This Python code goes through the Iowa GOP's website (actually the info was pulled from the GOP site and posted on my personal site after I cleaned it up a bit), scrapes caucus locations and exports it into a TSV. Based on a tutorial from BuzzData

Iowa caucus location scraper

# Scraper based on this tutorial from BuzzData:
# http://blog.buzzdata.com/post/11871523667/how-to-scrape-toronto-data-a-basic-tutorial

import urllib2
from BeautifulSoup import BeautifulSoup

# Create a file called "ward_pop.tsv" where we'll save our data
f = open('caucus_locations02.tsv', 'w')

# Make a header row: locationname (tab) precinct (tab) address (tab) address2
f.write("locationname" + "\t" + "precinct" + "\t" + "address" + "\t" + "address2" + "\n")

# Location of the page we will scrape
url = 'http://chrisessig.com/caucus_locations02.html'
    
page = urllib2.urlopen(url)
soup = BeautifulSoup(page)

# Will have 1749 caucus precinct locations (total number of locations in Iowa)
for x in range(0, 1749):
    sentence = soup.findAll('div', attrs={'class': 'locationname'})[x].text
    sentence2 = soup.findAll('div', attrs={'class': 'precinct'})[x].text
    sentence3 = soup.findAll('div', attrs={'class': 'address'})[x].text
    sentence4 = soup.findAll('div', attrs={'class': 'address2'})[x].text

    # Extract the information from the word array
    location = str(sentence)
    precinct = str(sentence2)
    address = str(sentence3)
    address2 = str(sentence4)

    #write to file:
    f.write(location + "\t" + precinct + "\t" + address + "\t" + address2 + "\n")
	
#You're done! Close file.	
f.close()