Carbon Emissions

"""Carbon estimate response models for /carbon/estimate."""from __future__ import annotationsfrom dataclasses import dataclass@dataclassclass CarbonEstimateResponse:    departure_icao: str    arrival_icao: str    aircraft_type: str | None    aircraft_category: str    distance_km: float    distance_nm: float    passengers: int    passengers_source: str    co2_kg_total: float    co2_kg_per_passenger: float    rfi_applied: bool    rfi_factor: float    co2_equivalent_kg_total: float | None    co2_equivalent_kg_per_passenger: float | None    methodology: str    confidence: str    distance_source: str    notes: str    callsign: str | None = None    callsign_resolved: bool | None = None    route_confidence: str | None = None

import osfrom dataclasses import dataclassimport requestsBASE = "https://data.skylinkapi.com/v3.1"HEADERS = {    "x-api-key": os.getenv("SKYLINK_API_KEY", "YOUR_API_KEY")}@dataclassclass CarbonLabel:    route: str    co2_kg_total: float    co2_kg_per_passenger: float    passengers: int    methodology: str    rfi_applied: booldef fetch_carbon_estimate(    *,    departure_icao: str | None = None,    arrival_icao: str | None = None,    callsign: str | None = None,    aircraft_type: str | None = None,    passengers: int | None = None,    include_rfi: bool = False,) -> dict:    """Estimate flight CO2 using ICAO methodology."""    params: dict[str, str | int | bool] = {}    if departure_icao and arrival_icao:        params["departure_icao"] = departure_icao.upper()        params["arrival_icao"] = arrival_icao.upper()    elif callsign:        params["callsign"] = callsign.upper()    else:        raise ValueError("Provide departure_icao+arrival_icao or callsign")    if aircraft_type:        params["aircraft_type"] = aircraft_type.upper()    if passengers is not None:        params["passengers"] = passengers    if include_rfi:        params["include_rfi"] = True    r = requests.get(f"{BASE}/carbon/estimate", headers=HEADERS, params=params, timeout=(10, 20))    r.raise_for_status()    return r.json()def carbon_label(    departure_icao: str,    arrival_icao: str,    *,    passengers: int | None = None,    aircraft_type: str | None = None,) -> CarbonLabel:    data = fetch_carbon_estimate(        departure_icao=departure_icao,        arrival_icao=arrival_icao,        passengers=passengers,        aircraft_type=aircraft_type,    )    return CarbonLabel(        route=f"{data['departure_icao']} → {data['arrival_icao']}",        co2_kg_total=float(data["co2_kg_total"]),        co2_kg_per_passenger=float(data["co2_kg_per_passenger"]),        passengers=int(data["passengers"]),        methodology=data["methodology"],        rfi_applied=bool(data["rfi_applied"]),    )if __name__ == "__main__":    import json    from dataclasses import asdict    label = carbon_label("KJFK", "KLAX", passengers=180, aircraft_type="B738")    print(json.dumps(asdict(label), indent=2))