import sys
import os
from pathlib import Path

# Add real vnpy source code to sys.path
_VNPY_SRC = os.path.join(os.path.dirname(__file__), "..", "vnpy_v4.4.0")
_VNPY_SRC = os.path.abspath(_VNPY_SRC)
if _VNPY_SRC not in sys.path:
    sys.path.insert(0, _VNPY_SRC)

import pandas as pd
from datetime import datetime, date
from vnpy.trader.object import BarData
from vnpy.trader.constant import Exchange, Interval
from vnpy.trader.setting import SETTINGS

def read_parquet_daily(symbol: str, start: str, end: str, cfg, dir_key: str = "daily_dir") -> list[BarData]:
    daily_dir = Path(cfg.data_paths[dir_key])
    start_dt = datetime.strptime(start, "%Y-%m-%d")
    end_dt = datetime.strptime(end, "%Y-%m-%d")
    bars: list[BarData] = []
    prefix = "sh" if guess_exchange(symbol) == Exchange.SSE else "sz"
    for year in range(start_dt.year, end_dt.year + 1):
        f = daily_dir / str(year) / f"{prefix}{symbol}_daily.parquet"
        if not f.exists():
            continue
        df = pd.read_parquet(f)
        for _, row in df.iterrows():
            d = pd.to_datetime(row["date"])
            if start_dt <= d <= end_dt:
                bars.append(_row_to_bar(symbol, row, Interval.DAILY))
    return bars

def _row_to_bar(symbol: str, row, interval: Interval) -> BarData:
    return BarData(
        symbol=symbol,
        exchange=guess_exchange(symbol),  # Task 4 已改为 guess_exchange
        datetime=pd.to_datetime(row["date"]).to_pydatetime(),
        interval=interval,
        open_price=float(row["open"]),
        high_price=float(row["high"]),
        low_price=float(row["low"]),
        close_price=float(row["close"]),
        volume=float(row["volume"]),
        gateway_name="DATA",
    )


def guess_exchange(symbol: str) -> Exchange:
    """按代码前缀判断交易所：6/68/5x→SSE，0/3/15x→SZSE"""
    if symbol.startswith(("60", "68", "51", "56", "58")):
        return Exchange.SSE
    if symbol.startswith(("00", "30", "15")):
        return Exchange.SZSE
    return Exchange.SSE


def read_db_daily(symbol: str, start: str, end: str, cfg) -> list[BarData]:
    from vnpy.trader.database import get_database  # lazy：避免模块 import 依赖数据库驱动
    # Configure vnpy database SETTINGS before calling get_database()
    SETTINGS["database.name"] = "sqlite"
    SETTINGS["database.database"] = cfg.data_paths["vnpy_db"]

    db = get_database()
    start_dt = datetime.strptime(start, "%Y-%m-%d")
    end_dt = datetime.strptime(end, "%Y-%m-%d")
    return db.load_bar_data(
        symbol=symbol,
        exchange=guess_exchange(symbol),
        interval=Interval.DAILY,
        start=start_dt,
        end=end_dt,
    )


def read_parquet_15min(symbol: str, start: str, end: str, cfg, dir_key: str = "minute_15_dir") -> list[BarData]:
    """读 15min parquet（NAS /volume1/stock/minute_kline/15min/sh{symbol}_15min.parquet）。"""
    minute_dir = Path(cfg.data_paths[dir_key])
    start_dt = datetime.strptime(start, "%Y-%m-%d")
    end_dt = datetime.strptime(end, "%Y-%m-%d")
    prefix = "sh" if guess_exchange(symbol) == Exchange.SSE else "sz"
    f = minute_dir / f"{prefix}{symbol}_15min.parquet"
    if not f.exists():
        return []
    df = pd.read_parquet(f)
    # baostock 15min 有完整时分 datetime 列；旧数据用 date 列
    time_col = ("datetime" if "datetime" in df.columns
                else ("date" if "date" in df.columns else df.columns[0]))
    bars: list[BarData] = []
    for _, row in df.iterrows():
        d = pd.to_datetime(row[time_col])
        if start_dt <= d <= end_dt:
            bars.append(BarData(
                symbol=symbol,
                exchange=guess_exchange(symbol),
                datetime=d.to_pydatetime(),
                interval=Interval.MINUTE,
                open_price=float(row["open"]),
                high_price=float(row["high"]),
                low_price=float(row["low"]),
                close_price=float(row["close"]),
                volume=float(row["volume"]),
                gateway_name="DATA",
            ))
    return bars


def read_index_daily(code: str, start: date, end: date, cfg) -> pd.DataFrame:
    """
    读指数日线数据（sh000300/sz000905），复用 read_parquet_daily 的年分片 parquet 路径

    Args:
        code: 指数代码，如 "sh000300"（沪深300）、"sz000905"（中证500）
        start: 起始日期
        end: 结束日期
        cfg: 数据配置对象

    Returns:
        pd.DataFrame: 包含 date/open/high/low/close/volume 列的日线数据
    """
    daily_dir = Path(cfg.data_paths["daily_dir"])
    start_dt = start if isinstance(start, datetime) else datetime.combine(start, datetime.min.time())
    end_dt = end if isinstance(end, datetime) else datetime.combine(end, datetime.max.time())

    dfs: list[pd.DataFrame] = []

    # 按年分片读取（与 read_parquet_daily 相同路径逻辑）
    for year in range(start_dt.year, end_dt.year + 1):
        f = daily_dir / str(year) / f"{code}_daily.parquet"
        if not f.exists():
            continue
        df = pd.read_parquet(f)
        # 过滤日期范围
        df["date"] = pd.to_datetime(df["date"])
        mask = (df["date"] >= start_dt) & (df["date"] <= end_dt)
        filtered_df = df[mask].copy()
        if not filtered_df.empty:
            dfs.append(filtered_df)

    if dfs:
        result = pd.concat(dfs, ignore_index=True)
        result = result.sort_values("date")
        return result.reset_index(drop=True)
    else:
        return pd.DataFrame(columns=["date", "open", "high", "low", "close", "volume"])