HK Weather Prediction Market Pipeline: WeatherNext + HKO + Polymarket

- Open-Meteo WeatherNext API client for HK forecasts
- HKO public data client (current conditions, 9-day forecast, typhoon warnings)
- HK-specific weather extraction and calibration
- Polymarket market scanning, price discovery, and market creation proposals
- Trading strategy engine: edge detection, Kelly criterion sizing, probability calibration
- End-to-end pipeline with dry-run mode and scheduled runner
- Interactive dashboard with live HK weather + forecasts + trading signals

Dependencies: Python 3.10+, openmeteo-requests, pandas
No API keys needed for dry-run mode.
Polymarket trading requires private key in .env.

dashboard.py

@@ -0,0 +1,112 @@
+#!/usr/bin/env python3
+"""Quick test and display of HK weather forecasts with trading signals."""
+
+import sys
+from datetime import datetime, timedelta
+from weather.hk_extractor import HKExtractor
+from weather.hko_client import HKOClient
+from weather.openmeteo_client import OpenMeteoClient
+from strategy.signals import SignalGenerator
+from strategy.calibrator import ProbabilityCalibrator
+from strategy.kelly import KellyCriterion
+
+
+def main():
+    print("╔══════════════════════════════════════════════════════╗")
+    print("║   HK Weather Prediction Market Dashboard            ║")
+    print(f"║   {datetime.now():%Y-%m-%d %H:%M:%S} HKT                          ║")
+    print("╚══════════════════════════════════════════════════════╝")
+    print()
+
+    # Fetch data
+    weather = HKExtractor()
+    hko = HKOClient()
+
+    print("─── Current Conditions ───────────────────────────────")
+    current = hko.get_current_weather()
+    if current:
+        temps = current.get("temperature", [])
+        for t in temps[:3]:
+            print(f"  {t['place']:20s} {t['value']}°C")
+        print(f"  Humidity: {current.get('humidity', [{}])[0].get('value', 'N/A')}%")
+        warning = current.get("warning_message", "")
+        if warning:
+            print(f"  ⚠ {warning}")
+
+    om = OpenMeteoClient()
+    cur = om.get_current_conditions()
+    if cur:
+        print(f"  Feels like: {cur.get('apparent_temp', 'N/A')}°C")
+        print(f"  Wind: {cur.get('wind_speed', 'N/A'):.1f} km/h")
+        print(f"  Pressure: {cur.get('surface_pressure', 'N/A'):.1f} hPa")
+
+    # Typhoon info
+    typhoon = hko.get_typhoon_info()
+    if typhoon:
+        signal = hko.get_current_signal_level()
+        print(f"  Typhoon signal: {'T' + str(signal) if signal else 'None'}")
+
+    print()
+    print("─── HKO 9-Day Forecast ───────────────────────────────")
+    hko_fc = hko.get_forecast()
+    if hko_fc:
+        for day in hko_fc[:5]:
+            print(f"  {day['date']} ({day['week']}): "
+                  f"{day['forecast_temp_min']}-{day['forecast_temp_max']}°C, "
+                  f"Wind: {day.get('forecast_wind', 'N/A')}")
+
+    print()
+    print("─── WeatherNext (Open-Meteo) Forecast ───────────────")
+    fc = weather.get_hk_forecast(lead_days=5)
+    wnext = fc.get("sources", {}).get("weathernext", [])
+    for day in wnext[:5]:
+        print(f"  {day['date']}: "
+              f"↑{day['temp_max_calibrated']:.1f}°C ↓{day['temp_min_calibrated']:.1f}°C, "
+              f"Rain: {day['precipitation_probability_calibrated']:.1f}% ({day['precipitation_sum']:.1f}mm), "
+              f"Wind: {day['wind_speed_max_calibrated']:.1f} km/h")
+
+    print()
+    print("─── Trading Signals ──────────────────────────────────")
+    sig_gen = SignalGenerator()
+    sig_gen.generate_signals()
+    print(sig_gen.get_signal_summary())
+
+    # Also show market creation proposals
+    print()
+    print("─── Proposed Markets (for Polymarket) ────────────────")
+    tomorrow = datetime.now() + timedelta(days=1)
+    if wnext:
+        d1 = wnext[0] if len(wnext) > 0 else {}
+        rain_p = d1.get("precipitation_probability_calibrated", 50)
+        temp_p = d1.get("temp_max_calibrated", 30)
+        wind_p = d1.get("wind_speed_max_calibrated", 15)
+
+        print(f"  1. 'Will it rain in HK on {tomorrow:%Y-%m-%d}?' [YES: ~{rain_p:.0f}%]")
+        print(f"  2. 'Will HK temp exceed 33°C on {tomorrow:%Y-%m-%d}?' [YES: ~{min(95, max(5, 50 + (temp_p - 33) * 20)):.0f}%]")
+        print(f"  3. 'Will HK temp exceed 35°C on {tomorrow:%Y-%m-%d}?' [YES: ~{min(95, max(5, 50 + (temp_p - 35) * 20)):.0f}%]")
+        print(f"  4. 'Will rain exceed 10mm in HK on {tomorrow:%Y-%m-%d}?' [check hourly]")
+        print(f"  5. 'Will a T8 signal be hoisted in HK in the next 7 days?'")
+
+    print()
+    print("─── Kelly Sizing Sim ─────────────────────────────────")
+    kelly = KellyCriterion(bankroll_usdc=1000.0)
+    for name, our_p, mkt_p in [
+        ("Rain tomorrow", rain_p, 45),
+        ("Temp > 35°C", min(95, max(5, 50 + (temp_p - 35) * 20)), 30),
+    ]:
+        r = kelly.size_bet(our_p, mkt_p, "buy_yes")
+        if r.kelly_active:
+            print(f"  {name}: Bet ${r.size_usdc:.2f} YES (edge={r.edge:.3f})")
+        else:
+            r2 = kelly.size_bet(our_p, mkt_p, "buy_no")
+            if r2.kelly_active:
+                print(f"  {name}: Bet ${r2.size_usdc:.2f} NO (edge={r2.edge:.3f})")
+            else:
+                print(f"  {name}: No edge (model={our_p:.0f}% vs market={mkt_p:.0f}%)")
+
+    print()
+    print("═" * 56)
+
+
+if __name__ == "__main__":
+    main()