scrape_web

'''

'''
import urllib.request as urllib2 
from bs4 import BeautifulSoup 
import csv 
from datetime import datetime 

# Bloomberg URL
quote_page = 'http://www.bloomberg.com/quote/SPX:IND' 

# Query the website and return the HTML to the variable page 
page = urllib2.urlopen(quote_page) 

# parse the html using beautiful soup and store in a variable called soup
soup = BeautifulSoup(page, 'html.parser')

name_box = soup.find('h1', attrs = {'class': 'name'})

name = name_box.text.strip()
print(name)

price_box = soup.find('div', attrs = {'class': 'price'})
price = price_box.text
print(price)

# Open a csv file with append, so old data will not be erased 
with open('sp_index.csv', 'a') as csv_file:
    writer = csv.writer(csv_file)
    writer.writerow([name, price, datetime.now()])