app.py

import streamlit as st
import requests
import matplotlib.pyplot as plt

# API URLs
REST_COUNTRIES_API = "https://restcountries.com/v3.1/name/{}"
WORLD_BANK_API = "https://api.worldbank.org/v2/country/{}/indicator/{}?format=json"

# Function to get World Bank data
def get_world_bank_data(country_code, indicator):
    try:
        response = requests.get(WORLD_BANK_API.format(country_code, indicator))
        data = response.json()
        if isinstance(data, list) and len(data) > 1 and data[1]:
            return data[1][0].get('value', "N/A")
    except:
        pass
    return "N/A"

# Function to get country info (Area & Population)
def get_country_info(country_name):
    try:
        response = requests.get(REST_COUNTRIES_API.format(country_name))
        data = response.json()
        if isinstance(data, list) and len(data) > 0:
            country_data = data[0]
            return {
                "Area (sq km)": country_data.get("area", "N/A"),
                "Population": country_data.get("population", "N/A"),
                "Country Code": country_data.get("cca2", "").lower()  # Get country code for World Bank API
            }
    except:
        pass
    return None

# Function to fetch all military-related data
def get_military_data(country_name):
    country_info = get_country_info(country_name)
    if not country_info:
        return None
    
    country_code = country_info["Country Code"]
    
    return {
        "Country": country_name,
        "Population": country_info["Population"],
        "Area (sq km)": country_info["Area (sq km)"],
        "GDP (in USD)": get_world_bank_data(country_code, "NY.GDP.MKTP.CD"),
        "Military Expenditure (% of GDP)": get_world_bank_data(country_code, "MS.MIL.XPND.GD.ZS"),
        "Active Military Personnel": "N/A"  # No global API for this, needs a separate dataset
    }

# Streamlit UI
st.title("🌍 Military Data Explorer")

option = st.radio("Choose an option:", ["Single Country Data", "Compare Two Countries"])

if option == "Single Country Data":
    country = st.text_input("Enter Country Name:")
    if st.button("Get Military Data"):
        data = get_military_data(country)
        if data:
            st.json(data)
            
            # Ensure numeric values for plotting (replace "N/A" with 0)
            def safe_float(value):
                try:
                    return float(value)
                except:
                    return 0

            values = [
                safe_float(data["GDP (in USD)"]),
                safe_float(data["Military Expenditure (% of GDP)"]),
                safe_float(data["Active Military Personnel"]),
                safe_float(data["Area (sq km)"]),
                safe_float(data["Population"])
            ]

            # Visualization: Bar Chart
            fig, ax = plt.subplots(figsize=(7, 5))
            labels = ["GDP", "Military Expenditure (% of GDP)", "Active Military", "Area", "Population"]
            ax.bar(labels, values, color=['blue', 'red', 'green', 'purple', 'orange'])
            ax.set_ylabel("Value")
            ax.set_title(f"Military Data for {country}")
            st.pyplot(fig)
        else:
            st.error("No data found. Please try another country.")

elif option == "Compare Two Countries":
    col1, col2 = st.columns(2)

    with col1:
        country1 = st.text_input("Enter First Country:")
    with col2:
        country2 = st.text_input("Enter Second Country:")

    if st.button("Compare"):
        data1 = get_military_data(country1)
        data2 = get_military_data(country2)

        if data1 and data2:
            st.subheader(f"📊 Comparison: {data1['Country']} vs {data2['Country']}")
            st.table([
                ["Metric", data1['Country'], data2['Country']],
                ["Population", data1['Population'], data2['Population']],
                ["Area (sq km)", data1['Area (sq km)'], data2['Area (sq km)']],
                ["GDP (in USD)", data1['GDP (in USD)'], data2['GDP (in USD)']],
                ["Military Expenditure (% of GDP)", data1['Military Expenditure (% of GDP)'], data2['Military Expenditure (% of GDP)']],
                ["Active Military Personnel", data1['Active Military Personnel'], data2['Active Military Personnel']],
            ])

            # Ensure numeric values for plotting (replace "N/A" with 0)
            def safe_float(value):
                try:
                    return float(value)
                except:
                    return 0

            values1 = [safe_float(data1["GDP (in USD)"]), safe_float(data1["Military Expenditure (% of GDP)"]),
                       safe_float(data1["Active Military Personnel"]), safe_float(data1["Area (sq km)"]), safe_float(data1["Population"])]

            values2 = [safe_float(data2["GDP (in USD)"]), safe_float(data2["Military Expenditure (% of GDP)"]),
                       safe_float(data2["Active Military Personnel"]), safe_float(data2["Area (sq km)"]), safe_float(data2["Population"])]

            # Visualization: Comparison Bar Chart
            fig, ax = plt.subplots(figsize=(7, 5))
            labels = ["GDP", "Military Expenditure (% of GDP)", "Active Military", "Area", "Population"]
            x = range(len(labels))

            ax.bar(x, values1, width=0.4, label=data1["Country"], color='blue', align='center')
            ax.bar([i + 0.4 for i in x], values2, width=0.4, label=data2["Country"], color='red', align='center')

            ax.set_xticks([i + 0.2 for i in x])
            ax.set_xticklabels(labels)
            ax.set_ylabel("Value")
            ax.set_title(f"Military Data Comparison: {data1['Country']} vs {data2['Country']}")
            ax.legend()

            st.pyplot(fig)

        else:
            st.error("Data not found for one or both countries.")