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/query_scraped_db.py

@@ -0,0 +1,44 @@
+import sqlite3
+import json
+
+conn = sqlite3.connect('data/travel_rates_scraped.sqlite3')
+
+print('\n=== SCRAPED DATABASE ANALYSIS ===\n')
+
+# Tables
+print('📊 Tables:')
+tables = [row[0] for row in conn.execute('SELECT name FROM sqlite_master WHERE type="table"').fetchall()]
+for table in tables:
+    count = conn.execute(f'SELECT COUNT(*) FROM {table}').fetchone()[0]
+    print(f'  - {table}: {count} rows')
+
+# Unique currencies
+print('\n💰 Unique Currencies in rate_entries:')
+currencies = [row[0] for row in conn.execute('SELECT DISTINCT currency FROM rate_entries WHERE currency IS NOT NULL ORDER BY currency').fetchall()]
+print(f'  {", ".join(currencies)}')
+
+# Argentina data
+print('\n🇦🇷 Argentina entries:')
+for row in conn.execute('SELECT country, city, currency, rate_type, rate_amount FROM rate_entries WHERE country="Argentina" LIMIT 10').fetchall():
+    print(f'  {row[0]} - {row[1]} - Currency: {row[2]} - {row[3]}: ${row[4]:.2f}')
+
+# Sample rate entries by country
+print('\n🌍 Sample entries by country (first 3 countries):')
+for row in conn.execute('SELECT DISTINCT country FROM rate_entries WHERE country IS NOT NULL LIMIT 3').fetchall():
+    country = row[0]
+    print(f'\n  {country}:')
+    for entry in conn.execute('SELECT city, currency, rate_type, rate_amount FROM rate_entries WHERE country=? LIMIT 3', (country,)).fetchall():
+        print(f'    {entry[0]} - {entry[1]} - {entry[2]}: ${entry[3]:.2f}')
+
+# Exchange rates
+print('\n💱 Exchange rates:')
+for row in conn.execute('SELECT currency, rate_to_cad, effective_date FROM exchange_rates WHERE currency IS NOT NULL LIMIT 10').fetchall():
+    print(f'  {row[0]}: {row[1]:.4f} CAD (effective: {row[2]})')
+
+# Accommodations
+print('\n🏨 Accommodation entries (sample):')
+for row in conn.execute('SELECT property_name, city, province, rate_amount, currency FROM accommodations WHERE rate_amount IS NOT NULL LIMIT 10').fetchall():
+    print(f'  {row[0]} - {row[1]}, {row[2]} - ${row[3]:.2f} {row[4]}')
+
+conn.close()
+print('\n✅ Done!')