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

Chapter 1
Introduction
(pred4,prob4) = self.get_score(f,
value)
return (pred1 + pred2 + pred3 + pred4),
(prob1 + prob2 + prob3 + prob4)
if f == 'client_time':
value = str(self.get_hour(int(value)))
if f == 'domain':
conn = sqlite3.connect('multiplier.db')
cursor = conn.execute("SELECT high,low from
multiplier where domain='" + value + "'")
row = cursor.fetchone()
if row is not None:
self.high = row[0]
self.low = row[1]
return self.get_score(f, value)
def on_post(self, req, resp):
input_json = json.loads(req.stream.
read(),encoding='utf-8')
input_json['ip'] = unicode(req.remote_addr)
pred = 1
prob = 1
with ThreadPoolExecutor(max_workers=8) as pool:
future_array = { pool.submit(self.get_
value,f,input_json[f]) : f for f in
input_json}
for future in as_completed(future_array):
pred1, prob1 = future.result()
pred = pred + pred1
prob = prob - prob1
resp.status = falcon.HTTP_200
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