Model logs

app.py

@@ -3,10 +3,19 @@ from joblib import load
 from PIL import Image
 
 import pandas as pd
+import random
 import streamlit as st
 
 model = load("model.joblib")
 
+session = st.session_state
+
+if 'df' not in session:
+    session.df = pd.read_csv("model_log.csv").drop_duplicates()
+
+if 'user_id' not in session:
+    session.user_id = random.randint(1, 1_000_000)
+
 st.markdown('# Titanic Workshop - Would you be able to survive the Titanic disaster?')
 image = Image.open('titanic.jpeg')
 st.image(image)
@@ -43,10 +52,8 @@ passenger_data = {
     'Parch': parents,
 }
 
-passenger_data_df = pd.DataFrame.from_dict([passenger_data])
-
 if st.button("Calculate my chances of survival"):
-
+    passenger_data_df = pd.DataFrame.from_dict([passenger_data])
     prediction = model.predict(passenger_data_df)[0]
     prediction_proba = model.predict_proba(passenger_data_df)[:,1][0]
 
@@ -62,8 +69,21 @@ if st.button("Calculate my chances of survival"):
     
     st.write(f"Probabilty of survival: {round(prediction_proba, 2)* 100}%.")
 
-    passenger_data_df.insert(0, "date", str(datetime.now()))
-    passenger_data_df["survived"] = prediction
-    passenger_data_df["survival_prob"] = prediction_proba
+    passenger_data['user_id'] = session.user_id
+    passenger_data['date'] = str(datetime.now())
+    passenger_data["survived"] = prediction
+    passenger_data["survival_prob"] = prediction_proba
+    
+    session.df = pd.concat(
+        [
+            session.df,
+            pd.DataFrame([passenger_data])
+        ],
+        ignore_index=True
+        )
+    
+    session.df.drop_duplicates().to_csv('model_log.csv', mode="a", header=False, index=False)
 
-    passenger_data_df.to_csv('model_log.csv', mode='a', header=False, index=False)
+session.df = pd.read_csv("model_log.csv")
+session.df = session.df.drop_duplicates()
+session.df.to_csv("model_log.csv", index=False)

model_log.csv

@@ -1,2 +1 @@
-date,Age,is_male,Pclass_class 1,Pclass_class 2, Pclass_class 3, Embarked_C, Embarked_Q, Embarked_S, SibSp, Parch, survived, survival_prob,
-
+Age,is_male,Pclass_class 1,Pclass_class 2,Pclass_class 3,Embarked_C,Embarked_Q,Embarked_S,SibSp,Parch,user_id,date,survived,survival_prob