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_extraction_debug.py

@@ -0,0 +1,61 @@
+"""Test currency extraction step by step"""
+import sqlite3
+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
+
+conn = sqlite3.connect('data/travel_rates_scraped.sqlite3')
+cursor = conn.cursor()
+
+print("Testing currency extraction from stored titles:\n")
+
+# Get Argentina table title
+cursor.execute("""
+    SELECT title 
+    FROM raw_tables
+    WHERE title LIKE '%Argentina%'
+""")
+row = cursor.fetchone()
+if row:
+    title = row[0]
+    print(f"Argentina Title: {title}")
+    currency = _extract_currency_from_title(title)
+    print(f"Extracted Currency: {currency}")
+
+# Get Albania table title
+cursor.execute("""
+    SELECT title 
+    FROM raw_tables
+    WHERE title LIKE '%Albania%'
+""")
+row = cursor.fetchone()
+if row:
+    title = row[0]
+    print(f"\nAlbania Title: {title}")
+    currency = _extract_currency_from_title(title)
+    print(f"Extracted Currency: {currency}")
+
+# Check what entries we actually have
+cursor.execute("""
+    SELECT COUNT(*)
+    FROM rate_entries
+    WHERE currency IS NOT NULL
+""")
+print(f"\nTotal entries with currency: {cursor.fetchone()[0]}")
+
+cursor.execute("""
+    SELECT COUNT(*)
+    FROM rate_entries
+    WHERE currency IS NULL
+""")
+print(f"Total entries WITHOUT currency: {cursor.fetchone()[0]}")
+
+conn.close()