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app.py

@@ -66,32 +66,32 @@ def predict_churn_batch():
 
     return output_dict
 
-### Debugger function
-@churn_predictor_api.post('/v1/customer')
-def predict_churn():
-    try:
-        customer_data = request.get_json()
-        sample = {
+# ### Debugger function
+# @churn_predictor_api.post('/v1/customer')
+# def predict_churn():
+#     try:
+#         customer_data = request.get_json()
+#         sample = {
             
-            'Partner': customer_data['Partner'],
-            'Dependents': customer_data['Dependents'],
-            'PhoneService': customer_data['PhoneService'],
-            'InternetService': customer_data['InternetService'],
-            'Contract': customer_data['Contract'],
-            'PaymentMethod': customer_data['PaymentMethod'],
-            'tenure': customer_data['tenure'],
-            'MonthlyCharges': customer_data['MonthlyCharges'],
-            'TotalCharges': customer_data['TotalCharges'],
-            'SeniorCitizen':customer_data['SeniorCitizen']
-            }
+#             'Partner': customer_data['Partner'],
+#             'Dependents': customer_data['Dependents'],
+#             'PhoneService': customer_data['PhoneService'],
+#             'InternetService': customer_data['InternetService'],
+#             'Contract': customer_data['Contract'],
+#             'PaymentMethod': customer_data['PaymentMethod'],
+#             'tenure': customer_data['tenure'],
+#             'MonthlyCharges': customer_data['MonthlyCharges'],
+#             'TotalCharges': customer_data['TotalCharges'],
+#             'SeniorCitizen':customer_data['SeniorCitizen']
+#             }
       
 
-        input_data = pd.DataFrame([sample])
-        prediction = model.predict(input_data).tolist()[0]
-        prediction_label = "churn" if prediction == 1 else "not churn"
-        return jsonify({'Prediction': prediction_label})
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
+#         input_data = pd.DataFrame([sample])
+#         prediction = model.predict(input_data).tolist()[0]
+#         prediction_label = "churn" if prediction == 1 else "not churn"
+#         return jsonify({'Prediction': prediction_label})
+#     except Exception as e:
+#         return jsonify({"error": str(e)}), 500
 ### debugger Ends
 
 # Run the Flask app in debug mode