238 lines
7.7 KiB
Python
238 lines
7.7 KiB
Python
#!/usr/bin/env python3
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import argparse
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import json
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import os
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from collections import Counter
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import psycopg2
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DB_NAME = "data_centers"
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POINT_TABLE = "public.us_dc_sample_geocoded"
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def connect():
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return psycopg2.connect(
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host=os.environ["PGWEB_HOST"],
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port=os.environ["PGWEB_PORT"],
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user=os.environ["PGWEB_USER"],
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password=os.environ["PGWEB_PASSWORD"],
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dbname=DB_NAME,
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)
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def load_points(conn):
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with conn.cursor() as cur:
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cur.execute(
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f"""
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select
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id,
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coalesce(provider, '') as provider,
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coalesce(facility_name, '') as facility_name,
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coalesce(city, '') as city,
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coalesce(state_code, '') as state_code,
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longitude,
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latitude,
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coalesce(geocode_source, '') as geocode_source,
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coalesce(geocode_precision, '') as geocode_precision,
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coalesce(geoid, '') as geoid
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from {POINT_TABLE}
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where longitude is not null and latitude is not null
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"""
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)
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rows = cur.fetchall()
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points = []
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for row in rows:
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points.append(
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{
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"id": row[0],
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"provider": row[1],
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"facility_name": row[2],
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"city": row[3],
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"state_code": row[4],
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"lon": float(row[5]),
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"lat": float(row[6]),
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"geocode_source": row[7],
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"geocode_precision": row[8],
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"geoid": row[9],
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}
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)
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return points
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def compute_center(points):
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if not points:
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return 39.5, -98.35
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lat = sum(p["lat"] for p in points) / len(points)
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lon = sum(p["lon"] for p in points) / len(points)
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return lat, lon
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def build_stats(points):
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by_source = Counter(p["geocode_source"] or "(blank)" for p in points)
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by_precision = Counter(p["geocode_precision"] or "(blank)" for p in points)
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return {
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"total": len(points),
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"by_source": dict(sorted(by_source.items(), key=lambda x: x[0])),
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"by_precision": dict(sorted(by_precision.items(), key=lambda x: x[0])),
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}
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def render_html(points, center_lat, center_lon, output_path):
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stats = build_stats(points)
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points_json = json.dumps(points)
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stats_json = json.dumps(stats)
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html = f"""<!doctype html>
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<html lang=\"en\">
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<head>
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<meta charset=\"utf-8\" />
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<meta name=\"viewport\" content=\"width=device-width, initial-scale=1\" />
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<title>US Data Centers Map</title>
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<link rel=\"stylesheet\" href=\"https://unpkg.com/leaflet@1.9.4/dist/leaflet.css\" />
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<style>
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html, body {{ height: 100%; margin: 0; font-family: system-ui, -apple-system, Segoe UI, sans-serif; }}
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#layout {{ display: grid; grid-template-columns: 320px 1fr; height: 100%; }}
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#panel {{ padding: 14px; border-right: 1px solid #ddd; overflow: auto; background: #f8fafb; }}
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#map {{ height: 100%; width: 100%; }}
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h1 {{ margin: 0 0 8px; font-size: 18px; }}
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h2 {{ margin: 16px 0 8px; font-size: 14px; }}
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.stat-row {{ display: flex; justify-content: space-between; padding: 2px 0; font-size: 13px; }}
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.dot {{ width: 10px; height: 10px; border-radius: 50%; display: inline-block; margin-right: 8px; }}
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@media (max-width: 900px) {{
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#layout {{ grid-template-columns: 1fr; grid-template-rows: 220px 1fr; }}
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#panel {{ border-right: 0; border-bottom: 1px solid #ddd; }}
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}}
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</style>
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</head>
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<body>
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<div id=\"layout\">
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<div id=\"panel\">
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<h1>US Data Centers</h1>
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<div class=\"stat-row\"><span>Total points</span><strong id=\"total\"></strong></div>
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<h2>Geocode Source</h2>
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<div id=\"sourceStats\"></div>
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<h2>Geocode Precision</h2>
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<div id=\"precisionStats\"></div>
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<h2>Source Colors</h2>
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<div class=\"stat-row\"><span><span class=\"dot\" style=\"background:#1f77b4\"></span>IM3_Existing_DataCenters</span></div>
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<div class=\"stat-row\"><span><span class=\"dot\" style=\"background:#2ca02c\"></span>US Census Geocoder</span></div>
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<div class=\"stat-row\"><span><span class=\"dot\" style=\"background:#ff7f0e\"></span>Nominatim/OpenStreetMap</span></div>
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<div class=\"stat-row\"><span><span class=\"dot\" style=\"background:#7f7f7f\"></span>Other/Blank</span></div>
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</div>
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<div id=\"map\"></div>
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</div>
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<script src=\"https://unpkg.com/leaflet@1.9.4/dist/leaflet.js\"></script>
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<script>
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const points = {points_json};
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const stats = {stats_json};
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function colorForSource(source) {{
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if (source === 'IM3_Existing_DataCenters') return '#1f77b4';
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if (source === 'US Census Geocoder') return '#2ca02c';
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if (source === 'Nominatim/OpenStreetMap') return '#ff7f0e';
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return '#7f7f7f';
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}}
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function escapeHtml(value) {{
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return String(value || '')
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.replaceAll('&', '&')
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.replaceAll('<', '<')
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.replaceAll('>', '>')
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.replaceAll('"', '"')
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.replaceAll("'", ''');
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}}
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const map = L.map('map', {{ preferCanvas: true }}).setView([{center_lat}, {center_lon}], 5);
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L.tileLayer('https://tile.openstreetmap.org/{{z}}/{{x}}/{{y}}.png', {{
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maxZoom: 19,
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attribution: '© OpenStreetMap contributors'
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}}).addTo(map);
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const bounds = [];
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for (const p of points) {{
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const marker = L.circleMarker([p.lat, p.lon], {{
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radius: 4,
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color: colorForSource(p.geocode_source),
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fillColor: colorForSource(p.geocode_source),
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fillOpacity: 0.7,
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weight: 1
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}});
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const title = p.facility_name || p.id;
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const provider = p.provider || '(unknown provider)';
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const cityState = [p.city, p.state_code].filter(Boolean).join(', ');
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marker.bindPopup(`
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<strong>${{escapeHtml(title)}}</strong><br>
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Provider: ${{escapeHtml(provider)}}<br>
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ID: ${{escapeHtml(p.id)}}<br>
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Location: ${{escapeHtml(cityState)}}<br>
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Source: ${{escapeHtml(p.geocode_source)}}<br>
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Precision: ${{escapeHtml(p.geocode_precision)}}<br>
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GEOID: ${{escapeHtml(p.geoid)}}
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`);
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marker.addTo(map);
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bounds.push([p.lat, p.lon]);
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}}
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if (bounds.length > 0) {{
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map.fitBounds(bounds, {{ padding: [20, 20] }});
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}}
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document.getElementById('total').textContent = stats.total;
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const sourceStats = document.getElementById('sourceStats');
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for (const [k, v] of Object.entries(stats.by_source)) {{
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const div = document.createElement('div');
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div.className = 'stat-row';
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div.innerHTML = `<span>${{escapeHtml(k)}}</span><strong>${{v}}</strong>`;
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sourceStats.appendChild(div);
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}}
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const precisionStats = document.getElementById('precisionStats');
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for (const [k, v] of Object.entries(stats.by_precision)) {{
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const div = document.createElement('div');
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div.className = 'stat-row';
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div.innerHTML = `<span>${{escapeHtml(k)}}</span><strong>${{v}}</strong>`;
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precisionStats.appendChild(div);
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}}
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</script>
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</body>
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</html>
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"""
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with open(output_path, "w", encoding="utf-8") as f:
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f.write(html)
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def parse_args():
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parser = argparse.ArgumentParser(
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description="Generate an interactive HTML map from the PostGIS point table."
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)
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parser.add_argument(
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"--output",
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default="data_center_map.html",
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help="Output HTML path (default: data_center_map.html)",
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)
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return parser.parse_args()
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def main():
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args = parse_args()
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conn = connect()
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try:
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points = load_points(conn)
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finally:
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conn.close()
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center_lat, center_lon = compute_center(points)
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render_html(points, center_lat, center_lon, args.output)
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print(f"wrote {len(points)} points to {args.output}")
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if __name__ == "__main__":
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main()
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