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/checkMealRates.js

@@ -0,0 +1,86 @@
+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🍽️  Checking Meal Rates Table...\n');
+console.log('='.repeat(60));
+
+// Check if meal_rates table exists
+const checkTableQuery = `
+    SELECT name FROM sqlite_master 
+    WHERE type='table' AND name='meal_rates'
+`;
+
+db.get(checkTableQuery, [], (err, row) => {
+    if (err) {
+        console.error('❌ Query failed:', err);
+        db.close();
+        process.exit(1);
+    }
+
+    if (!row) {
+        console.log('\n❌ meal_rates table does NOT exist in database\n');
+        console.log('The database migration only created accommodation_rates table.');
+        console.log('Meal rates need to be added separately.\n');
+        db.close();
+        return;
+    }
+
+    console.log('✅ meal_rates table EXISTS\n');
+
+    // Count records
+    const countQuery = 'SELECT COUNT(*) as count FROM meal_rates';
+    
+    db.get(countQuery, [], (err, countRow) => {
+        if (err) {
+            console.error('❌ Count query failed:', err);
+            db.close();
+            process.exit(1);
+        }
+
+        console.log(`📊 Total meal rate records: ${countRow.count}\n`);
+
+        if (countRow.count === 0) {
+            console.log('⚠️  Table exists but is EMPTY - no meal rates imported\n');
+            db.close();
+            return;
+        }
+
+        // Show sample records
+        const sampleQuery = `
+            SELECT city_name, country, breakfast, lunch, dinner, incidentals, total_daily
+            FROM meal_rates
+            LIMIT 10
+        `;
+
+        db.all(sampleQuery, [], (err, rows) => {
+            if (err) {
+                console.error('❌ Sample query failed:', err);
+                db.close();
+                process.exit(1);
+            }
+
+            console.log('Sample meal rates:\n');
+            rows.forEach((row, index) => {
+                console.log(`${index + 1}. ${row.city_name}, ${row.country}`);
+                console.log(`   Breakfast: $${row.breakfast}`);
+                console.log(`   Lunch: $${row.lunch}`);
+                console.log(`   Dinner: $${row.dinner}`);
+                console.log(`   Incidentals: $${row.incidentals}`);
+                console.log(`   Total Daily: $${row.total_daily}\n`);
+            });
+
+            db.close();
+        });
+    });
+});
+
+console.log('='.repeat(60) + '\n');