""" .. module:: Pfn :synopsis: ProcessPool and related classes ProcessPool ProcessPool creates a pool of worker subprocesses to handle a queue of tasks much like the producers/consumers paradigm. Users just need to fill the queue with tasks to be executed and worker tasks will execute them. To construct ProcessPool one first should call its constructor:: pool = ProcessPool( minSize, maxSize, maxQueuedRequests ) where parameters are: :param int minSize: at least workers will be alive all the time :param int maxSize: no more than workers will be alive all the time :param int maxQueuedRequests: size for request waiting in a queue to be executed In case another request is added to the full queue, the execution will lock until another request is taken out. The ProcessPool will automatically increase and decrease the pool of workers as needed, of course not exceeding above limits. To add a task to the queue one should execute::: pool.createAndQueueTask( funcDef, args = ( arg1, arg2, ... ), kwargs = { "kwarg1" : value1, "kwarg2" : value2 }, callback = callbackDef, exceptionCallback = exceptionCallBackDef ) or alternatively by using ProcessTask instance::: task = ProcessTask( funcDef, args = ( arg1, arg2, ... ) kwargs = { "kwarg1" : value1, .. }, callback = callbackDef, exceptionCallback = exceptionCallbackDef ) pool.queueTask( task ) where parameters are: :param funcDef: callable by object definition (function, lambda, class with __call__ slot defined :param list args: argument list :param dict kwargs: keyword arguments dictionary :param callback: callback function definition :param exceptionCallback: exception callback function definition The callback, exceptionCallbaks and the parameters are all optional. Once task has been added to the pool, it will be executed as soon as possible. Worker subprocesses automatically return the return value of the task. To obtain those results one has to execute:: pool.processRequests() This method will process the existing return values of the task, even if the task does not return anything. This method has to be called to clean the result queues. To wait until all the requests are finished and process their result call:: pool.processAllRequests() This function will block until all requests are finished and their result values have been processed. It is also possible to set the ProcessPool in daemon mode, in which all results are automatically processed as soon they are available, just after finalization of task execution. To enable this mode one has to call:: pool.daemonize() Callback functions There are two types of callbacks that can be executed for each tasks: exception callback function and results callback function. The first one is executed when unhandled exception has been raised during task processing, and hence no task results are available, otherwise the execution of second callback type is performed. The callbacks could be attached in a two places: - directly in ProcessTask, in that case those have to be shelvable/picklable, so they should be defined as global functions with the signature :callback( task, taskResult ): where :task: is a :ProcessTask: reference and :taskResult: is whatever task callable it returning for results callback and :exceptionCallback( task, exc_info): where exc_info is a :S_ERROR( "Exception": { "Value" : exceptionName, "Exc_info" : exceptionInfo ): - in ProcessPool, in that case there is no limitation on the function type, except the signature, which should follow :callback( task ): or :exceptionCallback( task ):, as those callbacks definitions are not put into the queues The first types of callbacks could be used in case various callable objects are put into the ProcessPool, so you probably want to handle them differently depending on their results, while the second types are for executing same type of callables in subprocesses and hence you are expecting the same type of results everywhere. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function __RCSID__ = "c59810311 (2021-10-01 10:44:25 +0200) Chris Burr " import errno import inspect import multiprocessing import os import signal import sys import threading import time import six from six.moves import queue as Queue try: from DIRAC.FrameworkSystem.Client.Logger import gLogger except ImportError: gLogger = None try: from DIRAC.Core.Utilities.LockRing import LockRing except ImportError: LockRing = None try: from DIRAC.Core.Utilities.ReturnValues import S_OK, S_ERROR except ImportError: def S_OK(val=""): """dummy S_OK""" return {"OK": True, "Value": val} def S_ERROR(mess): """dummy S_ERROR""" return {"OK": False, "Message": mess} sLog = gLogger.getSubLogger(__name__) class WorkingProcess(multiprocessing.Process): """ .. class:: WorkingProcess WorkingProcess is a class that represents activity that runs in a separate process. It is running main thread (process) in daemon mode, reading tasks from :pendingQueue:, executing them and pushing back tasks with results to the :resultsQueue:. If task has got a timeout value defined a separate threading.Timer thread is started killing execution (and destroying worker) after :ProcessTask.__timeOut: seconds. Main execution could also terminate in a few different ways: * on every failed read attempt (from empty :pendingQueue:), the idle loop counter is increased, worker is terminated when counter is reaching a value of 10; * when stopEvent is set (so ProcessPool is in draining mode), * when parent process PID is set to 1 (init process, parent process with ProcessPool is dead). """ def __init__(self, pendingQueue, resultsQueue, stopEvent, keepRunning): """c'tor :param self: self reference :param pendingQueue: queue storing ProcessTask before exection :type pendingQueue: multiprocessing.Queue :param resultsQueue: queue storing callbacks and exceptionCallbacks :type resultsQueue: multiprocessing.Queue :param stopEvent: event to stop processing :type stopEvent: multiprocessing.Event """ multiprocessing.Process.__init__(self) # daemonize self.daemon = True # flag to see if task is being treated self.__working = multiprocessing.Value("i", 0) # task counter self.__taskCounter = multiprocessing.Value("i", 0) # task queue self.__pendingQueue = pendingQueue # results queue self.__resultsQueue = resultsQueue # stop event self.__stopEvent = stopEvent # keep process running until stop event self.__keepRunning = keepRunning # placeholder for watchdog thread self.__watchdogThread = None # placeholder for process thread self.__processThread = None # placeholder for current task self.task = None # start yourself at least self.start() def __watchdog(self): """ Watchdog thread target Terminating/killing WorkingProcess when parent process is dead :param self: self reference """ while True: # parent is dead, commit suicide if os.getppid() == 1: os.kill(self.pid, signal.SIGTERM) # wait for half a minute and if worker is still alive use REAL silencer time.sleep(30) # now you're dead os.kill(self.pid, signal.SIGKILL) # wake me up in 5 seconds time.sleep(5) def isWorking(self): """ Check if process is being executed :param self: self reference """ return self.__working.value == 1 def taskProcessed(self): """ Tell how many tasks have been processed so far :param self: self reference """ return self.__taskCounter def __processTask(self): """ processThread target :param self: self reference """ if self.task: self.task.process() def run(self): """ Task execution Reads and executes ProcessTask :task: out of pending queue and then pushes it to the results queue for callback execution. :param self: self reference """ # start watchdog thread self.__watchdogThread = threading.Thread(target=self.__watchdog) self.__watchdogThread.daemon = True self.__watchdogThread.start() if LockRing: # Reset all locks lr = LockRing() lr._openAll() lr._setAllEvents() # zero processed task counter taskCounter = 0 # zero idle loop counter idleLoopCount = 0 # main loop while True: # draining, stopEvent is set, exiting if self.__stopEvent.is_set(): return # clear task self.task = None # read from queue try: task = self.__pendingQueue.get(block=True, timeout=10) except Queue.Empty: # idle loop? idleLoopCount += 1 # 10th idle loop - exit, nothing to do if idleLoopCount == 10 and not self.__keepRunning: return continue # toggle __working flag self.__working.value = 1 # save task self.task = task # reset idle loop counter idleLoopCount = 0 # process task in a separate thread self.__processThread = threading.Thread(target=self.__processTask) self.__processThread.start() timeout = False noResults = False # join processThread with or without timeout if self.task.getTimeOut(): self.__processThread.join(self.task.getTimeOut() + 10) else: self.__processThread.join() # processThread is still alive? stop it! if self.__processThread.is_alive(): if six.PY2: self.__processThread._Thread__stop() # pylint: disable=no-member self.task.setResult(S_ERROR(errno.ETIME, "Timed out")) timeout = True # if the task finished with no results, something bad happened, e.g. # undetected timeout if not self.task.taskResults() and not self.task.taskException(): self.task.setResult(S_ERROR("Task produced no results")) noResults = True # check results and callbacks presence, put task to results queue if self.task.hasCallback() or self.task.hasPoolCallback(): self.__resultsQueue.put(task) if timeout or noResults: # The task execution timed out, stop the process to prevent it from running # in the background time.sleep(1) os.kill(self.pid, signal.SIGKILL) return # increase task counter taskCounter += 1 self.__taskCounter = taskCounter # toggle __working flag self.__working.value = 0 class ProcessTask(object): """Defines task to be executed in WorkingProcess together with its callbacks.""" # taskID taskID = 0 def __init__( self, taskFunction, args=None, kwargs=None, taskID=None, callback=None, exceptionCallback=None, usePoolCallbacks=False, timeOut=0, ): """c'tor :warning: taskFunction has to be callable: it could be a function, lambda OR a class with __call__ operator defined. But be carefull with interpretation of args and kwargs, as they are passed to different places in above cases: 1. for functions or lambdas args and kwargs are just treated as function parameters 2. for callable classess (say MyTask) args and kwargs are passed to class contructor (MyTask.__init__) and MyTask.__call__ should be a method without parameters, i.e. MyTask definition should be:: class MyTask: def __init__( self, *args, **kwargs ): ... def __call__( self ): ... :warning: depending on :timeOut: value, taskFunction execution can be forcefully terminated using SIGALRM after :timeOut: seconds spent, :timeOut: equal to zero means there is no any time out at all, except those during :ProcessPool: finalization :param self: self reference :param mixed taskFunction: definition of callable object to be executed in this task :param tuple args: non-keyword arguments :param dict kwargs: keyword arguments :param int taskID: task id, if not set, :param int timeOut: estimated time to execute taskFunction in seconds (default = 0, no timeOut at all) :param mixed callback: result callback function :param mixed exceptionCallback: callback function to be fired upon exception in taskFunction """ self.__taskFunction = taskFunction self.__taskArgs = args or [] self.__taskKwArgs = kwargs or {} self.__taskID = taskID self.__resultCallback = callback self.__exceptionCallback = exceptionCallback self.__timeOut = 0 # set time out self.setTimeOut(timeOut) self.__done = False self.__exceptionRaised = False self.__taskException = None self.__taskResult = None self.__usePoolCallbacks = usePoolCallbacks def taskResults(self): """ Get task results :param self: self reference """ return self.__taskResult def taskException(self): """ Get task exception :param self: self reference """ return self.__taskException def enablePoolCallbacks(self): """ (re)enable use of ProcessPool callbacks """ self.__usePoolCallbacks = True def disablePoolCallbacks(self): """ Disable execution of ProcessPool callbacks """ self.__usePoolCallbacks = False def usePoolCallbacks(self): """ Check if results should be processed by callbacks defined in the :ProcessPool: :param self: self reference """ return self.__usePoolCallbacks def hasPoolCallback(self): """ Check if asked to execute :ProcessPool: callbacks :param self: self reference """ return self.__usePoolCallbacks def setTimeOut(self, timeOut): """ Set time out (in seconds) :param self: selt reference :param int timeOut: new time out value """ try: self.__timeOut = int(timeOut) return S_OK(self.__timeOut) except (TypeError, ValueError) as error: return S_ERROR(str(error)) def getTimeOut(self): """ Get timeOut value :param self: self reference """ return self.__timeOut def hasTimeOutSet(self): """ Check if timeout is set :param self: self reference """ return bool(self.__timeOut != 0) def getTaskID(self): """ TaskID getter :param self: self reference """ return self.__taskID def hasCallback(self): """ Callback existence checking :param self: self reference :return: True if callback or exceptionCallback has been defined, False otherwise """ return self.__resultCallback or self.__exceptionCallback or self.__usePoolCallbacks def exceptionRaised(self): """ Flag to determine exception in process :param self: self reference """ return self.__exceptionRaised def doExceptionCallback(self): """ Execute exceptionCallback :param self: self reference """ if self.__done and self.__exceptionRaised and self.__exceptionCallback: self.__exceptionCallback(self, self.__taskException) def doCallback(self): """ Execute result callback function :param self: self reference """ if self.__done and not self.__exceptionRaised and self.__resultCallback: self.__resultCallback(self, self.__taskResult) def setResult(self, result): """ Set taskResult to result """ self.__taskResult = result def process(self): """ Execute task :param self: self reference """ self.__done = True try: # it's a function? if inspect.isfunction(self.__taskFunction): self.__taskResult = self.__taskFunction(*self.__taskArgs, **self.__taskKwArgs) # or a class? elif inspect.isclass(self.__taskFunction): # create new instance taskObj = self.__taskFunction(*self.__taskArgs, **self.__taskKwArgs) # ## check if it is callable, raise TypeError if not if not callable(taskObj): raise TypeError("__call__ operator not defined not in %s class" % taskObj.__class__.__name__) # ## call it at least self.__taskResult = taskObj() except Exception as x: self.__exceptionRaised = True if gLogger: gLogger.exception("Exception in process of pool") if self.__exceptionCallback or self.usePoolCallbacks(): retDict = S_ERROR("Exception") retDict["Value"] = str(x) retDict["Exc_info"] = sys.exc_info()[1] self.__taskException = retDict class ProcessPool(object): """ .. class:: ProcessPool ProcessPool This class is managing multiprocessing execution of tasks (:ProcessTask: instances) in a separate sub-processes (:WorkingProcess:). Pool depth The :ProcessPool: is keeping required number of active workers all the time: slave workers are only created when pendingQueue is being filled with tasks, not exceeding defined min and max limits. When pendingQueue is empty, active workers will be cleaned up by themselves, as each worker has got built in self-destroy mechanism after 10 idle loops. Processing and communication The communication between :ProcessPool: instance and slaves is performed using two :multiprocessing.Queues: * pendingQueue, used to push tasks to the workers, * resultsQueue for revert direction; and one :multiprocessing.Event: instance (stopEvent), which is working as a fuse to destroy idle workers in a clean manner. Processing of task begins with pushing it into :pendingQueue: using :ProcessPool.queueTask: or :ProcessPool.createAndQueueTask:. Every time new task is queued, :ProcessPool: is checking existance of active and idle workers and spawning new ones when required. The task is then read and processed on worker side. If results are ready and callback functions are defined, task is put back to the resultsQueue and it is ready to be picked up by ProcessPool again. To perform this last step one has to call :ProcessPool.processResults:, or alternatively ask for daemon mode processing, when this function is called again and again in separate background thread. Finalisation Finalization for task processing is done in several steps: * if pool is working in daemon mode, background result processing thread is joined and stopped * :pendingQueue: is emptied by :ProcessPool.processAllResults: function, all enqueued tasks are executed * :stopEvent: is set, so all idle workers are exiting immediately * non-hanging workers are joined and terminated politelty * the rest of workers, if any, are forcefully retained by signals: first by SIGTERM, and if is doesn't work by SIGKILL :warn: Be carefull and choose wisely :timeout: argument to :ProcessPool.finalize:. Too short time period can cause that all workers will be killed. """ def __init__( self, minSize=2, maxSize=0, maxQueuedRequests=10, strictLimits=True, poolCallback=None, poolExceptionCallback=None, keepProcessesRunning=True, ): """c'tor :param self: self reference :param int minSize: minimal number of simultaniously executed tasks :param int maxSize: maximal number of simultaniously executed tasks :param int maxQueueRequests: size of pending tasks queue :param bool strictLimits: flag to workers overcommitment :param callable poolCallbak: results callback :param callable poolExceptionCallback: exception callback """ # min workers self.__minSize = max(1, minSize) # max workers self.__maxSize = max(self.__minSize, maxSize) # queue size self.__maxQueuedRequests = maxQueuedRequests # flag to worker overcommit self.__strictLimits = strictLimits # pool results callback self.__poolCallback = poolCallback # pool exception callback self.__poolExceptionCallback = poolExceptionCallback # pending queue self.__pendingQueue = multiprocessing.Queue(self.__maxQueuedRequests) # results queue self.__resultsQueue = multiprocessing.Queue(0) # stop event self.__stopEvent = multiprocessing.Event() # keep processes running flag self.__keepRunning = keepProcessesRunning # lock self.__prListLock = threading.Lock() # workers dict self.__workersDict = {} # flag to trigger workers draining self.__draining = False # placeholder for daemon results processing self.__daemonProcess = False # create initial workers self.__spawnNeededWorkingProcesses() def stopProcessing(self, timeout=10): """ Case fire :param self: self reference """ self.finalize(timeout) def startProcessing(self): """ Restart processing again :param self: self reference """ self.__draining = False self.__stopEvent.clear() self.daemonize() def setPoolCallback(self, callback): """ Set ProcessPool callback function :param self: self reference :param callable callback: callback function """ if callable(callback): self.__poolCallback = callback def setPoolExceptionCallback(self, exceptionCallback): """ Set ProcessPool exception callback function :param self: self refernce :param callable exceptionCallback: exsception callback function """ if callable(exceptionCallback): self.__poolExceptionCallback = exceptionCallback def getMaxSize(self): """ MaxSize getter :param self: self reference """ return self.__maxSize def getMinSize(self): """ MinSize getter :param self: self reference """ return self.__minSize def getNumWorkingProcesses(self): """ Count processes currently being executed :param self: self reference """ counter = 0 self.__prListLock.acquire() try: counter = len([pid for pid, worker in self.__workersDict.items() if worker.isWorking()]) finally: self.__prListLock.release() return counter def getNumIdleProcesses(self): """ Count processes being idle :param self: self reference """ counter = 0 self.__prListLock.acquire() try: counter = len([pid for pid, worker in self.__workersDict.items() if not worker.isWorking()]) finally: self.__prListLock.release() return counter def getFreeSlots(self): """get number of free slots available for workers :param self: self reference """ return max(0, self.__maxSize - self.getNumWorkingProcesses()) def __spawnWorkingProcess(self): """ Create new process :param self: self reference """ self.__prListLock.acquire() try: worker = WorkingProcess(self.__pendingQueue, self.__resultsQueue, self.__stopEvent, self.__keepRunning) while worker.pid is None: time.sleep(0.1) self.__workersDict[worker.pid] = worker finally: self.__prListLock.release() def __cleanDeadProcesses(self): """ Delete references of dead workingProcesses from ProcessPool.__workingProcessList """ # check wounded processes self.__prListLock.acquire() try: for pid, worker in list(self.__workersDict.items()): if not worker.is_alive(): del self.__workersDict[pid] finally: self.__prListLock.release() def __spawnNeededWorkingProcesses(self): """ Create N working process (at least self.__minSize, but no more than self.__maxSize) :param self: self reference """ self.__cleanDeadProcesses() # if we're draining do not spawn new workers if self.__draining or self.__stopEvent.is_set(): return while len(self.__workersDict) < self.__minSize: if self.__draining or self.__stopEvent.is_set(): return self.__spawnWorkingProcess() while self.hasPendingTasks() and self.getNumIdleProcesses() == 0 and len(self.__workersDict) < self.__maxSize: if self.__draining or self.__stopEvent.is_set(): return self.__spawnWorkingProcess() time.sleep(0.1) def queueTask(self, task, blocking=True, usePoolCallbacks=False): """ Enqueue new task into pending queue :param self: self reference :param ProcessTask task: new task to execute :param bool blocking: flag to block if necessary and new empty slot is available (default = block) :param bool usePoolCallbacks: flag to trigger execution of pool callbacks (default = don't execute) """ if not isinstance(task, ProcessTask): raise TypeError("Tasks added to the process pool must be ProcessTask instances") if usePoolCallbacks and (self.__poolCallback or self.__poolExceptionCallback): task.enablePoolCallbacks() self.__prListLock.acquire() try: self.__pendingQueue.put(task, block=blocking) except Queue.Full: self.__prListLock.release() return S_ERROR("Queue is full") finally: self.__prListLock.release() self.__spawnNeededWorkingProcesses() # throttle a bit to allow task state propagation time.sleep(0.1) return S_OK() def createAndQueueTask( self, taskFunction, args=None, kwargs=None, taskID=None, callback=None, exceptionCallback=None, blocking=True, usePoolCallbacks=False, timeOut=0, ): """ Create new processTask and enqueue it in pending task queue :param self: self reference :param mixed taskFunction: callable object definition (FunctionType, LambdaType, callable class) :param tuple args: non-keyword arguments passed to taskFunction c'tor :param dict kwargs: keyword arguments passed to taskFunction c'tor :param int taskID: task Id :param mixed callback: callback handler, callable object executed after task's execution :param mixed exceptionCallback: callback handler executed if testFunction had raised an exception :param bool blocking: flag to block queue if necessary until free slot is available :param bool usePoolCallbacks: fire execution of pool defined callbacks after task callbacks :param int timeOut: time you want to spend executing :taskFunction: """ task = ProcessTask(taskFunction, args, kwargs, taskID, callback, exceptionCallback, usePoolCallbacks, timeOut) return self.queueTask(task, blocking) def hasPendingTasks(self): """ Check if taks are present in pending queue :param self: self reference :warning: results may be misleading if elements put into the queue are big """ return not self.__pendingQueue.empty() def isFull(self): """ Check in peding queue is full :param self: self reference :warning: results may be misleading if elements put into the queue are big """ return self.__pendingQueue.full() def isWorking(self): """ Check existence of working subprocesses :param self: self reference """ return not self.__pendingQueue.empty() or self.getNumWorkingProcesses() def processResults(self): """ Execute tasks' callbacks removing them from results queue :param self: self reference """ processed = 0 log = sLog.getSubLogger("WorkingProcess") while True: if ( not log.debug( "Start loop (t=0) queue size = %d, processed = %d" % (self.__resultsQueue.qsize(), processed) ) and processed == 0 and self.__resultsQueue.qsize() ): log.debug("Process results, queue size = %d" % self.__resultsQueue.qsize()) start = time.time() self.__cleanDeadProcesses() log.debug("__cleanDeadProcesses", "t=%.2f" % (time.time() - start)) if not self.__pendingQueue.empty(): self.__spawnNeededWorkingProcesses() log.debug("__spawnNeededWorkingProcesses", "t=%.2f" % (time.time() - start)) time.sleep(0.1) if self.__resultsQueue.empty(): if self.__resultsQueue.qsize(): log.warn("Results queue is empty but has non zero size", "%d" % self.__resultsQueue.qsize()) # We only commit suicide if we reach a backlog greater than the maximum number of workers if self.__resultsQueue.qsize() > self.__maxSize: return -1 else: return 0 if processed == 0: log.debug("Process results, but queue is empty...") break # get task task = self.__resultsQueue.get() log.debug("__resultsQueue.get", "t=%.2f" % (time.time() - start)) # execute callbacks try: task.doExceptionCallback() task.doCallback() log.debug("doCallback", "t=%.2f" % (time.time() - start)) if task.usePoolCallbacks(): if self.__poolExceptionCallback and task.exceptionRaised(): self.__poolExceptionCallback(task.getTaskID(), task.taskException()) if self.__poolCallback and task.taskResults(): self.__poolCallback(task.getTaskID(), task.taskResults()) log.debug("__poolCallback", "t=%.2f" % (time.time() - start)) except Exception as error: log.exception("Exception in callback", lException=error) pass processed += 1 if processed: log.debug("Processed %d results" % processed) else: log.debug("No results processed") return processed def processAllResults(self, timeout=10): """ Process all enqueued tasks at once :param self: self reference """ start = time.time() while self.getNumWorkingProcesses() or not self.__pendingQueue.empty(): self.processResults() time.sleep(1) if time.time() - start > timeout: break self.processResults() def finalize(self, timeout=60): """ Drain pool, shutdown processing in more or less clean way :param self: self reference :param timeout: seconds to wait before killing """ # start drainig self.__draining = True # join deamon process if self.__daemonProcess: self.__daemonProcess.join(timeout) # process all tasks self.processAllResults(timeout) # set stop event, all idle workers should be terminated self.__stopEvent.set() # join idle workers start = time.time() log = sLog.getSubLogger("finalize") nWorkers = 9999999 while self.__workersDict: self.__cleanDeadProcesses() if len(self.__workersDict) != nWorkers: nWorkers = len(self.__workersDict) log.debug("%d workers still active, timeout = %d" % (nWorkers, timeout)) if timeout <= 0 or time.time() - start >= timeout: break time.sleep(0.1) # second clean up - join and terminate workers if self.__workersDict: log.debug( "After cleaning dead processes, %d workers still active, timeout = %d" % (len(self.__workersDict), timeout) ) for worker in self.__workersDict.values(): if worker.is_alive(): worker.terminate() worker.join(5) self.__cleanDeadProcesses() # third clean up - kill'em all!!! if self.__workersDict: log.debug( "After terminating processes, %d workers still active, timeout = %d, kill them" % (len(self.__workersDict), timeout) ) self.__filicide() def __filicide(self): """ Kill all workers, kill'em all! :param self: self reference """ while self.__workersDict: pid = list(self.__workersDict).pop(0) worker = self.__workersDict[pid] if worker.is_alive(): os.kill(pid, signal.SIGKILL) del self.__workersDict[pid] def daemonize(self): """ Make ProcessPool a finite being for opening and closing doors between chambers. Also just run it in a separate background thread to the death of PID 0. :param self: self reference """ if self.__daemonProcess: return self.__daemonProcess = threading.Thread(target=self.__backgroundProcess) self.__daemonProcess.setDaemon(1) self.__daemonProcess.start() def __backgroundProcess(self): """ Daemon thread target :param self: self reference """ while True: if self.__draining: return self.processResults() time.sleep(1) def __del__(self): """ Delete slot :param self: self reference """ self.finalize(timeout=10)