2569718930@qq.com🌡️ 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.
🤖 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 London
Real-time Output:
📍 London 天气详情
⏱️ 生成时间: 00:41:17
═══ ═══ ═══ ═══ ═══ ═══
🕐 当地时间: 16:41📊 Open-Meteo 7天预测
👉 今天: 最高 12°C
02-09: 最高 11°C✈️ 机场实测 (EGLC)
🌡️ 10.0°C
💨 风速: 12kt
🕐 观测: 16:20 (当地)💡 态势分析
📉 处于降温期：气温已开始从峰值下滑，今日大概率不会再反弹。
🍃 清劲风：空气流动快，虽然有助于散热，但可能伴随阵风引起微小波动。
✨ Key Features
1. 💡 Intelligent Trend Analysis
The bot doesn't just show numbers; it performs a Live vs. Forecast analysis:
- Peak Detection: Determines if the daily high has likely already passed.
- Atmospheric Physics: Uses humidity and dew point to predict if the temperature will "stall" at night.
- Volatility Alerts: Flags high wind speeds that might cause rapid temperature swings.
2. ✈️ 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).
3. ⚡ 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) to deliver fresh results instead of stale cached snapshots.
🏗️ 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()inrun.py. - Documentation for inactive features: See MARKET_DISCOVERY.md and PAPER_TRADING_GUIDE.md.