Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

Chapter 1
Introduction
metadata1 = MetaData(db1)
metadata2 = MetaData(db2)
metadata3 = MetaData(db3)
self.scores = Table('scores', metadata1, autoload=True)
self.probabilities = Table('probabilities', metadata2,
autoload=True)
self.ctr = Table('ctr', metadata3, autoload=True)
client = MongoClient(connect=False,maxPoolSize=1)
self.db = client.frequency
self.gi = pygeoip.GeoIP('GeoIP.dat')
self.high = 1.2
self.low = .8
def get_hour(self,timestamp):
return dt.datetime.utcfromtimestamp(timestamp / 1e3).hour
def get_score(self, featurename, featurevalue):
prob = 0
pred = 0
s = self.scores.select((self.scores.c.feature_name
== featurename) & (self.scores.c.feature_value ==
featurevalue))
rs = s.execute()
row = rs.fetchone()
if row is not None:
pred = pred + float(row['score'])
s = self.probabilities.select((self.probabilities.c.feature_
name == featurename) & (self.probabilities.c.feature_value ==
featurevalue))
rs = s.execute()
row = rs.fetchone()
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