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backend/app/data/synthetic.py

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+"""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()