import urllib.request
import math

def stockCorrelate(ticker1, ticker2):
    prefix = 'http://ichart.finance.yahoo.com/table.csv?s='
    address1 = prefix + ticker1
    address2 = prefix + ticker2
    print('opening',address1)
    url1 = urllib.request.urlopen(address1)
    print('opening',address2)
    url2 = urllib.request.urlopen(address2)    
    t1Data = url1.readlines()
    print(len(t1Data),'lines from',address1)
    t2Data = url2.readlines()
    print(len(t2Data),'lines from',address2)
    t1Data = [line.decode('ascii').split(',') for line in t1Data[1:] ]  
    t2Data = [line.decode('ascii').split(',') for line in t2Data[1:] ]  
    t1Close = []
    t2Close = []
    for i in range(min(len(t1Data), len(t2Data))):   
        assert t1Data[i][0] == t2Data[i][0]
        t1Close.append(float(t1Data[i][6]))
        t2Close.append(float(t2Data[i][6]))      

    return correlation(t1Close, t2Close)

def correlation(xlist, ylist):
    xbar = mean(xlist)
    ybar = mean(ylist)
    xstd = standardDev(xlist)
    ystd = standardDev(ylist)
    num = 0.0
    for i in range(len(xlist)):
        num = num + (xlist[i]-xbar) * (ylist[i]-ybar)
    corr = num / ((len(xlist)-1) * xstd * ystd) 
    return corr

def mean(alist):
    mean = sum(alist) / len(alist)
    return mean

def standardDev(alist):
    theMean = mean(alist)
    
    sum = 0
    for item in alist:
        difference = item - theMean
        diffsq = difference ** 2
        sum = sum + diffsq
        
    sdev = math.sqrt(sum/(len(alist)-1))
    return sdev