mirror of
https://github.com/mblanke/Gov_Travel_App.git
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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.
25 lines
783 B
Markdown
25 lines
783 B
Markdown
# Gov_Travel_App
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## Overview
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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.
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## Setup
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```bash
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python -m venv .venv
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source .venv/bin/activate
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pip install -e .
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```
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## Run the scraper
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```bash
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python -m gov_travel.main --db data/travel_rates.sqlite3
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```
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The database includes:
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- `raw_tables` for every scraped HTML table.
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- `rate_entries` for parsed rate rows (country/city/province + rate fields).
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- `exchange_rates` for parsed currency rates.
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- `accommodations` for parsed lodging listings.
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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.
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