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app.py

@@ -6,7 +6,7 @@ from flask import Flask, request, jsonify
 
 # Initialize Flask app with a name
 app = Flask("Super Kart Product Pricing Predictor")
-saved_model = joblib.load("super_kart_product_pricing_model.joblib")
+model = joblib.load("super_kart_product_pricing_model.joblib")
 
 # Define a route for the home page, used to validate backend is functional and accessible
 @app.get('/')
@@ -19,7 +19,6 @@ def predict_sales():
     # Get JSON data from the request
     data = request.get_json()
 
-    print(f'data = {data}')
     # Extract relevant customer features from the input data. The order of the column names matters.
     sample = {
         'Product_Weight': data['Product_Weight'],
@@ -33,11 +32,10 @@ def predict_sales():
         'Product_Id_char': data['Product_Id_char'].astype(str),
         'Store_Age_Years': data['Store_Age_Years'],
     }
-    print(f'sample = {sample}')
 
     # Convert the extracted data into a DataFrame and preprocess it
     input_data = pd.DataFrame([sample])
-    prediction = saved_model.predict(input_data).tolist()[0]
+    prediction = model.predict(input_data).tolist()[0]
 
     # Return the prediction as a JSON response
     return jsonify({'Predicted Product Price': prediction})