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/verify_currencies.py

@@ -0,0 +1,58 @@
+import sqlite3
+import sys
+
+db_path = "data/travel_rates_scraped.sqlite3"
+
+try:
+    conn = sqlite3.connect(db_path)
+    cursor = conn.cursor()
+    
+    # Count total entries
+    cursor.execute("SELECT COUNT(*) FROM rate_entries")
+    total = cursor.fetchone()[0]
+    print(f"Total rate entries: {total}")
+    
+    # Count entries with currency
+    cursor.execute("SELECT COUNT(*) FROM rate_entries WHERE currency IS NOT NULL")
+    with_currency = cursor.fetchone()[0]
+    print(f"Entries with currency: {with_currency}")
+    print(f"Missing currency: {total - with_currency}")
+    
+    # Currency distribution
+    print("\nCurrency Distribution:")
+    cursor.execute("""
+        SELECT currency, COUNT(*) as count 
+        FROM rate_entries 
+        GROUP BY currency 
+        ORDER BY count DESC
+    """)
+    for row in cursor.fetchall():
+        currency = row[0] if row[0] else "NULL"
+        print(f"  {currency}: {row[1]}")
+    
+    # Sample entries with currency
+    print("\nSample Entries (Argentina ARS):")
+    cursor.execute("""
+        SELECT country, city, rate_type, rate_amount, currency
+        FROM rate_entries
+        WHERE country LIKE '%Argentina%'
+        LIMIT 5
+    """)
+    for row in cursor.fetchall():
+        print(f"  {row[0]} | {row[1]} | {row[2]}: ${row[3]} {row[4]}")
+    
+    print("\nSample Entries (Albania EUR):")
+    cursor.execute("""
+        SELECT country, city, rate_type, rate_amount, currency
+        FROM rate_entries
+        WHERE country LIKE '%Albania%'
+        LIMIT 5
+    """)
+    for row in cursor.fetchall():
+        print(f"  {row[0]} | {row[1]} | {row[2]}: ${row[3]} {row[4]}")
+    
+    conn.close()
+    
+except Exception as e:
+    print(f"Error: {e}")
+    sys.exit(1)