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

Chapter 7
Analytics at Scale
if prob > 0.9:
prob = 0.9
if self.big:
high, low, high_big, low_big =
thread.result()
if howbig > 0.6:
high = high_big
low = low_big
else:
high, low = thread.result()
multiplier = low + (high -low)*prob
res = multiplier*res
resp.body = str(res)
#except Exception,e:
# print(str(e))
# resp.status = falcon.HTTP_200
# resp.body = str("0.1")
cors = CORS(allow_all_origins=True,allow_all_
methods=True,allow_all_headers=True)
wsgi_app = api = falcon.API(middleware=[cors.middleware])
f = open('publishers2.list_test')
for line in f:
if "#" not in line:
fields = line.strip().split('\t')
domain = fields[0].strip()
big = (fields[1].strip() == '1')
p = Predictor(domain, big)
url = '/predict/' + domain
api.add_route(url, p)
f.close()
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