Customer-Churn-Project/app.py at main · Dhanush-Raj1/Customer-Churn-Project · GitHub

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from src.logger import logging
from src.pipelines.predict_pipeline import Predict, NewData

from flask import Flask, request, render_template

application = Flask(__name__)
app = application

# route for home page
@app.route('/')
def home():
    return render_template('home_page.html')


# route for predict page
@app.route('/predictdata', methods=['GET', 'POST'])
def predict():
    if request.method == 'GET':
        return render_template('predict_page.html')

    else:
        logging.info("POST Request has been made.")
        data = NewData( gender = request.form.get('Gender'),
                        SeniorCitizen = request.form.get('Senior Citizen'),
                        Partner = request.form.get('Partner'),
                        Dependents = request.form.get('Dependents'),
                        tenure = request.form.get('Tenure (months)'),
                        PhoneService = request.form.get('Phone Service'),
                        MultipleLines = request.form.get('Multiple Lines'),
                        InternetService = request.form.get('Internet Service'),
                        OnlineSecurity = request.form.get('Online Security'),
                        OnlineBackup = request.form.get('Online Backup'),
                        DeviceProtection = request.form.get('Device Protection'),
                        TechSupport = request.form.get('Tech Support'),
                        StreamingTV = request.form.get('Streaming TV'),
                        StreamingMovies = request.form.get('Streaming Movies'),
                        Contract = request.form.get('Contract Type'),
                        PaperlessBilling = request.form.get('Paperless Billing'),
                        PaymentMethod = request.form.get('Payment Method'),
                        MonthlyCharges = float(request.form.get('Monthly Charges')),
                        TotalCharges = float(request.form.get('Total Charges'))  )

        df = data.get_data_as_dataframe()
        logging.info("Data has been converted in to a DataFrame.")
        logging.info(f"DataFrame: \n{df.head()}")
        print(df.head())

        prediction = Predict()
        result = prediction.predict_data(df)
        print("Prediction result:", result)
        logging.info("Prediction Result: {result}")

        result_text = ""
        if result == 0:
            result_text = "Your customer will not churn from your business."
        else:
            result_text = "Your customer will churn from your business."

        return render_template('predict_page.html', result=result[0], result_text = result_text)

        #except Exception as e:
           # return render_template('predict_page.html', error=str(e))

    #else:
        #return render_template('predict_page.html')


if __name__ == "__main__":
    app.run(host='0.0.0.0', port=8000, debug=True, use_reloader=False)

    # host='0.0.0.0' is for aws eks, to make the app public
    # port=8000 to match the port in deployment.yaml and dockerfile
    # debug=False for production debug=True mode can cause issues
    # when deployed in eks the above app.run() command is ignored as gunicorn is used (in dockerfile) to run the app