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/debug_currency.py

@@ -0,0 +1,28 @@
+import sqlite3
+
+conn = sqlite3.connect('data/travel_rates_scraped.sqlite3')
+cursor = conn.cursor()
+
+# Get a raw table with title
+cursor.execute("""
+    SELECT title, data 
+    FROM raw_tables 
+    WHERE title LIKE '%Argentina%'
+    LIMIT 1
+""")
+row = cursor.fetchone()
+print(f"Title: {row[0]}")
+print(f"Data length: {len(row[1])} chars")
+
+# Now check the actual rate_entries for Argentina
+cursor.execute("""
+    SELECT country, city, rate_type, currency, rate_amount
+    FROM rate_entries
+    WHERE country LIKE '%Argentina%'
+    LIMIT 3
+""")
+print("\nRate Entries:")
+for r in cursor.fetchall():
+    print(f"  {r}")
+
+conn.close()