Airport Search

"""Text search response types - matches airport-search.mdx field tables."""from __future__ import annotationsfrom dataclasses import dataclass@dataclassclass TextSearchRequest:    q: str    limit: int = 10@dataclassclass TextSearchAirport:    ident: str    name: str    type: str    latitude_deg: float    longitude_deg: float    municipality: str | None    iso_country: str | None    iata_code: str | None    relevance_score: int@dataclassclass TextSearchResponse:    query: str    airports: list[TextSearchAirport]    airports_found: int@dataclassclass LocationSearchRequest:    lat: float    lon: float    radius: float = 50.0    type: str | None = None@dataclassclass LocationAirport:    ident: str    name: str    type: str    latitude_deg: float    longitude_deg: float    municipality: str | None    iso_country: str | None    iata_code: str | None    distance_km: float@dataclassclass LocationSearchResponse:    search_location: dict    airports: list[LocationAirport]    airports_found: int@dataclassclass AirportSuggestion:    """Shape returned by autocomplete_suggestions() in the text-search example."""    icao: str | None    iata: str | None    name: str    municipality: str | None    country: str | None    relevance_score: int

import osimport timefrom dataclasses import dataclassimport requestsHEADERS = {    "x-api-key": os.getenv("SKYLINK_API_KEY", "YOUR_API_KEY")}BASE = "https://data.skylinkapi.com/v3"CACHE: dict[str, tuple[dict, float]] = {}TEXT_SEARCH_TTL = 3600  # 1 h - airport names/codes are stable@dataclassclass AirportSuggestion:    icao: str | None    iata: str | None    name: str    municipality: str | None    country: str | None    relevance_score: intdef search_airports_text(query: str, limit: int = 10) -> dict:    cache_key = f"text:{query.lower()}:{limit}"    cached = CACHE.get(cache_key)    if cached and time.time() < cached[1]:        return cached[0]    r = requests.get(        f"{BASE}/airports/search/text",        headers=HEADERS,        params={"q": query, "limit": limit},        timeout=(10, 15),    )    r.raise_for_status()    data = r.json()    CACHE[cache_key] = (data, time.time() + TEXT_SEARCH_TTL)    return datadef autocomplete_suggestions(query: str, limit: int = 8) -> list[AirportSuggestion]:    payload = search_airports_text(query, limit=limit)    out: list[AirportSuggestion] = []    for row in payload.get("airports", []):        out.append(            AirportSuggestion(                icao=row.get("ident"),                iata=row.get("iata_code"),                name=row["name"],                municipality=row.get("municipality"),                country=row.get("iso_country"),                relevance_score=int(row.get("relevance_score") or 0),            )        )    return outif __name__ == "__main__":    import json    result = search_airports_text("JFK", limit=5)    print(json.dumps(result, indent=2, default=str))