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/test_currency_extraction.py

@@ -0,0 +1,25 @@
+import re
+
+def _extract_currency_from_title(title):
+    """Extract currency code from table title like 'Albania - Currency: Euro (EUR)'"""
+    if not title:
+        return None
+    # Pattern: "Currency: [Name] ([CODE])"
+    match = re.search(r"Currency:\s*[^(]+\(([A-Z]{3})\)", title)
+    if match:
+        return match.group(1)
+    return None
+
+# Test cases
+test_titles = [
+    "Argentina - Currency: Argentine Peso (ARS)",
+    "Albania - Currency: Euro (EUR)",
+    "Afghanistan - Currency: US Dollar (USD)",
+    "Canada - Currency: Canadian Dollar (CAD)",
+    None,
+    "Some random text"
+]
+
+for title in test_titles:
+    result = _extract_currency_from_title(title)
+    print(f"{title!r} -> {result}")