sorting.py :  » Database » Python-Remote-Objects » Pyro-3.10 » examples » distributed-computing » tasks » Python Open Source

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Python Open Source » Database » Python Remote Objects 
Python Remote Objects » Pyro 3.10 » examples » distributed computing » tasks » sorting.py
from tasks.task import PartitionableTask,TaskPartition

import time
import random
import string

#
# The 'main' task of sorting a big list of random numbers.
# It partitions the work in a way where each subtask
# sorts a chunk of the original huge list, and after that,
# all sorted chunks are merged using a single merge pass of O(n).
#
class SortTask(PartitionableTask):
      
  def __init__(self, listSize):
    PartitionableTask.__init__(self,"data sorter")
    self.size=listSize
    self.chunks=[]
    self.numchunks=0
    self.result=[]
  def split(self, numPiecesHint):
    lst=[random.choice(string.lowercase) for i in range(self.size)]
    pieces=numPiecesHint*3 # number of pieces
    chunksize=self.size/pieces
    taskparts=[]
    for i in range(pieces+1):
      chunk = lst[0:chunksize]
      del lst[0:chunksize]
      if chunk:
        taskparts.append(SortTaskPartition(chunk, i+1))
      else:
        break
    self.numchunks=len(taskparts)
    return taskparts
  def join(self,task):
    self.chunks.append(task.result)
    return False  # not done yet, also join all other tasks
  def getResult(self):
    if len(self.chunks)!=self.numchunks:
      return None  # not yet enough chunks received
    if self.result:
      return self.result
    assert sum([len(x) for x in self.chunks])==self.size, "length of combined chunks is incorrect"
    # use a single pass of the generic merge sort O(n) to get the final sorted list.
    # we sort in reverse order because removing elements from the end of a list is O(1)
    result=[]
    starttime=time.time()
    while len(result)<self.size:
      for chunk in self.chunks:
        if chunk:
          largest_chunk=chunk
          largest_elt=chunk[-1]
          break
      for chunk in self.chunks[1:]:
        if chunk and chunk[-1]>largest_elt:
          largest_elt=chunk[-1]
          largest_chunk=chunk
      result.append(largest_elt)
      del largest_chunk[-1]
    result.reverse()
    self.result=result
    print "Chunks merged in %.03f seconds." % (time.time()-starttime)
    return self.result
        


#
# The subtask responsible for sorting a certain part of the full list
#
class SortTaskPartition(TaskPartition):
  def __init__(self, unsortedList, chunknumber):
    TaskPartition.__init__(self,"sort chunk %d" % chunknumber )
    self.lst = unsortedList
    self.result=None
    self.size=len(self.lst)
  def work(self):
    prevprogress=time.time()
    result=[]
    while self.lst:
      elt=self.lst.pop()
      i=0
      while i<len(result):
        if result[i]>=elt:
          break
        i+=1
      result.insert(i, elt)
      if (time.time()-prevprogress)>0.3:
        yield len(result)
        prevprogress=time.time()
    self.result=result
      
  def progress(self, pos):
    return pos/float(self.size)



#
# The 'user interface' for the sort task.
#
class UserInterface(object):
  def begin(self):
    print "Big data array sorting."
    size=input("Enter the size of the data array (>100): ")
    return size
  def info(self, task):
    print "Sorting the data array of length %d..." % task.size
  def result(self,taskresult):
    filename="sorted.txt"
    print "\nWriting the sorted data array to",filename
    out=open(filename,"w")
    while taskresult:
      print >>out, "".join(taskresult[:70])
      del taskresult[:70]
    out.close()
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