Update app.py

app.py

@@ -10,11 +10,6 @@ st.set_page_config(layout="centered", page_title="Restaurant Data Viewer")
 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__}")  
-  
 # Inject custom CSS for better mobile compatibility  
 st.markdown(  
     """  
@@ -66,13 +61,13 @@ def display_tiles(df, cols):
     for i, (_, row) in enumerate(df.iterrows()):  
         col = cols[i % len(cols)]  
         with col:  
-            st.markdown(f"**Name:** {row['Name']}")  
-            st.markdown(f"**Cuisine:** {row['Cuisine']}")  
-            st.markdown(f"**Location:** {row['Location']}")  
-            st.markdown(f"**Restaurant Type:** {row['Restaurant Type']}")  
+            st.markdown(f"**Company Name:** {row['Company Name']}")  
+            st.markdown(f"**Region:** {row['Region']}")  
+            st.markdown(f"**Factory Type:** {row['Factory Type']}")  
             st.markdown(f"**Expiry Date:** {row['Expiry Date']}")  
-            st.markdown(f"**Website:** {row['Website']}")  
-            st.markdown(f"**Directions:** {row['Directions']}")  
+            st.markdown(f"**Contact:** {row['Contact']}")  
+            st.markdown(f"**Phone:** {row['Phone']}")  
+            st.markdown(f"**E-mail:** {row['E-mail']}")  
             st.markdown("---")  
   
 # Initialize session state  
@@ -95,14 +90,15 @@ def authenticate(username, password):
   
 # Function to trigger rerun  
 def trigger_rerun():  
-    st.experimental_set_query_params(rerun=str(pd.Timestamp.now()))  
+    st.experimental_rerun()  
   
 # Authentication block  
 if not st.session_state.authenticated:  
     st.title("Login")  
     username = st.text_input("Username")  
     password = st.text_input("Password", type="password")  
-    if st.button("Login"):  
+    login_button = st.button("Login")  
+    if login_button:  
         if authenticate(username, password):  
             st.session_state.authenticated = True  
             trigger_rerun()  
@@ -159,14 +155,18 @@ else:
         df = st.session_state.df  
   
         # Define required columns  
-        required_columns = ['Name', 'Cuisine', 'Location', 'Restaurant Type', 'Expiry Date', 'Website', 'Directions']  
+        required_columns = [  
+            'Issued Date', 'Expiry Date', 'Cert. No', 'Company Name', 'Address', 'Region',   
+            'Factory Type', 'Contact', 'Phone', 'E-mail', 'Status', 'Member Since'  
+        ]  
   
         # Verify required columns  
         missing_columns = verify_columns(df, required_columns)  
         if missing_columns:  
             st.error(f"The following required columns are missing from the uploaded file: {', '.join(missing_columns)}")  
         else:  
-            # Format the expiry date column to remove time  
+            # Format the date columns to remove time  
+            df = format_date_column(df, 'Issued Date')  
             df = format_date_column(df, 'Expiry Date')  
   
             # Display the dataframe  
@@ -179,14 +179,14 @@ else:
             col1, col2, col3, col4 = st.columns(4)  
   
             with col1:  
-                # Filter by Name  
-                name_filter = st.text_input("Name contains")  
+                # Filter by Company Name  
+                company_name_filter = st.text_input("Company Name contains")  
             with col2:  
-                # Filter by Location  
-                location_filter = st.multiselect("Location", df['Location'].drop_duplicates())  
+                # Filter by Region  
+                region_filter = st.multiselect("Region", df['Region'].drop_duplicates())  
             with col3:  
-                # Filter by Restaurant Type  
-                restaurant_type_filter = st.multiselect("Restaurant Type", df['Restaurant Type'].drop_duplicates())  
+                # Filter by Factory Type  
+                factory_type_filter = st.multiselect("Factory Type", df['Factory Type'].drop_duplicates())  
             with col4:  
                 # Filter by Expiry Date  
                 expiry_date_filter = st.date_input("Expiry Date", [])  
@@ -194,12 +194,12 @@ else:
             # Apply filters  
             filtered_df = df.copy()  
   
-            if name_filter:  
-                filtered_df = filtered_df[filtered_df['Name'].str.contains(name_filter, case=False, na=False)]  
-            if location_filter:  
-                filtered_df = filtered_df[filtered_df['Location'].isin(location_filter)]  
-            if restaurant_type_filter:  
-                filtered_df = filtered_df[filtered_df['Restaurant Type'].isin(restaurant_type_filter)]  
+            if company_name_filter:  
+                filtered_df = filtered_df[filtered_df['Company Name'].str.contains(company_name_filter, case=False, na=False)]  
+            if region_filter:  
+                filtered_df = filtered_df[filtered_df['Region'].isin(region_filter)]  
+            if factory_type_filter:  
+                filtered_df = filtered_df[filtered_df['Factory Type'].isin(factory_type_filter)]  
             if expiry_date_filter:  
                 if len(expiry_date_filter) == 1:  
                     filtered_df = filtered_df[filtered_df['Expiry Date'] == expiry_date_filter[0]]  
@@ -223,4 +223,4 @@ else:
                     mime='text/csv',  
                 )  
             else:  
-                st.info("No data matches the filter criteria.")
+                st.info("No data matches the filter criteria.")