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214 lines
7.4 KiB
Python
Executable File
214 lines
7.4 KiB
Python
Executable File
from pandac.libpandaexpressModules import TrueClock
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from direct.showbase.PythonUtil import (
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StdoutCapture, _installProfileCustomFuncs,_removeProfileCustomFuncs,
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_profileWithoutGarbageLeak, _getProfileResultFileInfo, _setProfileResultsFileInfo,
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_clearProfileResultFileInfo, )
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import __builtin__
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import profile
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import pstats
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from StringIO import StringIO
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import marshal
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class ProfileSession:
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# class that encapsulates a profile of a single callable using Python's standard
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# 'profile' module
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#
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# defers formatting of profile results until they are requested
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#
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# implementation sidesteps memory leak in Python profile module,
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# and redirects file output to RAM file for efficiency
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DefaultFilename = 'profilesession'
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DefaultLines = 80
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DefaultSorts = ['cumulative', 'time', 'calls']
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TrueClock = TrueClock.getGlobalPtr()
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def __init__(self, func, name):
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self._func = func
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self._name = name
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self._filenameBase = 'profileData-%s-%s' % (self._name, id(self))
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self._refCount = 0
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self._reset()
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self.acquire()
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def acquire(self):
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self._refCount += 1
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def release(self):
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self._refCount -= 1
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if not self._refCount:
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self._destroy()
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def _destroy(self):
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del self._func
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del self._name
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del self._filenameBase
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del self._filenameCounter
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del self._filenames
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del self._duration
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del self._filename2ramFile
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del self._resultCache
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del self._successfulProfiles
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def _reset(self):
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self._filenameCounter = 0
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self._filenames = []
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# index of next file to be added to stats object
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self._statFileCounter = 0
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self._successfulProfiles = 0
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self._duration = None
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self._filename2ramFile = {}
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self._stats = None
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self._resultCache = {}
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def _getNextFilename(self):
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filename = '%s-%s' % (self._filenameBase, self._filenameCounter)
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self._filenameCounter += 1
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return filename
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def run(self, aggregate=True):
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# make sure this instance doesn't get destroyed inside self._func
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self.acquire()
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if not aggregate:
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self._reset()
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# if we're already profiling, just run the func and don't profile
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if 'globalProfileFunc' in __builtin__.__dict__:
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result = self._func()
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if self._duration is None:
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self._duration = 0.
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else:
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# put the function in the global namespace so that profile can find it
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__builtin__.globalProfileFunc = self._func
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__builtin__.globalProfileResult = [None]
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# set up the RAM file
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self._filenames.append(self._getNextFilename())
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filename = self._filenames[-1]
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_installProfileCustomFuncs(filename)
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# do the profiling
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Profile = profile.Profile
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statement = 'globalProfileResult[0]=globalProfileFunc()'
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sort = -1
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retVal = None
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# this is based on profile.run, the code is replicated here to allow us to
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# eliminate a memory leak
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prof = Profile()
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try:
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prof = prof.run(statement)
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except SystemExit:
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pass
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# this has to be run immediately after profiling for the timings to be accurate
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# tell the Profile object to generate output to the RAM file
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prof.dump_stats(filename)
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# eliminate the memory leak
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del prof.dispatcher
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# store the RAM file for later
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profData = _getProfileResultFileInfo(filename)
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self._filename2ramFile[filename] = profData
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# calculate the duration (this is dependent on the internal Python profile data format.
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# see profile.py and pstats.py, this was copied from pstats.Stats.strip_dirs)
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maxTime = 0.
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for cc, nc, tt, ct, callers in profData[1].itervalues():
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if ct > maxTime:
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maxTime = ct
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self._duration = maxTime
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# clean up the RAM file support
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_removeProfileCustomFuncs(filename)
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# clean up the globals
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result = globalProfileResult[0]
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del __builtin__.__dict__['globalProfileFunc']
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del __builtin__.__dict__['globalProfileResult']
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self._successfulProfiles += 1
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self.release()
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return result
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def getDuration(self):
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return self._duration
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def profileSucceeded(self):
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return self._successfulProfiles > 0
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def _restoreRamFile(self, filename):
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# set up the RAM file
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_installProfileCustomFuncs(filename)
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# install the stored RAM file from self.run()
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_setProfileResultsFileInfo(filename, self._filename2ramFile[filename])
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def _discardRamFile(self, filename):
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# take down the RAM file
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_removeProfileCustomFuncs(filename)
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# and discard it
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del self._filename2ramFile[filename]
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def getResults(self,
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lines=80,
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sorts=['cumulative', 'time', 'calls'],
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callInfo=False):
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if not self.profileSucceeded():
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output = '%s: profiler already running, could not profile' % self._name
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else:
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# make sure our stats object exists and is up-to-date
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statsChanged = (self._statFileCounter < len(self._filenames))
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if self._stats is None:
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for filename in self._filenames:
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self._restoreRamFile(filename)
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self._stats = pstats.Stats(*self._filenames)
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self._statFileCounter = len(self._filenames)
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for filename in self._filenames:
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self._discardRamFile(filename)
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else:
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while self._statFileCounter < len(self._filenames):
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filename = self._filenames[self._statFileCounter]
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self._restoreRamFile(filename)
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self._stats.add(filename)
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self._discardRamFile(filename)
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if statsChanged:
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self._stats.strip_dirs()
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# throw out any cached result strings
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self._resultCache = {}
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# make sure the arguments will hash efficiently if callers provide different types
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lines = int(lines)
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sorts = list(sorts)
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callInfo = bool(callInfo)
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k = str((lines, sorts, callInfo))
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if k in self._resultCache:
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# we've already created this output string, get it from the cache
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output = self._resultCache[k]
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else:
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# now get human-readable output from the profile stats
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# capture print output to a string
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sc = StdoutCapture()
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# print the info to stdout
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s = self._stats
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for sort in sorts:
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s.sort_stats(sort)
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s.print_stats(lines)
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if callInfo:
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s.print_callees(lines)
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s.print_callers(lines)
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# make a copy of the print output
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output = sc.getString()
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# restore stdout to what it was before
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sc.destroy()
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# cache this result
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self._resultCache[k] = output
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return output
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