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app.py

@@ -1,7 +1,6 @@
 import joblib
 import pandas as pd
 from flask import Flask, request, jsonify
-from datetime import datetime
 
 # Initialize Flask app
 super_kart_api = Flask("Super Kart Product Sales Predictor")
@@ -20,8 +19,6 @@ def predict_product_sales_price():
     # Get JSON data from the request
     product_data = request.get_json()
 
-    Store_Age = datetime.now().year - int(product_data['Store_Establishment_Year'])
-
     # Extract relevant house features from the input data
     sample = {
         'Product_Weight': product_data['Product_Weight'],
@@ -29,7 +26,6 @@ def predict_product_sales_price():
         'Product_Type': product_data['Product_Type'],
         'Product_MRP': product_data['Product_MRP'],
         'Store_Id': product_data['Store_Id'],
-        'Store_Age': Store_Age,
         'Store_Size': product_data['Store_Size'],
         'Store_Location_City_Type': product_data['Store_Location_City_Type'],
         'Store_Type': product_data['Store_Type']
@@ -47,7 +43,6 @@ def predict_product_sales_price():
 # Define an endpoint to predict product sales price for a batch of product
 @super_kart_api.post('/v1/productbatch')
 def predict_product_batch():
-  try:
     # Get the uploaded CSV file from the request
     file = request.files['file']
 
@@ -55,22 +50,18 @@ def predict_product_batch():
     data = pd.read_csv(file)
 
     input_data = data.copy()
-    input_data['Store_Age'] = datetime.now().year - input_data['Store_Establishment_Year']
     input_data = input_data.drop(['Product_Id','Store_Establishment_Year','Product_Allocated_Area'],axis=1)
 
-    
-
     # Make predictions for the batch data
     predictions = model.predict(input_data).tolist()
 
     # Add predictions to the DataFrame
-    data['Predicted_Product_Sales'] = predictions
+    input_data['Predicted_Product_Sales'] = predictions
 
     # Convert results to dictionary
-    result = data.to_dict(orient="records")
-  except Exception as e:
-      return jsonify({'error': str(e)}), 400
-  return jsonify(result)
+    result = input_data.to_dict(orient="records")
+
+    return jsonify(result)
 
 
 # Run the Flask app in debug mode