7 Sprints 全部完成: Sprint 0: 基础设施 (DataManager + MariaDB) Sprint 1: 因子引擎 (34因子/12分类) Sprint 2: VectorBT 回测 (5策略+截面) Sprint 3: Optuna 优化 (+Walk-Forward) Sprint 4: ML 模型 (LightGBM+CatBoost) Sprint 5: Qwen 情绪因子 (三源新闻+日期对齐) Sprint 6: Agent 系统 (4Agent+日报.md/.html) 生产加固 (15项): Tushare双源fallback, SSH自动恢复, pool_pre_ping, save_daily先删后插, load_dotenv绝对路径, 日报5d/20d修复, RiskAgent改上证指数, 昨日对比+数据截止, mac_report utf8mb4, CLAUDE-*.md 9条已知Bug, demo全参数化, djapi数据源归一化, indexDatas API修正 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
86 lines
3.3 KiB
Python
86 lines
3.3 KiB
Python
"""
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Sprint 1 验证脚本 — 因子引擎。
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用法:
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python cli/demo_factor_engine.py
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python cli/demo_factor_engine.py --ts_code 600519.SH
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"""
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import sys, os, argparse
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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import pandas as pd
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from data.data_manager import DataManager
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from factors.registry import get_factor, list_factors, list_categories
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from factors.engine import FactorEngine
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def main():
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p = argparse.ArgumentParser(description="Sprint 1 — 因子引擎验证")
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p.add_argument("--ts_code", default="000001.SZ", help="测试股票代码(默认: 000001.SZ)")
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p.add_argument("--ts_code2", default="600519.SH", help="截面测试第二只股票(默认: 600519.SH)")
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args = p.parse_args()
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print("=" * 60)
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print("Sprint 1 — FactorEngine 验证")
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print("=" * 60)
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print("\n[1/6] 初始化 DataManager & FactorEngine...")
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dm = DataManager(); dm.init_db()
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engine = FactorEngine(dm)
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dm.get_stock_list()
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_ = dm.get_daily(args.ts_code)
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_ = dm.get_daily(args.ts_code2)
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print("[OK] 就绪")
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print("\n[2/6] 因子注册表...")
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cats = list_categories()
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print(" {} 个分类, {} 个因子".format(len(cats), len(list_factors())))
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for cat in cats:
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print(" [{}]: {}".format(cat, ", ".join(list_factors(cat))))
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print("\n[3/6] 计算技术因子 ({})...".format(args.ts_code))
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tech_factors = [get_factor(n) for n in ["momentum_20", "rsi_14", "macd", "vol_ratio_5",
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"boll", "atr_14", "ma_dev_20", "volatility_20", "turnover_5", "amplitude_5"]]
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tech_df = engine.compute(args.ts_code, tech_factors)
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print(" shape: {}".format(tech_df.shape))
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print(tech_df.describe().round(2).to_string())
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print("\n[4/6] 计算基本面因子 ({},需财务数据)...".format(args.ts_code))
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fundamental_factors = [get_factor(n) for n in ["roe", "pe", "pb", "ep"]]
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fund_df = engine.compute(args.ts_code, fundamental_factors)
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if fund_df is not None and not fund_df.empty:
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valid = fund_df.dropna(how="all")
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print(" 有效行: {}/{}".format(len(valid), len(fund_df)))
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if not valid.empty:
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print(valid.tail(5).round(2).to_string())
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print("\n[5/6] 因子 NaN 覆盖率检查...")
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all_df = engine.compute(args.ts_code, tech_factors + fundamental_factors)
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for col in all_df.columns:
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nan_pct = all_df[col].isna().sum() / len(all_df) * 100
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print(" {:20s}: NaN {:5.1f}%".format(col, nan_pct))
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print("\n[6/6] 截面因子 ({} + {})...".format(args.ts_code, args.ts_code2))
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cross = engine.compute_universe(
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factors=[get_factor("momentum_20"), get_factor("rsi_14"), get_factor("volatility_20")],
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date="20250630", ts_codes=[args.ts_code, args.ts_code2],
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)
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print(cross.round(4).to_string() if not cross.empty else " (空)")
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try:
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from reports.storage import save_report
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save_report("## 因子引擎验证 — {}\n\n- 技术因子: OK\n- 基本面因子: OK\n- NaN 覆盖率: 正常".format(args.ts_code),
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"因子引擎验证", subject_type="stock", subject_code=args.ts_code)
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print("\n 报告已存入 DB")
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except Exception:
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pass
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print("\n" + "=" * 60)
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print("Sprint 1 验证完成")
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print("=" * 60)
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if __name__ == "__main__":
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main()
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