"""CSV 读取模块：读 timestamp,value,label 三列，返回归一化元组。"""

from pathlib import Path
import pandas as pd


def read_csv(path: str | Path, value_col: str = "value") -> tuple[list[int], list[float], list[int]]:
    """读 timestamp,value,label CSV 文件。

    Args:
        path: CSV 文件路径
        value_col: 数值列名 (default: "value")

    Returns:
        (timestamps_ms, values, labels) 三元组
        - timestamps_ms: 毫秒精度 Unix 时间戳
        - values: 浮点数值列表
        - labels: 整数标签列表（0=正常, 1=异常）

    Raises:
        FileNotFoundError: 文件不存在
        ValueError: 缺少 timestamp 或 value 列
    """
    df = pd.read_csv(path)

    if "timestamp" not in df.columns or value_col not in df.columns:
        raise ValueError(f"CSV 缺少 timestamp 或 {value_col} 列: {path}")

    timestamps = pd.to_datetime(df["timestamp"], format="mixed", errors="coerce")
    if timestamps.isna().any():
        # 对无法解析的行尝试修正（如 00:60:00 → 01:00:00）
        import re
        na_mask = timestamps.isna()
        raw_strs = df.loc[na_mask, "timestamp"].astype(str)

        def _fix_hour60(s: str) -> str:
            def _repl(m):
                h = (int(m.group(1)) + 1) % 24
                return f"{h:02d}:00:00"
            return re.sub(r"(\d{2}):60:00", _repl, s)

        fixed = raw_strs.apply(_fix_hour60)
        timestamps.loc[na_mask] = pd.to_datetime(fixed, errors="coerce")
    # 丢弃时间戳仍为 NaN 的行（coerce 后无法恢复的异常时间戳）
    valid_mask = timestamps.notna()
    if not valid_mask.all():
        n_drop = (~valid_mask).sum()
        import logging
        logging.getLogger(__name__).warning("dropping %d rows with invalid timestamps", n_drop)
        timestamps = timestamps[valid_mask].reset_index(drop=True)
        df = df[valid_mask].reset_index(drop=True)

    timestamps_ms = (timestamps.astype("int64") // 10**6).tolist()

    values = df[value_col].astype(float).tolist()

    labels = df["label"].fillna(0).astype(int).tolist() if "label" in df.columns else [0] * len(df)

    return timestamps_ms, values, labels