sadness

import operator
import numpy

def average(itemlist, dictratings):
    '''Returns a list consisting of the average ratings for each
    item'''

    lst = []
    for num in range(len(itemlist)):
        nlst = []
        for v in dictratings.values():
            nlst.append(v[num])
        leng = len([num for num in nlst if num != 0])
        avg = sum(nlst) / float(leng)
        lst.append(avg)
    ans = list(zip(itemlist, lst))
    averageList = sorted(ans, key = operator.itemgetter(1), reverse=True)
    return averageList


def similarities(name, dictratings):
    '''Returns a list of tuples, sorted based on how similar
    others are to the given name
    '''
    print dictratings
    orig = dictratings[name]

    lst = []
    dictratings.pop(name)
    for a,b in dictratings.iteritems():
        dp = numpy.dot(orig, b)
        tp = (a, float(dp))
        lst.append(tp)
    similarList = sorted(lst, key = operator.itemgetter(1), reverse=True)
#     return similarList


def recommended(simlist, itemlist, dictratings, n):
    '''Returns the recommended list, which is weighted based on
    how similar the tastes of person is to others
    '''

    nsimlist = simlist[:n]

    lst = []
    for elem in nsimlist:
        vec = dictratings[elem[0]]
        c = elem[1]
        slst = [c*b for b in dictratings[elem[0]]]
        lst.append(slst)

#         print elem[0]
#         print vec
#         print c
#


    leng = len(lst[0])
    finlst = []
    zlst = []
    for num in range(leng):
        sum = 0
        zcount = 0
        for sublst in lst:
            sum += sublst[num]
            if sublst[num] != 0:
                zcount += 1
        finlst.append(sum)
        zlst.append(zcount)

    ans = [a/b for a,b in zip(finlst, zlst)]
    finans = [(a,b) for a,b in zip(itemlist, ans)]
    recommendList = sorted(finans, key=operator.itemgetter(1), reverse=True)
    return recommendList


itemlist = ['IlForno', 'TheCommons', 'DivinityCafe', 'PandaExpress', 'TheSkillet', 'Tandoor', 'McDonalds']
dictratings = {'JoJo': [0, 0, 0, 1, 1, 3, 1], 'SoonLee': [1, 0, 3, -3, -1, 5, 0], 'Lee': [1, 3, 5, 0, 3, 3, 0], 'Bruce': [3, 3, 5, 3, 1, 3, 1], 'Xiawei': [0, 5, 5, -5, 1, 0, -3], 'Shirley': [3, 3, 5, 0, 0, 1, -1]}
simlist = similarities("Xiawei", dictratings)
n = 3

print similarities("SoonLee", dictratings)
# print recommended(simlist, itemlist, dictratings, n)