import pandas as pd
from db_config import DatabaseManager, DatabaseConfig
from loguru import logger
from datetime import datetime
import akshare as ak
# from index_downloader import get_all_stock_index
from em_index_sport import get_index_latest_data
import schedule
import time
import traceback
from dingtalk import DingTalkBot
import os
from signal_calc import main_calc_process

webhook = "https://oapi.dingtalk.com/robot/send?access_token=21de667159edadd33172c6ec414a2addf9c6359189350ffd36819d2a20e8a0f4"
secret = "SEC43a0fa0b29717f98637a119b92a0bd5f7b2b6da671bdd2bd1279ed8323454d5e"
dingtalk = DingTalkBot(webhook, secret)


def get_latest_index_kline_date():
    # df = pd.read_csv(
    #     "/Users/aszer/Documents/vscode/etf/index_all_stock.csv", encoding="utf-8-sig"
    # )
    # index_hist_df = pd.read_csv(
    #     "/Users/aszer/Documents/vscode/etf/data/index_history_data/000001.csv",
    #     encoding="utf-8-sig",
    # )
    # df = get_all_stock_index()
    df = get_index_latest_data()
    column_mapping = {
        "date": "date",
        "代码": "code",
        "今开": "open",
        "最高": "high",
        "最低": "low",
        "最新价": "close",
        "成交量": "volume",
    }

    df["date"] = None
    df = df.rename(columns=column_mapping)
    df = df[column_mapping.values()]
    df = df.drop_duplicates(subset=["code"])

    # 获取上证指数最近30天的数据
    code = "000001"  # 用来获取当前最新k线数据的日期，参考 上证指数
    latest = df[df["code"] == code].to_dict(orient="records")[0]
    h, l, o, c = latest["high"], latest["low"], latest["open"], latest["close"]
    cur_date = datetime.now().strftime("%Y%m%d")
    seven_days_ago = (datetime.now() - pd.Timedelta(days=30)).strftime("%Y%m%d")
    index_hist_df = ak.index_zh_a_hist(
        symbol=code,
        period="daily",
        start_date=seven_days_ago,
        end_date=cur_date,
    )

    index_hist_df = index_hist_df.sort_values(
        by="日期", ascending=False
    )  # 按时间降序排列
    index_hist_df = index_hist_df[
        (index_hist_df["最高"] == h)
        & (index_hist_df["最低"] == l)
        & (index_hist_df["开盘"] == o)
        & (index_hist_df["收盘"] == c)
    ]
    index_hist = index_hist_df.to_dict(orient="records")[0]
    hist_date = index_hist["日期"]
    df["date"] = hist_date
    return df


def main():
    if datetime.today().weekday() >= 5:
        logger.info(f"非交易日")
        return

    try:
        db_config = DatabaseConfig(env="daily")
        logger.info(f"数据库连接: {db_config.connection_string}")

        # 如果只是测试连接
        db_manager = DatabaseManager(db_config)
        if db_manager.test_connection():
            logger.info("✅ 数据库连接测试成功")
        else:
            logger.error("❌ 数据库连接测试失败")
            raise Exception("数据库连接测试失败")

        df = get_latest_index_kline_date()
        logger.info(df.head())
        latest_date = df["date"].values[0]
        res = db_manager.execute_query(
            f"SELECT date, code, open, high, low, close, volume FROM public.index_kline where code='000001' and date='{latest_date}' order by date desc limit 1;"
        )
        # print(dict(res))
        logger.info(len(res))
        if len(res) == 0:
            res = db_manager.insert_dataframe(df, "index_kline")
            logger.info(res)
        main_calc_process()
    except Exception as e:
        error_message = f"{e}\n{traceback.format_exc()}"
        logger.error(error_message)
        dingtalk.send_text(f"A股指数抓取失败: \n{error_message}")


if __name__ == "__main__":
    # main()
    logger.info(datetime.now())
    PULL_SCHEDULE: str = os.getenv("PULL_SCHEDULE", "16:00")
    logger.info(f"PULL_SCHEDULE: {PULL_SCHEDULE}")
    schedule.every().day.at(PULL_SCHEDULE).do(main)
    while True:
        schedule.run_pending()
        time.sleep(1)