"""S1: 验证 vnpy.alpha 能否处理 A 股数据（Phase 1 真实数据 → AlphaLab → 因子计算）。

验证链：
1. AlphaLab init
2. read_db_daily 读 A 股 bars（Phase 1）
3. save_bar_data + load_bar_data（存取兼容性）
4. 构造 panel df（datetime, vt_symbol, OHLCV）
5. AlphaDataset + add_feature(ma5) + prepare_data（spawn pool 因子计算）
6. fetch_raw（验证因子列生成）

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，
由策略/回测层处理；因子计算只需 OHLCV，A 股数据格式无差异。
"""
import sys
import os

sys.path.insert(0, "/app/vnpy_v4.4.0")
sys.path.insert(0, "/app")


def main():
    from vnpy.alpha.lab import AlphaLab
    from vnpy.alpha.dataset import AlphaDataset, Segment
    from vnpy.trader.constant import Interval
    import polars as pl

    results = {}

    # 1. AlphaLab init
    try:
        lab = AlphaLab("/tmp/alpha_lab_spike")
        results["alphalab_init"] = "OK"
    except Exception as e:
        results["alphalab_init"] = f"FAIL: {e}"
        return _print(results)

    # 2. read A 股
    try:
        from sanguo_data.datareader import read_db_daily
        from sanguo_data.config import load_config
        cfg = load_config("/app/config/data_platform.yaml")
        bars = read_db_daily("600000", "2024-01-01", "2024-06-30", cfg)
        results["read_bars"] = f"OK ({len(bars)} bars)" if bars else "FAIL: 0 bars"
        if not bars:
            return _print(results)
    except Exception as e:
        import traceback; traceback.print_exc()
        results["read_bars"] = f"FAIL: {e}"
        return _print(results)

    # 3. save + load
    try:
        lab.save_bar_data(bars)
        vt = bars[0].vt_symbol
        loaded = lab.load_bar_data(vt, Interval.DAILY, "2024-01-01", "2024-06-30")
        results["save_load"] = f"OK (vt={vt}, loaded={len(loaded)})"
    except Exception as e:
        import traceback; traceback.print_exc()
        results["save_load"] = f"FAIL: {e}"
        return _print(results)

    # 4. panel df + AlphaDataset + add_feature + prepare + fetch
    try:
        df = pl.DataFrame({
            "datetime": [b.datetime.replace(tzinfo=None) for b in bars],
            "vt_symbol": [b.vt_symbol for b in bars],
            "open": [b.open_price for b in bars],
            "high": [b.high_price for b in bars],
            "low": [b.low_price for b in bars],
            "close": [b.close_price for b in bars],
            "volume": [b.volume for b in bars],
            "turnover": [b.turnover for b in bars],
            "open_interest": [b.open_interest for b in bars],
        })
        ds = AlphaDataset(df, ("2024-01-01", "2024-04-30"),
                          ("2024-05-01", "2024-05-15"),
                          ("2024-05-16", "2024-06-30"))
        ds.add_feature("ma5", "ts_mean(close, 5)")
        ds.prepare_data(max_workers=1)
        raw = ds.fetch_raw(Segment.TEST)
        has_ma5 = "ma5" in raw.columns
        results["factor_calc"] = f"OK (cols={raw.columns}, rows={raw.height}, ma5={has_ma5})"
    except Exception as e:
        import traceback; traceback.print_exc()
        results["factor_calc"] = f"FAIL: {e}"

    _print(results)


def _print(results):
    print("=== S1 Spike Result ===")
    for k, v in results.items():
        print(f"  {k}: {v}")
    ok = all("OK" in v for v in results.values())
    print(f"\nS1 VERDICT: {'PASS' if ok else 'PARTIAL/FAIL'}")


if __name__ == "__main__":
    main()