from __future__ import annotations

import os
from dataclasses import dataclass

import pandas as pd
from dotenv import load_dotenv


@dataclass(frozen=True)
class TushareConfig:
    token: str
    timeout: int = 30


def load_tushare_config(env_path: str | None = None) -> TushareConfig:
    if env_path:
        load_dotenv(env_path)
    else:
        load_dotenv()

    token = os.getenv("TUSHARE_TOKEN", "").strip()
    if not token:
        raise RuntimeError("TUSHARE_TOKEN is required (set it in .env)")

    timeout_s = os.getenv("TUSHARE_TIMEOUT", "30").strip() or "30"
    try:
        timeout = int(timeout_s)
    except ValueError:
        timeout = 30

    return TushareConfig(token=token, timeout=timeout)


def pro_api(cfg: TushareConfig):
    import tushare as ts

    ts.set_token(cfg.token)
    return ts.pro_api(timeout=cfg.timeout)


def fetch_stock_daily(
    cfg: TushareConfig,
    ts_code: str | None = None,
    trade_date: str | None = None,
    start_date: str | None = None,
    end_date: str | None = None,
    fields: str | None = None,
) -> pd.DataFrame:
    api = pro_api(cfg)
    return api.daily(
        ts_code=ts_code,
        trade_date=trade_date,
        start_date=start_date,
        end_date=end_date,
        fields=fields,
    )


def fetch_fund_daily(
    cfg: TushareConfig,
    ts_code: str | None = None,
    trade_date: str | None = None,
    start_date: str | None = None,
    end_date: str | None = None,
    fields: str | None = None,
) -> pd.DataFrame:
    """Fetch ETF/fund daily bars via Tushare Pro `fund_daily`."""
    api = pro_api(cfg)
    return api.fund_daily(
        ts_code=ts_code,
        trade_date=trade_date,
        start_date=start_date,
        end_date=end_date,
        fields=fields,
    )