synopsis:ProcessPool and related classes


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 <minSize> workers will be alive all the time
param int maxSize:
 no more than <maxSize> 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:


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:


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:


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.

class DIRAC.Core.Utilities.ProcessPool.ProcessPool(minSize=2, maxSize=0, maxQueuedRequests=10, strictLimits=True, poolCallback=None, poolExceptionCallback=None, keepProcessesRunning=True)

Bases: object

class 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.


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.
__init__(minSize=2, maxSize=0, maxQueuedRequests=10, strictLimits=True, poolCallback=None, poolExceptionCallback=None, keepProcessesRunning=True)


  • self – self reference
  • minSize (int) – minimal number of simultaniously executed tasks
  • maxSize (int) – maximal number of simultaniously executed tasks
  • maxQueueRequests (int) – size of pending tasks queue
  • strictLimits (bool) – flag to workers overcommitment
  • poolCallbak (callable) – results callback
  • poolExceptionCallback (callable) – exception callback
createAndQueueTask(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

  • self – self reference
  • taskFunction (mixed) – callable object definition (FunctionType, LambdaType, callable class)
  • args (tuple) – non-keyword arguments passed to taskFunction c’tor
  • kwargs (dict) – keyword arguments passed to taskFunction c’tor
  • taskID (int) – task Id
  • callback (mixed) – callback handler, callable object executed after task’s execution
  • exceptionCallback (mixed) – callback handler executed if testFunction had raised an exception
  • blocking (bool) – flag to block queue if necessary until free slot is available
  • usePoolCallbacks (bool) – fire execution of pool defined callbacks after task callbacks
  • timeOut (int) – time you want to spend executing :taskFunction:

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.

Parameters:self – self reference

Drain pool, shutdown processing in more or less clean way

  • self – self reference
  • timeout – seconds to wait before killing

get number of free slots available for workers

Parameters:self – self reference

MaxSize getter

Parameters:self – self reference

MinSize getter

Parameters:self – self reference

Count processes being idle

Parameters:self – self reference

Count processes currently being executed

Parameters:self – self reference

Check if taks are present in pending queue

Parameters:self – self reference
Warning:results may be misleading if elements put into the queue are big

Check in peding queue is full

Parameters:self – self reference
Warning:results may be misleading if elements put into the queue are big

Check existence of working subprocesses

Parameters:self – self reference

Process all enqueued tasks at once

Parameters:self – self reference

Execute tasks’ callbacks removing them from results queue

Parameters:self – self reference
queueTask(task, blocking=True, usePoolCallbacks=False)

Enqueue new task into pending queue

  • self – self reference
  • task (ProcessTask) – new task to execute
  • blocking (bool) – flag to block if necessary and new empty slot is available (default = block)
  • usePoolCallbacks (bool) – flag to trigger execution of pool callbacks (default = don’t execute)

Set ProcessPool callback function

  • self – self reference
  • callback (callable) – callback function

Set ProcessPool exception callback function

  • self – self refernce
  • exceptionCallback (callable) – exsception callback function

Restart processing again

Parameters:self – self reference

Case fire

Parameters:self – self reference
class DIRAC.Core.Utilities.ProcessPool.ProcessTask(taskFunction, args=None, kwargs=None, taskID=None, callback=None, exceptionCallback=None, usePoolCallbacks=False, timeOut=0)

Bases: object

Defines task to be executed in WorkingProcess together with its callbacks.

__init__(taskFunction, args=None, kwargs=None, taskID=None, callback=None, exceptionCallback=None, usePoolCallbacks=False, timeOut=0)


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 ):

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

  • self – self reference
  • taskFunction (mixed) – definition of callable object to be executed in this task
  • args (tuple) – non-keyword arguments
  • kwargs (dict) – keyword arguments
  • taskID (int) – task id, if not set,
  • timeOut (int) – estimated time to execute taskFunction in seconds (default = 0, no timeOut at all)
  • callback (mixed) – result callback function
  • exceptionCallback (mixed) – callback function to be fired upon exception in taskFunction

Disable execution of ProcessPool callbacks


Execute result callback function

Parameters:self – self reference

Execute exceptionCallback

Parameters:self – self reference

(re)enable use of ProcessPool callbacks


Flag to determine exception in process

Parameters:self – self reference

TaskID getter

Parameters:self – self reference

Get timeOut value

Parameters:self – self reference

Callback existence checking

Parameters:self – self reference
Returns:True if callback or exceptionCallback has been defined, False otherwise

Check if asked to execute :ProcessPool: callbacks

Parameters:self – self reference

Check if timeout is set

Parameters:self – self reference

Execute task

Parameters:self – self reference

Set taskResult to result


Set time out (in seconds)

  • self – selt reference
  • timeOut (int) – new time out value

Get task exception

Parameters:self – self reference
taskID = 0

Get task results

Parameters:self – self reference

Check if results should be processed by callbacks defined in the :ProcessPool:

Parameters:self – self reference
class DIRAC.Core.Utilities.ProcessPool.WorkingProcess(pendingQueue, resultsQueue, stopEvent, keepRunning)

Bases: multiprocessing.process.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).
__init__(pendingQueue, resultsQueue, stopEvent, keepRunning)



Return whether process is a daemon


Return exit code of process or None if it has yet to stop


Return identifier (PID) of process or None if it has yet to start


Check if process is being executed

Parameters:self – self reference

Return whether process is alive


Wait until child process terminates


Return identifier (PID) of process or None if it has yet to start


Task execution

Reads and executes ProcessTask :task: out of pending queue and then pushes it to the results queue for callback execution.

Parameters:self – self reference

Start child process


Tell how many tasks have been processed so far

Parameters:self – self reference

Terminate process; sends SIGTERM signal or uses TerminateProcess()