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app.py

@@ -2,8 +2,10 @@
 import numpy as np
 import joblib  # For loading the serialized model
 import pandas as pd  # For data manipulation
+import logging #DEEPA
 from flask import Flask, request, jsonify  # For creating the Flask API
 
+
 # Initialize the Flask application
 product_sales_predictor_api = Flask("SuperKart Product Sales Predictor")
 
@@ -66,7 +68,11 @@ def predict_sales_batch():
     and returns the predicted  product sales prices as a dictionary in the JSON response.
     """
 
-    print("The function has entered")
+    handler = logging.FileHandler('app.log')
+    app.logger.addHandler(handler)
+    app.logger.setLevel(logging.INFO)
+    app.logger.info('Request received')
+    
     # Get the uploaded CSV file from the request
     file = request.files['file']