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mblanke
15094ac94b
- 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.
Gov_Travel_App
Overview
This repository contains a Python scraper that collects travel rate tables from the NJC and accommodation listings, then stores the raw tables and normalized entries in a SQLite database.
Setup
python -m venv .venv
source .venv/bin/activate
pip install -e .
Run the scraper
python -m gov_travel.main --db data/travel_rates.sqlite3
The database includes:
raw_tablesfor every scraped HTML table.rate_entriesfor parsed rate rows (country/city/province + rate fields).exchange_ratesfor parsed currency rates.accommodationsfor parsed lodging listings.
If a field is not detected by the heuristics, the full row is still preserved in raw_tables and the raw_json columns for deeper post-processing.