2569718930@qq.com
1306 lines
51 KiB
Python
1306 lines
51 KiB
Python
import requests
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import re
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import time
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from typing import Optional, Dict, List
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from datetime import datetime, timedelta
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from loguru import logger
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class WeatherDataCollector:
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"""
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Multi-source weather data collector
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Supports:
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- OpenWeatherMap (free, fast updates)
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- Weather Underground (Polymarket settlement source)
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- Visual Crossing (rich historical data)
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- NOAA Aviation Weather (METAR - airport observations)
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"""
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# Polymarket 12 个天气市场对应的 ICAO 机场代码
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# 这些是 Weather Underground 结算源使用的气象站
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CITY_TO_ICAO = {
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"seattle": "KSEA", # Seattle-Tacoma Airport
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"london": "EGLC", # London City Airport
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"dallas": "KDAL", # Dallas Love Field
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"miami": "KMIA", # Miami International
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"atlanta": "KATL", # Hartsfield-Jackson
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"chicago": "KORD", # O'Hare International
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"new york": "KLGA", # LaGuardia Airport
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"nyc": "KLGA", # Alias
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"seoul": "RKSI", # Incheon International
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"ankara": "LTAC", # Esenboğa International
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"toronto": "CYYZ", # Toronto Pearson
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"wellington": "NZWN", # Wellington International
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"buenos aires": "SAEZ", # Ezeiza International
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"paris": "LFPG", # Charles de Gaulle
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}
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def __init__(self, config: dict):
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self.config = config
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weather_cfg = config.get("weather", {})
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self.wunderground_key = weather_cfg.get("wunderground_api_key")
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self.meteoblue_key = weather_cfg.get("meteoblue_api_key")
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self.timeout = 30 # 增加超时以支持高延迟 VPS
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self.session = requests.Session()
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# 设置代理
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proxy = config.get("proxy")
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if proxy:
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if not proxy.startswith("http"):
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proxy = f"http://{proxy}"
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self.session.proxies = {"http": proxy, "https": proxy}
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logger.info(f"正在使用天气数据代理: {proxy}")
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logger.info("天气数据采集器初始化完成。")
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def fetch_from_openweather(self, city: str, country: str = None) -> Optional[Dict]:
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"""
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Fetch current weather and forecast from OpenWeatherMap
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Args:
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city: City name
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country: Country code (optional)
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Returns:
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dict: Weather data
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"""
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if not getattr(self, "openweather_key", None):
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return None
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query = f"{city},{country}" if country else city
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try:
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# Current weather
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current_url = "https://api.openweathermap.org/data/2.5/weather"
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current_response = self.session.get(
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current_url,
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params={"q": query, "appid": self.openweather_key, "units": "metric"},
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timeout=self.timeout,
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)
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current_response.raise_for_status()
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current_data = current_response.json()
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# 5-day forecast
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forecast_url = "https://api.openweathermap.org/data/2.5/forecast"
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forecast_response = self.session.get(
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forecast_url,
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params={"q": query, "appid": self.openweather_key, "units": "metric"},
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timeout=self.timeout,
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)
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forecast_response.raise_for_status()
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forecast_data = forecast_response.json()
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return {
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"source": "openweathermap",
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"timestamp": datetime.utcnow().isoformat(),
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"current": {
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"temp": current_data["main"]["temp"],
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"feels_like": current_data["main"]["feels_like"],
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"temp_min": current_data["main"]["temp_min"],
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"temp_max": current_data["main"]["temp_max"],
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"humidity": current_data["main"]["humidity"],
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"pressure": current_data["main"]["pressure"],
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"wind_speed": current_data["wind"]["speed"],
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"clouds": current_data["clouds"]["all"],
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"description": current_data["weather"][0]["description"],
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},
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"forecast": self._parse_openweather_forecast(forecast_data),
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}
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except requests.exceptions.RequestException as e:
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logger.error(f"OpenWeatherMap request failed: {e}")
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return None
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def _parse_openweather_forecast(self, data: dict) -> List[Dict]:
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"""Parse OpenWeatherMap forecast data"""
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forecasts = []
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for item in data.get("list", []):
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forecasts.append(
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{
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"datetime": item["dt_txt"],
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"temp": item["main"]["temp"],
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"temp_min": item["main"]["temp_min"],
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"temp_max": item["main"]["temp_max"],
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"humidity": item["main"]["humidity"],
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"description": item["weather"][0]["description"],
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}
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)
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return forecasts
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def fetch_from_visualcrossing(
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self, city: str, start_date: str = None, end_date: str = None
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) -> Optional[Dict]:
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"""
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Fetch historical weather data from Visual Crossing
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Args:
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city: City name
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start_date: Start date (YYYY-MM-DD)
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end_date: End date (YYYY-MM-DD)
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Returns:
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dict: Historical weather data
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"""
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if not getattr(self, "visualcrossing_key", None):
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return None
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# Default to last 30 days if no dates provided
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if not end_date:
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end_date = datetime.now().strftime("%Y-%m-%d")
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if not start_date:
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start_date = (datetime.now() - timedelta(days=30)).strftime("%Y-%m-%d")
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try:
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url = f"https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/{city}/{start_date}/{end_date}"
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response = self.session.get(
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url,
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params={
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"unitGroup": "metric",
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"key": self.visualcrossing_key,
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"contentType": "json",
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"include": "days",
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},
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timeout=self.timeout,
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)
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response.raise_for_status()
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data = response.json()
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return {
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"source": "visualcrossing",
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"timestamp": datetime.utcnow().isoformat(),
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"location": data.get("resolvedAddress"),
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"timezone": data.get("timezone"),
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"days": [
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{
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"date": day["datetime"],
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"temp_max": day.get("tempmax"),
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"temp_min": day.get("tempmin"),
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"temp_avg": day.get("temp"),
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"humidity": day.get("humidity"),
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"precip": day.get("precip"),
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"conditions": day.get("conditions"),
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}
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for day in data.get("days", [])
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],
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}
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except requests.exceptions.RequestException as e:
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logger.error(f"Visual Crossing request failed: {e}")
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return None
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def get_icao_code(self, city: str) -> Optional[str]:
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"""
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根据城市名获取对应的 ICAO 机场代码
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"""
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normalized = city.lower().strip()
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# 直接匹配
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if normalized in self.CITY_TO_ICAO:
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return self.CITY_TO_ICAO[normalized]
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# 模糊匹配
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for key, icao in self.CITY_TO_ICAO.items():
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if key in normalized or normalized in key:
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return icao
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return None
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def fetch_metar(
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self, city: str, use_fahrenheit: bool = False, utc_offset: int = 0
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) -> Optional[Dict]:
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"""
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从 NOAA Aviation Weather Center 获取 METAR 航空气象数据
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这是 Polymarket 天气市场的结算数据源 (Weather Underground) 使用的相同气象站
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Args:
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city: 城市名称
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use_fahrenheit: 是否转换为华氏度
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Returns:
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dict: METAR 数据，包含温度、露点、风速等
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"""
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icao = self.get_icao_code(city)
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if not icao:
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logger.warning(f"未找到城市 {city} 对应的 ICAO 代码")
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return None
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try:
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# NOAA Aviation Weather API (免费，无需 Key)
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url = "https://aviationweather.gov/api/data/metar"
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params = {
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"ids": icao,
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"format": "json",
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"hours": 24, # 抓取 24 小时数据以计算今日最高
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"_t": int(time.time()),
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}
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response = self.session.get(
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url,
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params=params,
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headers={"Cache-Control": "no-cache", "Pragma": "no-cache"},
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timeout=self.timeout,
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)
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response.raise_for_status()
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data = response.json()
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if not data:
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return None
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# 1. 取最新的观测作为当前状态
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latest = data[0]
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temp_c = latest.get("temp")
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dewp_c = latest.get("dewp")
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# 从 rawOb 中提取真实观测时间（比 reportTime 更准确，reportTime 会被取整）
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# rawOb 格式: "METAR EGLC 271150Z AUTO ..." → "271150Z" → 27日11:50 UTC
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def _parse_rawob_time(obs):
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"""从 rawOb 中提取精确的 UTC 观测时间"""
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raw = obs.get("rawOb", "")
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import re as _re
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m = _re.search(r"\b(\d{2})(\d{2})(\d{2})Z\b", raw)
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if m:
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_day, hour, minute = (
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int(m.group(1)),
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int(m.group(2)),
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int(m.group(3)),
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)
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# 用 reportTime 的日期部分 + rawOb 的时分
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fallback = obs.get("reportTime", "")
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try:
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clean = fallback.replace(" ", "T")
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if not clean.endswith("Z"):
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clean += "Z"
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base_dt = datetime.fromisoformat(clean.replace("Z", "+00:00"))
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result = base_dt.replace(hour=hour, minute=minute, second=0)
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# 处理跨日（如 rawOb 是23:50但 reportTime 已经是次日00:00）
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if result > base_dt + timedelta(hours=2):
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result -= timedelta(days=1)
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return result
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except Exception:
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pass
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# fallback 到 reportTime
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fallback = obs.get("reportTime", "")
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try:
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clean = fallback.replace(" ", "T")
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if not clean.endswith("Z"):
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clean += "Z"
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return datetime.fromisoformat(clean.replace("Z", "+00:00"))
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except Exception:
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return None
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obs_dt = _parse_rawob_time(latest)
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obs_time = (
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obs_dt.strftime("%Y-%m-%dT%H:%M:%S.000Z")
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if obs_dt
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else latest.get("reportTime", "")
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)
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# 2. 精确计算"当地今天"的最高温
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from datetime import timezone, timedelta
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now_utc = datetime.now(timezone.utc)
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local_now = now_utc + timedelta(seconds=utc_offset)
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local_midnight = local_now.replace(
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hour=0, minute=0, second=0, microsecond=0
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)
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utc_midnight = local_midnight - timedelta(seconds=utc_offset)
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max_so_far_c = -999
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max_temp_time = None
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for obs in data:
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obs_dt_iter = _parse_rawob_time(obs)
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if obs_dt_iter is None:
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continue
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try:
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if obs_dt_iter >= utc_midnight:
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t = obs.get("temp")
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if t is not None and t > max_so_far_c:
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max_so_far_c = t
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local_report = obs_dt_iter + timedelta(seconds=utc_offset)
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max_temp_time = local_report.strftime("%H:%M")
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except Exception:
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continue
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# 3. 提取最近 4 条报文的多维数据（温度 + 风/云/压强，用于趋势和 shock_score）
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recent_temps_raw = [] # [(local_time_str, temp_c), ...]
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recent_obs_raw = [] # [{time, temp, wdir, wspd, clouds, altim}, ...]
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today_obs_raw = [] # [(local_time_str, temp_c), ...] 今天全部观测
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cloud_rank_map = {
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"CLR": 0, "SKC": 0, "FEW": 1, "SCT": 2, "BKN": 3, "OVC": 4,
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}
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for i_obs, obs in enumerate(data): # data 已按时间倒序
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obs_temp = obs.get("temp")
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obs_dt_iter = _parse_rawob_time(obs)
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if obs_temp is not None and obs_dt_iter:
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local_rt = obs_dt_iter + timedelta(seconds=utc_offset)
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time_str = local_rt.strftime("%H:%M")
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# 收集今天全部观测点（用于图表叠加）
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if obs_dt_iter >= utc_midnight:
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today_obs_raw.append((time_str, obs_temp))
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# 只取前4条用于趋势分析和 shock_score
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if i_obs < 4:
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recent_temps_raw.append((time_str, obs_temp))
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clouds = obs.get("clouds", [])
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max_cloud_rank = 0
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for c in clouds:
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rank = cloud_rank_map.get(c.get("cover", ""), 0)
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if rank > max_cloud_rank:
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max_cloud_rank = rank
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recent_obs_raw.append(
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{
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"time": time_str,
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"temp": obs_temp,
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"wdir": obs.get("wdir"),
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"wspd": obs.get("wspd"),
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"cloud_rank": max_cloud_rank, # 0~4
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"altim": obs.get("altim"),
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}
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)
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# 转换为单位
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if use_fahrenheit:
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temp = temp_c * 9 / 5 + 32 if temp_c is not None else None
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max_so_far = max_so_far_c * 9 / 5 + 32 if max_so_far_c > -900 else None
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dewp = dewp_c * 9 / 5 + 32 if dewp_c is not None else None
|
||
unit = "fahrenheit"
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recent_temps = [
|
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(t, round(v * 9 / 5 + 32, 1)) for t, v in recent_temps_raw
|
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]
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||
today_obs = [
|
||
(t, round(v * 9 / 5 + 32, 1)) for t, v in today_obs_raw
|
||
]
|
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else:
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temp = temp_c
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max_so_far = max_so_far_c if max_so_far_c > -900 else None
|
||
dewp = dewp_c
|
||
unit = "celsius"
|
||
recent_temps = [(t, v) for t, v in recent_temps_raw]
|
||
today_obs = [(t, v) for t, v in today_obs_raw]
|
||
|
||
result = {
|
||
"source": "metar",
|
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"icao": icao,
|
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"station_name": latest.get("name", icao),
|
||
"timestamp": datetime.utcnow().isoformat(),
|
||
"observation_time": obs_time,
|
||
"current": {
|
||
"temp": round(temp, 1) if temp is not None else None,
|
||
"max_temp_so_far": round(max_so_far, 1)
|
||
if max_so_far is not None
|
||
else None,
|
||
"max_temp_time": max_temp_time,
|
||
"dewpoint": round(dewp, 1) if dewp is not None else None,
|
||
"humidity": latest.get("rh"),
|
||
"wind_speed_kt": latest.get("wspd"),
|
||
"wind_dir": latest.get("wdir"),
|
||
"visibility_mi": latest.get("visib"),
|
||
"wx_desc": latest.get("wxString"),
|
||
"altimeter": latest.get("altim"),
|
||
"clouds": latest.get("clouds", []),
|
||
},
|
||
"recent_temps": recent_temps, # 最近4条: [("15:00", 5), ("14:20", 5), ...]
|
||
"today_obs": today_obs, # 今天全部观测: [("00:00", 3), ("01:00", 2.5), ...]
|
||
"recent_obs": recent_obs_raw, # 最近4条多维数据（风/云/压强）
|
||
"unit": unit,
|
||
}
|
||
|
||
logger.info(
|
||
f"✈️ METAR {icao}: {temp:.1f}°{'F' if use_fahrenheit else 'C'} "
|
||
f"(obs: {obs_time})"
|
||
)
|
||
|
||
return result
|
||
|
||
except requests.exceptions.RequestException as e:
|
||
logger.error(f"METAR 请求失败 ({icao}): {e}")
|
||
return None
|
||
except (KeyError, IndexError, TypeError) as e:
|
||
logger.error(f"METAR 数据解析失败 ({icao}): {e}")
|
||
return None
|
||
|
||
def fetch_from_mgm(self, istno: str) -> Optional[Dict]:
|
||
"""
|
||
从土耳其气象局 (MGM) 获取实时数据和预测 (由用户提供其内部 API)
|
||
"""
|
||
base_url = "https://servis.mgm.gov.tr/web"
|
||
# 必须带 Origin，否则会被反爬拦截
|
||
headers = {
|
||
"Origin": "https://www.mgm.gov.tr",
|
||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
||
}
|
||
results = {}
|
||
|
||
try:
|
||
# 1. 实时数据 (添加时间戳防止 CDN 缓存)
|
||
import time
|
||
|
||
obs_resp = self.session.get(
|
||
f"{base_url}/sondurumlar?istno={istno}&_={int(time.time() * 1000)}",
|
||
headers=headers,
|
||
timeout=self.timeout,
|
||
)
|
||
if obs_resp.status_code == 200:
|
||
data = obs_resp.json()
|
||
if data:
|
||
latest = data[0] if isinstance(data, list) else data
|
||
# MGM 数据字段映射
|
||
# ruzgarHiz 实测为 km/h，转为 m/s 需要除以 3.6
|
||
ruz_hiz_kmh = latest.get("ruzgarHiz", 0)
|
||
|
||
# MGM 返回 -9999 表示数据缺失，需要过滤
|
||
def _valid(v):
|
||
return v is not None and v > -9000
|
||
|
||
results["current"] = {
|
||
"temp": latest.get("sicaklik")
|
||
if _valid(latest.get("sicaklik"))
|
||
else None,
|
||
"feels_like": latest.get("hissedilenSicaklik")
|
||
if _valid(latest.get("hissedilenSicaklik"))
|
||
else None,
|
||
"humidity": latest.get("nem")
|
||
if _valid(latest.get("nem"))
|
||
else None,
|
||
"wind_speed_ms": round(ruz_hiz_kmh / 3.6, 1)
|
||
if _valid(ruz_hiz_kmh)
|
||
else None,
|
||
"wind_speed_kt": round(ruz_hiz_kmh / 1.852, 1)
|
||
if _valid(ruz_hiz_kmh)
|
||
else None,
|
||
"wind_dir": latest.get("ruzgarYon")
|
||
if _valid(latest.get("ruzgarYon"))
|
||
else None,
|
||
"rain_24h": latest.get("toplamYagis")
|
||
if _valid(latest.get("toplamYagis"))
|
||
else None,
|
||
"pressure": latest.get("aktuelBasinc")
|
||
if _valid(latest.get("aktuelBasinc"))
|
||
else None,
|
||
"cloud_cover": latest.get("kapalilik"), # 0-8 八分位云量
|
||
"mgm_max_temp": latest.get("maxSicaklik")
|
||
if _valid(latest.get("maxSicaklik"))
|
||
else None,
|
||
"time": latest.get("veriZamani"),
|
||
"station_name": latest.get("istasyonAd")
|
||
or latest.get("adi")
|
||
or latest.get("merkezAd")
|
||
or "Ankara Bölge",
|
||
}
|
||
|
||
# 2. 每日预报（尝试两个可能的 API 路径）
|
||
forecast_urls = [
|
||
f"{base_url}/tahminler/gunluk?istno={istno}",
|
||
f"https://servis.mgm.gov.tr/api/tahminler/gunluk?istno={istno}",
|
||
]
|
||
for forecast_url in forecast_urls:
|
||
try:
|
||
daily_resp = self.session.get(
|
||
forecast_url, headers=headers, timeout=self.timeout
|
||
)
|
||
if daily_resp.status_code == 200:
|
||
forecasts = daily_resp.json()
|
||
if forecasts and isinstance(forecasts, list):
|
||
# Store today extra clearly
|
||
today = forecasts[0]
|
||
high_val = today.get("enYuksekGun1")
|
||
low_val = today.get("enDusukGun1")
|
||
if high_val is not None:
|
||
results["today_high"] = high_val
|
||
results["today_low"] = low_val
|
||
logger.info(f"📋 MGM 每日预报: 今天的最高温 {high_val}°C")
|
||
|
||
# Store all 5 days for multi_model_daily
|
||
results["daily_forecasts"] = {}
|
||
for i, day in enumerate(forecasts[:5]):
|
||
d_high = day.get("enYuksekGun1")
|
||
if d_high is not None:
|
||
# Calculate date (today + offset)
|
||
target_date = (datetime.now() + timedelta(days=i)).strftime("%Y-%m-%d")
|
||
results["daily_forecasts"][target_date] = d_high
|
||
break
|
||
else:
|
||
# 记录所有可用字段，方便调试
|
||
available_keys = [
|
||
k
|
||
for k in today.keys()
|
||
if "yuksek" in k.lower()
|
||
or "sicaklik" in k.lower()
|
||
or "gun" in k.lower()
|
||
]
|
||
logger.warning(
|
||
f"MGM 每日预报: enYuksekGun1 为空，可用字段: {available_keys}"
|
||
)
|
||
else:
|
||
logger.debug(
|
||
f"MGM forecast URL {forecast_url} returned {daily_resp.status_code}"
|
||
)
|
||
except Exception as e:
|
||
logger.debug(f"MGM forecast URL {forecast_url} failed: {e}")
|
||
|
||
# 3. 小时预报
|
||
try:
|
||
hourly_resp = self.session.get(
|
||
f"{base_url}/tahminler/saatlik?istno={istno}",
|
||
headers=headers,
|
||
timeout=self.timeout
|
||
)
|
||
if hourly_resp.status_code == 200:
|
||
h_data = hourly_resp.json()
|
||
if h_data and isinstance(h_data, list):
|
||
tahmin_list = h_data[0].get("tahmin", [])
|
||
results["hourly"] = []
|
||
for t_data in tahmin_list:
|
||
if "tarih" in t_data and "sicaklik" in t_data:
|
||
results["hourly"].append({
|
||
"time": t_data["tarih"],
|
||
"temp": t_data["sicaklik"]
|
||
})
|
||
except Exception as e:
|
||
logger.debug(f"MGM hourly failed: {e}")
|
||
|
||
# 4. Fallback for today_high (if daily forecast is missing it)
|
||
if "today_high" not in results:
|
||
# Try from current max
|
||
cur_max = results.get("current", {}).get("mgm_max_temp")
|
||
if cur_max is not None:
|
||
results["today_high"] = cur_max
|
||
logger.info(f"📋 MGM 每日预报: 使用当前测站最高温作为今日预报回退: {cur_max}°C")
|
||
elif "hourly" in results and results["hourly"]:
|
||
# Try from hourly
|
||
h_max = max((h["temp"] for h in results["hourly"] if h["temp"] is not None), default=None)
|
||
if h_max is not None:
|
||
results["today_high"] = h_max
|
||
logger.info(f"📋 MGM 每日预报: 使用小时预报最高温作为今日预报回退: {h_max}°C")
|
||
|
||
return results if "current" in results else None
|
||
except Exception as e:
|
||
logger.error(f"MGM API 请求失败 ({istno}): {e}")
|
||
return None
|
||
|
||
def fetch_nws(self, lat: float, lon: float) -> Optional[Dict]:
|
||
"""
|
||
从 NWS (美国国家气象局) 获取高精度预报
|
||
仅适用于美国城市，全球 VPS 均可访问
|
||
"""
|
||
try:
|
||
# 1. 获取网格点
|
||
points_url = f"https://api.weather.gov/points/{lat},{lon}"
|
||
headers = {"User-Agent": "PolyWeather/1.0 (weather-bot)"}
|
||
|
||
points_resp = self.session.get(
|
||
points_url, headers=headers, timeout=self.timeout
|
||
)
|
||
points_resp.raise_for_status()
|
||
points_data = points_resp.json()
|
||
|
||
forecast_url = points_data.get("properties", {}).get("forecast")
|
||
if not forecast_url:
|
||
return None
|
||
|
||
# 2. 获取预报
|
||
forecast_resp = self.session.get(
|
||
forecast_url, headers=headers, timeout=self.timeout
|
||
)
|
||
forecast_resp.raise_for_status()
|
||
forecast_data = forecast_resp.json()
|
||
|
||
periods = forecast_data.get("properties", {}).get("periods", [])
|
||
if not periods:
|
||
return None
|
||
|
||
# 3. 提取今日最高温（找 isDaytime=True 的第一个）
|
||
today_high = None
|
||
for p in periods:
|
||
if p.get("isDaytime") and "High" in p.get("name", ""):
|
||
today_high = p.get("temperature")
|
||
break
|
||
# 如果没有明确的 High，取第一个 daytime 的温度
|
||
if today_high is None:
|
||
for p in periods:
|
||
if p.get("isDaytime"):
|
||
today_high = p.get("temperature")
|
||
break
|
||
|
||
return {
|
||
"source": "nws",
|
||
"today_high": today_high,
|
||
"unit": "fahrenheit",
|
||
}
|
||
except Exception as e:
|
||
logger.warning(f"NWS 请求失败: {e}")
|
||
return None
|
||
|
||
def fetch_from_open_meteo(
|
||
self,
|
||
lat: float,
|
||
lon: float,
|
||
forecast_days: int = 14,
|
||
use_fahrenheit: bool = False,
|
||
) -> Optional[Dict]:
|
||
"""
|
||
Fetch weather from Open-Meteo with forecast data
|
||
|
||
Args:
|
||
lat: Latitude
|
||
lon: Longitude
|
||
forecast_days: Number of forecast days to fetch (default 14 to cover all market dates)
|
||
use_fahrenheit: Whether to return temperatures in Fahrenheit (for US markets)
|
||
"""
|
||
try:
|
||
url = "https://api.open-meteo.com/v1/forecast"
|
||
params = {
|
||
"latitude": lat,
|
||
"longitude": lon,
|
||
"current_weather": "true",
|
||
"hourly": "temperature_2m,shortwave_radiation",
|
||
"daily": "temperature_2m_max,apparent_temperature_max,sunrise,sunset,sunshine_duration",
|
||
"timezone": "auto",
|
||
"forecast_days": forecast_days,
|
||
"_t": int(time.time()), # 禁用缓存，强制刷新
|
||
}
|
||
|
||
# 显式指定单位，防止 API 默认行为漂移
|
||
if use_fahrenheit:
|
||
params["temperature_unit"] = "fahrenheit"
|
||
else:
|
||
params["temperature_unit"] = "celsius"
|
||
|
||
response = self.session.get(
|
||
url,
|
||
params=params,
|
||
headers={"Cache-Control": "no-cache", "Pragma": "no-cache"},
|
||
timeout=self.timeout,
|
||
)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
|
||
current = data.get("current_weather", {})
|
||
utc_offset = data.get("utc_offset_seconds", 0)
|
||
timezone_name = data.get("timezone", "UTC")
|
||
|
||
# 处理多模型数据 (如果请求了 models 参数，返回结构会变化)
|
||
daily_data = data.get("daily", {})
|
||
if "temperature_2m_max_ecmwf_ifs04" in daily_data:
|
||
ecmwf_max = daily_data.get("temperature_2m_max_ecmwf_ifs04", [])
|
||
hrrr_max = daily_data.get("temperature_2m_max_ncep_hrrr_conus", [])
|
||
|
||
# 记录今日模型分歧
|
||
daily_data["model_split"] = {
|
||
"ecmwf": ecmwf_max[0] if ecmwf_max else None,
|
||
"hrrr": hrrr_max[0] if hrrr_max else None,
|
||
}
|
||
|
||
# 智能合并：HRRR 仅覆盖 48 小时，远期用 ECMWF 补全
|
||
merged_max = []
|
||
for i in range(len(ecmwf_max)):
|
||
hrrr_val = hrrr_max[i] if i < len(hrrr_max) else None
|
||
ecmwf_val = ecmwf_max[i] if i < len(ecmwf_max) else None
|
||
|
||
# 优先 HRRR，其次 ECMWF，都没有就跳过
|
||
if hrrr_val is not None:
|
||
merged_max.append(hrrr_val)
|
||
elif ecmwf_val is not None:
|
||
merged_max.append(ecmwf_val)
|
||
else:
|
||
# 两个都没有，用占位符 (理论上不应该发生)
|
||
merged_max.append(ecmwf_val) # None
|
||
daily_data["temperature_2m_max"] = merged_max
|
||
|
||
# 映射逐小时数据
|
||
hourly_data = data.get("hourly", {})
|
||
if "temperature_2m_ncep_hrrr_conus" in hourly_data:
|
||
hourly_data["temperature_2m"] = hourly_data[
|
||
"temperature_2m_ncep_hrrr_conus"
|
||
]
|
||
|
||
# 计算精确的当地时间
|
||
now_utc = datetime.utcnow()
|
||
local_now = now_utc + timedelta(seconds=utc_offset)
|
||
local_time_str = local_now.strftime("%Y-%m-%d %H:%M")
|
||
|
||
return {
|
||
"source": "open-meteo",
|
||
"timestamp": now_utc.isoformat(),
|
||
"timezone": timezone_name,
|
||
"utc_offset": utc_offset,
|
||
"current": {
|
||
"temp": current.get("temperature"),
|
||
"local_time": local_time_str,
|
||
},
|
||
"hourly": hourly_data,
|
||
"daily": daily_data,
|
||
"unit": "fahrenheit" if use_fahrenheit else "celsius",
|
||
}
|
||
except Exception as e:
|
||
logger.error(f"Open-Meteo forecast failed: {e}")
|
||
return None
|
||
|
||
def fetch_ensemble(
|
||
self,
|
||
lat: float,
|
||
lon: float,
|
||
use_fahrenheit: bool = False,
|
||
) -> Optional[Dict]:
|
||
"""
|
||
从 Open-Meteo Ensemble API 获取 51 成员集合预报
|
||
用于计算预报不确定性范围（散度）
|
||
"""
|
||
try:
|
||
url = "https://ensemble-api.open-meteo.com/v1/ensemble"
|
||
params = {
|
||
"latitude": lat,
|
||
"longitude": lon,
|
||
"daily": "temperature_2m_max",
|
||
"timezone": "auto",
|
||
"forecast_days": 3,
|
||
"_t": int(time.time()),
|
||
}
|
||
if use_fahrenheit:
|
||
params["temperature_unit"] = "fahrenheit"
|
||
else:
|
||
params["temperature_unit"] = "celsius"
|
||
|
||
response = self.session.get(
|
||
url,
|
||
params=params,
|
||
headers={"Cache-Control": "no-cache"},
|
||
timeout=self.timeout,
|
||
)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
|
||
daily = data.get("daily", {})
|
||
# 每个成员都会返回一组 temperature_2m_max
|
||
# 格式: {"time": [...], "temperature_2m_max_member01": [...], ...}
|
||
today_highs = []
|
||
for key, values in daily.items():
|
||
if key.startswith("temperature_2m_max") and key != "temperature_2m_max":
|
||
if values and values[0] is not None:
|
||
today_highs.append(values[0])
|
||
|
||
# 也检查非成员键（有些返回格式不同）
|
||
if not today_highs:
|
||
raw_max = daily.get("temperature_2m_max", [])
|
||
if isinstance(raw_max, list) and raw_max:
|
||
if isinstance(raw_max[0], list):
|
||
# 嵌套列表格式: [[member1_day1, member1_day2], [member2_day1, ...]]
|
||
today_highs = [m[0] for m in raw_max if m and m[0] is not None]
|
||
elif raw_max[0] is not None:
|
||
today_highs = [raw_max[0]]
|
||
|
||
if len(today_highs) < 3:
|
||
logger.warning(f"Ensemble 数据不足: 仅获取 {len(today_highs)} 个成员")
|
||
return None
|
||
|
||
today_highs.sort()
|
||
n = len(today_highs)
|
||
median = today_highs[n // 2]
|
||
p10 = today_highs[max(0, int(n * 0.1))]
|
||
p90 = today_highs[min(n - 1, int(n * 0.9))]
|
||
|
||
result = {
|
||
"source": "ensemble",
|
||
"members": n,
|
||
"median": round(median, 1),
|
||
"p10": round(p10, 1),
|
||
"p90": round(p90, 1),
|
||
"min": round(today_highs[0], 1),
|
||
"max": round(today_highs[-1], 1),
|
||
"unit": "fahrenheit" if use_fahrenheit else "celsius",
|
||
}
|
||
|
||
logger.info(
|
||
f"📊 Ensemble ({n} members): median={median:.1f}, "
|
||
f"p10={p10:.1f}, p90={p90:.1f}"
|
||
)
|
||
return result
|
||
except Exception as e:
|
||
logger.warning(f"Ensemble API 请求失败: {e}")
|
||
return None
|
||
|
||
def fetch_multi_model(
|
||
self,
|
||
lat: float,
|
||
lon: float,
|
||
use_fahrenheit: bool = False,
|
||
) -> Optional[Dict]:
|
||
"""
|
||
从 Open-Meteo 获取多个独立 NWP 模型的预报
|
||
用于真正的多模型共识评分
|
||
|
||
模型列表:
|
||
- ECMWF IFS (欧洲中期天气预报中心)
|
||
- GFS (美国 NOAA)
|
||
- ICON (德国气象局 DWD)
|
||
- GEM (加拿大气象局)
|
||
- JMA (日本气象厅)
|
||
|
||
返回 3 天的预报数据，支持今日+明日共识分析
|
||
"""
|
||
try:
|
||
url = "https://api.open-meteo.com/v1/forecast"
|
||
models = "ecmwf_ifs025,gfs_seamless,icon_seamless,gem_seamless,jma_seamless"
|
||
params = {
|
||
"latitude": lat,
|
||
"longitude": lon,
|
||
"daily": "temperature_2m_max",
|
||
"models": models,
|
||
"timezone": "auto",
|
||
"forecast_days": 3,
|
||
"_t": int(time.time()),
|
||
}
|
||
if use_fahrenheit:
|
||
params["temperature_unit"] = "fahrenheit"
|
||
|
||
response = self.session.get(
|
||
url,
|
||
params=params,
|
||
headers={"Cache-Control": "no-cache"},
|
||
timeout=self.timeout,
|
||
)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
|
||
daily = data.get("daily", {})
|
||
dates = daily.get("time", [])
|
||
|
||
model_labels = {
|
||
"ecmwf_ifs025": "ECMWF",
|
||
"gfs_seamless": "GFS",
|
||
"icon_seamless": "ICON",
|
||
"gem_seamless": "GEM",
|
||
"jma_seamless": "JMA",
|
||
}
|
||
|
||
# 按天提取每个模型的预报
|
||
daily_forecasts = {} # {"2026-02-23": {"ECMWF": 7.9, "GFS": 6.5, ...}, ...}
|
||
for day_idx, date_str in enumerate(dates):
|
||
day_data = {}
|
||
for model_key, label in model_labels.items():
|
||
key = f"temperature_2m_max_{model_key}"
|
||
values = daily.get(key, [])
|
||
if day_idx < len(values) and values[day_idx] is not None:
|
||
day_data[label] = round(values[day_idx], 1)
|
||
if day_data:
|
||
daily_forecasts[date_str] = day_data
|
||
|
||
if not daily_forecasts:
|
||
logger.warning("Multi-model: 无有效模型数据")
|
||
return None
|
||
|
||
# 今天的预报 (向后兼容)
|
||
today_date = dates[0] if dates else None
|
||
forecasts = daily_forecasts.get(today_date, {})
|
||
|
||
labels_str = ", ".join([f"{k}={v}" for k, v in forecasts.items()])
|
||
logger.info(
|
||
f"🔬 Multi-model ({len(forecasts)}个, {len(daily_forecasts)}天): {labels_str}"
|
||
)
|
||
|
||
return {
|
||
"source": "multi_model",
|
||
"forecasts": forecasts, # 今天 {"ECMWF": 12.3, "GFS": 11.8, ...} (向后兼容)
|
||
"daily_forecasts": daily_forecasts, # 按天 {"2026-02-23": {...}, "2026-02-24": {...}}
|
||
"dates": dates,
|
||
"unit": "fahrenheit" if use_fahrenheit else "celsius",
|
||
}
|
||
except Exception as e:
|
||
logger.warning(f"Multi-model API 请求失败: {e}")
|
||
return None
|
||
|
||
def fetch_from_meteoblue(
|
||
self,
|
||
lat: float,
|
||
lon: float,
|
||
timezone_name: str = "UTC",
|
||
use_fahrenheit: bool = False,
|
||
) -> Optional[Dict]:
|
||
"""
|
||
通过 Meteoblue 官方 API 获取高精度预测数据
|
||
"""
|
||
if not self.meteoblue_key:
|
||
logger.warning("Meteoblue API Key 未配置，跳过抓取。")
|
||
return None
|
||
|
||
try:
|
||
# 1. 调用官方 API (使用 basic-day 包，它是多模型 ML 融合结果)
|
||
# 格式: https://my.meteoblue.com/packages/basic-day?apikey=KEY&lat=LAT&lon=LON&format=json
|
||
url = "https://my.meteoblue.com/packages/basic-day"
|
||
params = {
|
||
"apikey": self.meteoblue_key,
|
||
"lat": lat,
|
||
"lon": lon,
|
||
"format": "json",
|
||
"as_daylight": "true",
|
||
}
|
||
|
||
response = self.session.get(url, params=params, timeout=self.timeout)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
|
||
day_data = data.get("data_day", {})
|
||
max_temps = day_data.get("temperature_max", [])
|
||
|
||
if not max_temps:
|
||
logger.warning(
|
||
f"Meteoblue API 返回数据中找不到最高温 (坐标: {lat},{lon})"
|
||
)
|
||
return None
|
||
|
||
# 2. 转换单位
|
||
def c_to_f(c):
|
||
return round((c * 9 / 5) + 32, 1)
|
||
|
||
result = {
|
||
"source": "meteoblue",
|
||
"today_high": None,
|
||
"daily_highs": [],
|
||
"unit": "fahrenheit" if use_fahrenheit else "celsius",
|
||
"url": f"https://www.meteoblue.com/en/weather/week/{lat}N{lon}E", # 仅供参考
|
||
}
|
||
|
||
# 提取今日最高
|
||
mb_today_c = max_temps[0]
|
||
result["today_high"] = c_to_f(mb_today_c) if use_fahrenheit else mb_today_c
|
||
|
||
# 提取接下来几天的最高温
|
||
if use_fahrenheit:
|
||
result["daily_highs"] = [c_to_f(t) for t in max_temps]
|
||
else:
|
||
result["daily_highs"] = max_temps
|
||
|
||
logger.info(
|
||
f"✅ Meteoblue API 获取成功 ({lat},{lon}): 今天 {result['today_high']}{result['unit']}"
|
||
)
|
||
return result
|
||
except Exception as e:
|
||
logger.error(f"Meteoblue API fetch 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)
|
||
"""
|
||
# 坐标使用 METAR 机场位置（Polymarket 以机场数据结算）
|
||
static_coords = {
|
||
"london": {"lat": 51.5053, "lon": 0.0553}, # EGLC London City
|
||
"paris": {"lat": 49.0097, "lon": 2.5478}, # LFPG Charles de Gaulle
|
||
"new york": {"lat": 40.7750, "lon": -73.8750}, # KLGA LaGuardia
|
||
"new york's central park": {"lat": 40.7812, "lon": -73.9665},
|
||
"nyc": {"lat": 40.7750, "lon": -73.8750}, # KLGA LaGuardia
|
||
"seattle": {"lat": 47.4499, "lon": -122.3118}, # KSEA Sea-Tac
|
||
"chicago": {"lat": 41.9769, "lon": -87.9081}, # KORD O'Hare
|
||
"dallas": {"lat": 32.8459, "lon": -96.8509}, # KDAL Love Field
|
||
"miami": {"lat": 25.7933, "lon": -80.2906}, # KMIA International
|
||
"atlanta": {"lat": 33.6367, "lon": -84.4281}, # KATL Hartsfield-Jackson
|
||
"seoul": {"lat": 37.4691, "lon": 126.4510}, # RKSI Incheon
|
||
"toronto": {"lat": 43.6759, "lon": -79.6294}, # CYYZ Pearson
|
||
"ankara": {"lat": 40.1281, "lon": 32.9950}, # LTAC Esenboğa
|
||
"wellington": {"lat": -41.3272, "lon": 174.8053}, # NZWN Wellington
|
||
"buenos aires": {"lat": -34.8222, "lon": -58.5358}, # SAEZ Ezeiza
|
||
}
|
||
|
||
normalized_city = city.lower().strip()
|
||
if normalized_city in static_coords:
|
||
return static_coords[normalized_city]
|
||
|
||
# 模糊匹配映射 (针对包含城市名的情况)
|
||
for key in static_coords:
|
||
if key in normalized_city:
|
||
logger.debug(f"地理编码命中模糊映射: {city} -> {key}")
|
||
return static_coords[key]
|
||
|
||
try:
|
||
url = "https://geocoding-api.open-meteo.com/v1/search"
|
||
response = self.session.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",
|
||
"seoul": "Seoul",
|
||
"首尔": "Seoul",
|
||
"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",
|
||
}
|
||
|
||
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 fetch_all_sources(
|
||
self, city: str, lat: float = None, lon: float = None, country: str = None
|
||
) -> Dict:
|
||
"""
|
||
Fetch weather data from all available sources
|
||
"""
|
||
results = {}
|
||
|
||
# 判断是否为美国市场（使用华氏度）
|
||
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",
|
||
"austin",
|
||
"san diego",
|
||
"detroit",
|
||
"cleveland",
|
||
"minneapolis",
|
||
"st. louis",
|
||
}
|
||
city_lower = city.lower().strip()
|
||
# 严格判断是否为美国市场（必须完全匹配列表或缩写）
|
||
use_fahrenheit = city_lower in us_cities
|
||
|
||
if use_fahrenheit:
|
||
logger.info(f"🌡️ {city} 使用华氏度 (°F)")
|
||
else:
|
||
logger.info(f"🌡️ {city} 使用摄氏度 (°C)")
|
||
|
||
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)
|
||
metar_data = self.fetch_metar(
|
||
city, use_fahrenheit=use_fahrenheit, utc_offset=utc_offset
|
||
)
|
||
if metar_data:
|
||
results["metar"] = metar_data
|
||
|
||
# 对安卡拉，额外获取 MGM 官方数据 (17130 为 Ankara Bölge 市区测站)
|
||
if city_lower == "ankara":
|
||
mgm_data = self.fetch_from_mgm("17130")
|
||
if mgm_data:
|
||
results["mgm"] = mgm_data
|
||
|
||
# 对伦敦，获取 Meteoblue 预测 (公认最准)
|
||
if city_lower == "london":
|
||
mb_data = self.fetch_from_meteoblue(
|
||
lat,
|
||
lon,
|
||
timezone_name=open_meteo.get("timezone", "UTC"),
|
||
use_fahrenheit=use_fahrenheit,
|
||
)
|
||
if mb_data:
|
||
results["meteoblue"] = mb_data
|
||
|
||
# 对美国城市，额外获取 NWS 高精预报
|
||
if use_fahrenheit:
|
||
nws_data = self.fetch_nws(lat, lon)
|
||
if nws_data:
|
||
results["nws"] = nws_data
|
||
|
||
# 集合预报 (所有城市通用，用于不确定性分析)
|
||
ens_data = self.fetch_ensemble(lat, lon, use_fahrenheit=use_fahrenheit)
|
||
if ens_data:
|
||
results["ensemble"] = ens_data
|
||
|
||
# 多模型预报 (所有城市通用，用于共识评分)
|
||
mm_data = self.fetch_multi_model(
|
||
lat, lon, use_fahrenheit=use_fahrenheit
|
||
)
|
||
if mm_data:
|
||
results["multi_model"] = mm_data
|
||
else:
|
||
# Open-Meteo 失败时，仍然尝试获取 METAR 和 NWS
|
||
metar_data = self.fetch_metar(city, use_fahrenheit=use_fahrenheit)
|
||
if metar_data:
|
||
results["metar"] = metar_data
|
||
if use_fahrenheit:
|
||
nws_data = self.fetch_nws(lat, lon)
|
||
if nws_data:
|
||
results["nws"] = nws_data
|
||
else:
|
||
# 降级方案（无经纬度）
|
||
metar_data = self.fetch_metar(city, use_fahrenheit=use_fahrenheit)
|
||
if metar_data:
|
||
results["metar"] = metar_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,
|
||
}
|