diff --git a/src/data_collection/weather_sources.py b/src/data_collection/weather_sources.py index 727392ce..d98cec15 100644 --- a/src/data_collection/weather_sources.py +++ b/src/data_collection/weather_sources.py @@ -1378,25 +1378,20 @@ class WeatherDataCollector: results["metar"] = metar_data # 对土耳其城市，额外获取 MGM 官方数据与周边测站 - # 后面可以扩展更多土耳其城市，只需在这里添加映射 turkish_provinces = { - "ankara": ("17130", "Ankara"), # (主测站ID, 省份名用于周边) + "ankara": ("17130", "Ankara"), "istanbul": ("17060", "Istanbul"), } - if city_lower in turkish_provinces: istno, province = turkish_provinces[city_lower] mgm_data = self.fetch_from_mgm(istno) if mgm_data: results["mgm"] = mgm_data - - # 抓取并追加周边参考站数据 (并发模式) nearby = self.fetch_mgm_nearby_stations(province) if nearby: results["mgm_nearby"] = nearby # 全球通用：对有预定义集群的城市，抓取周边 METAR 参考站 - # 这可以让 Buenos Aires, London, NYC 等城市也拥有类似安卡拉的多测站地图分布 if city_lower in self.CITY_METAR_CLUSTERS and "mgm_nearby" not in results: cluster_icaos = self.CITY_METAR_CLUSTERS[city_lower] cluster_data = self.fetch_metar_nearby_cluster( @@ -1405,6 +1400,11 @@ class WeatherDataCollector: if cluster_data: results["mgm_nearby"] = cluster_data + if open_meteo: + results["open-meteo"] = open_meteo + # 获取时区偏移以过滤 METAR + utc_offset = open_meteo.get("utc_offset", 0) + # 对伦敦，获取 Meteoblue 预测 (公认最准) if city_lower == "london": mb_data = self.fetch_from_meteoblue( diff --git a/web/app.py b/web/app.py index b1afb3d6..39c3032b 100644 --- a/web/app.py +++ b/web/app.py @@ -43,19 +43,19 @@ _weather = WeatherDataCollector(_config) # City Registry # ────────────────────────────────────────────────────────── CITIES: Dict[str, Dict[str, Any]] = { - "ankara": {"lat": 40.1281, "lon": 32.9951, "f": False}, # LTAC (Esenboğa) - "london": {"lat": 51.5048, "lon": 0.0522, "f": False}, # EGLC (London City) - "paris": {"lat": 49.0097, "lon": 2.5480, "f": False}, # LFPG (Charles de Gaulle) - "seoul": {"lat": 37.4602, "lon": 126.4407, "f": False}, # RKSI (Incheon) - "toronto": {"lat": 43.6777, "lon": -79.6248, "f": False}, # CYYZ (Pearson) - "buenos aires": {"lat": -34.8222, "lon": -58.5358, "f": False}, # SAEZ (Ezeiza) - "wellington": {"lat": -41.3272, "lon": 174.8053, "f": False}, # NZWN (Wellington) - "new york": {"lat": 40.7769, "lon": -73.8740, "f": True}, # KLGA (LaGuardia) - "chicago": {"lat": 41.9742, "lon": -87.9073, "f": True}, # KORD (O'Hare) - "dallas": {"lat": 32.8471, "lon": -96.8518, "f": True}, # KDAL (Dallas Love Field) - "miami": {"lat": 25.7959, "lon": -80.2870, "f": True}, # KMIA (Miami) - "atlanta": {"lat": 33.6407, "lon": -84.4277, "f": True}, # KATL (Hartsfield-Jackson) - "seattle": {"lat": 47.4502, "lon": -122.3088, "f": True}, # KSEA (Sea-Tac) + "ankara": {"lat": 40.1281, "lon": 32.9951, "f": False, "tz": 10800}, + "london": {"lat": 51.5048, "lon": 0.0522, "f": False, "tz": 0}, + "paris": {"lat": 49.0097, "lon": 2.5480, "f": False, "tz": 3600}, + "seoul": {"lat": 37.4602, "lon": 126.4407, "f": False, "tz": 32400}, + "toronto": {"lat": 43.6777, "lon": -79.6248, "f": False, "tz": -18000}, + "buenos aires": {"lat": -34.8222, "lon": -58.5358, "f": False, "tz": -10800}, + "wellington": {"lat": -41.3272, "lon": 174.8053, "f": False, "tz": 46800}, + "new york": {"lat": 40.7769, "lon": -73.8740, "f": True, "tz": -18000}, + "chicago": {"lat": 41.9742, "lon": -87.9073, "f": True, "tz": -21600}, + "dallas": {"lat": 32.8471, "lon": -96.8518, "f": True, "tz": -21600}, + "miami": {"lat": 25.7959, "lon": -80.2870, "f": True, "tz": -18000}, + "atlanta": {"lat": 33.6407, "lon": -84.4277, "f": True, "tz": -18000}, + "seattle": {"lat": 47.4502, "lon": -122.3088, "f": True, "tz": -28800}, } ALIASES = { @@ -135,7 +135,8 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]: obs_time_str = "" metar_age_min = None obs_t = metar.get("observation_time", "") if metar else "" - utc_offset = om.get("utc_offset", 0) + # 优先从 API 获取偏移，若失败则使用 CITIES 预设的静态偏移 (兜底当地时间) + utc_offset = om.get("utc_offset", info.get("tz", 0)) if obs_t and "T" in obs_t: try: dt = datetime.fromisoformat(obs_t.replace("Z", "+00:00")) @@ -150,15 +151,22 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]: # ── 3. Local time parsing ── local_time_full = om.get("current", {}).get("local_time", "") local_hour, local_minute = 12, 0 - local_date_str = datetime.now().strftime("%Y-%m-%d") + now_utc = datetime.now(timezone.utc) + local_now = now_utc + timedelta(seconds=utc_offset) + local_date_str = local_now.strftime("%Y-%m-%d") + try: - local_date_str = local_time_full.split(" ")[0] - tp = local_time_full.split(" ")[1].split(":") - local_hour = int(tp[0]) - local_minute = int(tp[1]) if len(tp) > 1 else 0 + if local_time_full: + local_date_str = local_time_full.split(" ")[0] + tp = local_time_full.split(" ")[1].split(":") + local_hour = int(tp[0]) + local_minute = int(tp[1]) if len(tp) > 1 else 0 + else: + local_hour = local_now.hour + local_minute = local_now.minute except Exception: - local_hour = datetime.now().hour - local_minute = datetime.now().minute + local_hour = local_now.hour + local_minute = local_now.minute local_time_str = f"{local_hour:02d}:{local_minute:02d}" local_hour_frac = local_hour + local_minute / 60