ptt, pframe, pcur = rcur
- self.cur = pt, ptt+rt, pframe, pcur
-
- if self.timings.has_key(rfn):
- nc, tt = self.timings[rfn]
- self.timings[rfn] = nc + 1, rt + rtt + tt
- else:
- self.timings[rfn] = 1, rt + rtt
-
- return 1
-
-
- def snapshot_stats(self):
- self.stats = {}
- for func in self.timings.keys():
- nc, tt = self.timings[func]
- self.stats[func] = nc, nc, tt, 0, {}
-
-
-
- #****************************************************************************
- def Stats(*args):
- print 'Report generating functions are in the "pstats" module\a'
-
-
- # When invoked as main program, invoke the profiler on a script
- if __name__ == '__main__':
- import sys
- import os
- if not sys.argv[1:]:
- print "usage: profile.py scriptfile [arg] ..."
- sys.exit(2)
-
- filename = sys.argv[1] # Get script filename
-
- del sys.argv[0] # Hide "profile.py" from argument list
-
- # Insert script directory in front of module search path
- sys.path.insert(0, os.path.dirname(filename))
-
- run('execfile(' + `filename` + ')')
-