from random import random
from math import pi

def mcpi(nsamples):
    s = 0
    for i in xrange(nsamples):
        x = random()
        y = random()
        if x*x + y*y <= 1:
            s+=1
    return 4.*s/nsamples

for n in [10, 100, 1000, 10000, 100000, 1000000]:
    print "%8i" % n,
    for i in range(3):
        print "%.5f" % mcpi(n),
    print

%timeit mcpi(1000000)

from IPython import parallel
rc = parallel.Client()

view = rc[:]

%loadpy soln/mcpi.py

multi_mcpi(view, 10000000)

from IPython.parallel.error import RemoteError

e0 = rc[0]
try:
    e0.execute("1/0", block=True)
except RemoteError as e:
    if e.ename == 'ZeroDivisionError':
        print "oops, divided by zero!"
    else:
        # unhandled error
        raise e
            

%loadpy soln/remoteiterhint.py

%loadpy soln/remoteiter.py

# Slightly modified version of:
# http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/511509

import heapq

def mergesort(list_of_lists, key=None):
    """ Perform an N-way merge operation on sorted lists.

    @param list_of_lists: (really iterable of iterable) of sorted elements
    (either by naturally or by C{key})
    @param key: specify sort key function (like C{sort()}, C{sorted()})

    Yields tuples of the form C{(item, iterator)}, where the iterator is the
    built-in list iterator or something you pass in, if you pre-generate the
    iterators.

    This is a stable merge; complexity O(N lg N)

    Examples::

    >>> print list(mergesort([[1,2,3,4],
    ...                      [2,3.25,3.75,4.5,6,7],
    ...                      [2.625,3.625,6.625,9]]))
    [1, 2, 2, 2.625, 3, 3.25, 3.625, 3.75, 4, 4.5, 6, 6.625, 7, 9]

    # note stability
    >>> print list(mergesort([[1,2,3,4],
    ...                      [2,3.25,3.75,4.5,6,7],
    ...                      [2.625,3.625,6.625,9]],
    ...                      key=int))
    [1, 2, 2, 2.625, 3, 3.25, 3.75, 3.625, 4, 4.5, 6, 6.625, 7, 9]


    >>> print list(mergesort([[4, 3, 2, 1],
    ...                      [7, 6, 4.5, 3.75, 3.25, 2],
    ...                      [9, 6.625, 3.625, 2.625]],
    ...                      key=lambda x: -x))
    [9, 7, 6.625, 6, 4.5, 4, 3.75, 3.625, 3.25, 3, 2.625, 2, 2, 1]
    """

    heap = []
    for i, itr in enumerate(iter(pl) for pl in list_of_lists):
        try:
            item = itr.next()
            if key:
                toadd = (key(item), i, item, itr)
            else:
                toadd = (item, i, itr)
            heap.append(toadd)
        except StopIteration:
            pass
    heapq.heapify(heap)

    if key:
        while heap:
            _, idx, item, itr = heap[0]
            yield item
            try:
                item = itr.next()
                heapq.heapreplace(heap, (key(item), idx, item, itr) )
            except StopIteration:
                heapq.heappop(heap)

    else:
        while heap:
            item, idx, itr = heap[0]
            yield item
            try:
                heapq.heapreplace(heap, (itr.next(), idx, itr))
            except StopIteration:
                heapq.heappop(heap)

a0 = range(5,20)
a1 = range(10)
a2 = range(15,25)

rc[0]['a'] = a0
rc[1]['a'] = a1
rc[2]['a'] = a2

ra0 = remote_iterator(rc[0],'a')
ra1 = remote_iterator(rc[1],'a')
ra2 = remote_iterator(rc[2],'a')

print 'Merge the local datasets:'
print list(mergesort([a0,a1,a2]))
    
print 'Locally merge the remote sets:'
print list(mergesort([ra0,ra1,ra2]))