- Implemented multiple scripts to check and inspect meal plans, scraped data, and accommodations for Munich and Riga.
- Added a migration script to convert scraped data into the application's database format.
- Introduced new database service methods for querying and updating travel rates.
- Enhanced server configuration for serving static files in production.
- Updated PostCSS configuration for consistency.
- Added openFlightsService.js to fetch and cache OpenFlights airport/airline/routes data
- Validates airport codes exist in OpenFlights database (6072+ airports)
- Generates realistic flights using major international airlines
- Creates varied routing options: direct, 1-stop, 2-stop flights
- Updated flightService.js to use OpenFlights as primary source before Amadeus
- OpenFlights as fallback if Amadeus unavailable or returns no results
- No API keys or authentication required
- Cached locally to avoid repeated network requests
- Realistic pricing, times, and stop locations
Docker container rebuilt with OpenFlights integration.
- Implemented alphabet navigation (A-Z) for NJC international rates page
- Added request delays (2s) and retry logic with exponential backoff to avoid server timeouts
- Added error handling for pages without tables
- Installed html5lib for better HTML parsing
- Now scrapes 233 countries (up from 15) with 104 unique currencies
- Total 11,628 international rate entries collected
- Added verification scripts to check all countries and their currencies
- Fixed currency extraction working perfectly for EUR, USD, CAD, AUD, ARS, and 99+ other currencies
- 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.
