diff options
| author | jhugunin <jhugunin> | 2003-01-03 23:19:47 +0000 |
|---|---|---|
| committer | jhugunin <jhugunin> | 2003-01-03 23:19:47 +0000 |
| commit | 8ec8f0c0c6c68d9b13c3bc3416c3234eddd48379 (patch) | |
| tree | 8a2e07ba2a0048aae570053e019e02bd093f175f /lib/jython/Lib/profile.py | |
| parent | f685f979a4d3eb3844f74850deece1da265bc975 (diff) | |
| download | aspectj-8ec8f0c0c6c68d9b13c3bc3416c3234eddd48379.tar.gz aspectj-8ec8f0c0c6c68d9b13c3bc3416c3234eddd48379.zip | |
making jython-2.1 available for scripting
Diffstat (limited to 'lib/jython/Lib/profile.py')
| -rw-r--r-- | lib/jython/Lib/profile.py | 580 |
1 files changed, 580 insertions, 0 deletions
diff --git a/lib/jython/Lib/profile.py b/lib/jython/Lib/profile.py new file mode 100644 index 000000000..8a502e67c --- /dev/null +++ b/lib/jython/Lib/profile.py @@ -0,0 +1,580 @@ +#! /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
+
+"""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
+
+__all__ = ["run","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):
+ """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()
+
+# 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:
+ """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.
+
+ [ 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
+ [ 2] = Cumulative time spent in this frame's function, including time in
+ all subfunctions to this frame.
+ [-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[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.
+ """
+
+ 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 routine 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 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)
+ 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 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. 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). 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.)
+ #
+ # 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
+
+
+
+class OldProfile(Profile):
+ """A derived profiler that simulates the old style profile, providing
+ errant results on recursive functions. The reason for the usefulness 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.
+ """
+
+ 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
+
+
+
+class HotProfile(Profile):
+ """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 due to its very low overhead.
+ """
+
+ 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` + ')')
|