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app.py
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from flask import Flask, render_template, request
import os
import numpy as np
import pandas as pd
from mlProject.pipeline.prediction import PredictionPipeline
app = Flask(__name__) # initializing a flask app
@app.route('/',methods=['GET']) # route to display the home page
def homePage():
return render_template("index.html")
@app.route('/train',methods=['GET']) # route to train the pipeline
def training():
os.system("python main.py")
return "Training Successful!"
@app.route('/predict',methods=['POST','GET']) # route to show the predictions in a web UI
def index():
if request.method == 'POST':
try:
# reading the inputs given by the user
destination = float(request.form['destination'])
passanger = float(request.form['passanger'])
weather = float(request.form['weather'])
temparature = float(request.form['temparature'])
time = float(request.form['time'])
coupon = float(request.form['coupon'])
expiration = float(request.form['expiration'])
gender = float(request.form['gender'])
age = float(request.form['age'])
maritalStatus = float(request.form['maritalStatus'])
has_children = int(request.form['has_children'])
education = float(request.form['education'])
income = float(request.form['income'])
to_coupon = int(request.form['to_coupon'])
coupon_freq = float(request.form['coupon_freq'])
occupation_class = int(request.form['occupation_class'])
data = [destination, passanger, weather, temparature, time, coupon, expiration, gender, age, maritalStatus, has_children, education, income, to_coupon, coupon_freq, occupation_class]
data = np.array(data).reshape(1, 16)
obj = PredictionPipeline()
predict = obj.predict(data)
if predict == 1:
predict = "Coupon will be accepted"
else:
predict = "Coupon will not be accepted"
return render_template('results.html', prediction = str(predict))
except Exception as e:
print('The Exception message is: ',e)
return 'Something is Wrong'
else:
return render_template('index.html')
if __name__ == "__main__":
# app.run(host="0.0.0.0", port = 8080, debug=True)
app.run(host="0.0.0.0", port = 8080)