100 lines
3.5 KiB
Python
100 lines
3.5 KiB
Python
"""S1: 验证 vnpy.alpha 能否处理 A 股数据（Phase 1 真实数据 → AlphaLab → 因子计算）。
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验证链：
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1. AlphaLab init
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2. read_db_daily 读 A 股 bars（Phase 1）
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3. save_bar_data + load_bar_data（存取兼容性）
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4. 构造 panel df（datetime, vt_symbol, OHLCV）
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5. AlphaDataset + add_feature(ma5) + prepare_data（spawn pool 因子计算）
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6. fetch_raw（验证因子列生成）
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A 股特性支撑度（T+1/涨跌停/停牌）在因子层层面：alpha 模块本身不强制这些约束，
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由策略/回测层处理；因子计算只需 OHLCV，A 股数据格式无差异。
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"""
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import sys
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import os
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sys.path.insert(0, "/app/vnpy_v4.4.0")
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sys.path.insert(0, "/app")
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def main():
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from vnpy.alpha.lab import AlphaLab
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from vnpy.alpha.dataset import AlphaDataset, Segment
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from vnpy.trader.constant import Interval
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import polars as pl
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results = {}
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# 1. AlphaLab init
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try:
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lab = AlphaLab("/tmp/alpha_lab_spike")
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results["alphalab_init"] = "OK"
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except Exception as e:
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results["alphalab_init"] = f"FAIL: {e}"
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return _print(results)
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# 2. read A 股
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try:
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from sanguo_data.datareader import read_db_daily
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from sanguo_data.config import load_config
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cfg = load_config("/app/config/data_platform.yaml")
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bars = read_db_daily("600000", "2024-01-01", "2024-06-30", cfg)
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results["read_bars"] = f"OK ({len(bars)} bars)" if bars else "FAIL: 0 bars"
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if not bars:
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return _print(results)
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except Exception as e:
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import traceback; traceback.print_exc()
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results["read_bars"] = f"FAIL: {e}"
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return _print(results)
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# 3. save + load
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try:
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lab.save_bar_data(bars)
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vt = bars[0].vt_symbol
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loaded = lab.load_bar_data(vt, Interval.DAILY, "2024-01-01", "2024-06-30")
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results["save_load"] = f"OK (vt={vt}, loaded={len(loaded)})"
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except Exception as e:
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import traceback; traceback.print_exc()
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results["save_load"] = f"FAIL: {e}"
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return _print(results)
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# 4. panel df + AlphaDataset + add_feature + prepare + fetch
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try:
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df = pl.DataFrame({
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"datetime": [b.datetime.replace(tzinfo=None) for b in bars],
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"vt_symbol": [b.vt_symbol for b in bars],
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"open": [b.open_price for b in bars],
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"high": [b.high_price for b in bars],
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"low": [b.low_price for b in bars],
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"close": [b.close_price for b in bars],
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"volume": [b.volume for b in bars],
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"turnover": [b.turnover for b in bars],
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"open_interest": [b.open_interest for b in bars],
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})
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ds = AlphaDataset(df, ("2024-01-01", "2024-04-30"),
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("2024-05-01", "2024-05-15"),
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("2024-05-16", "2024-06-30"))
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ds.add_feature("ma5", "ts_mean(close, 5)")
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ds.prepare_data(max_workers=1)
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raw = ds.fetch_raw(Segment.TEST)
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has_ma5 = "ma5" in raw.columns
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results["factor_calc"] = f"OK (cols={raw.columns}, rows={raw.height}, ma5={has_ma5})"
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except Exception as e:
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import traceback; traceback.print_exc()
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results["factor_calc"] = f"FAIL: {e}"
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_print(results)
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def _print(results):
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print("=== S1 Spike Result ===")
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for k, v in results.items():
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print(f" {k}: {v}")
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ok = all("OK" in v for v in results.values())
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print(f"\nS1 VERDICT: {'PASS' if ok else 'PARTIAL/FAIL'}")
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if __name__ == "__main__":
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main()
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