Files
Gov_Travel_App/scripts/listCountries.js
mblanke 15094ac94b 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.
2026-01-13 09:21:43 -05:00

47 lines
1.2 KiB
JavaScript

const sqlite3 = require('sqlite3').verbose();
const path = require('path');
const dbPath = path.join(__dirname, '..', 'database', 'travel_rates.db');
const db = new sqlite3.Database(dbPath, (err) => {
if (err) {
console.error('❌ Database connection failed:', err);
process.exit(1);
}
});
console.log('\n📊 Countries in Database:\n');
console.log('='.repeat(60));
const query = `
SELECT
country,
COUNT(*) as city_count,
region,
currency
FROM accommodation_rates
GROUP BY country
ORDER BY country
`;
db.all(query, [], (err, rows) => {
if (err) {
console.error('❌ Query failed:', err);
db.close();
process.exit(1);
}
rows.forEach((row, index) => {
console.log(`\n${index + 1}. ${row.country}`);
console.log(` Region: ${row.region}`);
console.log(` Currency: ${row.currency}`);
console.log(` Cities: ${row.city_count}`);
});
console.log('\n' + '='.repeat(60));
console.log(`\n📍 Total Countries: ${rows.length}`);
console.log(`📍 Total Cities: ${rows.reduce((sum, r) => sum + r.city_count, 0)}\n`);
db.close();
});