application.py

from flask import Flask,request,render_template
import numpy as np
import pandas as pd
import sys
sys.path.append('')

from sklearn.preprocessing import StandardScaler
from src.pipeline.predict_pipeline import CustomData,PredictPipeline


application = Flask(__name__)

app = application

# Route for the home page

@app.route('/')
def index():
    return render_template('index.html')


@app.route('/predictdata',methods = ["GET","POST"])
def predict_datapoint():
    if request.method == "GET":
        return render_template('home.html')
    else:
        data = CustomData(
            NetThrust = request.form.get('NetThrust'),
            CoreNozzleGrossThrust = request.form.get('CoreNozzleGrossThrust'),
            BypassNozzleGrossThrust = request.form.get('BypassNozzleGrossThrust'),
            Sp_FuelConsumption = request.form.get('Sp_FuelConsumption'),
            SpecificThrust = request.form.get('SpecificThrust'),
            CoreNozzleVel = request.form.get('CoreNozzleVel'),
            CoreNozzlePressureRatio = request.form.get('CoreNozzlePressureRatio'),
            BypassNozzleVel = request.form.get('BypassNozzleVel'),
            BypassNozzlePressureRatio = request.form.get('BypassNozzlePressureRatio'),
            BurnerEfficiency = request.form.get('BurnerEfficiency'),
            EnginePressureRatio = request.form.get('EnginePressureRatio'),
            HPSpoolSpeed = request.form.get('HPSpoolSpeed'),
            LPSpoolSpeed = request.form.get('LPSpoolSpeed'),
            FuelFlow = request.form.get('FuelFlow'),
            LPTExitPressure = request.form.get('LPTExitPressure'),
            LPTExitTemperature = request.form.get('LPTExitTemperature')
        )


        pred_df = data.get_data_as_data_frame()
        print(pred_df)

        predict_pipeline = PredictPipeline()
        results = predict_pipeline.predict(pred_df)
        return render_template('home.html',results = results[0])


if __name__ == "__main__":
    app.run(host="0.0.0.0", debug=True)