985 lines
41 KiB
Python
985 lines
41 KiB
Python
"""HTTP 路由（OpenAPI 契约的载体）。
|
||
|
||
GET /api/health 健康检查
|
||
GET /api/candles/{sym} 取 K 线（支持 1d/1w/1M/1y 周期，日线为基底聚合）
|
||
GET /api/stocks 全市场股票列表（基本信息 + 最新行情 + 缓存条数）
|
||
GET /api/market/overview 主页大盘总览（A 股/港美指数 + 两市市值成交统计）
|
||
POST /api/backtest 跑回测，返回 K线+指标+买卖点+净值+绩效
|
||
POST /api/screener/run 智能选股：自然语言 -> 条件 -> 全市场筛选
|
||
POST /api/screener/sync 启动全市场数据同步（后台任务）
|
||
GET /api/screener/sync/status 同步任务状态与数据实况
|
||
"""
|
||
from __future__ import annotations
|
||
|
||
import bisect
|
||
import json
|
||
from datetime import datetime
|
||
|
||
import pandas as pd
|
||
from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
|
||
from sqlalchemy import delete, func, select, text
|
||
from sqlalchemy.ext.asyncio import AsyncSession
|
||
from sqlalchemy.sql.elements import TextClause
|
||
|
||
from .backtest.engine import BacktestConfig, run_backtest
|
||
from . import cache
|
||
from .auth import require_user
|
||
from .backtest.events import EventEngineError, run_event_backtest
|
||
from .backtest.strategies import build_strategy
|
||
from .config import settings
|
||
from .data import fetcher, repository
|
||
from .data.aggregation import bars_per_year, resample_bars
|
||
from .data.market_overview import MarketOverviewError, fetch_overview
|
||
from .data.symbols import plain_code
|
||
from .db import get_session
|
||
from .domain import Bar
|
||
from . import indicators as ind
|
||
from .trades import parse_statement
|
||
from .models import (
|
||
AdjFactor,
|
||
BacktestRun,
|
||
Candle,
|
||
DailySnapshot,
|
||
ScreenerQuery,
|
||
StockBasic,
|
||
UserPreference,
|
||
UserTrade,
|
||
WatchlistItem,
|
||
)
|
||
from .schemas import (
|
||
BacktestRequest,
|
||
BacktestResponse,
|
||
CandleOut,
|
||
EquityPoint,
|
||
EventBacktestRequest,
|
||
EventBacktestResponse,
|
||
IndicatorOut,
|
||
MarketOverviewResponse,
|
||
MetricsOut,
|
||
PreferencesOut,
|
||
PreferencesUpdate,
|
||
PreviewInfoOut,
|
||
PreviewResponse,
|
||
ScreenerQueryListResponse,
|
||
ScreenerQueryOut,
|
||
ScreenerRunRequest,
|
||
ScreenerRunResponse,
|
||
ScreenerSyncRequest,
|
||
ScreenerSyncStatus,
|
||
SignalOut,
|
||
StockListItemOut,
|
||
StockListResponse,
|
||
StockFacetsResponse,
|
||
FacetItemOut,
|
||
SyncRequest,
|
||
SyncResponse,
|
||
TradesClearResponse,
|
||
TradesImportResponse,
|
||
UserTradeOut,
|
||
WatchlistOp,
|
||
)
|
||
from .screener import engine, market_sync
|
||
from .screener.engine import DataNotReadyError
|
||
from .screener.llm import ScreenerError, parse_conditions, parse_event_spec
|
||
|
||
router = APIRouter(prefix="/api", dependencies=[Depends(require_user)])
|
||
|
||
|
||
def _series_to_jsonable(s: pd.Series) -> list[float | None]:
|
||
"""NaN -> None（lightweight-charts 的 whitespace data，跳过指标预热期）。"""
|
||
out: list[float | None] = []
|
||
for v in s.tolist():
|
||
if v is None or (isinstance(v, float) and v != v):
|
||
out.append(None)
|
||
else:
|
||
out.append(float(v))
|
||
return out
|
||
|
||
|
||
def _rows_to_bars(rows) -> list[Bar]:
|
||
return [
|
||
Bar(
|
||
ts=r.ts, open=r.open, high=r.high, low=r.low, close=r.close, volume=r.volume,
|
||
amount=getattr(r, "amount", None), turnover=getattr(r, "turnover", None),
|
||
)
|
||
for r in rows
|
||
]
|
||
|
||
|
||
_ADJUST_MODES = ("bfq", "qfq", "hfq")
|
||
# MA 全量集合（前端已改为本地计算 MA，后端始终返回此集合以保证缓存一致）
|
||
_FULL_MA_SET = (5, 10, 20, 30, 60, 120, 250)
|
||
|
||
|
||
def _adjust_bars(bars: list[Bar], factors, from_mode: str, to_mode: str) -> list[Bar]:
|
||
"""按复权因子把 K 线从 from_mode 换算到 to_mode（bfq/qfq/hfq）。
|
||
|
||
相对不复权的乘数：bfq=1，qfq=f(t)/f(latest)，hfq=f(t)。
|
||
因子缺失的日期向前沿用最近因子（因子是阶梯函数，除权日之间不变）。
|
||
"""
|
||
fd = sorted((f.trade_date.date(), float(f.adj_factor)) for f in factors)
|
||
fdates = [d for d, _ in fd]
|
||
f_latest = fd[-1][1]
|
||
|
||
def _f_at(d) -> float:
|
||
i = bisect.bisect_right(fdates, d) - 1
|
||
return fd[i][1] if i >= 0 else fd[0][1]
|
||
|
||
def _mult(mode: str, f: float) -> float:
|
||
if mode == "bfq":
|
||
return 1.0
|
||
return f / f_latest if mode == "qfq" else f
|
||
|
||
out: list[Bar] = []
|
||
for b in bars:
|
||
f = _f_at(b.ts.date())
|
||
m = _mult(to_mode, f) / _mult(from_mode, f)
|
||
out.append(Bar(
|
||
ts=b.ts,
|
||
open=round(b.open * m, 3), high=round(b.high * m, 3),
|
||
low=round(b.low * m, 3), close=round(b.close * m, 3),
|
||
volume=b.volume,
|
||
# 成交额/换手率是名义量，不随复权缩放
|
||
amount=b.amount, turnover=b.turnover,
|
||
))
|
||
return out
|
||
|
||
|
||
@router.get("/candles/{symbol}", response_model=list[CandleOut])
|
||
async def get_candles(
|
||
symbol: str,
|
||
timeframe: str = "1d",
|
||
limit: int = 5000,
|
||
session: AsyncSession = Depends(get_session),
|
||
) -> list[CandleOut]:
|
||
# 始终以日线为基底，再聚合到目标周期（取最新 limit 根）
|
||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=limit)
|
||
bars = resample_bars(_rows_to_bars(rows), timeframe)
|
||
return [
|
||
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close,
|
||
volume=b.volume, amount=b.amount, turnover=b.turnover)
|
||
for b in bars
|
||
]
|
||
|
||
|
||
@router.post("/data/sync", response_model=SyncResponse)
|
||
async def sync_data(req: SyncRequest, session: AsyncSession = Depends(get_session)) -> SyncResponse:
|
||
"""主动拉取并缓存某标的的日线（Tushare 主 -> AKShare 兜底）。"""
|
||
try:
|
||
res = await fetcher.sync_symbol(
|
||
session, req.symbol, start=req.start, end=req.end, source=req.source, force=req.force
|
||
)
|
||
return SyncResponse(**res)
|
||
except Exception as e: # noqa: BLE001
|
||
raise HTTPException(status_code=502, detail=str(e))
|
||
|
||
|
||
# ---------- 股票列表（全市场浏览） ----------
|
||
# 过滤/排序/分页在 stock_basic+watchlist+daily_snapshot 上完成（快照按最新交易日
|
||
# 走唯一索引 join，便宜），再对「本页」≤limit 只股票补最新价/昨收（LATERAL 扫
|
||
# candles，贵）——旧写法对全市场 ~5000 只逐个算，每页都白算 50 倍的行情量。
|
||
# 排序列白名单（键→CTE 内表达式）；order_by 由白名单拼接进模板，不接收用户原文。
|
||
_STOCKS_SORTS = {
|
||
"symbol": "sb.symbol",
|
||
"total_mv": "snap.total_mv",
|
||
"circ_mv": "snap.circ_mv",
|
||
"pe_ttm": "snap.pe_ttm",
|
||
"pb": "snap.pb",
|
||
"turnover_rate": "snap.turnover_rate",
|
||
}
|
||
|
||
_STOCKS_SQL_TMPL = """
|
||
WITH page AS (
|
||
SELECT sb.ts_code, sb.symbol, sb.name, sb.industry, sb.market,
|
||
(w.id IS NOT NULL) AS watched,
|
||
snap.turnover_rate, snap.pe_ttm, snap.pb, snap.total_mv, snap.circ_mv
|
||
FROM stock_basic sb
|
||
LEFT JOIN watchlist_items w ON w.ts_code = sb.ts_code AND w.user_id = :uid
|
||
LEFT JOIN daily_snapshot snap ON snap.ts_code = sb.ts_code
|
||
AND snap.trade_date = (SELECT max(trade_date) FROM daily_snapshot)
|
||
WHERE sb.list_status = 'L'
|
||
AND (:search = '' OR sb.symbol LIKE :psearch OR sb.name LIKE :psearch)
|
||
AND (:market = '' OR sb.market = :market)
|
||
AND (:industry = '' OR sb.industry = :industry)
|
||
AND (:area = '' OR sb.area = :area)
|
||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||
ORDER BY {order_by}
|
||
LIMIT :limit OFFSET :offset
|
||
)
|
||
SELECT p.ts_code, p.symbol, p.name, p.industry, p.market, p.watched,
|
||
c.close AS close, prev.close AS prev_close, c.ts AS last_ts,
|
||
CASE WHEN c.close IS NOT NULL AND prev.close IS NOT NULL AND prev.close <> 0
|
||
THEN round(((c.close / prev.close - 1) * 100)::numeric, 2) END AS pct_chg,
|
||
p.turnover_rate, p.pe_ttm, p.pb,
|
||
round((p.total_mv / 10000.0)::numeric, 2) AS total_mv,
|
||
round((p.circ_mv / 10000.0)::numeric, 2) AS circ_mv
|
||
FROM page p
|
||
LEFT JOIN LATERAL (
|
||
SELECT close, ts FROM candles
|
||
WHERE symbol = p.symbol AND timeframe = '1d'
|
||
ORDER BY ts DESC LIMIT 1
|
||
) c ON true
|
||
LEFT JOIN LATERAL (
|
||
SELECT close FROM candles
|
||
WHERE symbol = p.symbol AND timeframe = '1d' AND ts < c.ts
|
||
ORDER BY ts DESC LIMIT 1
|
||
) prev ON c.ts IS NOT NULL
|
||
"""
|
||
|
||
|
||
def _stocks_sql(sort: str, order: str) -> TextClause:
|
||
col = _STOCKS_SORTS.get(sort, _STOCKS_SORTS["symbol"])
|
||
direction = "DESC" if order == "desc" else "ASC"
|
||
nulls = " NULLS LAST" if col != "sb.symbol" else "" # 快照缺失/亏损无 PE 的排最后
|
||
return text(_STOCKS_SQL_TMPL.format(order_by=f"{col} {direction}{nulls}"))
|
||
|
||
_STOCKS_COUNT_SQL = text("""
|
||
SELECT count(*) FROM stock_basic sb
|
||
LEFT JOIN watchlist_items w ON w.ts_code = sb.ts_code AND w.user_id = :uid
|
||
WHERE sb.list_status = 'L'
|
||
AND (:search = '' OR sb.symbol LIKE :psearch OR sb.name LIKE :psearch)
|
||
AND (:market = '' OR sb.market = :market)
|
||
AND (:industry = '' OR sb.industry = :industry)
|
||
AND (:area = '' OR sb.area = :area)
|
||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||
""")
|
||
|
||
|
||
@router.get("/stocks", response_model=StockListResponse)
|
||
async def list_stocks(
|
||
search: str = "",
|
||
market: str = "",
|
||
industry: str = "",
|
||
area: str = "",
|
||
watched_only: bool = False,
|
||
sort: str = "symbol",
|
||
order: str = "asc",
|
||
limit: int = 100,
|
||
offset: int = 0,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> StockListResponse:
|
||
"""全市场股票列表：stock_basic 基本信息 + candles 最新行情 + daily_snapshot 估值指标
|
||
（换手率/PE-TTM/PB/市值，无快照则这些列为空）。
|
||
watched_only=true 只看自选（自选有独立的「自选」分类入口，列表不再把自选排最前）。
|
||
sort ∈ {symbol,total_mv,circ_mv,pe_ttm,pb,turnover_rate}（白名单，其他值回落 symbol），
|
||
order ∈ asc/desc；快照列排序时缺失值（无快照/亏损无 PE）恒排末尾。
|
||
Redis 缓存：按「用户自选版本 + 查询参数（含排序）」缓存整页（含 total）；自选增删即时失效。"""
|
||
search = search.strip()
|
||
sort = sort if sort in _STOCKS_SORTS else "symbol"
|
||
order = "desc" if order.lower() == "desc" else "asc"
|
||
limit = max(1, min(limit, 500))
|
||
offset = max(0, offset)
|
||
key = (
|
||
f"stocks:u{user.id}"
|
||
f":v{await cache.get_version(f'watchlist:{user.id}')}"
|
||
f":{cache.digest(search, market, industry, area, watched_only, sort, order, limit, offset)}"
|
||
)
|
||
cached = await cache.cache_get(key)
|
||
if cached is not None:
|
||
return StockListResponse(**cached)
|
||
params = {
|
||
"search": search,
|
||
"psearch": f"%{search}%",
|
||
"market": market,
|
||
"industry": industry,
|
||
"area": area,
|
||
"watched_only": watched_only,
|
||
"uid": user.id,
|
||
"limit": limit,
|
||
"offset": offset,
|
||
}
|
||
total = (await session.execute(_STOCKS_COUNT_SQL, params)).scalar_one()
|
||
rows = (await session.execute(_stocks_sql(sort, order), params)).mappings().all()
|
||
resp = StockListResponse(total=total, items=[StockListItemOut(**r) for r in rows])
|
||
await cache.cache_set(key, resp.model_dump(mode="json"), settings.stocks_cache_ttl)
|
||
return resp
|
||
|
||
|
||
@router.get("/stocks/facets", response_model=StockFacetsResponse)
|
||
async def stock_facets(session: AsyncSession = Depends(get_session)) -> StockFacetsResponse:
|
||
"""看股页筛选项：行业 / 地域（含数量，按数量降序）。stock_basic 很少变，长缓存。"""
|
||
cached = await cache.cache_get("facets:stocks")
|
||
if cached is not None:
|
||
return StockFacetsResponse(**cached)
|
||
industries = (
|
||
await session.execute(text("""
|
||
SELECT industry AS name, count(*) AS n FROM stock_basic
|
||
WHERE list_status = 'L' AND industry IS NOT NULL AND industry <> ''
|
||
GROUP BY industry ORDER BY n DESC
|
||
"""))
|
||
).mappings().all()
|
||
areas = (
|
||
await session.execute(text("""
|
||
SELECT area AS name, count(*) AS n FROM stock_basic
|
||
WHERE list_status = 'L' AND area IS NOT NULL AND area <> ''
|
||
GROUP BY area ORDER BY n DESC
|
||
"""))
|
||
).mappings().all()
|
||
resp = StockFacetsResponse(
|
||
industries=[FacetItemOut(name=r["name"], count=r["n"]) for r in industries],
|
||
areas=[FacetItemOut(name=r["name"], count=r["n"]) for r in areas],
|
||
)
|
||
await cache.cache_set("facets:stocks", resp.model_dump(mode="json"), settings.facets_cache_ttl)
|
||
return resp
|
||
|
||
|
||
@router.get("/market/overview", response_model=MarketOverviewResponse)
|
||
async def get_market_overview() -> MarketOverviewResponse:
|
||
"""主页大盘总览：A 股 + 港美指数最近收盘（含迷你走势），沪深两市市值/成交统计。
|
||
|
||
收盘口径（token 无实时权限），展示时标注交易日；部分来源失败不影响其余。
|
||
"""
|
||
try:
|
||
data = await fetch_overview()
|
||
except MarketOverviewError as e:
|
||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||
return MarketOverviewResponse(**data)
|
||
|
||
|
||
@router.post("/backtest", response_model=BacktestResponse)
|
||
async def backtest(
|
||
req: BacktestRequest,
|
||
session: AsyncSession = Depends(get_session),
|
||
) -> BacktestResponse:
|
||
# 真实数据：本地无缓存则先拉取
|
||
if not await fetcher.is_cached(session, req.symbol):
|
||
try:
|
||
await fetcher.sync_symbol(session, req.symbol, source="auto")
|
||
except Exception as e: # noqa: BLE001
|
||
raise HTTPException(status_code=502, detail=f"数据拉取失败: {e}")
|
||
|
||
# 日线为基底，聚合到请求周期
|
||
rows = await repository.get_candles(
|
||
session, req.symbol, "1d", start=req.start, end=req.end, limit=100000
|
||
)
|
||
if not rows:
|
||
raise HTTPException(status_code=404, detail=f"无数据: symbol={req.symbol}")
|
||
|
||
bars = resample_bars(_rows_to_bars(rows), req.timeframe)
|
||
if len(bars) < 2:
|
||
raise HTTPException(status_code=400, detail=f"周期 {req.timeframe} 下数据不足，无法回测")
|
||
|
||
try:
|
||
strategy = build_strategy(req.strategy, req.params)
|
||
except Exception as e: # noqa: BLE001
|
||
raise HTTPException(status_code=400, detail=f"策略构建失败: {e}")
|
||
cfg = BacktestConfig(
|
||
initial_cash=req.initial_cash,
|
||
fast_mode=req.fast_mode,
|
||
bars_per_year=bars_per_year(req.timeframe),
|
||
)
|
||
result = run_backtest(bars, strategy, cfg)
|
||
|
||
df: pd.DataFrame = result["df"]
|
||
m = result["metrics"]
|
||
|
||
# 记录到回测运行注册表（可复现/可审计的基础）
|
||
session.add(
|
||
BacktestRun(
|
||
symbol=req.symbol,
|
||
strategy=req.strategy,
|
||
timeframe=req.timeframe,
|
||
params_json=json.dumps(req.params, ensure_ascii=False),
|
||
initial_cash=req.initial_cash,
|
||
total_return=m["total_return"],
|
||
max_drawdown=m["max_drawdown"],
|
||
sharpe=m["sharpe"],
|
||
num_trades=m["num_trades"],
|
||
)
|
||
)
|
||
await session.commit()
|
||
|
||
candles = [
|
||
CandleOut(ts=r["ts"], open=r["open"], high=r["high"], low=r["low"],
|
||
close=r["close"], volume=r["volume"],
|
||
amount=r["amount"] if "amount" in df.columns else None,
|
||
turnover=r["turnover"] if "turnover" in df.columns else None)
|
||
for _, r in df.iterrows()
|
||
]
|
||
signals = [
|
||
SignalOut(ts=f.ts, side=f.side.value, price=f.price, qty=f.qty)
|
||
for f in result["fills"]
|
||
]
|
||
indicators = IndicatorOut(
|
||
strategy=req.strategy,
|
||
data={col: _series_to_jsonable(df[col]) for col in result["indicator_cols"]},
|
||
)
|
||
equity = [EquityPoint(ts=t.to_pydatetime(), value=float(v))
|
||
for t, v in result["equity"].items()]
|
||
|
||
return BacktestResponse(
|
||
symbol=req.symbol,
|
||
timeframe=req.timeframe,
|
||
strategy=req.strategy,
|
||
candles=candles,
|
||
indicators=indicators,
|
||
signals=signals,
|
||
equity=equity,
|
||
metrics=MetricsOut(**m),
|
||
final_cash=result["final_cash"],
|
||
final_position=result["final_position"],
|
||
initial_cash=req.initial_cash,
|
||
)
|
||
|
||
|
||
@router.post("/backtest/event", response_model=EventBacktestResponse)
|
||
async def backtest_event(
|
||
req: EventBacktestRequest,
|
||
session: AsyncSession = Depends(get_session),
|
||
) -> EventBacktestResponse:
|
||
"""自然语言事件回测：入场条件命中 -> 次日买入 -> 持有 N 日，单股或全市场汇总统计。
|
||
直传 spec 则跳过 LLM（前端调参重跑）。"""
|
||
try:
|
||
spec = req.spec or await parse_event_spec(req.text)
|
||
result = await run_event_backtest(
|
||
session, spec,
|
||
ts_code=req.ts_code,
|
||
start=req.start.date() if req.start else None,
|
||
end=req.end.date() if req.end else None,
|
||
)
|
||
except ScreenerError as e:
|
||
raise HTTPException(status_code=502, detail=str(e))
|
||
except EventEngineError as e:
|
||
raise HTTPException(status_code=400, detail=str(e))
|
||
except Exception as e: # noqa: BLE001
|
||
raise HTTPException(status_code=500, detail=f"事件回测失败: {e}")
|
||
return EventBacktestResponse(
|
||
text=req.text,
|
||
spec=result["spec"],
|
||
universe=result["universe"],
|
||
start=result["start"],
|
||
end=result["end"],
|
||
stats=result["stats"],
|
||
trades=result["trades"],
|
||
total=result["total"],
|
||
)
|
||
|
||
|
||
# ---------- 智能选股 ----------
|
||
@router.post("/screener/run", response_model=ScreenerRunResponse)
|
||
async def screener_run(
|
||
req: ScreenerRunRequest,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> ScreenerRunResponse:
|
||
"""自然语言 -> LLM 解析条件 -> 全市场筛选。也可直传 conditions 跳过 LLM（微调再跑）。
|
||
成功的提问（含解析出的条件与命中数）记录到 screener_queries，供历史一键重跑。"""
|
||
try:
|
||
conds = req.conditions or await parse_conditions(req.text)
|
||
if not conds.indicator and not conds.snapshot:
|
||
raise HTTPException(status_code=400, detail="AI 未从描述中解析出任何筛选条件，请换种说法")
|
||
result = await engine.run_screen(session, conds, settings.screener_default_limit)
|
||
# 相同文本 + 相同条件的上一条不重复记录（一键重跑场景）
|
||
exists = (
|
||
await session.execute(
|
||
select(ScreenerQuery.id).where(
|
||
ScreenerQuery.user_id == user.id,
|
||
ScreenerQuery.text == req.text.strip(),
|
||
ScreenerQuery.conditions_json == json.dumps(conds.model_dump(), ensure_ascii=False),
|
||
)
|
||
)
|
||
).scalar_one_or_none()
|
||
if exists is None:
|
||
session.add(ScreenerQuery(
|
||
user_id=user.id,
|
||
text=req.text.strip(),
|
||
conditions_json=json.dumps(conds.model_dump(), ensure_ascii=False),
|
||
hit_count=result.get("total", 0),
|
||
))
|
||
await session.commit()
|
||
return ScreenerRunResponse(**result)
|
||
except HTTPException:
|
||
raise
|
||
except DataNotReadyError as e:
|
||
raise HTTPException(status_code=409, detail=str(e))
|
||
except ValueError as e: # 未知指标/字段、条件为空
|
||
raise HTTPException(status_code=400, detail=str(e))
|
||
except ScreenerError as e:
|
||
code = 503 if "未配置 LLM_API_KEY" in str(e) else 502
|
||
raise HTTPException(status_code=code, detail=str(e))
|
||
|
||
|
||
@router.get("/screener/queries", response_model=ScreenerQueryListResponse)
|
||
async def screener_queries(
|
||
limit: int = 20,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> ScreenerQueryListResponse:
|
||
"""当前用户的提问历史（最新在前，含解析出的条件与命中数，可一键重跑）。"""
|
||
limit = max(1, min(limit, 100))
|
||
rows = (
|
||
await session.execute(
|
||
select(ScreenerQuery)
|
||
.where(ScreenerQuery.user_id == user.id)
|
||
.order_by(ScreenerQuery.created_at.desc())
|
||
.limit(limit)
|
||
)
|
||
).scalars().all()
|
||
items = []
|
||
for r in rows:
|
||
conds = None
|
||
if r.conditions_json:
|
||
try:
|
||
from .schemas import ScreenConditions
|
||
conds = ScreenConditions.model_validate_json(r.conditions_json)
|
||
except Exception: # noqa: BLE001 —— 旧格式/解析失败则只展示文本
|
||
conds = None
|
||
items.append(ScreenerQueryOut(
|
||
id=r.id, text=r.text, conditions=conds, hit_count=r.hit_count, created_at=r.created_at
|
||
))
|
||
return ScreenerQueryListResponse(items=items)
|
||
|
||
|
||
@router.delete("/screener/queries/{query_id}", status_code=204)
|
||
async def screener_query_delete(
|
||
query_id: int,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> None:
|
||
await session.execute(
|
||
text("DELETE FROM screener_queries WHERE id = :i AND user_id = :u"),
|
||
{"i": query_id, "u": user.id},
|
||
)
|
||
await session.commit()
|
||
|
||
|
||
# ---------- 用户偏好 ----------
|
||
@router.get("/preferences", response_model=PreferencesOut)
|
||
async def get_preferences(
|
||
session: AsyncSession = Depends(get_session), user=Depends(require_user)
|
||
) -> PreferencesOut:
|
||
prefs: dict[str, object] = {}
|
||
rows = (
|
||
await session.execute(select(UserPreference).where(UserPreference.user_id == user.id))
|
||
).scalars().all()
|
||
for r in rows:
|
||
try:
|
||
prefs[r.key] = json.loads(r.value_json)
|
||
except Exception: # noqa: BLE001
|
||
prefs[r.key] = None
|
||
return PreferencesOut(prefs=prefs)
|
||
|
||
|
||
@router.put("/preferences", response_model=PreferencesOut)
|
||
async def put_preferences(
|
||
req: PreferencesUpdate,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> PreferencesOut:
|
||
"""部分更新：只覆盖出现的 key；值为 null 表示删除该 key。返回更新后的全量。"""
|
||
for key, value in req.prefs.items():
|
||
if not key or len(key) > 64:
|
||
continue
|
||
if value is None:
|
||
await session.execute(
|
||
text("DELETE FROM user_preferences WHERE user_id = :u AND key = :k"),
|
||
{"u": user.id, "k": key},
|
||
)
|
||
continue
|
||
existing = (
|
||
await session.execute(
|
||
select(UserPreference).where(
|
||
UserPreference.user_id == user.id, UserPreference.key == key
|
||
)
|
||
)
|
||
).scalars().first()
|
||
vj = json.dumps(value, ensure_ascii=False)
|
||
if existing:
|
||
existing.value_json = vj
|
||
else:
|
||
session.add(UserPreference(user_id=user.id, key=key, value_json=vj))
|
||
await session.commit()
|
||
return await get_preferences(session=session, user=user)
|
||
|
||
|
||
# ---------- 自选股 ----------
|
||
@router.get("/watchlist", response_model=list[str])
|
||
async def get_watchlist(
|
||
session: AsyncSession = Depends(get_session), user=Depends(require_user)
|
||
) -> list[str]:
|
||
"""当前用户自选股 ts_code 列表（加入时间倒序）。"""
|
||
rows = (
|
||
await session.execute(
|
||
select(WatchlistItem.ts_code)
|
||
.where(WatchlistItem.user_id == user.id)
|
||
.order_by(WatchlistItem.created_at.desc(), WatchlistItem.id.desc())
|
||
)
|
||
).scalars().all()
|
||
return list(rows)
|
||
|
||
|
||
@router.post("/watchlist", response_model=list[str])
|
||
async def add_watchlist(
|
||
req: WatchlistOp,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> list[str]:
|
||
exists = (
|
||
await session.execute(
|
||
select(WatchlistItem.id).where(
|
||
WatchlistItem.user_id == user.id, WatchlistItem.ts_code == req.ts_code
|
||
)
|
||
)
|
||
).scalar_one_or_none()
|
||
if exists is None:
|
||
session.add(WatchlistItem(user_id=user.id, ts_code=req.ts_code))
|
||
await session.commit()
|
||
await cache.bump_version(f"watchlist:{user.id}") # 作废该用户的股票列表缓存
|
||
return await get_watchlist(session=session, user=user)
|
||
|
||
|
||
@router.delete("/watchlist/{ts_code}", response_model=list[str])
|
||
async def remove_watchlist(
|
||
ts_code: str,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> list[str]:
|
||
await session.execute(
|
||
text("DELETE FROM watchlist_items WHERE user_id = :u AND ts_code = :c"),
|
||
{"u": user.id, "c": ts_code},
|
||
)
|
||
await session.commit()
|
||
await cache.bump_version(f"watchlist:{user.id}") # 作废该用户的股票列表缓存
|
||
return await get_watchlist(session=session, user=user)
|
||
|
||
|
||
# ---------- 交割单（个人实盘买卖点） ----------
|
||
def _trade_out(r: UserTrade) -> UserTradeOut:
|
||
return UserTradeOut(
|
||
id=r.id, ts_code=r.ts_code, name=r.name, trade_date=r.trade_date,
|
||
direction=r.direction, price=r.price, qty=r.qty, amount=r.amount, fee=r.fee,
|
||
)
|
||
|
||
|
||
@router.get("/trades", response_model=list[UserTradeOut])
|
||
async def list_trades(
|
||
ts_code: str | None = None,
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> list[UserTradeOut]:
|
||
"""当前用户导入的实盘成交（可选 ts_code 过滤，按日期升序；K线买卖点数据源）。"""
|
||
q = (
|
||
select(UserTrade)
|
||
.where(UserTrade.user_id == user.id)
|
||
.order_by(UserTrade.trade_date, UserTrade.id)
|
||
)
|
||
if ts_code:
|
||
q = q.where(UserTrade.ts_code == ts_code)
|
||
rows = (await session.execute(q)).scalars().all()
|
||
return [_trade_out(r) for r in rows]
|
||
|
||
|
||
@router.post("/trades/import", response_model=TradesImportResponse)
|
||
async def import_trades(
|
||
file: UploadFile = File(...),
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> TradesImportResponse:
|
||
"""上传券商交割单（CSV/Excel/HTML 表格均可，自动识别列名），解析出买卖成交入库。
|
||
|
||
同一笔成交（同日同股同向同价同量）重复上传会跳过，重复导出幂等。
|
||
"""
|
||
data = await file.read()
|
||
if not data:
|
||
raise HTTPException(status_code=422, detail="文件是空的")
|
||
if len(data) > 20 * 1024 * 1024:
|
||
raise HTTPException(status_code=413, detail="文件超过 20MB，请分时间段导出")
|
||
|
||
parsed = parse_statement(data, file.filename or "")
|
||
|
||
# 无证券代码列的导出（招商式）：按证券名称反查 stock_basic 补 ts_code；同名多码或查不到则弃行
|
||
unnamed = {t.name for t in parsed.trades if not t.ts_code and t.name}
|
||
if unnamed:
|
||
name_map: dict[str, str] = {}
|
||
for ts_code, name in (await session.execute(
|
||
select(StockBasic.ts_code, StockBasic.name).where(StockBasic.name.in_(unnamed))
|
||
)).all():
|
||
name_map[name] = "" if name in name_map else ts_code
|
||
for t in parsed.trades:
|
||
if not t.ts_code and t.name:
|
||
tc = name_map.get(t.name, "")
|
||
if tc:
|
||
t.ts_code, t.code = tc, tc.split(".")[0]
|
||
else:
|
||
parsed.skipped_bad.append(f"{t.trade_date} {t.name} 名称无法唯一对应代码，未入库")
|
||
|
||
def _key(t) -> tuple:
|
||
return (t.trade_date, t.ts_code, t.direction, None if t.price is None else round(t.price, 4), round(t.qty, 4))
|
||
|
||
# Python 侧去重兜底（唯一约束对 NULL price 不生效）
|
||
existing = {
|
||
(r.trade_date, r.ts_code, r.direction, None if r.price is None else round(r.price, 4), round(r.qty, 4))
|
||
for r in (
|
||
await session.execute(
|
||
select(UserTrade.trade_date, UserTrade.ts_code, UserTrade.direction, UserTrade.price, UserTrade.qty)
|
||
.where(UserTrade.user_id == user.id, UserTrade.ts_code.in_({t.ts_code for t in parsed.trades}))
|
||
)
|
||
).all()
|
||
}
|
||
inserted: list[UserTrade] = []
|
||
seen: set[tuple] = set()
|
||
skipped_dup = 0
|
||
for t in parsed.trades:
|
||
if not t.ts_code:
|
||
continue # 名称反查失败的行，已在 bad 里说明
|
||
k = _key(t)
|
||
if k in existing or k in seen:
|
||
skipped_dup += 1
|
||
continue
|
||
seen.add(k)
|
||
inserted.append(UserTrade(
|
||
user_id=user.id, ts_code=t.ts_code, code=t.code, name=t.name or None,
|
||
trade_date=t.trade_date, direction=t.direction, price=t.price,
|
||
qty=t.qty, amount=t.amount, fee=t.fee,
|
||
raw_json=json.dumps(t.raw, ensure_ascii=False, default=str),
|
||
))
|
||
if inserted:
|
||
session.add_all(inserted)
|
||
await session.commit()
|
||
|
||
return TradesImportResponse(
|
||
inserted=len(inserted),
|
||
skipped_dup=skipped_dup,
|
||
skipped_other=parsed.skipped_other,
|
||
stocks=len({t.ts_code for t in parsed.trades}),
|
||
bad=parsed.skipped_bad[:5],
|
||
sample=[_trade_out(r) for r in inserted[:5]],
|
||
)
|
||
|
||
|
||
@router.delete("/trades", response_model=TradesClearResponse)
|
||
async def clear_trades(
|
||
session: AsyncSession = Depends(get_session),
|
||
user=Depends(require_user),
|
||
) -> TradesClearResponse:
|
||
"""清空当前用户导入的全部成交（重新导入前用）。"""
|
||
res = await session.execute(delete(UserTrade).where(UserTrade.user_id == user.id))
|
||
await session.commit()
|
||
return TradesClearResponse(deleted=res.rowcount or 0)
|
||
|
||
|
||
@router.post("/screener/sync", response_model=ScreenerSyncStatus)
|
||
async def screener_sync_start(
|
||
req: ScreenerSyncRequest, session: AsyncSession = Depends(get_session)
|
||
) -> ScreenerSyncStatus:
|
||
"""启动全市场数据同步（后台任务，立即返回状态）。"""
|
||
try:
|
||
await market_sync.start_sync(session, req.days, req.force)
|
||
except ScreenerError as e:
|
||
raise HTTPException(status_code=503, detail=str(e))
|
||
status = await market_sync.get_sync_status(session)
|
||
return ScreenerSyncStatus(**{k: status.get(k) for k in ScreenerSyncStatus.model_fields})
|
||
|
||
|
||
@router.get("/screener/sync/status", response_model=ScreenerSyncStatus)
|
||
async def screener_sync_status(session: AsyncSession = Depends(get_session)) -> ScreenerSyncStatus:
|
||
"""同步任务状态 + 数据实况（最新交易日/行数/ready）。"""
|
||
status = await market_sync.get_sync_status(session)
|
||
return ScreenerSyncStatus(**{k: status.get(k) for k in ScreenerSyncStatus.model_fields})
|
||
|
||
|
||
@router.get("/screener/preview/{ts_code}", response_model=PreviewResponse)
|
||
async def screener_preview(
|
||
ts_code: str, limit: int = 500, adjust: str = "qfq", timeframe: str = "1d", mas: str = "5,10,20,60",
|
||
zx: str = "10,20,30,60", end: str | None = None,
|
||
session: AsyncSession = Depends(get_session),
|
||
) -> PreviewResponse:
|
||
"""个股详情预览：日线（candles 不复权底座 + adj_factor 本地换算 bfq/qfq/hfq，
|
||
未缓存自动拉取，落后全市场最新交易日则强制刷新）+ 全套指标 + 最新截面信息卡。
|
||
timeframe 聚合到周/月/年（先复权再聚合）；mas 指定主图 MA 周期（逗号分隔）。
|
||
end=YYYY-MM-DD 时为「向前翻页」：返回该日之前最近 limit 根（含预热计算指标），
|
||
has_more 标记窗口前是否还有更早历史，前端据此继续向左滚动加载。"""
|
||
if adjust not in _ADJUST_MODES:
|
||
raise HTTPException(status_code=400, detail=f"adjust 仅支持 {'/'.join(_ADJUST_MODES)}")
|
||
if timeframe not in ("1d", "1w", "1M", "1y"):
|
||
raise HTTPException(status_code=400, detail="timeframe 仅支持 1d/1w/1M/1y")
|
||
try:
|
||
ma_periods = sorted({int(p) for p in mas.split(",") if p.strip().isdigit() and 1 <= int(p) <= 500})
|
||
except ValueError:
|
||
raise HTTPException(status_code=400, detail="mas 格式应为逗号分隔的数字，如 5,10,20,60")
|
||
if not ma_periods:
|
||
ma_periods = [5, 10, 20, 60]
|
||
try:
|
||
zx_periods = sorted({int(p) for p in zx.split(",") if p.strip().isdigit() and 1 <= int(p) <= 500})
|
||
except ValueError:
|
||
raise HTTPException(status_code=400, detail="zx 格式应为逗号分隔的数字，如 10,20,30,60")
|
||
if not zx_periods:
|
||
zx_periods = [10, 20, 30, 60]
|
||
limit = max(30, min(limit, 5000))
|
||
end_dt: datetime | None = None
|
||
if end:
|
||
try:
|
||
end_dt = datetime.strptime(end.strip()[:10], "%Y-%m-%d")
|
||
except ValueError:
|
||
raise HTTPException(status_code=400, detail="end 格式应为 YYYY-MM-DD")
|
||
symbol = plain_code(ts_code)
|
||
|
||
# --- Redis 读缓存：历史窗口（end 翻页）只增不改，最新窗口每日由全市场同步推进；
|
||
# 键含 ver:candles 版本号（同步完成后自增，旧缓存全部失效），TTL 兜底（cache.py）
|
||
# 注：ma_periods 不参与缓存键 —— 前端已改为本地计算 MA，后端始终返回全量 MA 集合
|
||
cache_key = cache.digest(
|
||
"preview", ts_code, timeframe, limit, adjust,
|
||
end_dt.strftime("%Y-%m-%d") if end_dt else None,
|
||
await cache.get_version("candles"),
|
||
)
|
||
cached = await cache.cache_get(f"pv:{cache_key}")
|
||
if cached is not None:
|
||
return PreviewResponse.model_validate(cached)
|
||
|
||
# --- 日线：candles(全量不复权底座)；未缓存拉取，落后于全市场最新交易日则强制刷新 ---
|
||
# fetcher 只做「不复权」增量 upsert，底座口径恒为 bfq（TDX 全量 + Tushare 增量），
|
||
# 复权（qfq/hfq）读取时按 adj_factor 表本地换算。
|
||
# 每次只取「窗口 + 400 根预热」行（MA250/MACD EMA 在 400 根内充分收敛），不拉全量：
|
||
# 首屏 ~500 根秒开，向左滚动时按 end 参数逐页向前翻。
|
||
global_latest = await session.scalar(
|
||
select(func.max(Candle.ts)).where(Candle.timeframe == "1d")
|
||
)
|
||
frame_mult = {"1d": 1, "1w": 6, "1M": 24, "1y": 280}[timeframe]
|
||
fetch_n = min(100000, limit * frame_mult + 400)
|
||
source = "bfq"
|
||
mode = "bfq"
|
||
if end_dt is not None:
|
||
# 向前翻页：取 end 之前的历史窗口，不触发同步（历史浏览）
|
||
rows = await repository.get_candles_before(session, symbol, "1d", before=end_dt, limit=fetch_n)
|
||
else:
|
||
# 注意取「最新 fetch_n 根」而非最旧：get_candles 是 asc+limit（取最旧），窗口化后首屏会停在过期日期
|
||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
|
||
try:
|
||
if not rows:
|
||
await fetcher.sync_symbol(session, symbol, source="auto")
|
||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
|
||
elif global_latest is not None and rows[-1].ts.date() < global_latest.date():
|
||
await fetcher.sync_symbol(session, symbol, source="auto", force=True)
|
||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
|
||
except Exception: # noqa: BLE001 —— tushare/写库失败时回滚会话（否则毒化后兜底查询 500）
|
||
await session.rollback()
|
||
if not rows:
|
||
rows = []
|
||
bars = _rows_to_bars(rows)
|
||
|
||
if not bars and end_dt is None:
|
||
raise HTTPException(status_code=404, detail=f"无数据: {ts_code}（可先点「同步市场数据」）")
|
||
# 信息卡取未聚合的日线最新 bar（聚合后 ts 是周期起点，不适用于「最新交易日」）
|
||
last_daily = bars[-1] if bars else None
|
||
prev_daily = bars[-2] if len(bars) > 1 else None
|
||
# 翻页到底（end 之前无数据）：返回空页 + has_more=False，前端停止向前翻页
|
||
|
||
# --- 复权换算：请求模式与底座模式不同时按 adj_factor 本地换算（无因子则维持原样） ---
|
||
# 只取窗口内因子（qfq 归一还需全局最新因子，追加到最后一行即可，_adjust_bars 取 f_latest=末项）
|
||
if adjust != mode and bars:
|
||
fq = select(AdjFactor).where(AdjFactor.ts_code == ts_code)
|
||
window_end = end_dt if end_dt is not None else bars[-1].ts
|
||
if window_end is not None:
|
||
fq = fq.where(AdjFactor.trade_date <= window_end)
|
||
factors = list((await session.execute(fq.order_by(AdjFactor.trade_date))).scalars().all())
|
||
if factors:
|
||
latest_f = (
|
||
await session.execute(
|
||
select(AdjFactor).where(AdjFactor.ts_code == ts_code)
|
||
.order_by(AdjFactor.trade_date.desc()).limit(1)
|
||
)
|
||
).scalars().first()
|
||
if latest_f is not None:
|
||
factors.append(latest_f)
|
||
bars = _adjust_bars(bars, factors, mode, adjust)
|
||
mode = adjust
|
||
source = adjust
|
||
|
||
# --- 周期聚合：复权之后按日历聚合到周/月/年，指标在聚合后的序列上计算 ---
|
||
bars = resample_bars(bars, timeframe)
|
||
|
||
# --- 指标（在预热窗口上计算后截尾，保证预热正确；翻页到底的空页跳过） ---
|
||
has_more = len(bars) > limit # 返回窗口之前还有更早历史（含预热行）
|
||
indicators: dict[str, dict[str, list[float | None]]] = {}
|
||
if bars:
|
||
df = pd.DataFrame({"close": [b.close for b in bars], "high": [b.high for b in bars], "low": [b.low for b in bars]})
|
||
closes, highs, lows = df["close"], df["high"], df["low"]
|
||
macd = ind.macd(closes)
|
||
kdj = ind.kdj(highs, lows, closes)
|
||
boll = ind.bollinger(closes)
|
||
indicators = {
|
||
# MA 始终返回全量集合（前端本地计算 MA，此处仅保留兼容；缓存键不依赖 ma_periods）
|
||
"ma": {f"ma{p}": _series_to_jsonable(ind.ma(closes, p)) for p in _FULL_MA_SET},
|
||
"macd": {
|
||
"dif": _series_to_jsonable(macd["macd"]),
|
||
"dea": _series_to_jsonable(macd["signal"]),
|
||
"hist": _series_to_jsonable(macd["hist"]),
|
||
},
|
||
"kdj": {k: _series_to_jsonable(kdj[k]) for k in ("k", "d", "j")},
|
||
"rsi": {
|
||
"rsi6": _series_to_jsonable(ind.rsi(closes, 6)),
|
||
"rsi12": _series_to_jsonable(ind.rsi(closes, 12)),
|
||
"rsi24": _series_to_jsonable(ind.rsi(closes, 24)),
|
||
},
|
||
"boll": {k: _series_to_jsonable(boll[k]) for k in ("upper", "mid", "lower")},
|
||
"zx": {
|
||
"short": _series_to_jsonable(ind.ema2(closes)),
|
||
"duokong": _series_to_jsonable(ind.avg_ma(closes, tuple(zx_periods))),
|
||
},
|
||
}
|
||
limit = max(30, min(limit, len(bars)))
|
||
for group in indicators.values():
|
||
for key in group:
|
||
group[key] = group[key][-limit:]
|
||
|
||
# --- 信息卡：stock_basic + candles 最新日线 bar + 与其对齐的快照（避免混用不同交易日） ---
|
||
sb = (await session.execute(select(StockBasic).where(StockBasic.ts_code == ts_code))).scalars().first()
|
||
ds = None
|
||
if last_daily is not None:
|
||
# 优先取与行情同日的快照；缺当日快照时退最新（字段可能与行情差日期，罕见）
|
||
ds = (
|
||
await session.execute(
|
||
select(DailySnapshot).where(
|
||
DailySnapshot.ts_code == ts_code, DailySnapshot.trade_date == last_daily.ts
|
||
)
|
||
)
|
||
).scalars().first()
|
||
if ds is None:
|
||
ds = (
|
||
await session.execute(
|
||
select(DailySnapshot).where(DailySnapshot.ts_code == ts_code).order_by(DailySnapshot.trade_date.desc()).limit(1)
|
||
)
|
||
).scalars().first()
|
||
|
||
def _yi(v) -> float | None:
|
||
if v is None:
|
||
return None
|
||
v = float(v)
|
||
return None if v != v else round(v / 1e4, 2) # 万元 -> 亿元
|
||
|
||
info = PreviewInfoOut(
|
||
ts_code=ts_code,
|
||
symbol=symbol,
|
||
name=sb.name if sb else ts_code,
|
||
industry=sb.industry if sb else None,
|
||
area=sb.area if sb else None,
|
||
market=sb.market if sb else None,
|
||
list_date=sb.list_date if sb else None,
|
||
trade_date=last_daily.ts if last_daily else None,
|
||
open=last_daily.open if last_daily else None,
|
||
high=last_daily.high if last_daily else None,
|
||
low=last_daily.low if last_daily else None,
|
||
close=last_daily.close if last_daily else None,
|
||
pre_close=prev_daily.close if prev_daily else None,
|
||
pct_chg=((last_daily.close / prev_daily.close - 1) * 100)
|
||
if last_daily and prev_daily and prev_daily.close else None,
|
||
volume_hand=round(last_daily.volume / 100, 0) if last_daily else None, # 股 -> 手
|
||
amount_yi=round(last_daily.amount / 1e8, 2) if last_daily and last_daily.amount else None, # 元 -> 亿元
|
||
turnover_rate=ds.turnover_rate if ds else None,
|
||
pe_ttm=ds.pe_ttm if ds else None,
|
||
pb=ds.pb if ds else None,
|
||
total_mv=_yi(ds.total_mv) if ds else None,
|
||
circ_mv=_yi(ds.circ_mv) if ds else None,
|
||
)
|
||
|
||
candles = [
|
||
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close,
|
||
volume=b.volume, amount=b.amount, turnover=b.turnover)
|
||
for b in bars[-limit:]
|
||
]
|
||
resp = PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info,
|
||
candles=candles, indicators=indicators, has_more=has_more)
|
||
await cache.cache_set(f"pv:{cache_key}", resp.model_dump(mode="json"), ttl=600)
|
||
return resp
|