Update app.py

app.py

@@ -8,12 +8,7 @@ st.set_page_config(layout="centered", page_title="Restaurant Data Viewer")
   
 # URLs for the logos  
 MAIN_LOGO_URL = "https://islamictrusthk.org/assets/images/top-logo.png"  
-SIDEBAR_LOGO_URL = "https://bot.islamictrusthk.org/assets/content_files/20240606095159123011.png"  
-  
-# Print the versions of the packages  
-st.write(f"Streamlit version: {st.__version__}")  
-st.write(f"Pandas version: {pd.__version__}")  
-st.write(f"Numpy version: {np.__version__}")  
+SIDEBAR_LOGO_URL = "https://bot.islamictrusthk.org/assets/content_files/20240606095159123011.png" 
   
 # Inject custom CSS for better mobile compatibility  
 st.markdown(  
@@ -95,7 +90,8 @@ def authenticate(username, password):
   
 # Function to trigger rerun  
 def trigger_rerun():  
-    st.experimental_rerun()  
+    st.set_query_params(rerun=str(pd.Timestamp.now()))  
+    st.experimental_rerun()  # Force page reload  
   
 # Authentication block  
 if not st.session_state.authenticated:  
@@ -176,21 +172,18 @@ else:
             # Filter functionality  
             st.subheader("Filters")  
             # Use columns for a more responsive layout  
-            col1, col2, col3, col4, col5 = st.columns(5)  
+            col1, col2, col3, col4 = st.columns(4)  
   
             with col1:  
                 # Filter by Name  
                 name_filter = st.text_input("Name contains")  
             with col2:  
-                # Filter by Cuisine  
-                cuisine_filter = st.multiselect("Cuisine", sorted(df['Cuisine'].drop_duplicates().unique()))  
-            with col3:  
                 # Filter by Location  
                 location_filter = st.multiselect("Location", df['Location'].drop_duplicates())  
-            with col4:  
+            with col3:  
                 # Filter by Restaurant Type  
                 restaurant_type_filter = st.multiselect("Restaurant Type", df['Restaurant Type'].drop_duplicates())  
-            with col5:  
+            with col4:  
                 # Filter by Expiry Date  
                 expiry_date_filter = st.date_input("Expiry Date", [])  
   
@@ -199,8 +192,6 @@ else:
   
             if name_filter:  
                 filtered_df = filtered_df[filtered_df['Name'].str.contains(name_filter, case=False, na=False)]  
-            if cuisine_filter:  
-                filtered_df = filtered_df[filtered_df['Cuisine'].isin(cuisine_filter)]  
             if location_filter:  
                 filtered_df = filtered_df[filtered_df['Location'].isin(location_filter)]  
             if restaurant_type_filter:  
@@ -228,4 +219,4 @@ else:
                     mime='text/csv',  
                 )  
             else:  
-                st.info("No data matches the filter criteria.")  
+                st.info("No data matches the filter criteria.")