"""
龙虎榜采集器
主方案：AkShare stock_lhb_detail_daily_sina（已实测可用，含上榜原因）
备选：东财 datacenter 接口（报表名不确定，暂时注释备用）
"""

import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent.parent))

import akshare as ak
import pandas as pd
from datetime import datetime, timedelta
from src.storage.db import upsert_df, upsert_log, get_last_fetch


def fetch_lhb_date(trade_date: str) -> pd.DataFrame:
    """
    获取单日龙虎榜
    trade_date: "YYYY-MM-DD" 或 "YYYYMMDD"
    """
    # 统一为 YYYYMMDD 格式
    ds = trade_date.replace("-", "")
    try:
        df = ak.stock_lhb_detail_daily_sina(date=ds)
    except Exception as e:
        print(f"  [WARN] LHB Sina failed for {trade_date}: {e}")
        return pd.DataFrame()

    if df is None or df.empty:
        return pd.DataFrame()

    # Sina 返回列（实测）：序号, 股票代码, 股票名称, 收盘价, 涨跌幅, 成交额, 成交额, 上榜原因
    # 编码问题导致中文列名显示乱码，用位置索引映射
    # 0=序号, 1=代码, 2=名称, 3=收盘, 4=涨跌幅, 5=成交额, 6=??? 7=上榜原因
    df.columns = ["no", "ts_code", "name", "close", "pct_change", "amount", "amount2", "reason"]

    df["trade_date"] = trade_date.replace("-", "")
    # 格式化为 YYYY-MM-DD
    df["trade_date"] = pd.to_datetime(df["trade_date"]).dt.strftime("%Y-%m-%d")

    # 保留有用字段
    keep = ["trade_date", "ts_code", "name", "close", "pct_change", "amount", "reason"]
    df = df[[c for c in keep if c in df.columns]]
    return df


def fetch_lhb_range(start_date: str, end_date: str = None) -> pd.DataFrame:
    """抓取日期区间的龙虎榜（逐日）"""
    end_date = end_date or datetime.today().strftime("%Y-%m-%d")
    all_days = []
    cur  = datetime.strptime(start_date.replace("-", ""), "%Y%m%d")
    end  = datetime.strptime(end_date.replace("-", ""),   "%Y%m%d")
    while cur <= end:
        ds = cur.strftime("%Y-%m-%d")
        df = fetch_lhb_date(ds)
        if df is not None and not df.empty:
            all_days.append(df)
        cur += timedelta(days=1)
    if all_days:
        return pd.concat(all_days, ignore_index=True)
    return pd.DataFrame()


def incremental_lhb(source: str = "lhb_daily") -> pd.DataFrame:
    """增量采集：只抓上次之后的新交易日"""
    last = get_last_fetch(source)
    start = last.get("last_date") or (datetime.today() - timedelta(days=7)).strftime("%Y-%m-%d")
    end   = datetime.today().strftime("%Y-%m-%d")
    df = fetch_lhb_range(start, end)
    if df is not None and not df.empty:
        upsert_df(df, "lhb_daily")
        upsert_log(source, param="", last_date=end)
    return df


if __name__ == "__main__":
    import fire
    fire.Fire({
        "date":  lambda d: upsert_df(fetch_lhb_date(d), "lhb_daily"),
        "range": lambda s, e=None: upsert_df(fetch_lhb_range(s, e), "lhb_daily"),
        "incr":  lambda: incremental_lhb(),
    })