There are other ways of doing this, this is the one I used for where I was working with this for something that parallelized easily.

chunkit.py

from __future__ import print_function
import numpy
import random

mylist = range(0,100)
random.shuffle(mylist)
myarray = numpy.array(mylist)

# via http://stackoverflow.com/questions/2130016/splitting-a-list-of-arbitrary-size-into-only-roughly-n-equal-parts
def chunkit(seq, N):
    """
    Prints the bounds of a list divided into at most N chunks.
    This is simple but useful in the case of spawning lots of workers from the
    command line, where you need to process (0, x), (x+1, 2x+1), etc. records at a time.
    and where you're going to have some irregular divisions.
    """
    avg = len(seq) / float(N)
    out = []
    last = 0.0
    while last < len(seq):
        out.append((int(last), min(int(last + avg), len(seq))))
        last += (avg + 1)
    return(out)

f = lambda x: print("f --lower {} --higher {}".format(x[0],x[1]))
    
bounds = chunkit(mylist, 6)
print(bounds)
for b in bounds:
    f(b)

print("and with map")

map(f,bounds)