#!/usr/local/bin/python
import cgi, cgitb, json, os
import opinionsToGraph as OTG
cgitb.enable()
print "Content-Type: text/html"
print
print """
<form>
<center><input type="text" name="searchTerm"><input type="submit" value="Go"></center>
</form>
"""
form = cgi.FieldStorage()
try:
searchTerm = form["searchTerm"].value
nodes = OTG.getNodes('/Users/andrewgambardella/Sites/data/' + searchTerm +
'.txt')
(allNodes, links) = OTG.getAllNodesAndLinks(nodes)
os.system('rm /Users/andrewgambardella/Sites/opinions.json')
with open('/Users/andrewgambardella/Sites/opinions.json', 'w') as out:
out.write(json.dumps({"nodes": allNodes, "links": links}))
print """
<iframe id="graph" width="70%" height="90%" src="http://localhost/~andrewgambardella/graph.html"></iframe>
<iframe id="info" width="29%" height="90%" src="http://localhost/~andrewgambardella/info.html"></iframe>
"""
except:
pass
p[0] = ('List of premises', p[1])
if len(p) == 3:
p[0] = ('List of premises', p[1], p[2])
def p_dHelper(p):
'''dHelper : VC S dHelper
| VC S
| PERIOD dHelper
| PERIOD'''
if len(p) == 2:
p[0] = ('Conclusive verb', p[1])
if len(p) == 3:
p[0] = ('Conclusive verb', p[1], p[2])
if len(p) == 4:
p[0] = ('Conclusive verb', p[1], p[2], p[3])
#Error rule for syntax errors
def p_error(p):
print "Syntax error in input!"
if __name__ == "__main__":
import os
import ply.yacc as yacc
import opinionsToGraph as otg
yacc.yacc()
nodes = []
for aFile in os.listdir('../data/'):
nodes += otg.getNodes('../data/' + aFile)
while 1:
yacc.parse(nodes[0].get('text'))
#!/usr/local/bin/python
import cgi, cgitb, json, os
import opinionsToGraph as OTG
cgitb.enable()
print "Content-Type: text/html"
print
print """
<form>
<center><input type="text" name="searchTerm"><input type="submit" value="Go"></center>
</form>
"""
form = cgi.FieldStorage()
try:
searchTerm = form["searchTerm"].value
nodes = OTG.getNodes('/Users/andrewgambardella/Sites/data/' + searchTerm + '.txt')
(allNodes, links) = OTG.getAllNodesAndLinks(nodes)
os.system('rm /Users/andrewgambardella/Sites/opinions.json')
with open('/Users/andrewgambardella/Sites/opinions.json', 'w') as out:
out.write(json.dumps({"nodes":allNodes,"links":links}))
print """
<iframe id="graph" width="70%" height="90%" src="http://localhost/~andrewgambardella/graph.html"></iframe>
<iframe id="info" width="29%" height="90%" src="http://localhost/~andrewgambardella/info.html"></iframe>
"""
except:
pass
ret = []
with open(filename) as f:
lines = f.readlines()
for line in lines:
line = line.strip()
ret.append(line)
return ret
if __name__ == "__main__":
import argparse, json, os
parser = argparse.ArgumentParser(description='Get links from a file.')
parser.add_argument('f', metavar='filename', action='store', help='Directory of files to parse (LexisNexis format)')
args = parser.parse_args()
nodes = []
for aFile,color in zip(os.listdir(args.f),range(0,len(os.listdir(args.f)))):
nodes += otg.getNodes(args.f + aFile,color)
all_text = []
for node in nodes:
all_text.append(node.get('text') + ' ')
all_text = ''.join(all_text)
trainer = punkt.PunktSentenceTokenizer()
trainer.train("data/real_estate.txt") #Sentence fragmenter trained on real_estate (arbitrarily)
sentTokens = trainer.tokenize(all_text)
wordTokens = [nltk.wordpunct_tokenize(s) for s in sentTokens]
flatWords = [item.lower() for sublist in wordTokens for item in sublist if item.isalpha()] #puts all words into one list
finder = BigramCollocationFinder.from_words(flatWords)
finder.apply_word_filter(lambda w: w in getBlacklist('data/english.stop.txt'))
bigram_measures = nltk.collocations.BigramAssocMeasures()
scored = finder.score_ngrams(bigram_measures.likelihood_ratio)
print scored
