Files
PolyWeather/src/data_collection/weather_sources.py
T
2569718930@qq.com 64f8ff21ec @
新增机场高频推送:10分钟级温度监控 + DEB预测快报

为首尔/釜山/东京三大机场城市实现高频温度监控通道:
- 新增 airport_obs_log 表积累观测数据,支持趋势检测
- AMOS/JMA 成功后自动写入观测日志
- 新增 airport_rapid_temp_change 告警规则(20min窗口、0.5°C/10min阈值)
- 10分钟间隔高频子循环 + 30分钟机场快照(含 DEB 预测最高温)
- 最高温锁定后自动跳过,快照仅当地 08:00-20:00 发送

Tested: ruff check 通过
@
2026-05-12 17:04:17 +08:00

1151 lines
44 KiB
Python

import os
import httpx
import re
import threading
import time
from typing import Optional, Dict, List
from datetime import datetime, timedelta
from loguru import logger
from src.data_collection.open_meteo_cache import OpenMeteoCacheMixin
from src.data_collection.settlement_sources import SettlementSourceMixin
from src.data_collection.metar_sources import MetarSourceMixin
from src.data_collection.mgm_sources import MgmSourceMixin
from src.data_collection.jma_amedas_sources import JmaAmedasSourceMixin
from src.data_collection.russia_station_sources import RussiaStationSourceMixin
from src.data_collection.nmc_sources import NmcSourceMixin
from src.data_collection.nws_open_meteo_sources import NwsOpenMeteoSourceMixin
from src.data_collection.amos_station_sources import AmosStationSourceMixin
from src.database.db_manager import DBManager
class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSourceMixin, MgmSourceMixin, JmaAmedasSourceMixin, RussiaStationSourceMixin, NmcSourceMixin, NwsOpenMeteoSourceMixin, AmosStationSourceMixin):
"""
Multi-source weather data collector
Supports:
- Open-Meteo (global forecast + multi-model ensemble)
- METAR/TAF (aviation weather observations)
- AMOS (Korean runway-level airport sensors — RKSI, RKPK)
- NWS (US National Weather Service)
- MGM (Turkish Meteorological Service)
- JMA / NMC / HKO / CWA (country official networks)
- Polymarket (weather derivative markets)
"""
from src.data_collection.city_registry import CITY_REGISTRY
CITY_TO_ICAO = {cid: info["icao"] for cid, info in CITY_REGISTRY.items()}
# Alias
CITY_TO_ICAO["nyc"] = "KLGA"
# 城市周边 METAR 集群(用于在全球城市模拟类似安卡拉的多测站地图分布)
CITY_METAR_CLUSTERS = {
"buenos aires": ["SAEZ", "SABE", "SADP", "SADF", "SADL", "SADJ"],
"istanbul": ["LTFM", "LTBA", "LTFJ"],
"moscow": ["UUWW", "UUEE", "UUDD", "UUBW", "UUMO"],
"london": ["EGLL", "EGLC", "EGKK", "EGSS", "EGGW"],
"new york": ["KLGA", "KJFK", "KEWR", "KTEB", "KHPN"],
"los angeles": ["KLAX", "KBUR", "KLGB", "KSNA", "KVNY"],
"san francisco": ["KSFO", "KOAK", "KSJC", "KHAF"],
"aurora": ["KBKF", "KDEN", "KAPA", "KBJC"],
"austin": ["KAUS", "KEDC", "KSAT"],
"houston": ["KHOU", "KIAH", "KSGR", "KCXO"],
"mexico city": ["MMMX", "MMSM", "MMTO"],
"paris": ["LFPB", "LFPG", "LFPO"],
"seoul": ["RKSI", "RKSS"],
"busan": ["RKPK", "RKSS"],
"hong kong": ["VHHH", "VMMC", "ZGSZ"],
"taipei": ["RCSS", "RCTP"],
"chengdu": ["ZUUU", "ZUTF"],
"chongqing": ["ZUCK", "ZUPS"],
"guangzhou": ["ZGGG", "ZGSZ"],
"qingdao": ["ZSQD"],
"shenzhen": ["ZGSZ", "ZGGG"],
"beijing": ["ZBAA", "ZBAD"],
"wuhan": ["ZHHH", "ZHES"],
"shanghai": ["ZSPD", "ZSSS", "ZSNB", "ZSHC"],
"singapore": ["WSSS", "WSAP", "WMKK"],
"kuala lumpur": ["WMKK", "WMSA"],
"jakarta": ["WIHH", "WIII"],
"manila": ["RPLL"],
"karachi": ["OPKC"],
"tokyo": ["RJTT", "RJAA", "RJAH", "RJTJ"],
"tel aviv": ["LLBG"],
"milan": ["LIMC", "LIML", "LIME", "LIPO"],
"toronto": ["CYYZ", "CYTZ", "CYKF"],
"warsaw": ["EPWA", "EPMO", "EPLL"],
"helsinki": ["EFHK", "EETN"],
"amsterdam": ["EHAM", "EHRD"],
"panama city": ["MPMG", "MPTO"],
"madrid": ["LEMD", "LETO", "LEGT"],
"chicago": ["KORD", "KMDW", "KPWK", "KDPA"],
"dallas": ["KDAL", "KDFW", "KADS", "KGKY"],
"atlanta": ["KATL", "KPDK", "KFTY"],
"miami": ["KMIA", "KOPF", "KTMB"],
"seattle": ["KSEA", "KBFI", "KPAE"],
"sao paulo": ["SBGR", "SBSP", "SBKP"],
"munich": ["EDDM", "EDMO", "EDJA"],
}
US_CITIES = {
"dallas",
"nyc",
"new york",
"seattle",
"miami",
"atlanta",
"chicago",
"los angeles",
"san francisco",
"washington",
"boston",
"houston",
"phoenix",
"philadelphia",
"new york's central park",
"portland",
"denver",
"aurora",
"austin",
"san diego",
"detroit",
"cleveland",
"minneapolis",
"st. louis",
}
TURKISH_PROVINCES = {
"ankara": ("17128", "Ankara"),
"istanbul": ("17058", "Istanbul"),
}
def __init__(self, config: dict):
self.config = config
# Keep external calls short so one degraded source cannot block the whole city pipeline.
self.timeout = max(
2.0, float(os.getenv("POLYWEATHER_HTTP_TIMEOUT_SEC", "8"))
)
self.http_retry_count = max(
0, int(os.getenv("POLYWEATHER_HTTP_RETRY_COUNT", "0"))
)
self.http_retry_backoff_sec = max(
0.0, float(os.getenv("POLYWEATHER_HTTP_RETRY_BACKOFF_SEC", "0.2"))
)
self.open_meteo_timeout_sec = max(
2.0, float(os.getenv("POLYWEATHER_OPEN_METEO_TIMEOUT_SEC", "5"))
)
self.metar_timeout_sec = max(
2.0, float(os.getenv("POLYWEATHER_METAR_TIMEOUT_SEC", "4"))
)
self.metar_latest_timeout_sec = max(
1.0, float(os.getenv("POLYWEATHER_METAR_LATEST_TIMEOUT_SEC", "2.5"))
)
self.metar_cluster_timeout_sec = max(
2.0, float(os.getenv("POLYWEATHER_METAR_CLUSTER_TIMEOUT_SEC", "3.5"))
)
self.user_agent = str(
os.getenv(
"POLYWEATHER_USER_AGENT",
"PolyWeather/1.0 (+https://polyweather-pro.vercel.app)",
)
).strip()
self.session = httpx.Client(
timeout=self.timeout,
follow_redirects=True,
headers={"User-Agent": self.user_agent},
limits=httpx.Limits(max_connections=50, max_keepalive_connections=20),
)
self.open_meteo_cache_ttl_sec = int(
os.getenv("OPEN_METEO_CACHE_TTL_SEC", "900")
)
self.open_meteo_ensemble_cache_ttl_sec = int(
os.getenv("OPEN_METEO_ENSEMBLE_CACHE_TTL_SEC", "900")
)
self.open_meteo_multi_model_cache_ttl_sec = int(
os.getenv("OPEN_METEO_MULTI_MODEL_CACHE_TTL_SEC", "900")
)
self.multi_model_cache_version = str(
os.getenv("OPEN_METEO_MULTI_MODEL_CACHE_VERSION", "v3")
).strip() or "v3"
self._open_meteo_cache: Dict[str, Dict] = {}
self._ensemble_cache: Dict[str, Dict] = {}
self._multi_model_cache: Dict[str, Dict] = {}
self._open_meteo_cache_lock = threading.Lock()
self._ensemble_cache_lock = threading.Lock()
self._multi_model_cache_lock = threading.Lock()
# Open-Meteo 共享 429 冷却计时器:触发限流后所有 OM 端点暂停请求
self._open_meteo_rate_limit_until: float = 0.0
self._open_meteo_rl_cooldown: int = int(
os.getenv("OPEN_METEO_RATE_LIMIT_COOLDOWN_SEC", "900") # 默认 15 分钟
)
self._open_meteo_rl_lock = threading.Lock()
# Open-Meteo burst control: avoid hammering API with many cities at once.
self._open_meteo_min_interval_sec: float = float(
os.getenv("OPEN_METEO_MIN_CALL_INTERVAL_SEC", "1")
)
self._open_meteo_last_call_ts: float = 0.0
self._open_meteo_call_lock = threading.Lock()
self.metar_cache_ttl_sec = int(
os.getenv("METAR_CACHE_TTL_SEC", "600") # 默认 10 分钟
)
self.metar_fast_cache_ttl_sec = int(
os.getenv("METAR_FAST_CACHE_TTL_SEC", "60")
)
self._metar_cache: Dict[str, Dict] = {}
self._metar_cache_lock = threading.Lock()
self.taf_cache_ttl_sec = int(
os.getenv("TAF_CACHE_TTL_SEC", "900")
)
self._taf_cache: Dict[str, Dict] = {}
self._taf_cache_lock = threading.Lock()
self.nmc_cache_ttl_sec = int(
os.getenv("NMC_CACHE_TTL_SEC", "300")
)
self._nmc_cache: Dict[str, Dict] = {}
self._nmc_cache_lock = threading.Lock()
self.jma_cache_ttl_sec = int(
os.getenv("JMA_AMEDAS_CACHE_TTL_SEC", "120")
)
self._jma_cache: Dict[str, Dict] = {}
self._jma_cache_lock = threading.Lock()
self.ru_station_cache_ttl_sec = int(
os.getenv("RU_STATION_CACHE_TTL_SEC", "300")
)
self.ru_station_max_stale_sec = int(
os.getenv("RU_STATION_MAX_STALE_SEC", str(4 * 3600))
)
self._ru_station_cache: Dict[str, Dict] = {}
self._ru_station_cache_lock = threading.Lock()
self.settlement_cache_ttl_sec = int(
os.getenv("SETTLEMENT_SOURCE_CACHE_TTL_SEC", "120")
)
self._settlement_cache: Dict[str, Dict] = {}
self._settlement_cache_lock = threading.Lock()
self.cwa_open_data_auth = (
os.getenv("CWA_OPEN_DATA_AUTH")
or os.getenv("CWA_OPEN_DATA_API_KEY")
or "rdec-key-123-45678-011121314"
).strip()
# 磁盘持久化缓存:重启后即可加载上次的预报数据,避免冷启动请求爆发
self._disk_cache_path = os.getenv(
"OPEN_METEO_DISK_CACHE_PATH", "/app/data/open_meteo_cache.json"
)
self._disk_cache_max_age_sec = int(
os.getenv("OPEN_METEO_DISK_CACHE_MAX_AGE_SEC", "86400")
)
self._disk_cache_lock = threading.Lock()
self._disk_cache_last_mtime: float = 0.0
self._load_open_meteo_disk_cache()
logger.info(
f"Open-Meteo 磁盘缓存路径: {self._disk_cache_path} (max_age={self._disk_cache_max_age_sec}s)"
)
# 设置代理
proxy = config.get("proxy")
if proxy:
if not proxy.startswith("http"):
proxy = f"http://{proxy}"
self.session = httpx.Client(
timeout=self.timeout,
follow_redirects=True,
proxy=proxy,
headers={"User-Agent": self.user_agent},
limits=httpx.Limits(max_connections=50, max_keepalive_connections=20),
)
logger.info(f"正在使用天气数据代理: {proxy}")
logger.info("天气数据采集器初始化完成。")
@staticmethod
def _is_retryable_status(status_code: int) -> bool:
return status_code in {408, 500, 502, 503, 504}
def _http_get(self, url: str, **kwargs) -> httpx.Response:
if "timeout" not in kwargs:
kwargs["timeout"] = self.timeout
last_exc: Optional[Exception] = None
last_response: Optional[httpx.Response] = None
attempts = self.http_retry_count + 1
for attempt in range(attempts):
try:
response = self.session.get(url, **kwargs)
last_response = response
if (
attempt < attempts - 1
and self._is_retryable_status(response.status_code)
):
wait_for = self.http_retry_backoff_sec * (attempt + 1)
logger.debug(
"HTTP GET retrying url={} status={} attempt={}/{} wait={}s",
url,
response.status_code,
attempt + 1,
attempts,
round(wait_for, 2),
)
if wait_for > 0:
time.sleep(wait_for)
continue
return response
except (httpx.TimeoutException, httpx.NetworkError) as exc:
last_exc = exc
if attempt >= attempts - 1:
break
wait_for = self.http_retry_backoff_sec * (attempt + 1)
logger.debug(
"HTTP GET retrying url={} error={} attempt={}/{} wait={}s",
url,
type(exc).__name__,
attempt + 1,
attempts,
round(wait_for, 2),
)
if wait_for > 0:
time.sleep(wait_for)
if last_exc is not None:
raise last_exc
if last_response is not None:
return last_response
raise RuntimeError(f"HTTP GET failed without response: {url}")
def _http_get_json(self, url: str, **kwargs):
response = self._http_get(url, **kwargs)
response.raise_for_status()
return response.json()
def fetch_from_openweather(self, city: str, country: str = None) -> Optional[Dict]:
"""
Fetch current weather and forecast from OpenWeatherMap
Args:
city: City name
country: Country code (optional)
Returns:
dict: Weather data
"""
if not getattr(self, "openweather_key", None):
return None
query = f"{city},{country}" if country else city
try:
# Current weather
current_url = "https://api.openweathermap.org/data/2.5/weather"
current_response = self._http_get(
current_url,
params={"q": query, "appid": self.openweather_key, "units": "metric"},
timeout=self.timeout,
)
current_response.raise_for_status()
current_data = current_response.json()
# 5-day forecast
forecast_url = "https://api.openweathermap.org/data/2.5/forecast"
forecast_response = self._http_get(
forecast_url,
params={"q": query, "appid": self.openweather_key, "units": "metric"},
timeout=self.timeout,
)
forecast_response.raise_for_status()
forecast_data = forecast_response.json()
return {
"source": "openweathermap",
"timestamp": datetime.utcnow().isoformat(),
"current": {
"temp": current_data["main"]["temp"],
"feels_like": current_data["main"]["feels_like"],
"temp_min": current_data["main"]["temp_min"],
"temp_max": current_data["main"]["temp_max"],
"humidity": current_data["main"]["humidity"],
"pressure": current_data["main"]["pressure"],
"wind_speed": current_data["wind"]["speed"],
"clouds": current_data["clouds"]["all"],
"description": current_data["weather"][0]["description"],
},
"forecast": self._parse_openweather_forecast(forecast_data),
}
except httpx.HTTPError as e:
logger.error(f"OpenWeatherMap request failed: {e}")
return None
def _parse_openweather_forecast(self, data: dict) -> List[Dict]:
"""Parse OpenWeatherMap forecast data"""
forecasts = []
for item in data.get("list", []):
forecasts.append(
{
"datetime": item["dt_txt"],
"temp": item["main"]["temp"],
"temp_min": item["main"]["temp_min"],
"temp_max": item["main"]["temp_max"],
"humidity": item["main"]["humidity"],
"description": item["weather"][0]["description"],
}
)
return forecasts
def fetch_from_visualcrossing(
self, city: str, start_date: str = None, end_date: str = None
) -> Optional[Dict]:
"""
Fetch historical weather data from Visual Crossing
Args:
city: City name
start_date: Start date (YYYY-MM-DD)
end_date: End date (YYYY-MM-DD)
Returns:
dict: Historical weather data
"""
if not getattr(self, "visualcrossing_key", None):
return None
# Default to last 30 days if no dates provided
if not end_date:
end_date = datetime.now().strftime("%Y-%m-%d")
if not start_date:
start_date = (datetime.now() - timedelta(days=30)).strftime("%Y-%m-%d")
try:
url = f"https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/{city}/{start_date}/{end_date}"
response = self._http_get(
url,
params={
"unitGroup": "metric",
"key": self.visualcrossing_key,
"contentType": "json",
"include": "days",
},
timeout=self.timeout,
)
response.raise_for_status()
data = response.json()
return {
"source": "visualcrossing",
"timestamp": datetime.utcnow().isoformat(),
"location": data.get("resolvedAddress"),
"timezone": data.get("timezone"),
"days": [
{
"date": day["datetime"],
"temp_max": day.get("tempmax"),
"temp_min": day.get("tempmin"),
"temp_avg": day.get("temp"),
"humidity": day.get("humidity"),
"precip": day.get("precip"),
"conditions": day.get("conditions"),
}
for day in data.get("days", [])
],
}
except httpx.HTTPError as e:
logger.error(f"Visual Crossing request failed: {e}")
return None
def extract_date_from_title(self, title: str) -> Optional[str]:
"""
从标题中提取日期并标准化为 YYYY-MM-DD
支持: "February 6", "2月6日", "2-6" 等
"""
# 1. 尝试英文月份
months = {
"January": "01",
"February": "02",
"March": "03",
"April": "04",
"May": "05",
"June": "06",
"July": "07",
"August": "08",
"September": "09",
"October": "10",
"November": "11",
"December": "12",
}
for month_name, month_val in months.items():
if month_name in title:
match = re.search(f"{month_name}\\s+(\\d+)", title)
if match:
day = int(match.group(1))
year = datetime.now().year
return f"{year}-{month_val}-{day:02d}"
# 2. 尝试中文格式 "2月7日" 或 "02月07日"
zh_match = re.search(r"(\d{1,2})月(\d{1,2})日", title)
if zh_match:
month = int(zh_match.group(1))
day = int(zh_match.group(2))
year = datetime.now().year
return f"{year}-{month:02d}-{day:02d}"
# 3. 尝试 ISO 格式 YYYY-MM-DD
iso_match = re.search(r"(\d{4})-(\d{2})-(\d{2})", title)
if iso_match:
return iso_match.group(0)
return None
def get_coordinates(self, city: str) -> Optional[Dict[str, float]]:
"""
使用 Open-Meteo Geocoding API 获取城市坐标 (免费, 无需 Key)
"""
from src.data_collection.city_registry import CITY_REGISTRY
normalized_city = city.lower().strip()
# 1. Check registry first (Source of Truth)
if normalized_city in CITY_REGISTRY:
info = CITY_REGISTRY[normalized_city]
return {"lat": info["lat"], "lon": info["lon"]}
# 2. Hardcoded specific cases or aliases
static_aliases = {
"new york's central park": "new york",
"nyc": "new york"
}
if normalized_city in static_aliases:
root_city = static_aliases[normalized_city]
info = CITY_REGISTRY[root_city]
return {"lat": info["lat"], "lon": info["lon"]}
for key in CITY_REGISTRY:
if key in normalized_city:
logger.debug(f"地理编码命中模糊映射: {city} -> {key}")
info = CITY_REGISTRY[key]
return {"lat": info["lat"], "lon": info["lon"]}
try:
url = "https://geocoding-api.open-meteo.com/v1/search"
response = self._http_get(
url,
params={"name": city, "count": 1, "language": "en", "format": "json"},
timeout=15, # 增加超时时间到 15s
)
response.raise_for_status()
results = response.json().get("results", [])
if results:
res = results[0]
return {
"lat": res.get("latitude"),
"lon": res.get("longitude"),
"name": res.get("name"),
"country": res.get("country"),
}
except Exception as e:
logger.error(f"地理编码失败 ({city}): {e}")
return None
def extract_city_from_question(self, question: str) -> Optional[str]:
"""
从 Polymarket 问题描述或 Slug 中提取城市名称
"""
q = question.lower()
# 1. 优先尝试已知城市列表 (硬编码匹配)
known_cities = {
"london": "London",
"伦敦": "London",
"new york": "New York",
"new york's central park": "New York",
"nyc": "New York",
"纽约": "New York",
"seattle": "Seattle",
"西雅图": "Seattle",
"chicago": "Chicago",
"芝加哥": "Chicago",
"dallas": "Dallas",
"达拉斯": "Dallas",
"miami": "Miami",
"迈阿密": "Miami",
"atlanta": "Atlanta",
"亚特兰大": "Atlanta",
"istanbul": "Istanbul",
"ist": "Istanbul",
"ltfm": "Istanbul",
"moscow": "Moscow",
"mos": "Moscow",
"mow": "Moscow",
"uuww": "Moscow",
"vnukovo": "Moscow",
"莫斯科": "Moscow",
"伊斯坦布尔": "Istanbul",
"seoul": "Seoul",
"首尔": "Seoul",
"busan": "Busan",
"pusan": "Busan",
"釜山": "Busan",
"hong kong": "Hong Kong",
"hong kong international airport": "Hong Kong",
"香港": "Hong Kong",
"shek kong": "Shek Kong",
"vhsk": "Shek Kong",
"石岗": "Shek Kong",
"石崗": "Shek Kong",
"lau fau shan": "Lau Fau Shan",
"lfs": "Lau Fau Shan",
"流浮山": "Lau Fau Shan",
"taipei": "Taipei",
"台北": "Taipei",
"臺北": "Taipei",
"chengdu": "Chengdu",
"成都": "Chengdu",
"chongqing": "Chongqing",
"重庆": "Chongqing",
"shenzhen": "Shenzhen",
"深圳": "Shenzhen",
"qingdao": "Qingdao",
"青岛": "Qingdao",
"青島": "Qingdao",
"beijing": "Beijing",
"北京": "Beijing",
"wuhan": "Wuhan",
"武汉": "Wuhan",
"shanghai": "Shanghai",
"上海": "Shanghai",
"singapore": "Singapore",
"新加坡": "Singapore",
"kuala lumpur": "Kuala Lumpur",
"sepang": "Kuala Lumpur",
"吉隆坡": "Kuala Lumpur",
"jakarta": "Jakarta",
"雅加达": "Jakarta",
"雅加達": "Jakarta",
"manila": "Manila",
"rpll": "Manila",
"马尼拉": "Manila",
"馬尼拉": "Manila",
"karachi": "Karachi",
"opkc": "Karachi",
"卡拉奇": "Karachi",
"helsinki": "Helsinki",
"vantaa": "Helsinki",
"赫尔辛基": "Helsinki",
"赫爾辛基": "Helsinki",
"amsterdam": "Amsterdam",
"schiphol": "Amsterdam",
"阿姆斯特丹": "Amsterdam",
"panama city": "Panama City",
"巴拿马城": "Panama City",
"tokyo": "Tokyo",
"东京": "Tokyo",
"東京": "Tokyo",
"milan": "Milan",
"米兰": "Milan",
"米蘭": "Milan",
"madrid": "Madrid",
"马德里": "Madrid",
"馬德里": "Madrid",
"tel aviv": "Tel Aviv",
"特拉维夫": "Tel Aviv",
"toronto": "Toronto",
"多伦多": "Toronto",
"ankara": "Ankara",
"安卡拉": "Ankara",
"wellington": "Wellington",
"惠灵顿": "Wellington",
"buenos aires": "Buenos Aires",
"布宜诺斯艾利斯": "Buenos Aires",
"warsaw": "Warsaw",
"华沙": "Warsaw",
"華沙": "Warsaw",
}
for key, val in known_cities.items():
if key in q:
return val
# 2. 从英文模板中提取
triggers = [
"temperature in ",
"temp in ",
"weather in ",
"highest-temperature-in-",
"temperature-in-",
]
for trigger in triggers:
if trigger in q:
part = q.split(trigger)[1]
delimiters = [
" on ",
" at ",
" above ",
" below ",
" be ",
" is ",
" will ",
" has ",
" reached ",
"?",
" (",
", ",
"-",
]
city = part
for d in delimiters:
if d in city:
city = city.split(d)[0]
return city.strip().title()
return None
def _evict_city_caches(
self,
city: str,
lat: Optional[float],
lon: Optional[float],
use_fahrenheit: bool,
) -> None:
"""Drop in-memory caches for one city before a force-refresh query."""
if lat is not None and lon is not None:
base = f"{round(float(lat), 4)}:{round(float(lon), 4)}"
unit = "f" if use_fahrenheit else "c"
open_meteo_key = f"{base}:14:{unit}"
ensemble_key = f"{base}:{unit}"
cache_city = str(city or "").strip().lower()
multi_model_key = (
f"{base}:{cache_city}:{unit}:{self.multi_model_cache_version}"
)
with self._open_meteo_cache_lock:
self._open_meteo_cache.pop(open_meteo_key, None)
with self._ensemble_cache_lock:
self._ensemble_cache.pop(ensemble_key, None)
with self._multi_model_cache_lock:
self._multi_model_cache.pop(multi_model_key, None)
icao = self.get_icao_code(city)
if icao:
prefix = f"{icao}:"
with self._metar_cache_lock:
for key in list(self._metar_cache.keys()):
if key.startswith(prefix):
self._metar_cache.pop(key, None)
normalized = str(city or "").strip().lower()
with self._jma_cache_lock:
self._jma_cache.pop(f"{normalized}:{use_fahrenheit}", None)
with self._nmc_cache_lock:
self._nmc_cache.pop(f"{normalized}:{use_fahrenheit}", None)
with self._ru_station_cache_lock:
self._ru_station_cache.pop(f"{normalized}:{use_fahrenheit}", None)
with self._settlement_cache_lock:
city_meta = self.CITY_REGISTRY.get(normalized) or {}
settlement_source = str(city_meta.get("settlement_source") or "").strip().lower()
if settlement_source == "hko":
station_code = (
str(city_meta.get("settlement_station_code") or "").strip()
or str(city_meta.get("icao") or "").strip()
or normalized
)
self._settlement_cache.pop(f"hko:{station_code.lower()}", None)
elif settlement_source == "noaa":
station_code = (
str(city_meta.get("settlement_station_code") or "").strip()
or str(city_meta.get("icao") or "").strip()
or normalized
)
self._settlement_cache.pop(f"noaa:{station_code.lower()}", None)
elif settlement_source == "cwa":
station_code = (
str(city_meta.get("settlement_station_code") or "").strip()
or normalized
)
self._settlement_cache.pop(f"cwa:{station_code.lower()}", None)
def _uses_fahrenheit(self, city_lower: str) -> bool:
return city_lower in self.US_CITIES
def _supports_aviationweather(self, city_lower: str) -> bool:
city_meta = self.CITY_REGISTRY.get(str(city_lower or "").strip().lower(), {}) or {}
settlement_source = str(city_meta.get("settlement_source") or "").strip().lower()
# HKO-settled Hong Kong cities (Hong Kong, Lau Fau Shan, future HKO stations)
# are official observatory stations, not airport/METAR contracts. Do not fetch
# AviationWeather for their city cards; Shenzhen remains ZGSZ/Bao'an METAR-backed.
if settlement_source == "hko":
return False
return not bool(city_meta.get("disable_aviationweather"))
def _log_temperature_unit(self, city: str, use_fahrenheit: bool) -> None:
unit = "华氏度 (°F)" if use_fahrenheit else "摄氏度 (°C)"
logger.info(f"🌡️ {city} 使用{unit}")
def _attach_settlement_sources(self, results: Dict, city_lower: str) -> None:
settlement_current = self.fetch_settlement_current(city_lower)
if settlement_current:
results["settlement_current"] = settlement_current
city_meta = self.CITY_REGISTRY.get(str(city_lower or "").strip().lower()) or {}
settlement_source = str(city_meta.get("settlement_source") or "").strip().lower()
if settlement_source == "hko" or city_lower in ["hong_kong", "hong kong", "香港", "hk"]:
hko_forecast = self.fetch_hko_forecast()
if hko_forecast:
results["hko_forecast"] = hko_forecast
elif settlement_source == "cwa":
cwa_forecast = self.fetch_cwa_taipei_forecast()
if cwa_forecast is not None:
results["cwa_forecast"] = cwa_forecast
def _attach_turkish_mgm_data(
self,
results: Dict,
city_lower: str,
*,
include_mgm: bool = True,
include_nearby: bool = True,
) -> None:
if not include_mgm or city_lower not in self.TURKISH_PROVINCES:
return
istno, province = self.TURKISH_PROVINCES[city_lower]
mgm_data = self.fetch_from_mgm(istno)
if not mgm_data:
return
results["mgm"] = mgm_data
if include_nearby:
results["nearby_source"] = "mgm"
nearby = self.fetch_mgm_nearby_stations(province, root_ist_no=istno)
if nearby:
results["mgm_nearby"] = nearby
def _attach_global_nearby_cluster(
self, results: Dict, city_lower: str, use_fahrenheit: bool
) -> None:
city_meta = self.CITY_REGISTRY.get(str(city_lower or "").strip().lower()) or {}
settlement_source = str(city_meta.get("settlement_source") or "").strip().lower()
if (
city_lower not in self.CITY_METAR_CLUSTERS
or "mgm_nearby" in results
or settlement_source in {"hko", "cwa"}
):
return
cluster_icaos = self.CITY_METAR_CLUSTERS[city_lower]
cluster_data = self.fetch_metar_nearby_cluster(
cluster_icaos, use_fahrenheit=use_fahrenheit
)
if cluster_data:
results["mgm_nearby"] = cluster_data
results["nearby_source"] = "metar_cluster"
def _attach_china_official_nearby(
self, results: Dict, city_lower: str, use_fahrenheit: bool
) -> None:
if city_lower not in {
"beijing",
"chengdu",
"chongqing",
"shanghai",
"shenzhen",
"wuhan",
}:
return
official_rows = self.fetch_nmc_official_nearby(
city_lower, use_fahrenheit=use_fahrenheit
)
if not official_rows:
return
results["nmc_official_nearby"] = official_rows
if "mgm_nearby" not in results:
results["mgm_nearby"] = official_rows
results["nearby_source"] = "nmc"
def _attach_japan_official_nearby(
self, results: Dict, city_lower: str, use_fahrenheit: bool
) -> None:
if city_lower != "tokyo":
return
official_rows = self.fetch_jma_amedas_official_nearby(
city_lower, use_fahrenheit=use_fahrenheit
)
if not official_rows:
return
results["jma_official_nearby"] = official_rows
if "mgm_nearby" not in results:
results["mgm_nearby"] = official_rows
results["nearby_source"] = "jma"
try:
row = official_rows[0] if official_rows else {}
icao = str(row.get("icao") or row.get("istNo") or "RJTT")
DBManager().append_airport_obs(
icao=icao,
city=city_lower,
temp_c=row.get("temp"),
obs_time=str(row.get("obs_time") or datetime.now().isoformat()),
)
except Exception:
logger.exception("airport_obs_log append failed for jma city={}", city_lower)
def _attach_korean_amos_data(
self, results: Dict, city_lower: str, use_fahrenheit: bool
) -> None:
"""Fetch AMOS runway-level observations for Seoul and Busan."""
if city_lower not in ("seoul", "busan"):
return
try:
logger.info("AMOS: fetching for city={}", city_lower)
amos_data = self.fetch_amos_official_current(
city_lower, use_fahrenheit=use_fahrenheit
)
if amos_data:
logger.info("AMOS: got data for city={} temp_c={} source={} runway_pairs={}",
city_lower, amos_data.get("temp_c"), amos_data.get("temp_source"),
len(amos_data.get("runway_obs", {}).get("runway_pairs", []) or []))
results["amos"] = amos_data
try:
DBManager().append_airport_obs(
icao=amos_data.get("icao") or "",
city=city_lower,
temp_c=amos_data.get("temp_c"),
wind_kt=amos_data.get("wind_kt"),
pressure_hpa=amos_data.get("pressure_hpa"),
obs_time=amos_data.get("observation_time") or datetime.now().isoformat(),
)
except Exception:
logger.exception("airport_obs_log append failed for amos city={}", city_lower)
else:
logger.warning("AMOS: no data returned for city={}", city_lower)
except Exception as exc:
logger.warning("AMOS attach failed city={}: {}", city_lower, exc)
def _attach_russia_official_nearby(
self, results: Dict, city_lower: str, use_fahrenheit: bool
) -> None:
if city_lower != "moscow":
return
official_rows = self.fetch_russia_moscow_official_nearby(
city_lower, use_fahrenheit=use_fahrenheit
)
if not official_rows:
return
# Pogodaiklimat station rows are SYNOP/archive-style reference observations,
# not realtime enough for the map. Keep them out of official_nearby/mgm_nearby
# so Moscow uses the live METAR cluster for nearby map temperatures.
results["ru_reference_nearby"] = official_rows
def _attach_warsaw_official_nearby(
self, results: Dict, use_fahrenheit: bool
) -> None:
if "mgm_nearby" in results:
return
official_rows = []
epwa_rows = self.fetch_metar_nearby_cluster(["EPWA"], use_fahrenheit=use_fahrenheit)
if epwa_rows:
epwa = dict(epwa_rows[0])
epwa["name"] = "Warszawa-Okęcie (EPWA)"
official_rows.append(epwa)
imgw_row = self.fetch_imgw_synoptic_station_current(
"Warszawa",
display_name="Warszawa (IMGW synoptic)",
use_fahrenheit=use_fahrenheit,
)
if imgw_row:
official_rows.append(imgw_row)
if official_rows:
results["mgm_nearby"] = official_rows
results["nearby_source"] = "official_cluster"
def _attach_nws_and_models(
self,
results: Dict,
city: str,
lat: float,
lon: float,
use_fahrenheit: bool,
*,
include_ensemble: bool = True,
include_multi_model: bool = True,
) -> None:
if use_fahrenheit:
nws_data = self.fetch_nws(lat, lon)
if nws_data:
results["nws"] = nws_data
if include_ensemble:
ensemble_data = self.fetch_ensemble(lat, lon, use_fahrenheit=use_fahrenheit)
if ensemble_data:
results["ensemble"] = ensemble_data
if include_multi_model:
multi_model_data = self.fetch_multi_model(
lat, lon, city=city, use_fahrenheit=use_fahrenheit
)
if multi_model_data:
results["multi_model"] = multi_model_data
def fetch_all_sources(
self,
city: str,
lat: float = None,
lon: float = None,
country: str = None,
force_refresh: bool = False,
include_taf: bool = True,
include_nearby: bool = True,
include_ensemble: bool = True,
include_multi_model: bool = True,
include_mgm: bool = True,
) -> Dict:
"""
Fetch weather data from all available sources
"""
results = {}
city_lower = city.lower().strip()
use_fahrenheit = self._uses_fahrenheit(city_lower)
supports_aviationweather = self._supports_aviationweather(city_lower)
if force_refresh:
self._evict_city_caches(
city=city,
lat=lat,
lon=lon,
use_fahrenheit=use_fahrenheit,
)
self._log_temperature_unit(city, use_fahrenheit)
self._attach_settlement_sources(results, city_lower)
if lat and lon:
open_meteo = self.fetch_from_open_meteo(
lat, lon, use_fahrenheit=use_fahrenheit
)
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)
if supports_aviationweather:
metar_data = self.fetch_metar(
city, use_fahrenheit=use_fahrenheit, utc_offset=utc_offset
)
if metar_data:
results["metar"] = metar_data
if include_taf and supports_aviationweather and city_lower != "hong kong":
taf_data = self.fetch_taf(city, utc_offset=utc_offset)
if taf_data:
results["taf"] = taf_data
self._attach_turkish_mgm_data(
results,
city_lower,
include_mgm=include_mgm,
include_nearby=include_nearby,
)
self._attach_korean_amos_data(results, city_lower, use_fahrenheit)
if include_nearby:
self._attach_china_official_nearby(results, city_lower, use_fahrenheit)
self._attach_japan_official_nearby(results, city_lower, use_fahrenheit)
self._attach_russia_official_nearby(results, city_lower, use_fahrenheit)
if city_lower == "warsaw":
self._attach_warsaw_official_nearby(results, use_fahrenheit)
self._attach_global_nearby_cluster(
results, city_lower, use_fahrenheit
)
self._attach_nws_and_models(
results,
city,
lat,
lon,
use_fahrenheit,
include_ensemble=include_ensemble,
include_multi_model=include_multi_model,
)
else:
fallback_utc_offset = int(
self.CITY_REGISTRY.get(city_lower, {}).get("tz_offset", 0)
)
if supports_aviationweather:
metar_data = self.fetch_metar(
city,
use_fahrenheit=use_fahrenheit,
utc_offset=fallback_utc_offset,
)
if metar_data:
results["metar"] = metar_data
if include_taf and supports_aviationweather and city_lower != "hong kong":
taf_data = self.fetch_taf(city, utc_offset=fallback_utc_offset)
if taf_data:
results["taf"] = taf_data
self._attach_turkish_mgm_data(
results,
city_lower,
include_mgm=include_mgm,
include_nearby=include_nearby,
)
self._attach_korean_amos_data(results, city_lower, use_fahrenheit)
if include_nearby:
self._attach_china_official_nearby(results, city_lower, use_fahrenheit)
self._attach_japan_official_nearby(results, city_lower, use_fahrenheit)
self._attach_russia_official_nearby(results, city_lower, use_fahrenheit)
if city_lower == "warsaw":
self._attach_warsaw_official_nearby(results, use_fahrenheit)
self._attach_global_nearby_cluster(
results, city_lower, use_fahrenheit
)
self._attach_nws_and_models(
results,
city,
lat,
lon,
use_fahrenheit,
include_ensemble=include_ensemble,
include_multi_model=include_multi_model,
)
else:
if supports_aviationweather:
metar_data = self.fetch_metar(city, use_fahrenheit=use_fahrenheit)
if metar_data:
results["metar"] = metar_data
if include_taf and supports_aviationweather and city_lower != "hong kong":
taf_data = self.fetch_taf(city)
if taf_data:
results["taf"] = taf_data
return results
def check_consensus(self, forecasts: Dict) -> Dict:
"""
Check consensus across multiple weather sources
Args:
forecasts: Dict of forecasts from different sources
Returns:
dict: Consensus analysis
"""
predictions = []
for source, data in forecasts.items():
if data and "current" in data:
predictions.append({"source": source, "temp": data["current"]["temp"]})
if len(predictions) == 0:
return {"consensus": False, "reason": "No weather data available"}
temps = [p["temp"] for p in predictions]
avg_temp = sum(temps) / len(temps)
# If only one source, consensus is implicitly true
if len(predictions) == 1:
return {
"consensus": True,
"average_temp": avg_temp,
"max_difference": 0.0,
"predictions": predictions,
"note": "Single source only",
}
max_diff = max(abs(t - avg_temp) for t in temps)
# Consensus if all predictions within 2.5°C
is_consensus = max_diff <= 2.5
return {
"consensus": is_consensus,
"average_temp": avg_temp,
"max_difference": max_diff,
"predictions": predictions,
}