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feat(qmt): 优化定时重连机制避免与健康检查冲突

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- 添加 is_scheduled_reconnecting 标志位协调重连逻辑
- 增强定时重连任务的日志前缀便于追踪
- 改进异常处理和资源清理日志
- 优化代码格式和注释
This commit is contained in:
liaozhaorun
2026-02-09 22:12:14 +08:00
parent 7ae3d16a5e
commit e407225d29
11 changed files with 746 additions and 677 deletions
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34
main/train/Classify2_load_model.ipynb
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@@ -78,7 +78,7 @@
"cyq perf\n",
"left merge on ['ts_code', 'trade_date']\n",
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 9359748 entries, 0 to 9359747\n",
"RangeIndex: 9410807 entries, 0 to 9410806\n",
"Data columns (total 33 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
@@ -116,7 +116,7 @@
" 31 weight_avg float64 \n",
" 32 winner_rate float64 \n",
"dtypes: bool(1), datetime64[ns](1), float64(30), object(1)\n",
"memory usage: 2.2+ GB\n",
"memory usage: 2.3+ GB\n",
"None\n"
]
}
@@ -600,7 +600,7 @@
"Calculating cs_rank_size...\n",
"Finished cs_rank_size.\n",
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 5042085 entries, 0 to 5042084\n",
"RangeIndex: 5072276 entries, 0 to 5072275\n",
"Columns: 181 entries, ts_code to cs_rank_size\n",
"dtypes: bool(10), datetime64[ns](1), float64(165), int64(3), object(2)\n",
"memory usage: 6.5+ GB\n",
@@ -1409,7 +1409,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"MAD Filtering: 100%|██████████| 131/131 [00:13<00:00, 9.39it/s]\n"
"MAD Filtering: 100%|██████████| 131/131 [00:13<00:00, 10.05it/s]\n"
]
},
{
@@ -1424,7 +1424,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"MAD Filtering: 100%|██████████| 131/131 [00:15<00:00, 8.45it/s]\n"
"MAD Filtering: 100%|██████████| 131/131 [00:16<00:00, 8.05it/s]\n"
]
},
{
@@ -1464,13 +1464,13 @@
"截面 MAD 去极值处理完成。\n",
"feature_columns: ['vol', 'pct_chg', 'turnover_rate', 'volume_ratio', 'winner_rate', 'undist_profit_ps', 'ocfps', 'AR', 'BR', 'AR_BR', 'cashflow_to_ev_factor', 'book_to_price_ratio', 'turnover_rate_mean_5', 'variance_20', 'bbi_ratio_factor', 'daily_deviation', 'lg_elg_net_buy_vol', 'flow_lg_elg_intensity', 'sm_net_buy_vol', 'total_buy_vol', 'lg_elg_buy_prop', 'flow_struct_buy_change', 'lg_elg_net_buy_vol_change', 'flow_lg_elg_accel', 'chip_concentration_range', 'chip_skewness', 'floating_chip_proxy', 'cost_support_15pct_change', 'cat_winner_price_zone', 'flow_chip_consistency', 'profit_taking_vs_absorb', 'cat_is_positive', 'upside_vol', 'downside_vol', 'vol_ratio', 'return_skew', 'return_kurtosis', 'volume_change_rate', 'cat_volume_breakout', 'turnover_deviation', 'cat_turnover_spike', 'avg_volume_ratio', 'cat_volume_ratio_breakout', 'vol_spike', 'vol_std_5', 'atr_14', 'atr_6', 'obv', 'maobv_6', 'rsi_3', 'return_5', 'return_20', 'std_return_5', 'std_return_90', 'std_return_90_2', 'act_factor1', 'act_factor2', 'act_factor3', 'act_factor4', 'rank_act_factor1', 'rank_act_factor2', 'rank_act_factor3', 'cov', 'delta_cov', 'alpha_22_improved', 'alpha_003', 'alpha_007', 'alpha_013', 'vol_break', 'weight_roc5', 'smallcap_concentration', 'cost_stability', 'high_cost_break_days', 'liquidity_risk', 'turnover_std', 'mv_volatility', 'volume_growth', 'mv_growth', 'momentum_factor', 'resonance_factor', 'log_close', 'cat_vol_spike', 'up', 'down', 'obv_maobv_6', 'std_return_5_over_std_return_90', 'std_return_90_minus_std_return_90_2', 'cat_af2', 'cat_af3', 'cat_af4', 'act_factor5', 'act_factor6', 'active_buy_volume_large', 'active_buy_volume_big', 'active_buy_volume_small', 'buy_lg_vol_minus_sell_lg_vol', 'buy_elg_vol_minus_sell_elg_vol', 'ctrl_strength', 'low_cost_dev', 'asymmetry', 'lock_factor', 'cat_vol_break', 'cost_atr_adj', 'cat_golden_resonance', 'mv_turnover_ratio', 'mv_adjusted_volume', 'mv_weighted_turnover', 'nonlinear_mv_volume', 'mv_volume_ratio', 'mv_momentum', 'lg_flow_mom_corr_20_60', 'lg_flow_accel', 'profit_pressure', 'underwater_resistance', 'cost_conc_std_20', 'profit_decay_20', 'vol_amp_loss_20', 'vol_drop_profit_cnt_5', 'lg_flow_vol_interact_20', 'cost_break_confirm_cnt_5', 'atr_norm_channel_pos_14', 'turnover_diff_skew_20', 'lg_sm_flow_diverge_20', 'pullback_strong_20_20', 'vol_wgt_hist_pos_20', 'vol_adj_roc_20', 'cs_rank_net_lg_flow_val', 'cs_rank_elg_buy_ratio', 'cs_rank_rel_profit_margin', 'cs_rank_cost_breadth', 'cs_rank_dist_to_upper_cost', 'cs_rank_winner_rate', 'cs_rank_intraday_range', 'cs_rank_close_pos_in_range', 'cs_rank_pos_in_hist_range', 'cs_rank_vol_x_profit_margin', 'cs_rank_lg_flow_price_concordance', 'cs_rank_turnover_per_winner', 'cs_rank_volume_ratio', 'cs_rank_elg_buy_sell_sm_ratio', 'cs_rank_cost_dist_vol_ratio', 'cs_rank_size', 'cat_up_limit', 'industry_obv', 'industry_return_5', 'industry_return_20', 'industry__ema_5', 'industry__ema_13', 'industry__ema_20', 'industry__ema_60', 'industry_act_factor1', 'industry_act_factor2', 'industry_act_factor3', 'industry_act_factor4', 'industry_act_factor5', 'industry_act_factor6', 'industry_rank_act_factor1', 'industry_rank_act_factor2', 'industry_rank_act_factor3', 'industry_return_5_percentile', 'industry_return_20_percentile', '000852.SH_MACD', '000905.SH_MACD', '399006.SZ_MACD', '000852.SH_MACD_hist', '000905.SH_MACD_hist', '399006.SZ_MACD_hist', '000852.SH_RSI', '000905.SH_RSI', '399006.SZ_RSI', '000852.SH_Signal_line', '000905.SH_Signal_line', '399006.SZ_Signal_line', '000852.SH_amount_change_rate', '000905.SH_amount_change_rate', '399006.SZ_amount_change_rate', '000852.SH_amount_mean', '000905.SH_amount_mean', '399006.SZ_amount_mean', '000852.SH_daily_return', '000905.SH_daily_return', '399006.SZ_daily_return', '000852.SH_up_ratio_20d', '000905.SH_up_ratio_20d', '399006.SZ_up_ratio_20d', '000852.SH_volatility', '000905.SH_volatility', '399006.SZ_volatility', '000852.SH_volume_change_rate', '000905.SH_volume_change_rate', '399006.SZ_volume_change_rate']\n",
"df最小日期: 2019-01-02\n",
"df最大日期: 2026-01-23\n",
"2055951\n",
"df最大日期: 2026-02-06\n",
"2055944\n",
"train_data最小日期: 2020-01-02\n",
"train_data最大日期: 2022-12-30\n",
"2267560\n",
"2297633\n",
"test_data最小日期: 2023-01-03\n",
"test_data最大日期: 2026-01-23\n",
"test_data最大日期: 2026-02-06\n",
" ts_code trade_date log_circ_mv\n",
"0 000001.SZ 2019-01-02 16.574219\n",
"1 000001.SZ 2019-01-03 16.583965\n",
@@ -1754,7 +1754,7 @@
{
"data": {
"text/plain": [
"<catboost.core.CatBoostClassifier at 0x7cca5687f800>"
"<catboost.core.CatBoostClassifier at 0x7b3eec333d70>"
]
},
"execution_count": 19,
@@ -1841,7 +1841,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"5584 2055951\n",
"5584 2055944\n",
" ts_code trade_date turnover_rate\n",
"0 000001.SZ 2023-01-03 1.1307\n",
"1 000001.SZ 2023-01-04 1.1284\n",
@@ -1849,13 +1849,13 @@
"3 000001.SZ 2023-01-06 0.6162\n",
"4 000001.SZ 2023-01-09 0.5450\n",
"... ... ... ...\n",
"2267555 605599.SH 2026-01-19 0.6158\n",
"2267556 605599.SH 2026-01-20 0.9493\n",
"2267557 605599.SH 2026-01-21 1.1732\n",
"2267558 605599.SH 2026-01-22 0.8848\n",
"2267559 605599.SH 2026-01-23 0.9550\n",
"2297628 605599.SH 2026-02-02 2.6968\n",
"2297629 605599.SH 2026-02-03 1.6084\n",
"2297630 605599.SH 2026-02-04 3.9328\n",
"2297631 605599.SH 2026-02-05 3.0072\n",
"2297632 605599.SH 2026-02-06 3.1129\n",
"\n",
"[2267560 rows x 3 columns]\n"
"[2297633 rows x 3 columns]\n"
]
}
],