initial commit

app.py

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+import streamlit as st
+import pandas as pd
+import requests
+
+def run():
+    with st.form(key='form_parameters'):
+        passenger_id = st.number_input('Passenger ID', step=1)
+        passenger_class = st.radio('Passenger Class', (1, 2, 3))
+        passenger_name = st.text_input('Passenger Name')
+        sex = st.radio('Sex', ('male', 'female'))
+        age = st.number_input('Age', min_value=0, value=17)
+        sibsp = st.number_input('Sibling/Spouse', min_value=0, value=0)
+        parch = st.number_input('Parent/Children', min_value=0, value=0)
+        ticket_number = st.text_input('Ticket Number') 
+        fare = st.number_input('Fare', min_value=0, value=10) 
+        cabin_number = st.text_input('Cabin Number')
+        embarked = st.radio('Port of Embarkation', ('C', 'Q', 'S'))
+
+        submitted = st.form_submit_button('Predict')
+    
+    # Create A New data
+    data_inf = {
+        'PassengerId': passenger_id,
+        'Pclass': passenger_class, 
+        'Name': passenger_name, 
+        'Sex': sex, 
+        'Age': age, 
+        'SibSp': sibsp,
+        'Parch': parch, 
+        'Ticket': ticket_number, 
+        'Fare': fare, 
+        'Cabin': cabin_number, 
+        'Embarked': embarked
+    }
+
+    if submitted:
+        # Show Inference DataFrame
+        st.dataframe(pd.DataFrame([data_inf]))
+        print('[DEBUG] Data Inference : \n', data_inf)
+        
+        # Predict
+        URL = "https://backend-titanic-danu.koyeb.app/predict"
+        r = requests.post(URL, json=data_inf)
+
+        if r.status_code == 200:
+            res = r.json()
+            st.write('## Prediction : ', res['label_names'])
+            print('[DEBUG] Result : ', res)
+            print('')
+        else:
+            st.write('Error with status code ', str(r.status_code))
+        
+
+if __name__ == '__main__':
+    run()

requirements.txt

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+streamlit
+pandas