# -*- coding: iso-8859-1 -*-
-# Copyright (C) 2007-2023 CEA, EDF, OPEN CASCADE
+# Copyright (C) 2007-2024 CEA, EDF, OPEN CASCADE
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
import SALOME__POA
import SALOME
import logging
+import abc
import os
import sys
from SALOME_ContainerHelper import ScriptExecInfo
MY_CONTAINER_ENTRY_IN_GLBS = "my_container"
+MY_PERFORMANCE_LOG_ENTRY_IN_GLBS = "my_log_4_this_session"
+
class Generic(SALOME__POA.GenericObj):
"""A Python implementation of the GenericObj CORBA IDL"""
def __init__(self,poa):
# default is 50 MB
SALOME_BIG_OBJ_ON_DISK_THRES_DFT = 50000000
-from ctypes import c_int
-TypeCounter = c_int
-
-def GetSizeOfTCnt():
- return len( bytes(TypeCounter(0) ) )
+DicoForProxyFile = { }
def GetSizeOfBufferedReader(f):
"""
def GetObjectFromFile(fname, visitor = None):
with open(fname,"rb") as f:
- cntb = f.read( GetSizeOfTCnt() )
- cnt = TypeCounter.from_buffer_copy( cntb ).value
if visitor:
visitor.setHDDMem( GetSizeOfBufferedReader(f) )
visitor.setFileName( fname )
obj = pickle.load(f)
- return obj,cnt
+ return obj
def DumpInFile(obj,fname):
with open(fname,"wb") as f:
- f.write( bytes( TypeCounter(1) ) )
f.write( obj )
def IncrRefInFile(fname):
- with open(fname,"rb") as f:
- cntb = f.read( GetSizeOfTCnt() )
- cnt = TypeCounter.from_buffer_copy( cntb ).value
- with open(fname,"rb+") as f:
- #import KernelServices ; KernelServices.EntryForDebuggerBreakPoint()
- f.write( bytes( TypeCounter(cnt+1) ) )
+ if fname in DicoForProxyFile:
+ DicoForProxyFile[fname] += 1
+ else:
+ DicoForProxyFile[fname] = 2
+ pass
def DecrRefInFile(fname):
- import os
- with open(fname,"rb") as f:
- cntb = f.read( GetSizeOfTCnt() )
- cnt = TypeCounter.from_buffer_copy( cntb ).value
- #
- #import KernelServices ; KernelServices.EntryForDebuggerBreakPoint()
- if cnt == 1:
- os.unlink( fname )
+ if fname not in DicoForProxyFile:
+ cnt = 1
else:
- with open(fname,"rb+") as f:
- f.write( bytes( TypeCounter(cnt-1) ) )
+ cnt = DicoForProxyFile[fname]
+ DicoForProxyFile[fname] -= 1
+ if cnt == 1:
+ del DicoForProxyFile[fname]
+ if cnt == 1:
+ if os.path.exists(fname):
+ os.unlink( fname )
+ pass
def GetBigObjectOnDiskThreshold():
import os
DumpInFile( objSerialized, self._filename )
def get(self, visitor = None):
- obj, _ = GetObjectFromFile( self._filename, visitor )
+ obj = GetObjectFromFile( self._filename, visitor )
return obj
def __float__(self):
else:
return obj
-class FileDeleter:
+class FileHolder:
def __init__(self, fileName):
self._filename = fileName
@property
def filename(self):
return self._filename
+
+class FileDeleter(FileHolder):
+ def __init__(self, fileName):
+ super().__init__( fileName )
def __del__(self):
import os
if os.path.exists( self._filename ):
os.unlink( self._filename )
-def LaunchMonitoring( intervalInMs ):
+class MonitoringInfo:
+ def __init__(self, pyFileName, intervalInMs, outFileName, pid):
+ self._py_file_name = pyFileName
+ self._interval_in_ms = intervalInMs
+ self._out_file_name = outFileName
+ self._pid = pid
+
+ @property
+ def pyFileName(self):
+ return self._py_file_name
+
+ @property
+ def pid(self):
+ return self._pid
+
+ @pid.setter
+ def pid(self, value):
+ self._pid = value
+
+ @property
+ def outFileName(self):
+ return self._out_file_name
+
+ @property
+ def intervalInMs(self):
+ return self._interval_in_ms
+
+def FileSystemMonitoring(intervalInMs, dirNameToInspect, outFileName = None):
+ """
+ This method loops indefinitely every intervalInMs milliseconds to scan
+ number of inodes and size of content recursively included into the in input directory.
+
+ Args:
+ ----
+
+ outFileName (str) : name of file inside the results will be written. If None a new file is generated
+
+ See also CPUMemoryMonitoring
+ """
+ global orb
+ import os
+ dirNameToInspect2 = os.path.abspath( os.path.expanduser(dirNameToInspect) )
+ import tempfile
+ import logging
+ import KernelBasis
+ # outFileNameSave stores the content of outFileName during phase of dumping
+ with tempfile.NamedTemporaryFile(prefix="fs_monitor_",suffix=".txt") as f:
+ outFileNameSave = f.name
+ with tempfile.NamedTemporaryFile(prefix="fs_monitor_",suffix=".py") as f:
+ tempPyFile = f.name
+ tempOutFile = outFileName
+ if tempOutFile is None:
+ tempOutFile = "{}.txt".format( os.path.splitext( tempPyFile )[0] )
+ with open(tempPyFile,"w") as f:
+ f.write("""
+import subprocess as sp
+import re
+import os
+import time
+import datetime
+with open("{tempOutFile}","a") as f:
+ f.write( "{{}}\\n".format( "{dirNameToInspect2}" ) )
+ f.write( "{{}}\\n".format( "{intervalInMs}" ) )
+ while(True):
+ nbinodes = -1
+ try:
+ nbinodes = sp.check_output("{{}} | wc -l".format( " ".join(["find","{dirNameToInspect2}"]), ), shell = True).decode().strip()
+ except:
+ pass
+ szOfDirStr = "fail"
+ try:
+ st = sp.check_output(["du","-sh","{dirNameToInspect2}"]).decode()
+ szOfDirStr = re.split("[\s]+",st)[0]
+ except:
+ pass
+ f.write( "{{}}\\n".format( str( datetime.datetime.now().timestamp() ) ) )
+ f.write( "{{}}\\n".format( str( nbinodes ) ) )
+ f.write( "{{}}\\n".format( str( szOfDirStr ) ) )
+ f.flush()
+ time.sleep( {intervalInMs} / 1000.0 )
+""".format( **locals()))
+ logging.debug( "File for FS monitoring dump file : {}".format(tempPyFile) )
+ pyFileName = FileDeleter( tempPyFile )
+ if outFileName is None:
+ outFileName = FileDeleter( tempOutFile )
+ else:
+ outFileName = FileHolder(outFileName)
+ return MonitoringInfo(pyFileName, intervalInMs, outFileName, None)
+
+def CPUMemoryMonitoring( intervalInMs, outFileName = None ):
"""
Launch a subprocess monitoring self process.
This monitoring subprocess is a python process lauching every intervalInMs ms evaluation of
- CPU usage and RSS memory.
+ CPU usage and RSS memory of the calling process.
Communication between subprocess and self is done by file.
+
+ Args:
+ ----
+ outFileName (str) : name of file inside the results will be written. If None a new file is generated
+
+ See also FileSystemMonitoring
"""
import KernelBasis
- def BuildPythonFileForCPUPercent( intervalInMs ):
+ def BuildPythonFileForCPUPercent( intervalInMs, outFileName):
import os
import tempfile
- with tempfile.NamedTemporaryFile(prefix="htop_",suffix=".py") as f:
+ with tempfile.NamedTemporaryFile(prefix="cpu_mem_monitor_",suffix=".py") as f:
tempPyFile = f.name
- tempOutFile = "{}.txt".format( os.path.splitext( tempPyFile )[0] )
+ tempOutFile = outFileName
+ if tempOutFile is None:
+ tempOutFile = "{}.txt".format( os.path.splitext( tempPyFile )[0] )
pid = os.getpid()
with open(tempPyFile,"w") as f:
f.write("""import psutil
process = psutil.Process( pid )
import time
with open("{}","a") as f:
+ f.write( "{{}}\\n".format( "{}" ) )
while True:
f.write( "{{}}\\n".format( str( process.cpu_percent() ) ) )
f.write( "{{}}\\n".format( str( process.memory_info().rss ) ) )
f.flush()
time.sleep( {} / 1000.0 )
-""".format(pid, tempOutFile, intervalInMs))
- return FileDeleter(tempPyFile), FileDeleter(tempOutFile)
- pyFileName, outFileName = BuildPythonFileForCPUPercent( intervalInMs )
- KernelBasis.LaunchMonitoring(pyFileName.filename,outFileName.filename)
- return pyFileName, outFileName
+""".format(pid, tempOutFile, intervalInMs, intervalInMs))
+ if outFileName is None:
+ autoOutFile = FileDeleter(tempOutFile)
+ else:
+ autoOutFile = FileHolder(tempOutFile)
+ return FileDeleter(tempPyFile),autoOutFile
+ pyFileName, outFileName = BuildPythonFileForCPUPercent( intervalInMs, outFileName )
+ return MonitoringInfo(pyFileName, intervalInMs, outFileName, None)
+
+class GenericPythonMonitoringLauncherCtxMgr:
+ def __init__(self, monitoringParams):
+ """
+ Args:
+ ----
+ monitoringParams (MonitoringInfo)
+ """
+ self._monitoring_params = monitoringParams
+ def __enter__(self):
+ import KernelBasis
+ pid = KernelBasis.LaunchMonitoring(self._monitoring_params.pyFileName.filename)
+ self._monitoring_params.pid = pid
+ return self._monitoring_params
+
+ def __exit__(self,exctype, exc, tb):
+ StopMonitoring( self._monitoring_params )
+
+def StopMonitoring( monitoringInfo ):
+ """
+ Kill monitoring subprocess.
-def StopMonitoring( ):
+ Args:
+ ----
+ monitoringInfo (MonitoringInfo): info returned by LaunchMonitoring
"""
- Retrieve data of monitoring and kill monitoring subprocess.
+ import KernelBasis
+ KernelBasis.StopMonitoring(monitoringInfo.pid)
+
+class CPUMemInfo:
+ def __init__(self, intervalInMs, cpu, mem_rss):
+ """
+ Args:
+ ----
+ intervalInMs (int)
+ cpu (list<float>) CPU usage
+ mem_rss (list<int>) rss memory usage
+ """
+ self._interval_in_ms = intervalInMs
+ self._data = [(a,b) for a,b in zip(cpu,mem_rss)]
+ def __str__(self):
+ st = """Interval in ms : {self.intervalInMs}
+Data : ${self.data}
+""".format( **locals() )
+ return st
+ @property
+ def intervalInMs(self):
+ return self._interval_in_ms
+ @property
+ def data(self):
+ """
+ list of triplets. First param of pair is cpu usage
+ Second param of pair is memory usage
+ """
+ return self._data
+
+def ReadCPUMemInfoInternal( fileName ):
+ intervalInMs = 0
+ cpu = [] ; mem_rss = []
+ if os.path.exists( fileName ):
+ try:
+ with open(fileName, "r") as f:
+ coarseData = [ elt.strip() for elt in f.readlines() ]
+ intervalInMs = int( coarseData[0] )
+ coarseData = coarseData[1:]
+ cpu = [float(elt) for elt in coarseData[::2]]
+ mem_rss = [ int(elt) for elt in coarseData[1::2]]
+ except:
+ pass
+ return CPUMemInfo(intervalInMs,cpu,mem_rss)
+
+def ReadCPUMemInfo( monitoringInfo ):
+ """
+ Retrieve CPU/Mem data of monitoring.
+
+ Args:
+ ----
+ monitoringInfo (MonitoringInfo): info returned by LaunchMonitoring
Returns
-------
- list<float,str> : list of pairs. First param of pair is CPU usage. Second param of pair is rss memory usage
+ CPUMemInfo instance
"""
- import KernelBasis
- ret = KernelBasis.StopMonitoring()
- cpu = ret[::2]
- mem_rss = [ int(elt) for elt in ret[1::2]]
- return [(a,b) for a,b in zip(cpu,mem_rss)]
+ return ReadCPUMemInfoInternal( monitoringInfo.outFileName.filename )
+
+class InodeSizeInfo:
+ def __init__(self, dirNameMonitored, intervalInMs, timeStamps, nbInodes, volumeOfDir):
+ """
+ Args:
+ ----
+ timeStamps (list<datetimestruct>)
+ nbInodes (list<int>)
+ volumeOfDir (list<str>)
+ """
+ self._dir_name_monitored = dirNameMonitored
+ self._interval_in_ms = intervalInMs
+ self._data = [(t,a,b) for t,a,b in zip(timeStamps,nbInodes,volumeOfDir)]
+ def __str__(self):
+ st = """Filename monitored : {self.dirNameMonitored}
+Interval in ms : ${self.intervalInMs}
+Data : ${self.data}
+""".format( **locals() )
+ return st
+ @property
+ def dirNameMonitored(self):
+ return self._dir_name_monitored
+ @property
+ def intervalInMs(self):
+ return self._interval_in_ms
+ @property
+ def data(self):
+ """
+ list of triplets. First param of triplet is datetimestruct
+ Second param of triplet is #inodes.
+ Thirst param of triplet is size.
+ """
+ return self._data
+
+def ReadInodeSizeInfoInternal( fileName ):
+ import datetime
+ import os
+ with open(fileName, "r") as f:
+ coarseData = [ elt.strip() for elt in f.readlines() ]
+ dirNameMonitored = coarseData[0] ; intervalInMs = int( coarseData[1] ) ; coarseData = coarseData[2:]
+ tss = [ datetime.datetime.fromtimestamp( float(elt) ) for elt in coarseData[::3] ]
+ nbInodes = [int(elt) for elt in coarseData[1::3]]
+ volumeOfDir = coarseData[2::3]
+ return InodeSizeInfo(dirNameMonitored,intervalInMs,tss,nbInodes,volumeOfDir)
+
+def ReadInodeSizeInfo( monitoringInfo ):
+ """
+ Retrieve nb of inodes and size of monitoring
+
+ Args:
+ ----
+ monitoringInfo (MonitoringInfo): info returned by LaunchMonitoring
+
+ Returns
+ -------
+ InodeSizeInfo
+ """
+ return ReadInodeSizeInfoInternal( monitoringInfo.outFileName.filename )
class SeqByteReceiver:
# 2GB limit to trigger split into chunks
data_for_split_case = bytes(0).join( [data_for_split_case,part] )
iStart = iEnd; iEnd = min(iStart + EFF_CHUNK_SIZE,size)
return data_for_split_case
+
+FinalCode = """import pickle
+from SALOME_PyNode import LogOfCurrentExecutionSession,MY_PERFORMANCE_LOG_ENTRY_IN_GLBS
+import CORBA
+import Engines
+orb = CORBA.ORB_init([''])
+codeFileName = "{}"
+inputFileName = "{}"
+outputFileName = "{}"
+outputsKeys = {}
+exec( "{{}} = LogOfCurrentExecutionSession( orb.string_to_object( \\"{}\\" ) )".format(MY_PERFORMANCE_LOG_ENTRY_IN_GLBS) )
+with open(inputFileName,"rb") as f:
+ context = pickle.load( f )
+context[MY_PERFORMANCE_LOG_ENTRY_IN_GLBS] = eval( MY_PERFORMANCE_LOG_ENTRY_IN_GLBS )
+with open(codeFileName,"r") as f:
+ code = f.read()
+# go for execution
+exec( code , context )
+# filter part of context to be exported to father process
+context = dict( [(k,v) for k,v in context.items() if k in outputsKeys] )
+#
+with open(outputFileName,"wb") as f:
+ pickle.dump( context, f )
+"""
+
+class PythonFunctionEvaluatorParams:
+ def __init__(self, mainFileName, codeFileName, inContextFileName, outContextFileName):
+ self._main_filename = mainFileName
+ self._code_filename = codeFileName
+ self._in_context_filename = inContextFileName
+ self._out_context_filename = outContextFileName
+ @property
+ def result(self):
+ import pickle
+ with open(self._out_context_filename,"rb") as f:
+ return pickle.load( f )
+ def destroyOnOK(self):
+ for fileToDestroy in [self._main_filename,self._code_filename,self._in_context_filename,self._out_context_filename]:
+ if os.path.exists( fileToDestroy ):
+ os.unlink( fileToDestroy )
+ def destroyOnKO(self, containerRef):
+ """
+ Called in the context of failure with replay mode activated
+ """
+ for fileToDestroy in [self._out_context_filename]:
+ if os.path.exists( fileToDestroy ):
+ os.unlink( fileToDestroy )
+ # register to container files group associated to the
+ containerRef.addLogFileNameGroup([self._main_filename,self._code_filename,self._in_context_filename])
+ @property
+ def replayCmd(self):
+ return "To replay : ( cd {} && python3 {} )".format(os.path.dirname(self._main_filename),os.path.basename(self._main_filename))
+
+ @property
+ def cleanOperations(self):
+ import os
+ return "To clean files : ( cd {} && rm {} )".format( os.path.dirname(self._main_filename)," ".join( [os.path.basename(self._main_filename),self._code_filename,self._in_context_filename] ) )
-class LogOfCurrentExecutionSession:
- def __init__(self, handleToCentralizedInst):
- self._remote_handle = handleToCentralizedInst
+ def strDependingOnReturnCode(self, keepFilesToReplay, returnCode):
+ if returnCode == -1:
+ return f"return with non zero code ({returnCode})"
+ else:
+ banner = 200*"*"
+ if keepFilesToReplay:
+ return f"""return with non zero code ({returnCode})
+{banner}
+Looks like a hard crash as returnCode {returnCode} != 0
+{self.replayCmd}
+{self.cleanOperations}
+{banner}
+"""
+ else:
+ return f"""return with non zero code ({returnCode})
+{banner}
+Looks like a hard crash as returnCode {returnCode} != 0
+{banner}
+"""
+
+def ExecCrashProofGeneric( code, context, outargsname, containerRef, instanceOfLogOfCurrentSession, keepFilesToReplay ):
+ """
+ Equivalent of exec(code,context) but executed in a separate subprocess to avoid to make the current process crash.
+
+ Args:
+ -----
+
+ code (str) : python code to be executed using context
+ context (dict) : context to be used for execution. This context will be updated in accordance with the execution of code.
+ outargsname (list<str>) : list of arguments to be exported
+ containerRef (Engines.Container) : Container ref (retrieving the Files to created when keepFilesToReplay is set to False)
+ instanceOfLogOfCurrentSession (LogOfCurrentExecutionSession) : instance of LogOfCurrentExecutionSession to build remotely the reference in order to log information
+ keepFilesToReplay (bool) : if True when something goes wrong during execution all the files to replay post mortem case are kept. If False only error is reported but files to replay are destoyed.
+
+ Return:
+ -------
+
+ ScriptExecInfo : instance serverside
+
+ In/Out:
+ -------
+
+ context will be modified by this method. elts in outargsname will be added and their corresponding value coming from evaluation.
+ """
+ import tempfile
+ import pickle
+ import subprocess as sp
+ import CORBA
+ #
+ def InternalExecResistant( code, context, outargsname):
+ orb = CORBA.ORB_init([''])
+ iorScriptLog = orb.object_to_string( instanceOfLogOfCurrentSession._remote_handle )#ref ContainerScriptPerfLog_ptr
+ ####
+ EXEC_CODE_FNAME_PXF = "execsafe_"
+ def RetrieveUniquePartFromPfx( fname ):
+ return os.path.splitext( os.path.basename(fname)[len(EXEC_CODE_FNAME_PXF):] )[0]
+ with tempfile.NamedTemporaryFile(dir=os.getcwd(),prefix=EXEC_CODE_FNAME_PXF,suffix=".py", mode="w", delete = False) as codeFd:
+ codeFd.write( code )
+ codeFd.flush()
+ codeFileName = os.path.basename( codeFd.name )
+ contextFileName = "contextsafe_{}.pckl".format( RetrieveUniquePartFromPfx( codeFileName ) )
+ with open(contextFileName,"wb") as contextFd:
+ pickle.dump( context, contextFd)
+ resFileName = "outcontextsafe_{}.pckl".format( RetrieveUniquePartFromPfx( codeFileName ) )
+ mainExecFileName = os.path.abspath( "mainexecsafe_{}.py".format( RetrieveUniquePartFromPfx( codeFileName ) ) )
+ with open(mainExecFileName,"w") as f:
+ f.write( FinalCode.format( codeFileName, contextFileName, resFileName, outargsname, iorScriptLog ) )
+ p = sp.Popen(["python3", mainExecFileName],stdout = sp.PIPE, stderr = sp.PIPE)
+ stdout, stderr = p.communicate()
+ returnCode = p.returncode
+ return returnCode, stdout, stderr, PythonFunctionEvaluatorParams(mainExecFileName,codeFileName,contextFileName,resFileName)
+ ret = instanceOfLogOfCurrentSession._current_instance
+ returnCode, stdout, stderr, evParams = InternalExecResistant( code, context, outargsname )
+ stdout = stdout.decode()
+ stderr = stderr.decode()
+ sys.stdout.write( stdout ) ; sys.stdout.flush()
+ sys.stderr.write( stderr ) ; sys.stderr.flush()
+ if returnCode == 0:
+ pcklData = instanceOfLogOfCurrentSession._remote_handle.getObj()
+ if len(pcklData) > 0:
+ ret = pickle.loads( pcklData )
+ context.update( evParams.result )
+ evParams.destroyOnOK()
+ return ret
+ if returnCode != 0:
+ if keepFilesToReplay:
+ evParams.destroyOnKO( containerRef )
+ else:
+ evParams.destroyOnOK()
+ raise RuntimeError(f"Subprocess launched {evParams.strDependingOnReturnCode(keepFilesToReplay,returnCode)}stdout :\n{stdout}\nstderr :\n{stderr}")
+
+def ExecCrashProofWithReplay( code, context, outargsname, containerRef, instanceOfLogOfCurrentSession ):
+ return ExecCrashProofGeneric(code, context, outargsname, containerRef, instanceOfLogOfCurrentSession, True)
+
+def ExecCrashProofWithoutReplay( code, context, outargsname, containerRef, instanceOfLogOfCurrentSession ):
+ return ExecCrashProofGeneric(code, context, outargsname, containerRef, instanceOfLogOfCurrentSession, False)
+
+def ExecLocal( code, context, outargsname, containerRef, instanceOfLogOfCurrentSession ):
+ exec( code, context )
+ return instanceOfLogOfCurrentSession._current_instance
+
+class LogOfCurrentExecutionSessionAbs(abc.ABC):
+ def __init__(self):
self._current_instance = ScriptExecInfo()
def addInfoOnLevel2(self, key, value):
setattr(self._current_instance,key,value)
+ @abc.abstractmethod
+ def addFreestyleAndFlush(self, value):
+ raise RuntimeError("Must be overloaded")
+
+class LogOfCurrentExecutionSession(LogOfCurrentExecutionSessionAbs):
+ def __init__(self, handleToCentralizedInst):
+ super().__init__()
+ self._remote_handle = handleToCentralizedInst
+
+ def addFreestyleAndFlush(self, value):
+ self._current_instance.freestyle = value
+ self.finalizeAndPushToMaster()
+
def finalizeAndPushToMaster(self):
self._remote_handle.assign( pickle.dumps( self._current_instance ) )
-class PyScriptNode_i (Engines__POA.PyScriptNode,Generic):
+class LogOfCurrentExecutionSessionStub(LogOfCurrentExecutionSessionAbs):
+ """
+ This class is to stub LogOfCurrentExecutionSession in context of replay where the server (handleToCentralizedInst) has vanished
+ """
+ def __init__(self, handleToCentralizedInst = None):
+ super().__init__()
+ def addFreestyleAndFlush(self, value):
+ pass
+
+class PyScriptNode_Abstract_i(Engines__POA.PyScriptNode,Generic,abc.ABC):
"""The implementation of the PyScriptNode CORBA IDL that executes a script"""
- def __init__(self, nodeName,code,poa,my_container,logscript):
+ def __init__(self, nodeName, code, poa, my_container, logscript):
"""Initialize the node : compilation in the local context"""
Generic.__init__(self,poa)
self.nodeName=nodeName
self._log_script = logscript
self._current_execution_session = None
sys.stdout.flush() ; sys.stderr.flush() # flush to correctly capture log per execution session
+
+ @abc.abstractmethod
+ def executeNow(self, outargsname):
+ raise RuntimeError("Must be overloaded")
def __del__(self):
# force removal of self.context. Don t know why it s not done by default
def executeFirst(self,argsin):
""" Same than first part of self.execute to reduce memory peak."""
+ def ArgInMananger(self,argsin):
+ argsInPy = SeqByteReceiver( argsin )
+ data = argsInPy.data()
+ self.addInfoOnLevel2("inputMem",len(data))
+ _,kws=pickle.loads(data)
+ return kws
try:
self.beginOfCurrentExecutionSession()
- data = None
self.addTimeInfoOnLevel2("startInputTime")
- if True: # to force call of SeqByteReceiver's destructor
- argsInPy = SeqByteReceiver( argsin )
- data = argsInPy.data()
- self.addInfoOnLevel2("inputMem",len(data))
- _,kws=pickle.loads(data)
+ # to force call of SeqByteReceiver's destructor
+ kws = ArgInMananger(self,argsin)
vis = InOutputObjVisitor()
for elt in kws:
# fetch real data if necessary
self.addTimeInfoOnLevel2("startExecTime")
##
self.addInfoOnLevel2("measureTimeResolution",self.my_container_py.monitoringtimeresms())
- monitoringParams = LaunchMonitoring( self.my_container_py.monitoringtimeresms() )
- exec(self.ccode, self.context)
- cpumeminfo = StopMonitoring( )
+ with GenericPythonMonitoringLauncherCtxMgr( CPUMemoryMonitoring( self.my_container_py.monitoringtimeresms() ) ) as monitoringParams:
+ self._current_execution_session._current_instance = self.executeNow( outargsname )
+ cpumeminfo = ReadCPUMemInfo( monitoringParams )
##
self.addInfoOnLevel2("CPUMemDuringExec",cpumeminfo)
del monitoringParams
def beginOfCurrentExecutionSession(self):
self._current_execution_session = LogOfCurrentExecutionSession( self._log_script.addExecutionSession() )
+ self.context[MY_PERFORMANCE_LOG_ENTRY_IN_GLBS] = self._current_execution_session
def endOfCurrentExecutionSession(self):
self._current_execution_session.finalizeAndPushToMaster()
def addTimeInfoOnLevel2(self, key):
from datetime import datetime
self._current_execution_session.addInfoOnLevel2(key,datetime.now())
+
+class PyScriptNode_i(PyScriptNode_Abstract_i):
+ def __init__(self, nodeName, code, poa, my_container, logscript):
+ super().__init__(nodeName, code, poa, my_container, logscript)
+
+ def executeNow(self, outargsname):
+ return ExecLocal(self.ccode,self.context,outargsname,self.my_container,self._current_execution_session)
+
+class PyScriptNode_OutOfProcess_i(PyScriptNode_Abstract_i):
+ def __init__(self, nodeName, code, poa, my_container, logscript):
+ super().__init__(nodeName, code, poa, my_container, logscript)
+
+ def executeNow(self, outargsname):
+ return ExecCrashProofWithoutReplay(self.code,self.context,outargsname,self.my_container,self._current_execution_session)
+
+class PyScriptNode_OutOfProcess_Replay_i(PyScriptNode_Abstract_i):
+ def __init__(self, nodeName, code, poa, my_container, logscript):
+ super().__init__(nodeName, code, poa, my_container, logscript)
+
+ def executeNow(self, outargsname):
+ return ExecCrashProofWithReplay(self.code,self.context,outargsname,self.my_container,self._current_execution_session)
