mirror of
https://github.com/mblanke/Gov_Travel_App.git
synced 2026-03-01 14:10:22 -05:00
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.
32 lines
967 B
Python
32 lines
967 B
Python
"""Inspect the actual table structure from NJC"""
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import sys
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sys.path.insert(0, 'src')
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from gov_travel.scrapers import SourceConfig, scrape_tables_from_source
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import json
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# Create a test source config
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source = SourceConfig(name="international", url="https://www.njc-cnm.gc.ca/directive/app_d.php?lang=en")
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# Get just the first table
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print("Fetching tables...")
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tables = scrape_tables_from_source(source)
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first_table = tables[0]
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print(f"\nTable {first_table['table_index']}")
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print(f"Title: {first_table['title']}")
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print(f"\nFirst data row:")
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print(json.dumps(first_table['data'][0], indent=2))
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print(f"\nSecond data row:")
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print(json.dumps(first_table['data'][1], indent=2))
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# Now try Argentina
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for table in tables:
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if table['title'] and 'Argentina' in table['title']:
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print(f"\n\n=== Argentina Table ===")
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print(f"Title: {table['title']}")
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print(f"\nFirst row:")
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print(json.dumps(table['data'][0], indent=2))
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break
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