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import streamlit as st
import pandas as pd
import bisect
def binary_search_nearest(df, target):
"""Find the nearest values using binary search."""
application_numbers = df['Application Number'].tolist()
pos = bisect.bisect_left(application_numbers, target)
# Find the nearest neighbors
before = application_numbers[pos - 1] if pos > 0 else None
after = application_numbers[pos] if pos < len(application_numbers) else None
return before, after
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)
# Search for the application number
result = df[df['Application Number'] == 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 using binary search
before, after = binary_search_nearest(df, application_number)
# Display nearest records
nearest_records = pd.DataFrame({
"Nearest Application": ["Before", "After"],
"Application Number": [before, after],
"Decision": [
df[df['Application Number'] == before]['Decision'].values[0] if before else None,
df[df['Application Number'] == after]['Decision'].values[0] if after else None
],
"Difference": [
application_number - before if before else None,
after - application_number if after else None
]
}).dropna()
if not nearest_records.empty:
st.subheader("Nearest Application Numbers")
st.table(nearest_records.reset_index(drop=True))
else:
st.info("No nearest application numbers found.")
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