#!/usr/bin/env python3
"""多源降级管理器 - 日线(akshare→腾讯) + 实时(新浪→东财→腾讯)"""
import pandas as pd
import urllib.request
import json
import logging
from datetime import datetime, timedelta
from typing import Optional

logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s %(message)s')
logger = logging.getLogger(__name__)


class FallbackManager:
    def __init__(self):
        self._source_used = ""

    def get_source_used(self) -> str:
        return self._source_used

    def get_daily(self, symbol: str, start_date: str, end_date: str) -> pd.DataFrame:
        """获取日线数据，降级链：akshare → 腾讯K线"""
        # 1. akshare
        try:
            df = self._fetch_akshare_daily(symbol, start_date, end_date)
            if df is not None and not df.empty:
                self._source_used = "akshare"
                return df
        except Exception as e:
            logger.warning(f"akshare日线失败 {symbol}: {e}")

        # 2. 腾讯K线
        try:
            df = self._fetch_tencent_daily(symbol, start_date, end_date)
            if df is not None and not df.empty:
                self._source_used = "tencent_kline"
                return df
        except Exception as e:
            logger.warning(f"腾讯K线失败 {symbol}: {e}")

        raise RuntimeError(f"所有日线数据源失败: {symbol} {start_date}~{end_date}")

    def get_realtime(self, symbol: str) -> dict:
        """获取实时行情，降级链：新浪→东财→腾讯"""
        from realtime import get_realtime_quote
        result = get_realtime_quote(symbol)
        self._source_used = result.get("source", "unknown")
        return result

    def _fetch_akshare_daily(self, symbol: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
        import akshare as ak
        code = symbol.replace("SH", "").replace("SZ", "").replace("sh", "").replace("sz", "")
        s = start_date.replace("-", "")
        e = end_date.replace("-", "")
        df = ak.stock_zh_a_hist(symbol=code, period="daily", start_date=s, end_date=e, adjust="")
        if df is None or df.empty:
            return None
        df = df.rename(columns={"日期": "date", "开盘": "open", "收盘": "close",
                                 "最高": "high", "最低": "low", "成交量": "volume",
                                 "成交额": "amount"})
        df["date"] = pd.to_datetime(df["date"]).dt.strftime("%Y-%m-%d")
        for c in ["open", "high", "low", "close", "volume", "amount"]:
            df[c] = pd.to_numeric(df[c], errors="coerce").fillna(0)
        return df[["date", "open", "high", "low", "close", "volume", "amount"]]

    def _fetch_tencent_daily(self, symbol: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
        """腾讯K线API获取日线"""
        code = symbol.replace("SH", "").replace("SZ", "").replace("sh", "").replace("sz", "")
        if code.startswith(("6", "5", "1")):
            prefix = "sh"
        else:
            prefix = "sz"
        tq_symbol = f"{prefix}{code}"

        days = (datetime.strptime(end_date, "%Y-%m-%d") - datetime.strptime(start_date, "%Y-%m-%d")).days + 10
        url = f"https://web.ifzq.gtimg.cn/appstock/app/fqkline/get?param={tq_symbol},day,{start_date},,{days},"
        try:
            import urllib.request, json as _json
            opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
            req = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})
            with opener.open(req, timeout=10) as r:
                resp = _json.loads(r.read())
            d = resp.get("data")
            if not isinstance(d, dict):
                return None
            klines = d.get(tq_symbol, {}).get("day", [])
            if not klines:
                return None
            df = pd.DataFrame(klines)
            ncols = len(df.columns)
            if ncols >= 7:
                df.columns = ["date", "open", "close", "high", "low", "volume", "amount"][:ncols]
            else:
                df.columns = ["date", "open", "close", "high", "low", "volume"][:ncols]
            if "amount" not in df.columns:
                df["amount"] = 0.0
            for c in ["open", "close", "high", "low", "volume", "amount"]:
                df[c] = pd.to_numeric(df[c], errors="coerce").fillna(0)
            df["date"] = pd.to_datetime(df["date"]).dt.strftime("%Y-%m-%d")
            mask = (df["date"] >= start_date) & (df["date"] <= end_date)
            return df.loc[mask, ["date", "open", "high", "low", "close", "volume", "amount"]]
        except Exception as e:
            logger.warning(f"腾讯K线请求失败: {e}")
            return None