feat: Initialize PolyWeather project structure including modules for data collection, analysis, strategy, trading, utilities, configuration, and a Streamlit dashboard.
This commit is contained in:
2569718930@qq.com
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import requests
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import re
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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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"""
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def __init__(self, config: dict):
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self.config = config
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self.openweather_key = config.get("openweather_api_key")
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self.wunderground_key = config.get("wunderground_api_key")
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self.visualcrossing_key = config.get("visualcrossing_api_key")
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self.timeout = 10
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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 self.openweather_key:
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logger.warning("OpenWeatherMap API key not configured")
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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 self.visualcrossing_key:
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logger.warning("Visual Crossing API key not configured")
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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 fetch_from_open_meteo(
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self,
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lat: float,
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lon: float,
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forecast_days: int = 14,
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use_fahrenheit: bool = False,
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) -> Optional[Dict]:
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"""
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Fetch weather from Open-Meteo with forecast data
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Args:
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lat: Latitude
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lon: Longitude
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forecast_days: Number of forecast days to fetch (default 14 to cover all market dates)
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use_fahrenheit: Whether to return temperatures in Fahrenheit (for US markets)
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"""
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try:
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url = "https://api.open-meteo.com/v1/forecast"
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params = {
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"latitude": lat,
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"longitude": lon,
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"current_weather": "true",
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"daily": "temperature_2m_max,apparent_temperature_max",
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"timezone": "auto",
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"forecast_days": forecast_days,
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}
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# 对于美国市场，使用华氏度
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if use_fahrenheit:
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params["temperature_unit"] = "fahrenheit"
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response = self.session.get(
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url,
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params=params,
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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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current = data.get("current_weather", {})
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return {
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"source": "open-meteo",
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"timestamp": datetime.utcnow().isoformat(),
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"current": {
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"temp": current.get("temperature"),
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"local_time": current.get("time", "").replace("T", " "),
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},
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"daily": data.get("daily", {}),
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"unit": "fahrenheit" if use_fahrenheit else "celsius",
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}
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except Exception as e:
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logger.error(f"Open-Meteo forecast failed: {e}")
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return None
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def extract_date_from_title(self, title: str) -> Optional[str]:
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"""
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从标题中提取日期并标准化为 YYYY-MM-DD
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例如: "Highest temperature in Seattle on February 6?" -> "2026-02-06"
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"""
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months = {
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"January": "01",
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"February": "02",
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"March": "03",
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"April": "04",
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"May": "05",
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"June": "06",
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"July": "07",
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"August": "08",
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"September": "09",
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"October": "10",
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"November": "11",
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"December": "12",
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}
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for month_name, month_val in months.items():
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if month_name in title:
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match = re.search(f"{month_name}\\s+(\\d+)", title)
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if match:
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day = int(match.group(1))
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year = datetime.now().year
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# 简单处理跨年逻辑：如果提取到的月份小于当前月份太多，可能是指明年
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# 但对于天气预报通常只看近期几天
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return f"{year}-{month_val}-{day:02d}"
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return None
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def get_coordinates(self, city: str) -> Optional[Dict[str, float]]:
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"""
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使用 Open-Meteo Geocoding API 获取城市坐标 (免费, 无需 Key)
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"""
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# 预设常用城市坐标，避免网络波动导致启动失败
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static_coords = {
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"london": {"lat": 51.5074, "lon": -0.1278},
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"new york": {"lat": 40.7128, "lon": -74.0060},
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"nyc": {"lat": 40.7128, "lon": -74.0060},
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"seattle": {"lat": 47.6062, "lon": -122.3321},
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"chicago": {"lat": 41.8781, "lon": -87.6298},
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"dallas": {"lat": 32.7767, "lon": -96.7970},
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"miami": {"lat": 25.7617, "lon": -80.1918},
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"atlanta": {"lat": 33.7490, "lon": -84.3880},
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"seoul": {"lat": 37.5665, "lon": 126.9780},
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"toronto": {"lat": 43.6532, "lon": -79.3832},
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"ankara": {"lat": 39.9334, "lon": 32.8597},
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"wellington": {"lat": -41.2865, "lon": 174.7762},
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"buenos aires": {"lat": -34.6037, "lon": -58.3816},
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}
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normalized_city = city.lower().strip()
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if normalized_city in static_coords:
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return static_coords[normalized_city]
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try:
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url = "https://geocoding-api.open-meteo.com/v1/search"
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response = self.session.get(
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url,
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params={"name": city, "count": 1, "language": "en", "format": "json"},
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timeout=15, # 增加超时时间到 15s
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)
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response.raise_for_status()
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results = response.json().get("results", [])
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if results:
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res = results[0]
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return {
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"lat": res.get("latitude"),
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"lon": res.get("longitude"),
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"name": res.get("name"),
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"country": res.get("country"),
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}
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except Exception as e:
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logger.error(f"地理编码失败 ({city}): {e}")
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return None
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def extract_city_from_question(self, question: str) -> Optional[str]:
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"""
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从 Polymarket 问题描述中提取城市名称
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支持多种描述方式:
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- "Highest temperature in Ankara on February 5?"
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- "Will the temperature in London be..."
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- "Temp in New York..."
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"""
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q = question.lower()
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# 移除常见的干扰词
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for noise in ["highest ", "the ", "will ", "lowest "]:
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if q.startswith(noise):
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q = q[len(noise) :]
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# 处理 "temperature in [City]" | "temp in [City]"
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triggers = ["temperature in ", "temp in ", "weather in "]
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for trigger in triggers:
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if trigger in q:
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part = q.split(trigger)[1]
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# 截断日期和其他后缀
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# 按照 "on", "at", "above", "below", "?", " ", "be", "is" 分割
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delimiters = [
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" on ",
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" at ",
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" above ",
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" below ",
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" be ",
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" is ",
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" will ",
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" has ",
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" reached ",
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"?",
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" (",
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", ",
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]
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city = part
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for d in delimiters:
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if d in city:
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city = city.split(d)[0]
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return city.strip().title()
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return None
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def fetch_all_sources(
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self, city: str, lat: float = None, lon: float = None, country: str = None
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) -> Dict:
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"""
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Fetch weather data from all available sources
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"""
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results = {}
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# 判断是否为美国市场（使用华氏度）
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us_cities = [
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"dallas",
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"nyc",
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"new york",
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"seattle",
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"miami",
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"atlanta",
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"chicago",
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"los angeles",
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"san francisco",
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"washington",
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"boston",
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"houston",
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"phoenix",
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"philadelphia",
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]
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use_fahrenheit = city.lower() in us_cities
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# Open-Meteo (Primary Free Source - No Key)
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if lat and lon:
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open_meteo = self.fetch_from_open_meteo(
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lat, lon, use_fahrenheit=use_fahrenheit
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)
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if open_meteo:
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results["open-meteo"] = open_meteo
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# OpenWeatherMap (Requires Key)
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openweather = self.fetch_from_openweather(city, country)
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if openweather:
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results["openweathermap"] = openweather
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# Visual Crossing (Requires Key)
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visualcrossing = self.fetch_from_visualcrossing(city)
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if visualcrossing:
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results["visualcrossing"] = visualcrossing
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return results
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def check_consensus(self, forecasts: Dict) -> Dict:
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"""
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Check consensus across multiple weather sources
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Args:
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forecasts: Dict of forecasts from different sources
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Returns:
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dict: Consensus analysis
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"""
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predictions = []
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for source, data in forecasts.items():
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if data and "current" in data:
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predictions.append({"source": source, "temp": data["current"]["temp"]})
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if len(predictions) == 0:
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return {"consensus": False, "reason": "No weather data available"}
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temps = [p["temp"] for p in predictions]
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avg_temp = sum(temps) / len(temps)
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# If only one source, consensus is implicitly true
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if len(predictions) == 1:
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return {
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"consensus": True,
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"average_temp": avg_temp,
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"max_difference": 0.0,
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"predictions": predictions,
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"note": "Single source only",
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}
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max_diff = max(abs(t - avg_temp) for t in temps)
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# Consensus if all predictions within 2.5°C
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is_consensus = max_diff <= 2.5
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return {
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"consensus": is_consensus,
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"average_temp": avg_temp,
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"max_difference": max_diff,
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"predictions": predictions,
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}
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