#!/usr/bin/env python3
"""
Export facilities data for frontend embedding.
Creates a minimal JSON file with only the data needed for the heatmap.
"""
import json
import sqlite3
from datetime import datetime
def export_facilities_data():
"""Export facilities data to a minimal JSON format for frontend embedding."""
print("📊 Exporting facilities data for frontend embedding...")
# Connect to SQLite database
conn = sqlite3.connect('ice_locator_facilities.db')
cursor = conn.cursor()
# Get all facilities with only the fields we need
cursor.execute("""
SELECT name, latitude, longitude, address, population_count
FROM facilities
WHERE population_count IS NOT NULL AND population_count > 0
ORDER BY population_count DESC
""")
facilities = []
for row in cursor.fetchall():
name, lat, lng, address, population = row
facilities.append({
"name": name,
"latitude": lat,
"longitude": lng,
"address": address or "",
"population_count": population
})
conn.close()
# Create the data structure for frontend
frontend_data = {
"metadata": {
"exported_at": datetime.now().isoformat(),
"total_facilities": len(facilities),
"total_population": sum(f["population_count"] for f in facilities),
"description": "ICE Detention Facilities - Population Data"
},
"facilities": facilities
}
# Save to JSON file
output_file = "web-app/src/data/facilities.json"
with open(output_file, 'w') as f:
json.dump(frontend_data, f, indent=2)
print(f"✅ Exported {len(facilities)} facilities to {output_file}")
print(f"📊 Total population: {frontend_data['metadata']['total_population']:,}")
# Also create a CSV for backup
csv_file = "web-app/public/facilities.csv"
with open(csv_file, 'w') as f:
f.write("name,latitude,longitude,address,population_count\n")
for facility in facilities:
f.write(f'"{facility["name"]}",{facility["latitude"]},{facility["longitude"]},"{facility["address"]}",{facility["population_count"]}\n')
print(f"📄 Also created CSV backup at {csv_file}")
return frontend_data
if __name__ == "__main__":
export_facilities_data()
