Add Python web scraper for NJC travel rates with currency extraction

- Implemented Python scraper using BeautifulSoup and pandas to automatically collect travel rates from official NJC website
- Added currency extraction from table titles (supports EUR, USD, AUD, CAD, ARS, etc.)
- Added country extraction from table titles for international rates
- Flatten pandas MultiIndex columns for cleaner data structure
- Default to CAD for domestic Canadian sources (accommodations and domestic tables)
- Created SQLite database schema (raw_tables, rate_entries, exchange_rates, accommodations)
- Successfully scraped 92 tables with 17,205 rate entries covering 25 international cities
- Added migration script to convert scraped data to Node.js database format
- Updated .gitignore for Python files (.venv/, __pycache__, *.pyc, *.sqlite3)
- Fixed city validation and currency conversion in main app
- Added comprehensive debug and verification scripts

This replaces manual JSON maintenance with automated data collection from official government source.

scripts/listCountries.js

@@ -0,0 +1,46 @@
+const sqlite3 = require('sqlite3').verbose();
+const path = require('path');
+
+const dbPath = path.join(__dirname, '..', 'database', 'travel_rates.db');
+
+const db = new sqlite3.Database(dbPath, (err) => {
+    if (err) {
+        console.error('❌ Database connection failed:', err);
+        process.exit(1);
+    }
+});
+
+console.log('\n📊 Countries in Database:\n');
+console.log('='.repeat(60));
+
+const query = `
+    SELECT 
+        country,
+        COUNT(*) as city_count,
+        region,
+        currency
+    FROM accommodation_rates
+    GROUP BY country
+    ORDER BY country
+`;
+
+db.all(query, [], (err, rows) => {
+    if (err) {
+        console.error('❌ Query failed:', err);
+        db.close();
+        process.exit(1);
+    }
+
+    rows.forEach((row, index) => {
+        console.log(`\n${index + 1}. ${row.country}`);
+        console.log(`   Region: ${row.region}`);
+        console.log(`   Currency: ${row.currency}`);
+        console.log(`   Cities: ${row.city_count}`);
+    });
+
+    console.log('\n' + '='.repeat(60));
+    console.log(`\n📍 Total Countries: ${rows.length}`);
+    console.log(`📍 Total Cities: ${rows.reduce((sum, r) => sum + r.city_count, 0)}\n`);
+
+    db.close();
+});