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# 🌡️ PolyWeather: Real-time Weather Query & Analysis Bot
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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.
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## 🚀 Quick Start
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### Requirements
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- **Python 3.11+**
- Dependencies: `pip install -r requirements.txt`
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### Running Locally (Windows/Linux)
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```bash
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# Windows
py -3.11 run.py
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# Linux/VPS
python3 run.py
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```
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_Note: The system is currently in **Weather Query Mode**. Active market monitoring and automated trading modules are suspended._
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---
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## 🤖 Telegram Bot Commands
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| 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 |
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### /city Command Example
```
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/city Chicago
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```
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**Real-time Output:**
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> 📍 **Chicago 天气详情**
> ⏱️ 生成时间: 12:45:30
> ════════════════════
> 🕐 当地时间: 12:45
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>
> 📊 **Open-Meteo 7天预测**
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> 👉 今天: 最高 22.4°F (NWS: 23°F)
> 02-08: 最高 26.2°F
> 02-09: 最高 37.2°F
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>
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> ✈️ **机场实测 (KORD)**
> 🌡️ 21.0°F (今日最高: 23.0°F)
> 💨 风速: 4kt
> 🕐 观测: 12:00 (当地)
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>
> 💡 **态势分析**
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> ⏱️ **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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---
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## ✨ Key Features
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### 1. 🏛️ Multi-Source Data Fusion
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The bot aggregates data from multiple authoritative sources:
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| Source | Data Type | Coverage |
| -------------- | ------------------------------ | ----------------- |
| **Open-Meteo** | 7-day forecast | Global |
| **NWS** | Official US forecast | US cities only ⚠️ |
| **METAR** | Real-time airport observations | Global airports |
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- **⚠️ 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)
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Directly connected to **NOAA Aviation Weather** , the bot fetches raw METAR data from major international airports.
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- Automatic conversion from UTC to **City Local Time** .
- Real-time station observations (Temperature, Wind, Dew Point).
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### 5. ⚡ Ultra-Fresh Data (Cache Busting)
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Engineered to bypass ISP and proxy caches:
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- Every request includes a **micro-timestamp token** .
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- Forces weather servers (Open-Meteo/NOAA/NWS) to deliver fresh results instead of stale cached snapshots.
---
## 🎯 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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---
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## 🏗️ Architecture Note
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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.
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- To re-enable monitoring: Uncomment `monitor_thread.start()` in `run.py` .
- Documentation for inactive features: See [MARKET_DISCOVERY.md ](./MARKET_DISCOVERY.md ) and [PAPER_TRADING_GUIDE.md ](./PAPER_TRADING_GUIDE.md ).