From c1c43d2ff7531d08cc8f117234d03c99326c9c82 Mon Sep 17 00:00:00 2001 From: cirry <812852553@qq.com> Date: Sat, 15 Aug 2026 08:57:15 +0800 Subject: [PATCH] =?UTF-8?q?=E5=8A=9F=E8=83=BD=E6=9B=B4=E6=96=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/.env.example | 2 +- backend/app/api.py | 417 +++++++++++++++++- backend/app/data/fetcher.py | 2 +- backend/app/data/synthetic.py | 78 ---- backend/app/data/tushare_provider.py | 2 +- backend/app/main.py | 2 +- backend/app/models.py | 61 ++- backend/app/schemas.py | 124 +++++- backend/app/screener/llm.py | 68 ++- backend/app/screener/market_sync.py | 24 +- backend/smoke_test.py | 2 +- frontend/index.html | 2 +- frontend/src/App.vue | 45 +- frontend/src/api/client.ts | 121 ++++- frontend/src/api/types.ts | 113 ++++- frontend/src/components/BacktestForm.vue | 123 ------ frontend/src/components/DetailKLine.vue | 288 +++++++++--- frontend/src/components/EquityChart.vue | 63 --- frontend/src/components/KLineChart.vue | 319 -------------- frontend/src/components/MetricsPanel.vue | 39 -- frontend/src/components/ScreenerForm.vue | 102 ++++- frontend/src/components/ScreenerTable.vue | 8 +- .../src/components/StockDetailOverlay.vue | 335 +++++++++++--- frontend/src/router.ts | 1 + frontend/src/stores/auth.ts | 3 + frontend/src/stores/backtest.ts | 43 -- frontend/src/stores/screener.ts | 10 +- frontend/src/views/BacktestView.vue | 361 +++++++++++++-- frontend/src/views/HomeView.vue | 35 +- frontend/src/views/ScreenerView.vue | 3 +- 30 files changed, 1908 insertions(+), 888 deletions(-) delete mode 100644 backend/app/data/synthetic.py delete mode 100644 frontend/src/components/BacktestForm.vue delete mode 100644 frontend/src/components/EquityChart.vue delete mode 100644 frontend/src/components/KLineChart.vue delete mode 100644 frontend/src/components/MetricsPanel.vue delete mode 100644 frontend/src/stores/backtest.ts diff --git a/backend/.env.example b/backend/.env.example index 2fbbddd..c2d017b 100644 --- a/backend/.env.example +++ b/backend/.env.example @@ -12,7 +12,7 @@ CORS_ORIGINS=http://localhost:5173 # 生产建议 false，关闭 /docs 与 /openapi.json。 EXPOSE_API_DOCS=true -# ---- 真实数据源（Tushare Pro；免费版即可。留空则仅 DEMO 合成数据可用）---- +# ---- 真实数据源（Tushare Pro；免费版即可）---- TUSHARE_TOKEN=你的token DATA_ADJUST=qfq # 复权：qfq 前复权 / hfq 后复权 / 留空不复权 DATA_DEFAULT_START=20200101 diff --git a/backend/app/api.py b/backend/app/api.py index d6e8bfa..848abd1 100644 --- a/backend/app/api.py +++ b/backend/app/api.py @@ -2,6 +2,7 @@ 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） 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） @@ -9,45 +10,66 @@ """ from __future__ import annotations +import bisect import json import pandas as pd from fastapi import APIRouter, Depends, HTTPException -from sqlalchemy import select +from sqlalchemy import select, text from sqlalchemy.ext.asyncio import AsyncSession from .backtest.engine import BacktestConfig, run_backtest 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.symbols import plain_code -from .data.synthetic import seed_if_empty from .db import get_session from .domain import Bar from . import indicators as ind -from .models import BacktestRun, DailySnapshot, MarketDaily, StockBasic +from .models import ( + AdjFactor, + BacktestRun, + DailySnapshot, + MarketDaily, + ScreenerQuery, + StockBasic, + UserPreference, + WatchlistItem, +) from .schemas import ( BacktestRequest, BacktestResponse, CandleOut, EquityPoint, + EventBacktestRequest, + EventBacktestResponse, IndicatorOut, MetricsOut, + PreferencesOut, + PreferencesUpdate, PreviewInfoOut, PreviewResponse, + ScreenerQueryListResponse, + ScreenerQueryOut, ScreenerRunRequest, ScreenerRunResponse, ScreenerSyncRequest, ScreenerSyncStatus, SignalOut, + StockListItemOut, + StockListResponse, + StockFacetsResponse, + FacetItemOut, SyncRequest, SyncResponse, + WatchlistOp, ) from .screener import engine, market_sync from .screener.engine import DataNotReadyError -from .screener.llm import ScreenerError, parse_conditions +from .screener.llm import ScreenerError, parse_conditions, parse_event_spec router = APIRouter(prefix="/api", dependencies=[Depends(require_user)]) @@ -67,6 +89,41 @@ 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) for r in rows] +_ADJUST_MODES = ("bfq", "qfq", "hfq") + + +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, + )) + return out + + @router.get("/candles/{symbol}", response_model=list[CandleOut]) async def get_candles( symbol: str, @@ -74,7 +131,6 @@ async def get_candles( limit: int = 5000, session: AsyncSession = Depends(get_session), ) -> list[CandleOut]: - await seed_if_empty(session, symbol="DEMO") # 始终以日线为基底，再聚合到目标周期 rows = await repository.get_candles(session, symbol, "1d", limit=limit) bars = resample_bars(_rows_to_bars(rows), timeframe) @@ -93,15 +149,114 @@ async def sync_data(req: SyncRequest, session: AsyncSession = Depends(get_sessio raise HTTPException(status_code=502, detail=str(e)) +# ---------- 股票列表（全市场浏览） ---------- +_STOCKS_SQL = text(""" + SELECT sb.ts_code, sb.symbol, sb.name, sb.industry, sb.market, + c.close AS close, p.close AS prev_close, c.ts AS last_ts, cnt.n AS bar_count, + CASE WHEN c.close IS NOT NULL AND p.close IS NOT NULL AND p.close <> 0 + THEN round(((c.close / p.close - 1) * 100)::numeric, 2) END AS pct_chg, + (w.id IS NOT NULL) AS watched + FROM stock_basic sb + LEFT JOIN LATERAL ( + SELECT close, ts FROM candles + WHERE symbol = sb.symbol AND timeframe = '1d' + ORDER BY ts DESC LIMIT 1 + ) c ON true + LEFT JOIN LATERAL ( + SELECT close FROM candles + WHERE symbol = sb.symbol AND timeframe = '1d' AND ts < c.ts + ORDER BY ts DESC LIMIT 1 + ) p ON c.ts IS NOT NULL + LEFT JOIN LATERAL ( + SELECT count(*) AS n FROM candles + WHERE symbol = sb.symbol AND timeframe = '1d' + ) cnt ON true + 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) + ORDER BY w.id DESC NULLS LAST, sb.symbol + LIMIT :limit OFFSET :offset +""") + +_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, + 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（本地缓存，无缓存则行情列为空）。 + 自选股（watchlist_items）排最前；watched_only=true 只看自选。""" + search = search.strip() + limit = max(1, min(limit, 500)) + offset = max(0, offset) + 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, params)).mappings().all() + return StockListResponse(total=total, items=[StockListItemOut(**r) for r in rows]) + + +@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）。""" + 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() + return 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], + ) + + @router.post("/backtest", response_model=BacktestResponse) async def backtest( req: BacktestRequest, session: AsyncSession = Depends(get_session), ) -> BacktestResponse: - await seed_if_empty(session, symbol="DEMO") - - # 非演示标的：首次自动拉取真实数据并缓存 - if req.symbol != "DEMO" and not await fetcher.is_cached(session, req.symbol): + # 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 @@ -179,17 +334,71 @@ async def backtest( ) +@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) + 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）。""" + """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 @@ -202,6 +411,148 @@ async def screener_run( 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() + 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() + return await get_watchlist(session=session, user=user) + + @router.post("/screener/sync", response_model=ScreenerSyncStatus) async def screener_sync_start( req: ScreenerSyncRequest, session: AsyncSession = Depends(get_session) @@ -224,10 +575,22 @@ async def screener_sync_status(session: AsyncSession = Depends(get_session)) -> @router.get("/screener/preview/{ts_code}", response_model=PreviewResponse) async def screener_preview( - ts_code: str, limit: int = 260, session: AsyncSession = Depends(get_session) + ts_code: str, limit: int = 500, adjust: str = "qfq", timeframe: str = "1d", mas: str = "5,10,20,60", + session: AsyncSession = Depends(get_session), ) -> PreviewResponse: - """个股详情预览：日线（qfq 全量缓存，未缓存/过期自动拉取，失败退 market_daily 近段） - + 全套指标（indicators.py 单一事实源）+ 最新截面信息卡。""" + """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，失败退 market_daily 近段）+ 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）。""" + 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] symbol = plain_code(ts_code) # 先取 market_daily 最新行：既做缓存过期判断，也做信息卡数据源 @@ -237,16 +600,20 @@ async def screener_preview( ) ).scalars().first() - # --- 日线：candles(qfq 全量) 优先；未缓存拉取，缓存落后于全市场最新交易日则强制刷新（每日至多一次） --- + # --- 日线：candles(不复权底座) 优先；未缓存拉取，缓存落后于全市场最新交易日则强制刷新（每日至多一次） --- + # fetcher 增量拉取写入的是 qfq（settings.data_adjust），此时底座模式记为 qfq。 rows = await repository.get_candles(session, symbol, "1d", limit=100000) - source = "qfq" + source = "bfq" + mode = "bfq" try: if not rows: await fetcher.sync_symbol(session, symbol, source="auto") rows = await repository.get_candles(session, symbol, "1d", limit=100000) + mode = settings.data_adjust if settings.data_adjust in _ADJUST_MODES else "qfq" elif md is not None and rows and rows[-1].ts.date() < md.trade_date.date(): await fetcher.sync_symbol(session, symbol, source="auto", force=True) rows = await repository.get_candles(session, symbol, "1d", limit=100000) + mode = settings.data_adjust if settings.data_adjust in _ADJUST_MODES else "qfq" 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: @@ -265,6 +632,22 @@ async def screener_preview( if not bars: raise HTTPException(status_code=404, detail=f"无数据: {ts_code}（可先点「同步市场数据」）") + # --- 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） --- + if adjust != mode: + factors = ( + await session.execute( + select(AdjFactor).where(AdjFactor.ts_code == ts_code).order_by(AdjFactor.trade_date) + ) + ).scalars().all() + if factors: + bars = _adjust_bars(bars, factors, mode, adjust) + mode = adjust + if source != "market": + 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（在全量历史上计算后截尾，保证预热正确） --- 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"] @@ -272,7 +655,7 @@ async def screener_preview( kdj = ind.kdj(highs, lows, closes) boll = ind.bollinger(closes) indicators: dict[str, dict[str, list[float | None]]] = { - "ma": {f"ma{p}": _series_to_jsonable(ind.ma(closes, p)) for p in (5, 10, 20, 60)}, + "ma": {f"ma{p}": _series_to_jsonable(ind.ma(closes, p)) for p in ma_periods}, "macd": { "dif": _series_to_jsonable(macd["macd"]), "dea": _series_to_jsonable(macd["signal"]), diff --git a/backend/app/data/fetcher.py b/backend/app/data/fetcher.py index 0d5b6cd..6295501 100644 --- a/backend/app/data/fetcher.py +++ b/backend/app/data/fetcher.py @@ -1,6 +1,6 @@ """数据编排：拉取（Tushare 主 -> AKShare 兜底）+ 本地缓存。 -真实行情落库到 candles 表（timeframe='1d'），回测统一从库读，与 DEMO 同路径。 +真实行情落库到 candles 表（timeframe='1d'），回测统一从库读。 """ from __future__ import annotations diff --git a/backend/app/data/synthetic.py b/backend/app/data/synthetic.py deleted file mode 100644 index d09a860..0000000 --- a/backend/app/data/synthetic.py +++ /dev/null @@ -1,78 +0,0 @@ -"""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() diff --git a/backend/app/data/tushare_provider.py b/backend/app/data/tushare_provider.py index c28d163..d807489 100644 --- a/backend/app/data/tushare_provider.py +++ b/backend/app/data/tushare_provider.py @@ -17,7 +17,7 @@ def _parse(date_str: str) -> datetime: def fetch_daily(code: str, start: str = "20200101", end: str | None = None, adjust: str = "qfq") -> list[Bar]: - import tushare as ts # 延迟导入：未装/无 token 时 DEMO 仍可用 + import tushare as ts # 延迟导入：未装或无 token 时该数据源不可用 if not settings.tushare_token: raise RuntimeError("未配置 TUSHARE_TOKEN") diff --git a/backend/app/main.py b/backend/app/main.py index e11ec3c..ddfd06d 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -21,7 +21,7 @@ async def lifespan(app: FastAPI): app = FastAPI( title="Stock Backtest", - description="历史回测 + 回放式模拟平台（A 股为主，不做实盘）", + description="股票研究平台：全市场数据 + 智能选股 + 事件回测（A 股为主，不做实盘）", version="0.1.0", lifespan=lifespan, docs_url="/docs" if settings.expose_api_docs else None, diff --git a/backend/app/models.py b/backend/app/models.py index 135c344..e0253b5 100644 --- a/backend/app/models.py +++ b/backend/app/models.py @@ -9,7 +9,7 @@ Candle 表设计与 TimescaleDB hypertable 完全兼容：将来在目标 PG 库 """ from datetime import datetime -from sqlalchemy import BigInteger, Boolean, DateTime, Float, ForeignKey, Integer, String, UniqueConstraint +from sqlalchemy import BigInteger, Boolean, DateTime, Float, ForeignKey, Integer, String, Text, UniqueConstraint from sqlalchemy.orm import Mapped, mapped_column, relationship from .db import Base @@ -124,6 +124,65 @@ class DailySnapshot(Base): ) +class AdjFactor(Base): + """复权因子（adj_factor，Tushare 原始值；qfq/hfq 本地换算的底座）。 + + 与 candles(不复权日线) 按 ts_code+trade_date 关联： + 前复权 qfq = 不复权价 × f(t) / f(latest)；后复权 hfq = 不复权价 × f(t)。 + """ + __tablename__ = "adj_factor" + + id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True) + trade_date: Mapped[datetime] = mapped_column(DateTime, index=True) + ts_code: Mapped[str] = mapped_column(String(12), index=True) + adj_factor: Mapped[float] = mapped_column(Float) + + __table_args__ = ( + UniqueConstraint("ts_code", "trade_date", name="uq_adj_code_date"), + ) + + +class UserPreference(Base): + """用户偏好键值对（配色/复权口径/MA 周期/副图布局等，value 存 JSON 字符串）。""" + __tablename__ = "user_preferences" + + id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True) + user_id: Mapped[int] = mapped_column(BigInteger, ForeignKey("users.id", ondelete="CASCADE"), index=True) + key: Mapped[str] = mapped_column(String(64)) + value_json: Mapped[str] = mapped_column(Text, default="null") + updated_at: Mapped[datetime] = mapped_column(DateTime, default=_utcnow, onupdate=_utcnow) + + __table_args__ = ( + UniqueConstraint("user_id", "key", name="uq_user_pref_key"), + ) + + +class WatchlistItem(Base): + """自选股（星标置顶）。""" + __tablename__ = "watchlist_items" + + id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True) + user_id: Mapped[int] = mapped_column(BigInteger, ForeignKey("users.id", ondelete="CASCADE"), index=True) + ts_code: Mapped[str] = mapped_column(String(12), index=True) + created_at: Mapped[datetime] = mapped_column(DateTime, default=_utcnow) + + __table_args__ = ( + UniqueConstraint("user_id", "ts_code", name="uq_watch_user_code"), + ) + + +class ScreenerQuery(Base): + """自然语言选股提问历史（文本 + 解析出的条件，便于一键重跑）。""" + __tablename__ = "screener_queries" + + id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True) + user_id: Mapped[int] = mapped_column(BigInteger, ForeignKey("users.id", ondelete="CASCADE"), index=True) + text: Mapped[str] = mapped_column(String(500)) + conditions_json: Mapped[str | None] = mapped_column(Text) + hit_count: Mapped[int | None] = mapped_column(Integer) + created_at: Mapped[datetime] = mapped_column(DateTime, default=_utcnow, index=True) + + class TradeCalendar(Base): """交易日历缓存（trade_cal 拉取一次宽范围后本地维护，低积分 token 限频 1 次/小时）。""" __tablename__ = "trade_calendar" diff --git a/backend/app/schemas.py b/backend/app/schemas.py index f5867dd..4c4b856 100644 --- a/backend/app/schemas.py +++ b/backend/app/schemas.py @@ -24,7 +24,7 @@ class CandleOut(BaseModel): # ---------- Backtest ---------- class BacktestRequest(BaseModel): - symbol: str = "DEMO" + symbol: str = "000001" timeframe: str = "1d" strategy: str = "macd_cross" # macd_cross | ma_cross | single_ma params: dict[str, float] = Field(default_factory=dict) # 各策略参数 @@ -82,6 +82,68 @@ class SyncRequest(BaseModel): force: bool = False # True => 忽略缓存重新拉取 +# ---------- Event Backtest（自然语言事件回测） ---------- +class EventBacktestSpec(BaseModel): + """事件回测参数：entry 条件在信号日 D 收盘确认 -> D+1 买入 -> 持有 N 日卖出。""" + entry: ScreenConditions + entry_timing: Literal["next_open", "next_close"] = "next_open" # 次日开盘/收盘买入 + holding_days: int = Field(default=3, ge=1, le=250) # 买入后再持有 N 个交易日 + exit_timing: Literal["close", "open"] = "close" # 到期按收盘/开盘卖出 + + +class EventBacktestRequest(BaseModel): + text: str = Field(min_length=2, max_length=500) + spec: EventBacktestSpec | None = None # 直传则跳过 LLM 解析（调参重跑） + ts_code: str | None = None # 指定则只回测该股；空则全市场 + start: datetime | None = None + end: datetime | None = None + + +class EventTradeOut(BaseModel): + ts_code: str + name: str | None = None + entry_date: datetime + entry_price: float + exit_date: datetime + exit_price: float + ret_pct: float # 区间收益率 %（复权校正） + + +class EventYearStatOut(BaseModel): + year: int + samples: int + mean_pct: float + median_pct: float + win_rate: float + + +class EventStatsOut(BaseModel): + samples: int + stocks: int + mean_pct: float + median_pct: float + win_rate: float # % + std_pct: float = 0.0 + p10_pct: float = 0.0 + p25_pct: float = 0.0 + p75_pct: float = 0.0 + p90_pct: float = 0.0 + max_pct: float = 0.0 + min_pct: float = 0.0 + by_year: list[EventYearStatOut] = Field(default_factory=list) + + +class EventBacktestResponse(BaseModel): + text: str + spec: EventBacktestSpec + universe: str # "all" 或 ts_code + start: datetime + end: datetime + stats: EventStatsOut + trades: list[EventTradeOut] = Field(default_factory=list) # 最好+最差样本（各 100） + total: int + + class SyncResponse(BaseModel): symbol: str bars: int @@ -197,7 +259,7 @@ class PreviewInfoOut(BaseModel): class PreviewResponse(BaseModel): ts_code: str symbol: str - source: str # qfq=回测缓存全量前复权 | market=近段未复权兜底 + source: str # bfq|qfq|hfq=实际复权口径（本地 adj_factor 换算） | market=近段未复权兜底 info: PreviewInfoOut candles: list[CandleOut] indicators: dict[str, dict[str, list[float | None]]] = Field(default_factory=dict) @@ -220,3 +282,61 @@ class CurrentUserOut(BaseModel): class LoginResponse(BaseModel): user: CurrentUserOut expires_at: datetime + + +# ---------- 股票列表（全市场浏览） ---------- +class StockListItemOut(BaseModel): + ts_code: str + symbol: str + name: str + industry: str | None = None + market: str | None = None + close: float | None = None # 最新收盘（candles 未复权） + prev_close: float | None = None + pct_chg: float | None = None # 最新两根日线计算 + last_ts: datetime | None = None + bar_count: int | None = None # 本地缓存日线条数 + watched: bool = False # 是否自选（当前用户） + + +class StockListResponse(BaseModel): + total: int + items: list[StockListItemOut] + + +# ---------- 看股页筛选项 ---------- +class FacetItemOut(BaseModel): + name: str + count: int + + +class StockFacetsResponse(BaseModel): + industries: list[FacetItemOut] = Field(default_factory=list) + areas: list[FacetItemOut] = Field(default_factory=list) + + +# ---------- 用户偏好 / 自选股 / 提问历史 ---------- +class PreferencesOut(BaseModel): + prefs: dict[str, object] = Field(default_factory=dict) # key -> JSON 值 + + +class PreferencesUpdate(BaseModel): + prefs: dict[str, object] # 部分更新：只覆盖出现的 key（值为 null 表示删除） + + +class WatchlistOp(BaseModel): + ts_code: str = Field(min_length=6, max_length=12) + + +class ScreenerQueryOut(BaseModel): + id: int + text: str + conditions: ScreenConditions | None = None + hit_count: int | None = None + created_at: datetime + + model_config = {"from_attributes": True} + + +class ScreenerQueryListResponse(BaseModel): + items: list[ScreenerQueryOut] diff --git a/backend/app/screener/llm.py b/backend/app/screener/llm.py index a1a8c87..d9de2f7 100644 --- a/backend/app/screener/llm.py +++ b/backend/app/screener/llm.py @@ -13,7 +13,7 @@ import re import httpx from ..config import settings -from ..schemas import ScreenConditions +from ..schemas import EventBacktestSpec, ScreenConditions SYSTEM_PROMPT = """你是 A 股选股条件解析器。把用户的自然语言解析成一个 JSON 对象，只输出 JSON，不要任何解释、注释或代码块围栏。完全无法理解时输出 {"error": "原因"}。 @@ -149,3 +149,69 @@ async def parse_conditions(text: str) -> ScreenConditions: except Exception as e: # noqa: BLE001 —— JSON/校验失败，带错误重试 retry_error = str(e)[:300] raise ScreenerError(f"AI 解析结果两次未通过校验，最后错误：{retry_error}") + + +# ---------- 事件回测解析（自然语言 -> EventBacktestSpec） ---------- + +EVENT_SYSTEM_PROMPT = """你是 A 股事件回测参数解析器。用户描述一个「入场信号 + 买卖时机 + 持有期」的事件回测需求，把它解析成 JSON，只输出 JSON，不要任何解释或代码块围栏。完全无法理解时输出 {"error": "原因"}。 + +输出结构： +{"entry": {"indicator": [...], "snapshot": [], "exclude_st": true, "exclude_delisted": true, "exclude_bj": true}, "entry_timing": "next_open", "holding_days": 3, "exit_timing": "close"} + +【entry.indicator 数组】入场信号条件（必填，至少 1 条），元素字段与白名单： +- "indicator": kdj_k / kdj_d / kdj_j（KDJ 的 K/D/J 值）、rsi、macd_dif / macd_dea / macd_hist（MACD 的 DIF/DEA/柱）、ma（收盘价均线）、boll_upper / boll_mid / boll_lower（布林轨道）、close（收盘价）、pct_chg（日涨跌幅%） +- "params": 指标参数（可选），默认：KDJ {"n":9,"m1":3,"m2":3}；RSI {"period":14}；MACD {"fast":12,"slow":26,"signal":9}；MA {"period":20}；BOLL {"period":20,"std":2} +- "op": "gt" | "ge" | "lt" | "le" | "between"；"value"（between 时为下界）、"value2"（上界） +- "value_indicator": 指标与指标比较时填另一指标名（同白名单），如 "DIF 大于 DEA" -> indicator=macd_dif, op=gt, value_indicator=macd_dea, value=0 +- "value_params": 比较对象指标参数不同时指定，如 "MA5 上穿 MA20" -> indicator=ma, params={"period":5}, op=gt, value_indicator=ma, value_params={"period":20}, value=0 +- "lookback": 信号需连续/曾经满足的交易日窗口（默认 1） +- "match": "all"（窗口内每天满足，默认）或 "any"（窗口内任一天满足） + +【时间语义】"连续三天 J 小于 10" -> lookback=3, match="all"；"近 5 天曾经金叉" -> lookback=5, match="any"。 + +【entry_timing】买入时机："第二天开盘购买/次日开盘买入" -> "next_open"（默认）；"第二天收盘买入" -> "next_close"。 + +【holding_days】买入后持有 N 个交易日（int，默认 3）。"未来三天的涨幅" -> holding_days=3；"持有 10 天" -> 10；"持有一个月" -> 20。 + +【exit_timing】到期卖出价："close"（收盘卖，默认）或 "open"（开盘卖）。 + +【entry.snapshot】截面过滤条件一般不适用于历史回测，除非用户明确说"只回测市值大于 X 亿的股票"才填，其余情况留空数组。 + +示例： +输入：在连续三天 J 小于 10 的时候第二天开盘购买，之后未来三天的涨幅有多少 +输出：{"entry":{"indicator":[{"indicator":"kdj_j","params":{"n":9,"m1":3,"m2":3},"op":"lt","value":10,"lookback":3,"match":"all"}],"snapshot":[],"exclude_st":true,"exclude_delisted":true,"exclude_bj":true},"entry_timing":"next_open","holding_days":3,"exit_timing":"close"} + +示例： +输入：RSI 低于 30 的第二天开盘买入持有 5 天收盘卖出 +输出：{"entry":{"indicator":[{"indicator":"rsi","params":{"period":14},"op":"lt","value":30,"lookback":1,"match":"all"}],"snapshot":[],"exclude_st":true,"exclude_delisted":true,"exclude_bj":true},"entry_timing":"next_open","holding_days":5,"exit_timing":"close"}""" + + +def _build_event_messages(text: str, retry_error: str | None = None) -> list[dict]: + user = f"解析以下事件回测需求：{text}" + if retry_error: + user += f"\n\n上一次输出无法通过校验，错误：{retry_error}。请修正后重新只输出 JSON。" + return [{"role": "system", "content": EVENT_SYSTEM_PROMPT}, {"role": "user", "content": user}] + + +async def parse_event_spec(text: str) -> EventBacktestSpec: + """自然语言 -> EventBacktestSpec。复用 _chat/_extract_json，失败带错误重试 1 次。""" + if not settings.llm_api_key: + raise ScreenerError( + "未配置 LLM_API_KEY：请在 backend/.env 填入 DeepSeek API Key（platform.deepseek.com 获取）后重启后端" + ) + retry_error: str | None = None + for _ in range(2): + content = await _chat(_build_event_messages(text, retry_error)) + try: + obj = _extract_json(content) + if "error" in obj and not obj.get("entry"): + raise ScreenerError(f"AI 无法理解该回测需求：{obj['error']}") + spec = EventBacktestSpec.model_validate(obj) + if not spec.entry.indicator: + raise ValueError("entry.indicator 不能为空") + return spec + except ScreenerError: + raise + except Exception as e: # noqa: BLE001 + retry_error = str(e)[:300] + raise ScreenerError(f"AI 解析回测参数两次未通过校验，最后错误：{retry_error}") diff --git a/backend/app/screener/market_sync.py b/backend/app/screener/market_sync.py index 3604230..fd562b1 100644 --- a/backend/app/screener/market_sync.py +++ b/backend/app/screener/market_sync.py @@ -16,7 +16,7 @@ from sqlalchemy import delete, func, insert, select from sqlalchemy.ext.asyncio import AsyncSession from ..config import settings -from ..models import DailySnapshot, MarketDaily, StockBasic, TradeCalendar +from ..models import AdjFactor, DailySnapshot, MarketDaily, StockBasic, TradeCalendar from .llm import ScreenerError # 进程内单例任务状态（uvicorn --reload 单进程场景够用） @@ -160,6 +160,18 @@ def _fetch_basic(pro, d: str) -> list[dict]: return rows +def _fetch_adj_factor(pro, d: str) -> list[dict]: + """拉取某交易日全市场复权因子（K线 bfq->qfq/hfq 本地换算的底座）。""" + time.sleep(settings.screener_sync_interval) + df = _call_retry(pro.adj_factor, trade_date=d) + if df is None or df.empty: + return [] + return [ + {"trade_date": _parse_d(d), "ts_code": r["ts_code"], "adj_factor": float(r["adj_factor"])} + for _, r in df.iterrows() + ] + + def _sync_stock_list_sync(pro) -> list[dict]: """拉取在市股票列表。""" time.sleep(settings.screener_sync_interval) @@ -243,6 +255,16 @@ async def _run_sync(days: int, force: bool) -> None: await _replace_day(session, MarketDaily, daily_rows, d) _sync_state["done_days"] += 1 + # 2.5) 复权因子（与日线同窗口增量；历史全量由 scripts/backfill_adj_factor.py 回补） + async with async_session() as session: + have_adj = set() if force else await _existing_dates(session, AdjFactor) + for d in [d for d in dates if d not in have_adj]: + _sync_state["step"] = f"正在同步 {d} 复权因子" + adj_rows = await asyncio.to_thread(_fetch_adj_factor, pro, d) + if adj_rows: + async with async_session() as session: + await _replace_day(session, AdjFactor, adj_rows, d) + # 3) 最新「有数据」交易日的快照（daily_basic，仅 1 次调用） # 用 market_daily 实际最大交易日（今天的数据收盘后才生成，日历最新日会拉到空） async with async_session() as session: diff --git a/backend/smoke_test.py b/backend/smoke_test.py index 45a9b98..6bb6de9 100644 --- a/backend/smoke_test.py +++ b/backend/smoke_test.py @@ -65,7 +65,7 @@ async def main() -> None: daily = await client.post( "/api/backtest", json={ - "symbol": "DEMO", + "symbol": "000001", "strategy": "macd_cross", "params": {"fast": 12, "slow": 26, "signal": 9}, "initial_cash": 100000.0, diff --git a/frontend/index.html b/frontend/index.html index fced06a..218479d 100644 --- a/frontend/index.html +++ b/frontend/index.html @@ -3,7 +3,7 @@ - 量化选股与回测平台 + 选股训练营 diff --git a/frontend/src/App.vue b/frontend/src/App.vue index af5310e..802df81 100644 --- a/frontend/src/App.vue +++ b/frontend/src/App.vue @@ -3,6 +3,7 @@ import { computed, ref } from 'vue'; import { RouterView } from 'vue-router'; import { useRoute, useRouter } from 'vue-router'; import { useAuthStore } from '@/stores/auth'; +import SettingsModal from '@/components/SettingsModal.vue'; const route = useRoute(); const router = useRouter(); @@ -10,6 +11,7 @@ const auth = useAuthStore(); const isHome = computed(() => route.name === 'home'); const isLogin = computed(() => route.name === 'login'); const loggingOut = ref(false); +const showSettings = ref(false); async function signOut() { loggingOut.value = true; @@ -28,13 +30,42 @@ async function signOut() {
-
- {{ auth.user?.username }} - -
-
+
+
+ + Stock +
+ {{ auth.user?.username }} +
+
+
+ + +
diff --git a/frontend/src/api/client.ts b/frontend/src/api/client.ts index bf8415d..2a9ecad 100644 --- a/frontend/src/api/client.ts +++ b/frontend/src/api/client.ts @@ -1,16 +1,23 @@ import type { + AdjustMode, BacktestRequest, BacktestResponse, CurrentUser, + EventBacktestRequest, + EventBacktestResponse, LoginRequest, LoginResponse, PreviewResponse, + ScreenerQueryItem, ScreenerRunRequest, ScreenerRunResponse, ScreenerSyncRequest, ScreenerSyncStatus, + StockFacets, + StockListResponse, SyncRequest, SyncResponse, + Timeframe, } from './types'; // dev 用 Vite 代理（/api -> :8000）；生产构建设 VITE_API_BASE 指向后端地址。 @@ -81,6 +88,28 @@ export async function syncData(req: SyncRequest): Promise { return (await res.json()) as SyncResponse; } +/** 自然语言事件回测。全市场扫描较慢，timeout 放宽到 15 分钟。 */ +export async function postEventBacktest(req: EventBacktestRequest): Promise { + const ctrl = new AbortController(); + const timer = setTimeout(() => ctrl.abort(), 15 * 60 * 1000); + try { + const res = await apiFetch('/api/backtest/event', { + method: 'POST', + body: JSON.stringify(req), + signal: ctrl.signal, + }); + if (!res.ok) throw new ApiError(await readError(res, `事件回测失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as EventBacktestResponse; + } catch (e) { + if (e instanceof DOMException && e.name === 'AbortError') { + throw new ApiError('事件回测超时（全市场扫描较慢，可先缩短日期范围或指定单只股票）', 0); + } + throw e; + } finally { + clearTimeout(timer); + } +} + export async function runScreener(req: ScreenerRunRequest): Promise { const res = await apiFetch('/api/screener/run', { method: 'POST', body: JSON.stringify(req) }); if (!res.ok) throw new ApiError(await readError(res, `选股失败 (HTTP ${res.status})`), res.status); @@ -99,8 +128,96 @@ export async function getScreenerSyncStatus(): Promise { return (await res.json()) as ScreenerSyncStatus; } -export async function getStockPreview(tsCode: string, limit = 260): Promise { - const res = await apiFetch(`/api/screener/preview/${encodeURIComponent(tsCode)}?limit=${limit}`); +export async function getStockPreview( + tsCode: string, + opts: { + limit?: number; + adjust?: AdjustMode; + timeframe?: Timeframe; + mas?: number[]; + } = {}, +): Promise { + const { limit = 10000, adjust = 'qfq', timeframe = '1d', mas } = opts; + const q = new URLSearchParams({ + limit: String(limit), + adjust, + timeframe, + ...(mas?.length ? { mas: mas.join(',') } : {}), + }); + const res = await apiFetch(`/api/screener/preview/${encodeURIComponent(tsCode)}?${q.toString()}`); if (!res.ok) throw new ApiError(await readError(res, `获取个股详情失败 (HTTP ${res.status})`), res.status); return (await res.json()) as PreviewResponse; } + +export async function getStocks(params: { + search?: string; + market?: string; + industry?: string; + area?: string; + watched_only?: boolean; + limit?: number; + offset?: number; +}): Promise { + const q = new URLSearchParams(); + if (params.search) q.set('search', params.search); + if (params.market) q.set('market', params.market); + if (params.industry) q.set('industry', params.industry); + if (params.area) q.set('area', params.area); + if (params.watched_only) q.set('watched_only', 'true'); + q.set('limit', String(params.limit ?? 100)); + q.set('offset', String(params.offset ?? 0)); + const res = await apiFetch(`/api/stocks?${q.toString()}`); + if (!res.ok) throw new ApiError(await readError(res, `获取股票列表失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as StockListResponse; +} + +export async function getStockFacets(): Promise { + const res = await apiFetch('/api/stocks/facets'); + if (!res.ok) throw new ApiError(await readError(res, `获取筛选项失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as StockFacets; +} + +// ---------- 用户偏好 / 自选股 / 提问历史 ---------- +export async function getPreferences(): Promise> { + const res = await apiFetch('/api/preferences'); + if (!res.ok) throw new ApiError(await readError(res, `获取偏好失败 (HTTP ${res.status})`), res.status); + const data = (await res.json()) as { prefs: Record }; + return data.prefs ?? {}; +} + +export async function putPreferences(prefs: Record): Promise> { + const res = await apiFetch('/api/preferences', { method: 'PUT', body: JSON.stringify({ prefs }) }); + if (!res.ok) throw new ApiError(await readError(res, `保存偏好失败 (HTTP ${res.status})`), res.status); + const data = (await res.json()) as { prefs: Record }; + return data.prefs ?? {}; +} + +export async function getWatchlist(): Promise { + const res = await apiFetch('/api/watchlist'); + if (!res.ok) throw new ApiError(await readError(res, `获取自选股失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as string[]; +} + +export async function addWatchlist(tsCode: string): Promise { + const res = await apiFetch('/api/watchlist', { method: 'POST', body: JSON.stringify({ ts_code: tsCode }) }); + if (!res.ok) throw new ApiError(await readError(res, `加自选失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as string[]; +} + +export async function removeWatchlist(tsCode: string): Promise { + const res = await apiFetch(`/api/watchlist/${encodeURIComponent(tsCode)}`, { method: 'DELETE' }); + if (!res.ok) throw new ApiError(await readError(res, `移除自选失败 (HTTP ${res.status})`), res.status); + return (await res.json()) as string[]; +} + +export async function getScreenerQueries(limit = 20): Promise { + const res = await apiFetch(`/api/screener/queries?limit=${limit}`); + if (!res.ok) throw new ApiError(await readError(res, `获取提问历史失败 (HTTP ${res.status})`), res.status); + const data = (await res.json()) as { items: ScreenerQueryItem[] }; + return data.items ?? []; +} + +export async function deleteScreenerQuery(id: number): Promise { + const res = await apiFetch(`/api/screener/queries/${id}`, { method: 'DELETE' }); + if (!res.ok && res.status !== 401) throw new ApiError(`删除失败 (HTTP ${res.status})`, res.status); +} diff --git a/frontend/src/api/types.ts b/frontend/src/api/types.ts index e360f32..9e6f73e 100644 --- a/frontend/src/api/types.ts +++ b/frontend/src/api/types.ts @@ -191,8 +191,119 @@ export interface PreviewInfo { export interface PreviewResponse { ts_code: string; symbol: string; - source: string; // qfq | market + source: string; // bfq | qfq | hfq | market（实际复权口径 / 近段未复权兜底） info: PreviewInfo; candles: Candle[]; indicators: Record>; } + +// ---------- 股票列表（全市场浏览） ---------- +export interface StockListItem { + ts_code: string; + symbol: string; + name: string; + industry?: string | null; + market?: string | null; + close?: number | null; + prev_close?: number | null; + pct_chg?: number | null; + last_ts?: string | null; + bar_count?: number | null; + watched: boolean; +} + +export interface StockListResponse { + total: number; + items: StockListItem[]; +} + +export interface FacetItem { + name: string; + count: number; +} + +export interface StockFacets { + industries: FacetItem[]; + areas: FacetItem[]; +} + +// ---------- 用户偏好 / 自选股 / 提问历史 ---------- +export type Timeframe = '1d' | '1w' | '1M' | '1y'; +export type AdjustMode = 'bfq' | 'qfq' | 'hfq'; + +/** 看股页图表布局偏好（存 user_preferences.chartLayout） */ +export interface ChartLayoutPrefs { + maPeriods: number[]; + subPanes: string[]; // 'vol' | 'macd' | 'kdj' | 'rsi'（顺序即面板顺序） + subHeights: Record; // 面板高度 px + timeframe?: Timeframe; +} + +export interface ScreenerQueryItem { + id: number; + text: string; + conditions: ScreenConditions | null; + hit_count: number | null; + created_at: string; +} + +// ---------- 事件回测（自然语言） ---------- +export interface EventBacktestSpec { + entry: ScreenConditions; + entry_timing: 'next_open' | 'next_close'; + holding_days: number; + exit_timing: 'close' | 'open'; +} + +export interface EventBacktestRequest { + text: string; + spec?: EventBacktestSpec | null; // 直传则跳过 LLM（调参重跑） + ts_code?: string | null; + start?: string | null; + end?: string | null; +} + +export interface EventTrade { + ts_code: string; + name: string | null; + entry_date: string; + entry_price: number; + exit_date: string; + exit_price: number; + ret_pct: number; +} + +export interface EventYearStat { + year: number; + samples: number; + mean_pct: number; + median_pct: number; + win_rate: number; +} + +export interface EventStats { + samples: number; + stocks: number; + mean_pct: number; + median_pct: number; + win_rate: number; + std_pct: number; + p10_pct: number; + p25_pct: number; + p75_pct: number; + p90_pct: number; + max_pct: number; + min_pct: number; + by_year: EventYearStat[]; +} + +export interface EventBacktestResponse { + text: string; + spec: EventBacktestSpec; + universe: string; + start: string; + end: string; + stats: EventStats; + trades: EventTrade[]; + total: number; +} diff --git a/frontend/src/components/BacktestForm.vue b/frontend/src/components/BacktestForm.vue deleted file mode 100644 index 6d11f1a..0000000 --- a/frontend/src/components/BacktestForm.vue +++ /dev/null @@ -1,123 +0,0 @@ - - - diff --git a/frontend/src/components/DetailKLine.vue b/frontend/src/components/DetailKLine.vue index fbe4970..ba415f2 100644 --- a/frontend/src/components/DetailKLine.vue +++ b/frontend/src/components/DetailKLine.vue @@ -1,6 +1,7 @@ diff --git a/frontend/src/components/EquityChart.vue b/frontend/src/components/EquityChart.vue deleted file mode 100644 index a9e4590..0000000 --- a/frontend/src/components/EquityChart.vue +++ /dev/null @@ -1,63 +0,0 @@ - - - diff --git a/frontend/src/components/KLineChart.vue b/frontend/src/components/KLineChart.vue deleted file mode 100644 index d42bac9..0000000 --- a/frontend/src/components/KLineChart.vue +++ /dev/null @@ -1,319 +0,0 @@ - - - diff --git a/frontend/src/components/MetricsPanel.vue b/frontend/src/components/MetricsPanel.vue deleted file mode 100644 index dc96388..0000000 --- a/frontend/src/components/MetricsPanel.vue +++ /dev/null @@ -1,39 +0,0 @@ - - - diff --git a/frontend/src/components/ScreenerForm.vue b/frontend/src/components/ScreenerForm.vue index 7b06f0c..c4156cc 100644 --- a/frontend/src/components/ScreenerForm.vue +++ b/frontend/src/components/ScreenerForm.vue @@ -1,8 +1,13 @@