| import joblib |
| import pandas as pd |
| from flask import Flask, request, jsonify |
|
|
| app = Flask("Superkart Sales Predictor") |
| model = joblib.load("superkart.joblib") |
|
|
| @app.get('/') |
| def home(): |
| return "Welcome to the Superkart Sales Predictor API" |
|
|
| @app.post('/v1/sales') |
| def predict_sales(): |
| product_data = request.get_json() |
|
|
| sample = { |
| 'Product_Type': product_data['Product_Type'], |
| 'Product_Sugar_Content': product_data['Product_Sugar_Content'], |
| 'Product_Weight': product_data['Product_Weight'], |
| 'Product_Allocated_Area': product_data['Product_Allocated_Area'], |
| 'Product_MRP': product_data['Product_MRP'], |
| 'Store_Id': product_data['Store_Id'], |
| 'Store_Size': product_data['Store_Size'], |
| 'Store_Type': product_data['Store_Type'], |
| 'Store_Location_City_Type': product_data['Store_Location_City_Type'], |
| 'Store_Establishment_Year': product_data['Store_Establishment_Year'] |
| } |
| input_data = pd.DataFrame([sample]) |
| input_data |
|
|
| prediction = model.predict(input_data).tolist()[0] |
| return jsonify({'prediction': prediction}) |
|
|
| if __name__ == '__main__': |
| app.run(debug=True) |
|
|