fix: timezone handling and prediction logic
- api/models.py: Fix timezone conversion in stats queries by calculating UTC ranges in Python instead of using SQL CONVERT_TZ. Ensure JSON serializable types.
- api/prediction_service.py:
- Update ensure_predictions_for_month to check previous day (ET) to cover CST month start.
- Update _generate_prediction_for_hour to skip saving unclosed candles (current hour).
- trader/auto_trade_polymarket.py: Update to use hourly_model_predictions (V2) table for storing live trading predictions.
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@@ -541,41 +541,43 @@ class PolymarketBTCTrader:
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final_probability = all_preds['dlinear']['probability']
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logger.warning("⚠️ 集成预测不可用，降级为 DLinear")
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# 保存所有预测结果到 model_predictions 表
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# 保存所有预测结果到 hourly_model_predictions 表 (V2)
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try:
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et_tz = ZoneInfo('America/New_York')
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current_time_utc = pd.Timestamp(current_time)
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current_time_et = current_time_utc.tz_localize('UTC').tz_convert(et_tz)
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common_data = {
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prediction_data = {
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"timestamp": current_time_utc.isoformat(),
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"timestamp_et": current_time_et.isoformat(),
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"date": current_time_et.strftime('%Y-%m-%d'),
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"hour": current_time_et.hour,
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"actual_result": None,
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"is_correct": None,
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"open_price": float(df['open'].iloc[-1]),
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"close_price": None,
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"actual_result": None,
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# DLinear
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"dlinear_prediction": all_preds.get('dlinear', {}).get('prediction'),
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"dlinear_prob": all_preds.get('dlinear', {}).get('probability'),
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"dlinear_correct": None,
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# N-BEATS
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"nbeats_prediction": all_preds.get('nbeats', {}).get('prediction'),
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"nbeats_prob": all_preds.get('nbeats', {}).get('probability'),
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"nbeats_correct": None,
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# TTM-R2
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"ttm_prediction": all_preds.get('ttm', {}).get('prediction'),
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"ttm_prob": all_preds.get('ttm', {}).get('probability'),
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"ttm_correct": None,
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# Ensemble
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"ensemble_prediction": all_preds.get('ensemble', {}).get('prediction'),
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"ensemble_votes": all_preds.get('ensemble', {}).get('votes'),
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"ensemble_correct": None,
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}
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# 辅助函数
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def save_single_pred(name, pred_res):
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data = common_data.copy()
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data['model_name'] = name
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data['prediction'] = pred_res['prediction']
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data['probability'] = pred_res.get('probability', 0.5)
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PredictionModel.save_prediction(data)
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if 'dlinear' in all_preds:
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save_single_pred("DLinear", all_preds['dlinear'])
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if 'nbeats' in all_preds:
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save_single_pred("N-BEATS", all_preds['nbeats'])
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if 'ttm' in all_preds:
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save_single_pred("TTM-R2", all_preds['ttm'])
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if 'ensemble' in all_preds and all_preds['ensemble']:
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# 集成也保存
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save_single_pred("Ensemble", all_preds['ensemble'])
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PredictionModel.save_hourly_prediction(prediction_data)
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logger.info(f"💾 所有模型预测记录已保存 (ET {current_time_et.strftime('%Y-%m-%d %H:%M')})")
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except Exception as e:
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logger.error(f"保存预测记录失败: {e}")
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@@ -599,22 +601,17 @@ class PolymarketBTCTrader:
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prev_close = float(prev_row['close'])
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actual_result = 1 if prev_close > prev_open else 0
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models_to_update = ["DLinear", "N-BEATS", "TTM-R2", "Ensemble"]
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# 使用 V2 更新方法 (宽表)
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updated = PredictionModel.update_actual_result_v2(
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date=prev_date,
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hour=prev_hour,
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actual_result=actual_result,
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close_price=prev_close
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)
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for model_name in models_to_update:
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updated = PredictionModel.update_actual_result(
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date=prev_date,
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hour=prev_hour,
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model_name=model_name,
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actual_result=actual_result,
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close_price=prev_close
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)
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if updated:
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# 仅打印一条日志代表更新成功，避免刷屏
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pass
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logger.info(f"📝 回填上一小时结果: ET {prev_date} {prev_hour}:00, "
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f"实际{'涨' if actual_result == 1 else '跌'} (O:{prev_open:.0f} C:{prev_close:.0f})")
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if updated:
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logger.info(f"📝 回填上一小时结果: ET {prev_date} {prev_hour}:00, "
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f"实际{'涨' if actual_result == 1 else '跌'} (O:{prev_open:.0f} C:{prev_close:.0f})")
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except Exception as e:
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logger.error(f"回填上一小时结果失败: {e}")
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@@ -801,30 +798,38 @@ class PolymarketBTCTrader:
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current_time_utc = pd.Timestamp(current_time)
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current_time_et = current_time_utc.tz_localize('UTC').tz_convert(et_tz)
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# 1. 保存预测到 model_predictions
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common_data = {
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# 1. 保存预测到 hourly_model_predictions (V2)
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prediction_data = {
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"timestamp": current_time_utc.isoformat(),
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"timestamp_et": current_time_et.isoformat(),
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"date": current_time_et.strftime('%Y-%m-%d'),
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"hour": current_time_et.hour,
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"actual_result": None,
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"is_correct": None,
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"open_price": float(df['open'].iloc[-1]),
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"close_price": None,
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"actual_result": None,
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# DLinear
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"dlinear_prediction": all_preds.get('dlinear', {}).get('prediction'),
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"dlinear_prob": all_preds.get('dlinear', {}).get('probability'),
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"dlinear_correct": None,
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# N-BEATS
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"nbeats_prediction": all_preds.get('nbeats', {}).get('prediction'),
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"nbeats_prob": all_preds.get('nbeats', {}).get('probability'),
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"nbeats_correct": None,
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# TTM-R2
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"ttm_prediction": all_preds.get('ttm', {}).get('prediction'),
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"ttm_prob": all_preds.get('ttm', {}).get('probability'),
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"ttm_correct": None,
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# Ensemble
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"ensemble_prediction": all_preds.get('ensemble', {}).get('prediction'),
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"ensemble_votes": all_preds.get('ensemble', {}).get('votes'),
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"ensemble_correct": None,
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}
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def save_single_pred(name, pred_res):
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data = common_data.copy()
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data['model_name'] = name
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data['prediction'] = pred_res['prediction']
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data['probability'] = pred_res.get('probability', 0.5)
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PredictionModel.save_prediction(data)
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if 'dlinear' in all_preds: save_single_pred("DLinear", all_preds['dlinear'])
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if 'nbeats' in all_preds: save_single_pred("N-BEATS", all_preds['nbeats'])
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if 'ttm' in all_preds: save_single_pred("TTM-R2", all_preds['ttm'])
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if 'ensemble' in all_preds and all_preds['ensemble']: save_single_pred("Ensemble", all_preds['ensemble'])
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PredictionModel.save_hourly_prediction(prediction_data)
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logger.info(f"💾 [Init] 初始预测已保存到数据库")
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# 2. 记录当前监控状态到 trades (作为 'in_progress')
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