Files
Flight-Ops/lib/airports.test.ts
kamilkrzywda 49dfd2ca6e
CI / build + unit + e2e (pull_request) Successful in 13m18s
v0.68.0: re-curate special remote airports — one per ~1000 km region (ISS-144)
Greedy sparse selection replaces the blanket 1000km-from-large filter that
over-filled central Australia / Canada edges with dozens of tiny strips:
candidates sorted by scheduled service, type rank (medium < small < seaplane),
numeric id; accepted only if >= REMOTE_RADIUS_KM from every already-accepted
special. CSV: 1483 -> 1161 rows (1119 large unchanged, specials 364 -> 42).
New unit test pins the pairwise-sparsity invariant on the committed dataset.
2026-09-23 20:33:25 +00:00

212 lines
9.0 KiB
TypeScript

import { promises as fs } from 'node:fs';
import path from 'node:path';
import { describe, expect, it } from 'vitest';
import { assertUniqueIcaos, filterWorldAirports, isRemote, parseCsv, toGeoJson, airportsHandler, REMOTE_RADIUS_KM } from './airports';
import { haversineKm } from './geo';
const HEADER =
'"id","ident","type","name","latitude_deg","longitude_deg","elevation_ft","continent","iso_country","iso_region","municipality","scheduled_service","icao_code","iata_code","gps_code","local_code","home_link","wikipedia_link","keywords"';
function row(over: Record<string, string> = {}): string {
const base: Record<string, string> = {
id: '1',
ident: 'XXXX',
type: 'small_airport',
name: 'Test Field',
latitude_deg: '50.0',
longitude_deg: '8.0',
elevation_ft: '',
continent: 'EU',
iso_country: 'DE',
iso_region: 'DE-BE',
municipality: 'Nowhere',
scheduled_service: 'no',
icao_code: 'XXXX',
iata_code: '',
gps_code: '',
local_code: '',
home_link: '',
wikipedia_link: '',
keywords: '',
};
return Object.entries({ ...base, ...over })
.map(([, v]) => `"${v.replace(/"/g, '""')}"`)
.join(',');
}
describe('parseCsv', () => {
it('parses simple rows into objects keyed by header', () => {
const text = [HEADER, row()].join('\n');
const rows = parseCsv(text);
expect(rows).toHaveLength(1);
expect(rows[0].ident).toBe('XXXX');
expect(rows[0].continent).toBe('EU');
});
it('handles quoted fields containing commas and escaped quotes', () => {
const text = [HEADER, row({ name: 'A, B "South" Field' })].join('\n');
const rows = parseCsv(text);
expect(rows[0].name).toBe('A, B "South" Field');
});
it('handles CRLF line endings and trailing newline', () => {
const text = [HEADER, row(), row({ ident: 'YYYY' })].join('\r\n') + '\r\n';
const rows = parseCsv(text);
expect(rows.map((r) => r.ident)).toEqual(['XXXX', 'YYYY']);
});
});
describe('filterWorldAirports (v0.44.0 — world dataset, no continent check)', () => {
it('keeps fixed-wing airports and seaplane bases from every continent, drops the rest by type', () => {
const rows = parseCsv(
[
HEADER,
row({ ident: 'EU-SMALL', type: 'small_airport' }),
row({ ident: 'NA-LRG', continent: 'NA', type: 'large_airport' }),
row({ ident: 'AS-LRG', continent: 'AS', type: 'large_airport' }),
row({ ident: 'EU-SEA', type: 'seaplane_base' }),
row({ ident: 'EU-LEGACY', type: 'airport' }),
row({ ident: 'NA-Helio', continent: 'NA', type: 'heliport' }),
row({ ident: 'AS-CLOSED', continent: 'AS', type: 'closed' }),
].join('\n'),
);
const kept = filterWorldAirports(rows).map((r) => r.ident);
expect(kept.sort()).toEqual(['AS-LRG', 'EU-LEGACY', 'EU-SEA', 'EU-SMALL', 'NA-LRG']);
});
});
describe('assertUniqueIcaos (v0.44.0 load-time guard)', () => {
it('passes a collection with unique ICACOs and throws on the first duplicate', () => {
const ok = toGeoJson(parseCsv([HEADER, row({ ident: 'AAAA', icao_code: 'AAAA' }), row({ ident: 'BBBB', icao_code: 'BBBB' })].join('\n')));
expect(() => assertUniqueIcaos(ok)).not.toThrow();
// icao_code empty → the effective key is the ident fallback (toGeoJson), so a duplicate
// ident must trip the guard too.
const dup = toGeoJson(parseCsv([HEADER, row({ ident: 'CCCC', icao_code: '' }), row({ ident: 'CCCC', icao_code: '', latitude_deg: '51.0' })].join('\n')));
expect(() => assertUniqueIcaos(dup)).toThrow(/duplicate ICAO.*CCCC/);
});
});
describe('toGeoJson', () => {
it('builds a FeatureCollection with [lon, lat] coordinates and expected properties', () => {
const fc = toGeoJson(parseCsv([HEADER, row({ ident: 'EDDF', icao_code: 'EDDF', name: 'Frankfurt Main Airport' })].join('\n')));
expect(fc.type).toBe('FeatureCollection');
expect(fc.features).toHaveLength(1);
const f = fc.features[0];
expect(f.geometry).toEqual({ type: 'Point', coordinates: [8.0, 50.0] });
expect(f.properties).toMatchObject({ name: 'Frankfurt Main Airport', icao: 'EDDF', lat: 50.0, lon: 8.0 });
});
it('falls back to ident when icao_code is empty and skips rows without valid coordinates', () => {
const fc = toGeoJson(
parseCsv(
[
HEADER,
row({ ident: 'NOICAO', icao_code: '' }),
row({ ident: 'BADLAT', latitude_deg: 'not-a-number' }),
row({ ident: 'NONAME', name: '' }),
].join('\n'),
),
);
expect(fc.features).toHaveLength(1);
expect(fc.features[0].properties.icao).toBe('NOICAO');
});
});
describe('/api/airports handler', () => {
it('returns a valid GeoJSON FeatureCollection of world airports', async () => {
const res = await airportsHandler();
expect(res.status).toBe(200);
expect(res.headers.get('content-type')).toContain('application/json');
const fc = (await res.json()) as { type: string; features: Array<{ properties: Record<string, unknown> }> };
expect(fc.type).toBe('FeatureCollection');
expect(fc.features.length).toBeGreaterThan(0);
for (const f of fc.features.slice(0, 50)) {
expect(f.properties.name).toBeTruthy();
expect(f.properties.icao).toBeTruthy();
expect(typeof f.properties.lat).toBe('number');
expect(typeof f.properties.lon).toBe('number');
}
});
it('caches the parsed dataset in memory', async () => {
const a = await airportsHandler();
const b = await airportsHandler();
expect(await a.json()).toEqual(await b.json());
});
});
describe('isRemote (v0.61.0 — ISS-097 special remote airports)', () => {
it('synthetic: an isolated point is remote; a neighbour inside the radius is not', () => {
// Equator pair: Δlon 8.5° ≈ 945 km (inside REMOTE_RADIUS_KM) vs Δlon 9.5° ≈ 1052 km (outside).
const near = [
{ icao: 'AAA', lat: 0, lon: 0 },
{ icao: 'BBB', lat: 0, lon: 8.5 },
];
expect(isRemote(near, 'AAA')).toBe(false);
expect(isRemote(near, 'BBB')).toBe(false);
const far = [
{ icao: 'AAA', lat: 0, lon: 0 },
{ icao: 'CCC', lat: 0, lon: 9.5 },
];
expect(isRemote(far, 'AAA')).toBe(true);
expect(isRemote(far, 'CCC')).toBe(true);
// A lone airport has no other member to be near — remote by definition.
expect(isRemote([{ icao: 'SOLO', lat: -77.84, lon: 166.91 }], 'SOLO')).toBe(true);
});
it('real coords: Frankfurt↔Amsterdam (~370 km) is not remote; McMurdo vs Christchurch (~3800 km) is', () => {
const eu = [
{ icao: 'EDDF', lat: 50.0376, lon: 8.5622 }, // Frankfurt Main
{ icao: 'EHAM', lat: 52.3093, lon: 13.3698 }, // Amsterdam Schiphol
];
expect(isRemote(eu, 'EDDF')).toBe(false);
const pacific = [
{ icao: 'MCDD', lat: -77.8425, lon: 166.9133 }, // McMurdo Station (Antarctica)
{ icao: 'NZCH', lat: -43.4893, lon: 172.5308 }, // Christchurch
];
expect(isRemote(pacific, 'MCDD')).toBe(true);
expect(REMOTE_RADIUS_KM).toBe(1000);
});
it('an unknown ICAO is not remote', () => {
expect(isRemote([{ icao: 'AAA', lat: 0, lon: 0 }], 'ZZZ')).toBe(false);
});
it('committed dataset curation rule: every non-large row has no large airport within REMOTE_RADIUS_KM', async () => {
const text = await fs.readFile(path.join(process.cwd(), 'data', 'airports_world.csv'), 'utf8');
const rows = filterWorldAirports(parseCsv(text));
expect(rows.length).toBeGreaterThan(0);
const large = rows.filter((r) => r.type === 'large_airport').map((r) => ({ icao: r.icao_code || r.ident, lat: +r.latitude_deg, lon: +r.longitude_deg }));
const nonLarge = rows.filter((r) => r.type !== 'large_airport');
// The dataset must actually carry the "special" airports — not just large ones.
expect(nonLarge.length).toBeGreaterThan(0);
for (const r of nonLarge) {
const self = { icao: r.icao_code || r.ident, lat: +r.latitude_deg, lon: +r.longitude_deg };
// Remote against the kept set: no LARGE airport within REMOTE_RADIUS_KM (the curation rule).
expect(isRemote([...large, self], self.icao), `${self.icao} (${r.name}) must be remote`).toBe(true);
}
});
it('committed dataset sparsity rule: every pair of non-large rows is at least REMOTE_RADIUS_KM apart', async () => {
const text = await fs.readFile(path.join(process.cwd(), 'data', 'airports_world.csv'), 'utf8');
const rows = filterWorldAirports(parseCsv(text));
// v0.68.0 (ISS-144): specials are greedily thinned to one per ~REMOTE_RADIUS_KM region, so no
// two non-large rows may sit closer than the radius. n≈dozens makes O(n²) trivial.
const nonLarge = rows.filter((r) => r.type !== 'large_airport').map((r) => ({ icao: r.icao_code || r.ident, lat: +r.latitude_deg, lon: +r.longitude_deg }));
expect(nonLarge.length).toBeGreaterThan(0);
for (let i = 0; i < nonLarge.length; i++) {
for (let j = i + 1; j < nonLarge.length; j++) {
const d = haversineKm(nonLarge[i].lat, nonLarge[i].lon, nonLarge[j].lat, nonLarge[j].lon);
expect(d, `${nonLarge[i].icao} ↔ ${nonLarge[j].icao}: ${d.toFixed(1)} km < ${REMOTE_RADIUS_KM}`).toBeGreaterThanOrEqual(REMOTE_RADIUS_KM);
}
}
});
});