Dadegan valency matching

matching.py

import codecs
from search.models import Valency, Dependency

for verb in codecs.open('static/verbs.txt', encoding='utf8'):
    verb = verb.strip()
	count = len(Dependency().findVerbSentences(verb))
	for valency in Valency().find(verb):
		print '%-15s\t%s %s' % ('%d/%d' % (len(valency['sentences']), count), valency['verb']['surface'].encode('utf8'), Valency().str(valency['verb']['valency']).encode('utf8'))

Just put it in dadegan root directory and make matching list.