Create search.py

search.py

@@ -0,0 +1,51 @@
+import streamlit as st
+import pandas as pd
+
+def search_application(df):
+    user_input = st.text_input("Enter your Application Number (including IRL if applicable):")
+
+    if user_input:
+        # Validate input
+        if "irl" in user_input.lower():
+            try:
+                application_number = int("".join(filter(str.isdigit, user_input.lower().split("irl")[-1])))
+                if len(str(application_number)) < 8:
+                    st.warning("Please enter a valid application number with at least 8 digits after IRL.")
+                    return
+            except ValueError:
+                st.error("Invalid input after IRL. Please enter only digits.")
+                return
+        else:
+            if not user_input.isdigit() or len(user_input) < 8:
+                st.warning("Please enter at least 8 digits for your VISA application number.")
+                return
+            elif len(user_input) > 8:
+                st.warning("The application number cannot exceed 8 digits. Please correct your input.")
+                return
+            application_number = int(user_input)
+
+        # Check for the application number in the DataFrame
+        result = df[df['Application Number'] == str(application_number)]
+
+        if not result.empty:
+            decision = result.iloc[0]['Decision']
+            if decision.lower() == 'refused':
+                st.error(f"Application Number: {application_number}\n\nDecision: **Refused**")
+            elif decision.lower() == 'approved':
+                st.success(f"Application Number: {application_number}\n\nDecision: **Approved**")
+            else:
+                st.info(f"Application Number: {application_number}\n\nDecision: **{decision}**")
+        else:
+            st.warning(f"No record found for Application Number: {application_number}.")
+
+            # Find nearest application numbers
+            df['Application Number'] = df['Application Number'].astype(int)
+            df['Difference'] = abs(df['Application Number'] - application_number)
+            nearest_records = df.nsmallest(2, 'Difference')
+
+            if not nearest_records.empty:
+                st.subheader("Nearest Application Numbers")
+                nearest_records['Nearest Application'] = ['Before', 'After']
+                st.table(nearest_records[['Nearest Application', 'Application Number', 'Decision', 'Difference']])
+            else:
+                st.info("No nearest application numbers found.")