In [2]:

    

import random
import time
import sys
from multiprocessing import Process, Queue
random.seed()
def genList (size):
    randomList = []
     
    #initialize random list with values between 0 and 100
    for i in range(size):
        randomList.append(random.randint(0,10))
         
    return randomList
#return the sum of all elements in the list
#This is the same as "return sum(inList)" but in long form for readability and emphasis
def sumList(inList):
    finalSum = 0
     
    #iterate over all values in the list, and calculate the cummulative sum
    for value in inList:
        finalSum = finalSum + value
    return finalSum
def doWork(N,q):
    #create a random list of N integers
    myList = genList (N)
    finalSum = sumList(myList)
    #put the result in the Queue to return the the calling process
    q.put(finalSum)
    
if len(sys.argv) == 2 and sys.argv[1].isdigit():
    N = int(sys.argv[1])
    #mark the start time
    startTime = time.time()
    #create a Queue to share results
    q = Queue()
    #create 4 sub-processes to do the work
    p1 = Process(target=doWork, args=(N/4,q))
    p1.start()
    p2 = Process(target=doWork, args=(N/4,q))
    p2.start()
    p3 = Process(target=doWork, args=(N/4,q))
    p3.start()
    p4 = Process(target=doWork, args=(N/4,q))
    p4.start()
         
    results = []
    #grab 4 values from the queue, one for each process
    for i in range(4):
        #set block=True to block until we get a result
        results.append(q.get(True))
         
    #sum the partial results to get the final result
    finalSum = sumList(results)
         
    p1.join()
    p2.join()
    p3.join()
    p4.join()
                 
    #mark the end time
    endTime = time.time()
    #calculate the total time it took to complete the work
    workTime =  endTime - startTime
         
    #print results
    print "The job took " + str(workTime) + " seconds to complete"
    print "The final sum was: " + str(finalSum)


    

In [4]:

    

from multiprocessing import Pool

def f(x):
    return x*x

with Pool(5) as p:
    print(p.map(f, [1, 2, 3]))


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-fdc638aafcb8> in <module>()
      4     return x*x
      5 
----> 6 with Pool(5) as p:
      7     print(p.map(f, [1, 2, 3]))

AttributeError: __exit__

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