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

Chapter 7
Analytics at Scale
def fetch_score(self, featurename, featurevalue, kind):
pred = 0
try:
key = self.client.key(kind,featurename +
"_" + featurevalue)
res= self.client.get(key)
if res is not None:
pred = res['score']
except:
pass
return pred
def get_score(self, featurename, featurevalue):
with ThreadPoolExecutor(max_workers=5) as pool:
future_score = pool.submit(self.fetch_
score,featurename, featurevalue,self.
scores)
future_prob = pool.submit(self.fetch_
score,featurename, featurevalue,self.
probabilities)
if self.big:
future_howbig = pool.submit(self.
fetch_score,featurename,
featurevalue,self.is_big)
future_predbig = pool.submit(self.
fetch_score,featurename,
featurevalue,self.scores_big)
future_probbig = pool.submit(self.
fetch_score,featurename,
featurevalue,self.probabilities_big)
pred = future_score.result()
prob = future_prob.result()
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