"""合成数据（MVP 零依赖可跑）。

生成随机游走 OHLCV，灌入 DB。仅用于让回测链路在没有真实数据源时也能跑通演示。
阶段1 接 Tushare/AKShare 后，这里仅保留为"离线测试夹具"。
"""
from __future__ import annotations

from datetime import datetime, timedelta, timezone

import numpy as np
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession

from ..domain import Bar
from ..models import Candle


def _trading_days(n: int) -> list[datetime]:
    """粗略生成 n 个工作日（跳过周末；节假日由阶段1 的交易日历服务处理）。"""
    start = datetime.now(timezone.utc).replace(tzinfo=None) - timedelta(days=int(n * 1.6))
    days: list[datetime] = []
    d = start
    while len(days) < n:
        if d.weekday() < 5:
            days.append(d.replace(hour=15, minute=0, second=0, microsecond=0))
        d += timedelta(days=1)
    return days


def generate_ohlcv(n: int = 500, seed: int = 42) -> list[Bar]:
    """随机游走 + A 股风格的价格区间（5~30 元）。"""
    rng = np.random.default_rng(seed)
    rets = rng.normal(loc=0.0003, scale=0.018, size=n)
    price = 10.0 * np.cumprod(1 + rets)
    days = _trading_days(n)
    bars: list[Bar] = []
    for i in range(n):
        close = float(price[i])
        op = close * (1 + rng.normal(0, 0.005))
        hi = max(op, close) * (1 + abs(rng.normal(0, 0.006)))
        lo = min(op, close) * (1 - abs(rng.normal(0, 0.006)))
        vol = float(rng.integers(1_000_000, 10_000_000))
        bars.append(
            Bar(
                ts=days[i],
                open=round(op, 2),
                high=round(hi, 2),
                low=round(lo, 2),
                close=round(close, 2),
                volume=vol,
            )
        )
    return bars


async def seed_if_empty(session: AsyncSession, symbol: str = "DEMO", n: int = 500) -> None:
    """若库中无该 symbol 数据，则灌入合成数据。"""
    existing = await session.execute(
        select(Candle.id).where(Candle.symbol == symbol).limit(1)
    )
    if existing.scalars().first() is not None:
        return

    bars = generate_ohlcv(n=n)
    for b in bars:
        session.add(
            Candle(
                symbol=symbol,
                timeframe="1d",
                ts=b.ts,
                open=b.open,
                high=b.high,
                low=b.low,
                close=b.close,
                volume=b.volume,
            )
        )
    await session.commit()