Pulling related Sentiment about Named Entities
import time
import urllib2
from urllib2 import urlopen
import re
import cookielib
from cookielib import CookieJar
import datetime
import sqlite3
##
import nltk
cj = CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
opener.addheaders = [('User-agent', 'Mozilla/5.0')]
conn = sqlite3.connect('knowledgeBase.db')
c = conn.cursor()
###define processor###
def processor(data):
namedEntArray = []
try:
tokenized = nltk.word_tokenize(data)
tagged = nltk.pos_tag(tokenized)
namedEnt = nltk.ne_chunk(tagged, binary=True)
entities = re.findall(r'NE\s(.*?)/',str(namedEnt))
#('not', 'RB')
descriptives = re.findall(r'\(\'(\w*)\',\s\'JJ\w?\'', str(tagged))
if len(entities) > 1:
pass
elif len(entities) == 0:
pass
else:
print '_________________________'
print 'Named:',entities[0]
print 'Descriptions:'
for eachDesc in descriptives:
print eachDesc
except Exception, e:
print 'failed in the main try of processor'
print str(e)
time.sleep(555)
def huffingtonRSSvisit():
try:
page = 'http://feeds.huffingtonpost.com/huffingtonpost/raw_feed'
sourceCode = opener.open(page).read()
try:
links = re.findall(r'<link.*href=\"(.*?)\"', sourceCode)
for link in links:
if '.rdf' in link:
pass
else:
print 'visiting the link'
print '###################'
linkSource = opener.open(link).read()
linesOfInterest = re.findall(r'<p>(.*?)</p>', str(linkSource))
print 'Content:'
for eachLine in linesOfInterest:
if '<img width' in eachLine:
pass
elif '<a href=' in eachLine:
pass
else:
#change this#
processor(eachLine)
time.sleep(5)
except Exception, e:
print 'failed 2nd loop of huffingtonRSS'
print str(e)
except Exception, e:
print 'failed main loop of huffingtonRSS'
print str(e)
huffingtonRSSvisit()
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