try 2

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-import main from main
+import main_fn from main
 
 #Input structure
 ##Postal_,age_,town_,storey_,room_ = 680705, 30, 'CHOA CHU KANG', 12, '5 ROOM'
@@ -8,7 +8,7 @@ town_list = ['ANG MO KIO', 'BEDOK', 'BISHAN', 'BUKIT BATOK', 'BUKIT MERAH', 'BUK
 room_list = ['1 ROOM', '2 ROOM', '3 ROOM', '4 ROOM', '5 ROOM', 'EXECUTIVE', 'MULTI-GENERATION']
 
 iface = gr.Interface(
-    fn=main, 
+    fn=main_fn, 
     inputs= [
             gr.inputs.Number(default=680705, label='Postal Code'),
             gr.inputs.Number(default=25, label='Age'),

main.py

@@ -1,7 +1,6 @@
 import json
 import requests
 from misc import nearest_mrt
-import time
 import pickle
 import os
 import pandas as pd
@@ -9,7 +8,7 @@ import pandas as pd
 ###This is to create MRT names and MRT locations
 
 
-def main(Postal_,age_,town_,storey_,room_):
+def main_fn(Postal_,age_,town_,storey_,room_):
 ##Input structure into model is##
     filename = 'finalized_model.sav'
 
@@ -91,5 +90,5 @@ def main(Postal_,age_,town_,storey_,room_):
 
 if __name__ == "__main__":
     Postal_,age_,town_,storey_,room_ = 680705, 30, 'CHOA CHU KANG', 12, '5 ROOM'
-    price = main(Postal_,age_,town_,storey_,room_)
+    price = main_fn(Postal_,age_,town_,storey_,room_)
     print(price)

misc.py

@@ -2,11 +2,7 @@ from dateutil.parser import parse
 import geopy.distance
 import json
 from datetime import datetime
-import math
 
-
-
-storey_dict = {'01 TO 03': 1, '04 TO 06': 2, '07 TO 09': 3, '10 TO 12': 4, '13 TO 15': 5, '16 TO 18': 6, '19 TO 21': 7, '22 TO 24': 8, '25 TO 27': 9, '28 TO 30': 10, '31 TO 33': 11, '34 TO 36': 12, '37 TO 39': 13, '40 TO 42': 14, '43 TO 45': 15, '46 TO 48': 16, '49 TO 51':17}
 RPI_dict = {'2Q2022': 163.9, '1Q2022': 159.5, '4Q2021': 155.7, '3Q2021': 150.6, '2Q2021': 146.4, '1Q2021': 142.2, '4Q2020': 138.1, '3Q2020': 133.9, '2Q2020': 131.9, '1Q2020': 131.5, '4Q2019': 131.5, '3Q2019': 130.9, '2Q2019': 130.8, '1Q2019': 131, '4Q2018': 131.4, '3Q2018': 131.6, '2Q2018': 131.7, '1Q2018': 131.6, '4Q2017': 132.6, '3Q2017': 132.8, '2Q2017': 133.7, '1Q2017': 133.9}
 
 def is_date(string, fuzzy=False):