Shared memory parallel processing in python

Question

I have a list of strings and I want to bucket these list elements into appropriate buckets.

def bucketElements(i):
 global buckA, buckB, buckC
 if i.startswith('A'):
 buckA.add(i)
 elif i.startswith('B'):
 buckB.add(i)
 elif i.startswith('C'):
 buckC.add(i)

Now I want to call this method in parallel for each element inside my List. Something like this,

buckA,buckB, buckC = set(), set(), set()
pool = multiprocessing.Pool(processes=10)
pool.map(bucketElements, buckList)

Since I'm updating global variables inside my function I cannot use multiprocessing. is there anyway I can improve my processing? currently I'm calling it like this,

buckA,buckB, buckC = set(), set(), set()
for i in buckList:
 bucketElements(i)

• Billy: what are the contents of buckList?
• MikA: sorry my bad i mentioned as list of integers, it is actually list of strings buckList = ['Adasdas', 'Asdsd', 'Xsadsad', 'Ssdsd', 'Bdasdsds']

Answer 1

You have 3 Options:

• Queue()
• Manager.Value()
• Manager.list()

Python » Documentation: multiprocessing.html#managers