def run(self):
config = {
'user': '******',
'passwd': 'RDKC1VlNyLSg',
'host': '127.7.115.1',
'db': 'backup'
}
self.cnx = MySQLdb.connect(**config)
logging.info("Classifying For %s." % self.Company)
neg_count = 0
pos_count = 0
try:
if (self.cnx == None):
self.cnx = MySQLdb.connect(**config)
d = datetime.datetime.today()
america = timezone('America/New_York')
india = timezone('Asia/Kolkata')
dd = america.localize(d)
dd = dd.astimezone(india)
get_tweet = "select * from tweets_" + self.Company + " where sentiment!=1"
cur = self.cnx.cursor()
cur.execute(get_tweet)
db_tweets = cur.fetchall()
for line in db_tweets:
value = PyClassi.classify(line[1], self.Company)
if value == 0:
neg_count += 1
elif value == 2:
pos_count += 1
update = "update tweets_" + self.Company + " set classified=" + str(
value) + " where id=" + str(line[0])
cur.execute(update)
sen_value = float(pos_count) / neg_count
add_Stock = "INSERT ignore INTO bay_%s VALUES (%s,%s)"
cur.execute(add_Stock % (self.Company, "'" + str(sen_value) + "'",
"'" + dd.strftime('%Y-%m-%d') + "'"))
self.cnx.commit()
except Exception as e:
logging.info(self.Company + "Error : " + str(type(e)) + str(e))
else:
logging.info(self.Company +
"Bayesian value Added To Database For %s." %
self.Company)
self.cnx.close()
def run(self):
config = {'user': '******','passwd': 'RDKC1VlNyLSg','host': '127.7.115.1','db': 'backup'}
self.cnx = MySQLdb.connect(**config)
logging.info("Classifying For %s."%self.Company)
neg_count=0
pos_count=0
try:
if(self.cnx==None):
self.cnx = MySQLdb.connect(**config)
d = datetime.datetime.today()
america=timezone('America/New_York')
india=timezone('Asia/Kolkata')
dd=america.localize(d)
dd=dd.astimezone(india)
get_tweet = "select * from tweets_"+self.Company+" where sentiment!=1"
cur=self.cnx.cursor()
cur.execute(get_tweet)
db_tweets = cur.fetchall()
for line in db_tweets:
value=PyClassi.classify(line[1],self.Company)
if value==0:
neg_count+=1
elif value==2:
pos_count+=1
update="update tweets_"+self.Company+" set classified="+str(value)+" where id="+str(line[0])
cur.execute(update)
sen_value=float(pos_count)/neg_count
add_Stock = "INSERT ignore INTO bay_%s VALUES (%s,%s)"
cur.execute(add_Stock%(self.Company,"'"+str(sen_value)+"'","'"+dd.strftime('%Y-%m-%d')+"'"))
self.cnx.commit()
except Exception as e :
logging.info(self.Company+"Error : "+str(type(e))+str(e))
else :
logging.info(self.Company+"Bayesian value Added To Database For %s."%self.Company)
self.cnx.close()
#! /usr/bin/python
import PyClassi as Classifier
from re import sub
import PyNegator
test=open("test.txt")
correct=0
wrong=0
falsepositive=0
falsenegative=0
for line in test.readlines():
status=line[0]
lne=sub(r"[!]|[.]|[#][^ ]+|[&]|[-]|[?]|[_]|((http|https)://)[^ ]+|\w*[@][^ ]+|\b[\S0-9]\b",'',line.lower())
classi=Classifier.classify(lne)
if status=='0': #polarity representation reversed for database representation sake :-/
if classi==status:
correct+=1
else:
falsepositive+=1
wrong+=1
elif status=='1':
if classi==status:
correct+=1
else:
falsenegative+=1
wrong+=1
print "Correct : ",correct,"\n Wrong : ",wrong,"\n falsenegative : ",falsenegative,"\n falsepositive",falsepositive
print "\n ratio : ",(float(correct)/(correct+wrong))*100
