Multi-threading in python with loop

Question

I'm trying to solve Problem 8 in project euler with multi-threading technique in python.

Find the greatest product of five consecutive digits in the 1000-digit number. The number can be found here.

My approach is to generate product from chunks of 5 from the original list and repeat this process 5 times, each with the starting index shifted one to the right.

Here is my thread class

class pThread(threading.Thread):
    def __init__(self, l):
        threading.Thread.__init__(self)
        self.l = l
        self.p = 0

    def run(self):

        def greatest_product(l):
        """
        Divide the list into chunks of 5 and find the greatest product
        """
            def product(seq):
                return reduce(lambda x,y : x*y, seq)

            def chunk_product(l, n=5):
                for i in range(0, len(l), n):
                    yield product(l[i:i+n])

            result = 0
            for p in chunk_product(num):
                result = result > p and result or p 

            return result

        self.p = greatest_product(self.l)

When I try to create 5 threads to cover all 5-digit chunks in my original list, the manual approach below gives the correct answer, with num being the list of single-digit numbers that I parse from the text:

thread1 = pThread(num)
del num[0]
thread2 = pThread(num)
del num[0]
thread3 = pThread(num)
del num[0]
thread4 = pThread(num)
del num[0]
thread5 = pThread(num)

thread1.start()
thread2.start()
thread3.start()
thread4.start()
thread5.start()

thread1.join()
thread2.join()
thread3.join()
thread4.join()
thread5.join()

def max(*args):
    result = 0
    for i in args:
        result = i > result and i or result
    return result

print max(thread1.p, thread2.p, thread3.p, thread4.p, thread5.p)

But this doesn't give the correct result:

threads = []
for i in range(0, 4):
    tmp = num[:]
    del tmp[0:i+1]
    thread = pThread(tmp)
    thread.start()
    threads.append(thread)

for i in range(0, 4):
    threads[i].join()

What did I do wrong here? I'm very new to multithreading so please be gentle.

Answer 1

There are 3 problems:

1. The first is that the "manual" approach does not give the correct answer. It just happens that the correct answer to the problem is at the offset 4 from the start of your list. You can see this by using:

   import operator as op
   print max(reduce(op.mul, num[i:i+5]) for i in range(1000))
   for k in range(5):
       print max(reduce(op.mul, num[i:i+5]) for i in range(k, 1000, 5))
   

   One problem with your "manual" approach is that the threads share the num variable, each has the same list. So when you do del num[0], all threadX.l are affected. The fact that you consistently get the same answer is due to the second problem.

2. The line

   for p in chunk_product(num):
   

   should be:

   for p in chunk_product(l):
   

   since you want to use the parameter of function greatest_product(l) and not the global variable num.

3. In the second method you only spawn 4 threads since the loops range over [0, 1, 2, 3]. Also, you want to delete the values tmp[0:i] and not tmp[0:i+1]. Here is the code:

   threads = []
   for i in range(5):
       tmp = num[:]
       del tmp[0:i]
       thread = pThread(tmp)
       thread.start()
       threads.append(thread)
   
   for i in range(5):
       threads[i].join()
   
   print len(threads), map(lambda th: th.p, threads)
   print max(map(lambda th: th.p, threads))
   

Answer 2

I took a stab at this mainly to get some practice multiprocessing, and to learn how to use argparse.

This took around 4-5 gigs of ram just in case your machine doesn't have a lot.

python euler.py -l 50000000 -n 100 -p 8

Took 5.836833333969116 minutes
The largest product of 100 consecutive numbers is: a very large number

If you type python euler.py -h at the commandline you get:

usage: euler.py [-h] -l L [L ...] -n N [-p P]

Calculates the product of consecutive numbers and return the largest product.

optional arguments:
  -h, --help    show this help message and exit
  -l L [L ...]  A single number or list of numbers, where each # is seperated
                by a space
  -n N          A number that specifies how many consecutive numbers should be
                multiplied together.
  -p P          Number of processes to create. Optional, defaults to the # of
                cores on the pc.        

And the code:

"""A multiprocess iplementation for calculation the maximum product of N consecutive
numbers in a given range (list of numbers)."""

import multiprocessing
import math
import time
import operator
from functools import reduce
import argparse

def euler8(alist,lenNums):
    """Returns the largest product of N consecutive numbers in a given range"""
    return max(reduce(operator.mul, alist[i:i+lenNums]) for i in range(len(alist)))

def split_list_multi(listOfNumbers,numLength,threads):
    """Split a list into N parts where N is the # of processes."""
    fullLength = len(listOfNumbers)
    single = math.floor(fullLength/threads)
    results = {}
    counter = 0
    while counter < threads:
        if counter == (threads-1):
            temp = listOfNumbers[single*counter::]
            if counter == 0:
                results[str(counter)] = listOfNumbers[single*counter::]
            else:
                prevListIndex = results[str(counter-1)][-int('{}'.format(numLength-1))::]
                newlist = prevListIndex + temp
                results[str(counter)] = newlist
        else:
            temp = listOfNumbers[single*counter:single*(counter+1)]
            if counter == 0:
                newlist = temp
            else:
                prevListIndex = results[str(counter-1)][-int('{}'.format(numLength-1))::]
                newlist = prevListIndex + temp
            results[str(counter)] = newlist
        counter += 1
    return results,threads

def worker(listNumbers,number,output):
    """A worker. Used to run seperate processes and put the results in the queue"""
    result = euler8(listNumbers,number)
    output.put(result)

def main(listOfNums,lengthNumbers,numCores=multiprocessing.cpu_count()):
    """Runs the module.
    listOfNums must be a list of ints, or single int
    lengthNumbers is N (an int) where N is the # of consecutive numbers to multiply together
    numCores (an int) defaults to however many the cpu has, can specify a number if you choose."""

    if isinstance(listOfNums,list):
        if len(listOfNums) == 1:
            valuesToSplit = [i for i in range(int(listOfNums[0]))]
        else:
            valuesToSplit = [int(i) for i in listOfNums]
    elif isinstance(listOfNums,int):
        valuesToSplit = [i for i in range(listOfNums)]
    else:
        print('First arg must be a number or a list of numbers')

    split = split_list_multi(valuesToSplit,lengthNumbers,numCores)
    done_queue = multiprocessing.Queue()
    jobs = []
    startTime = time.time()

    for num in range(split[1]):
        numChunks = split[0][str(num)]
        thread = multiprocessing.Process(target=worker, args=(numChunks,lengthNumbers,done_queue))
        jobs.append(thread)
        thread.start()

    resultlist = []
    for i in range(split[1]):
        resultlist.append(done_queue.get())

    for j in jobs:
        j.join()

    resultlist = max(resultlist)
    endTime = time.time()
    totalTime = (endTime-startTime)/60
    print("Took {} minutes".format(totalTime))

    return print("The largest product of {} consecutive numbers is: {}".format(lengthNumbers, resultlist))            

if __name__ == '__main__':
    #To call the module from the commandline with arguments
    parser = argparse.ArgumentParser(description="""Calculates the product of consecutive numbers \
    and return the largest product.""")
    parser.add_argument('-l', nargs='+', required=True,
                       help='A single number or list of numbers, where each # is seperated by a space')
    parser.add_argument('-n', required=True, type=int,
                        help = 'A number that specifies how many consecutive numbers should be \
                        multiplied together.')
    parser.add_argument('-p', default=multiprocessing.cpu_count(), type=int,
                       help='Number of processes to create. Optional, defaults to the # of cores on the pc.')
    args = parser.parse_args()
    main(args.l, args.n, args.p)