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/checkSchema.js

@@ -0,0 +1,30 @@
+const sqlite3 = require("sqlite3").verbose();
+const path = require("path");
+
+const db = new sqlite3.Database(
+  path.join(__dirname, "..", "travel_rates.db"),
+  (err) => {
+    if (err) {
+      console.error("Error opening database:", err);
+      process.exit(1);
+    }
+  }
+);
+
+db.all(
+  "SELECT name FROM sqlite_master WHERE type='table' ORDER BY name",
+  [],
+  (err, tables) => {
+    if (err) {
+      console.error("Error querying tables:", err);
+      process.exit(1);
+    }
+
+    console.log("Tables in travel_rates.db:");
+    tables.forEach((table) => {
+      console.log(`  - ${table.name}`);
+    });
+
+    db.close();
+  }
+);