search.py

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")
                
                # Exclude the index column from the display
                nearest_records['Nearest Application'] = ['Before', 'After']
                st.table(nearest_records[['Nearest Application', 'Application Number', 'Decision', 'Difference']].reset_index(drop=True))
            else:
                st.info("No nearest application numbers found.")