handler.py

import pickle
import os
import pandas as pd
from flask             import Flask, request, Response
from rossmann.Rossmann import Rossmann

# loading model
model = pickle.load( open( 'model/model_rossman.pkl', 'rb') )

# initialize API
app = Flask( __name__ )

@app.route( '/rossmann/predict', methods=['POST'] )
def rossmann_predict():
    test_json = request.get_json()
   
    if test_json: # there is data
        if isinstance( test_json, dict ): # unique example
            test_raw = pd.DataFrame( test_json, index=[0] )
            
        else: # multiple example
            test_raw = pd.DataFrame( test_json, columns=test_json[0].keys() )
            
        # Instantiate Rossmann class
        pipeline = Rossmann()
        
        # data cleaning
        df1 = pipeline.data_cleaning( test_raw )
        
        # feature engineering
        df2 = pipeline.feature_engineering( df1 )
        
        # data preparation
        df3 = pipeline.data_preparation( df2 )
        
        # prediction
        df_response = pipeline.get_prediction( model, test_raw, df3 )
        
        return df_response
        
        
    else:
        return Response( '{}', status=200, mimetype='application/json' )

if __name__ == '__main__':
    port = os.environ.get( 'PORT', 5000 )
    app.run(host='0.0.0.0' , port=port)