task.py :  » Development » Pyro » Pyro-3.10 » examples » distributed-computing » tasks » Python Open Source

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Python Open Source » Development » Pyro 
Pyro » Pyro 3.10 » examples » distributed computing » tasks » task.py
import sys
import Pyro.EventService.Clients
import Pyro.constants

#
# The 'main' Task abstract baseclass.
#
class PartitionableTask(object):
  def __init__(self, name):
    self.name=name
  def split(self, numPiecesHint): 
    pass  # implement in subclass
  def join(self, task):
    pass  # implement in subclass, return True to stop the whole task.
  def getResult(self):
    pass  # implement in subclass
  def __str__(self):
    return "<Task '%s'>" % self.name

#
# The subtask baseclass. The main task is split into these
# subtasks, which are distributed over the processors.
# The progress of each subtask can be monitored on the ES
# channels Distributed.cell.*  (*=subtask name)
# (use the monitor.py for this)
#
class TaskPartition(Pyro.EventService.Clients.Publisher):
  def __init__(self, name):
    Pyro.EventService.Clients.Publisher.__init__(self)
    self.name=name
  def run(self):
    self.publish("Distributed.cell."+self.name, "START")
    for pos in self.work():
      self.publish("Distributed.cell."+self.name, self.progress(pos))
    self.publish("Distributed.cell."+self.name, "FINISHED")
  def progress(self,pos):
    return 100.0*pos/100.0  # override in subclass
  def work(self):
    yield 100   # override this generator in subclass, here the actual work is done
  def __str__(self):
    return "<TaskPartition '%s'>" % self.name
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