🌡️ PolyWeather: Real-time Weather Query & Analysis Bot

An intelligent weather information bot designed to provide ultra-fast, live meteorological data, high-fidelity forecasts, and smart trend analysis. Built for speed and accuracy, it bypasses network caching to deliver the most up-to-date reports from global weather stations.

🚀 Quick Start

Requirements

• Python 3.11+
• Dependencies: pip install -r requirements.txt

Running Locally (Windows/Linux)

# Windows
py -3.11 run.py

# Linux/VPS
python3 run.py

Note: The system is currently in Weather Query Mode. Active market monitoring and automated trading modules are suspended.

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🤖 Telegram Bot Commands

Command	Description	Usage
/city [name]	Query City Weather	Get detailed forecasts, METAR & trend analysis
/id	Get Chat ID	Retrieve your current Telegram Chat ID
/help	Help	Display all available commands

/city Command Example

/city Chicago

Real-time Output:

📍 Chicago 天气详情
⏱️ 生成时间: 12:45:30
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🕐 当地时间: 12:45

📊 Open-Meteo 7天预测
👉 今天: 最高 22.4°F (NWS: 23°F)
02-08: 最高 26.2°F
02-09: 最高 37.2°F

✈️ 机场实测 (KORD)
🌡️ 21.0°F (今日最高: 23.0°F)
💨 风速: 4kt
🕐 观测: 12:00 (当地)

💡 态势分析
⏱️ 预计峰值时刻：今天 14:00 - 16:00 之间。
🎯 博弈建议：关注该时段实测能否站稳 22.4°F。
📈 升温进程中：距离峰值还有约 1.4° 空间，正向高点冲击。

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✨ Key Features

1. 🏛️ Multi-Source Data Fusion

The bot aggregates data from multiple authoritative sources:

Source	Data Type	Coverage
Open-Meteo	7-day forecast	Global
NWS	Official US forecast	US cities only ⚠️
METAR	Real-time airport observations	Global airports

• ⚠️ Divergence Alerts: When Open-Meteo and NWS disagree by >1°F, the bot flags it for your attention.

2. ⏱️ Peak Timing Prediction

For each city, the bot analyzes the hourly forecast curve to identify:

• Exact peak window: e.g., "14:00 - 16:00"
• Betting recommendation: Monitor real-time data during this window

3. 📊 Today's High Tracking

METAR data is filtered by local calendar day using UTC offset:

• Only observations from local midnight onwards are counted
• Ensures "Today's High" is accurate, not polluted by yesterday's warm afternoon

4. ✈️ High-Fidelity Airport Data (METAR)

Directly connected to NOAA Aviation Weather, the bot fetches raw METAR data from major international airports.

• Automatic conversion from UTC to City Local Time.
• Real-time station observations (Temperature, Wind, Dew Point).

5. ⚡ Ultra-Fresh Data (Cache Busting)

Engineered to bypass ISP and proxy caches:

• Every request includes a micro-timestamp token.
• Forces weather servers (Open-Meteo/NOAA/NWS) to deliver fresh results instead of stale cached snapshots.

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🎯 Betting Strategy Tips

1. Check model consensus: If Open-Meteo and NWS agree, confidence is high.
2. Watch the peak window: Monitor METAR during predicted peak hours.
3. Use "Today's High": Track the actual recorded maximum vs forecast.
4. Interpret ⚠️ warnings: Divergence means uncertainty—proceed with caution.

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🏗️ Architecture Note

The project contains a legacy Monitoring Engine and Paper Trading System (located in main.py). These features are currently deactivated to prioritize high-speed on-demand weather reporting.

• To re-enable monitoring: Uncomment monitor_thread.start() in run.py.
• Documentation for inactive features: See MARKET_DISCOVERY.md and PAPER_TRADING_GUIDE.md.