mirror of
https://github.com/mblanke/Gov_Travel_App.git
synced 2026-03-01 14:10:22 -05:00
- 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.
47 lines
1.2 KiB
JavaScript
47 lines
1.2 KiB
JavaScript
const sqlite3 = require('sqlite3').verbose();
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const path = require('path');
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const dbPath = path.join(__dirname, '..', 'database', 'travel_rates.db');
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const db = new sqlite3.Database(dbPath, (err) => {
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if (err) {
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console.error('❌ Database connection failed:', err);
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process.exit(1);
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}
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});
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console.log('\n📊 Countries in Database:\n');
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console.log('='.repeat(60));
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const query = `
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SELECT
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country,
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COUNT(*) as city_count,
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region,
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currency
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FROM accommodation_rates
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GROUP BY country
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ORDER BY country
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`;
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db.all(query, [], (err, rows) => {
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if (err) {
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console.error('❌ Query failed:', err);
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db.close();
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process.exit(1);
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}
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rows.forEach((row, index) => {
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console.log(`\n${index + 1}. ${row.country}`);
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console.log(` Region: ${row.region}`);
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console.log(` Currency: ${row.currency}`);
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console.log(` Cities: ${row.city_count}`);
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});
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console.log('\n' + '='.repeat(60));
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console.log(`\n📍 Total Countries: ${rows.length}`);
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console.log(`📍 Total Cities: ${rows.reduce((sum, r) => sum + r.city_count, 0)}\n`);
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db.close();
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});
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