import urllib

​

class Day:

    def __init__(self, date, open, high, low, close, volume):

        self.date = date

        self.open=float(open); self.high=float(high); self.low=float(low); self.close=float(close)

        self.volume=int(volume)

    def __repr__(self):

        return '%10s %4.2f %4.2f %4.2f %4.2f %10d'%(self.date, self.open, self.high, 

                   self.low, self.close, self.volume)

​

class Stock:

    def __init__(self, symbol):

        self.symbol = symbol.upper()

​

    def __repr__(self):

        return "%s (%s)"%(self.symbol, self.yahoo()['price'])

    def yahoo(self):

        url = 'http://finance.yahoo.com/d/quotes.csv?s=%s&f=%s' % (self.symbol, 'l1c1va2xj1b4j4dyekjm3m4rr5p5p6s7')

        values = urllib.urlopen(url).read().strip().strip('"').split(',')

        data = {}

        data['price'] = values[0]

        data['change'] = values[1]

        data['volume'] = values[2]

        data['avg_daily_volume'] = values[3]

        data['stock_exchange'] = values[4]

        data['market_cap'] = values[5]

        data['book_value'] = values[6]

        data['ebitda'] = values[7]

        data['dividend_per_share'] = values[8]

        data['dividend_yield'] = values[9]

        data['earnings_per_share'] = values[10]

        data['52_week_high'] = values[11]

        data['52_week_low'] = values[12]

        data['50day_moving_avg'] = values[13]

        data['200day_moving_avg'] = values[14]

        data['price_earnings_ratio'] = values[15]

        data['price_earnings_growth_ratio'] = values[16]

        data['price_sales_ratio'] = values[17]

        data['price_book_ratio'] = values[18]

        data['short_ratio'] = values[19]

        return data

​

    def historical(self):

        try:

            return self.__historical

        except AttributeError:

            pass

        symbol = self.symbol

        def get_data(exchange):

             name = get_remote_file('http://finance.google.com/finance/historical?q=%s:%s&output=csv'%(exchange, symbol.upper()), 

                       verbose=False)

             return open(name).read()

        R = get_data('NASDAQ')

        if "Bad Request" in R:

             R = get_data("NYSE")

        R = R.splitlines()

        headings = R[0].split(',')

        self.__historical = []

        try:

            for x in reversed(R[1:]):

                date, opn, high, low, close, volume = x.split(',')

                self.__historical.append(Day(date, opn,high,low,close,volume))

        except ValueError:

             pass

        self.__historical = Sequence(self.__historical,cr=True,universe=lambda x:x)

        return self.__historical

​

    def plot_average(self, spline_samples=10):

        d = self.historical()

        if len(d) == 0:

            return text('no historical data at Google Finance about %s'%self.symbol, (0,3))

        avg = list(enumerate([(z.high+z.low)/2 for z in d]))

        P = line(avg) + points(avg, rgbcolor='black', pointsize=4) + \

                 text(self.symbol, (len(d)*1.05, d[-1].low), horizontal_alignment='right', rgbcolor='black')

        if spline_samples > 0:

            k = 250//spline_samples

            spl = spline([avg[i*k] for i in range(len(d)//k)] + [avg[-1]])

            P += plot(spl, (0,len(d)+30), color=(0.7,0.7,0.7))

        P.xmax(260)

        return P

​

    def plot_diff(self):

        d = self.historical()

        if len(d) == 0:

            return text('no historical data at Google Finance about %s'%self.symbol, (0,3))

        diff = [] 

        for i in range(1, len(d)):

             z1 = d[i]; z0 = d[i-1]

             diff.append((i, (z1.high+z1.low)/2 - (z0.high + z0.low)/2))

        P = line(diff,thickness=0.5) + points(diff, rgbcolor='black', pointsize=4) + \

                 text(self.symbol, (len(d)*1.05, 0), horizontal_alignment='right', rgbcolor='black')

        P.xmax(260)

        return P

​

symbols = ['bsc', 'vmw', 'sbux', 'aapl', 'amzn', 'goog', 'wfmi', 'msft', 'yhoo', 'ebay', 'java', 'rht', ]; symbols.sort()

stocks = dict([(s,Stock(s)) for s in symbols])

​

@interact

def data(symbol = symbols, other_symbol='', spline_samples=(8,[0..15])):

     if other_symbol != '':

         symbol = other_symbol

     S = Stock(symbol)

     html('<h1 align=center><font color="darkred">%s</font></h1>'%S)

     S.plot_average(spline_samples).save('avg.png', figsize=[10,2])

     S.plot_diff().save('diff.png', figsize=[10,2])

​

     Y = S.yahoo()

     k = list(Y); k.sort()

     html('Price during last 52 weeks:<br>Grey line is a spline through %s points (do not take seriously!):<br> <img src="cell://avg.png">'%spline_samples)

     html('Difference from previous day:<br> <img src="cell://diff.png">')

     html('<table align=center>' + '\n'.join('<tr><td>%s</td><td>%s</td></tr>'%(k[i], Y[k[i]]) for i in range(len(k))) + '</table>')