Files
tick-stock-panel/backend/app/api/backtest.py
T
Jinfeng SunandClaude Opus 4.8 9aa96edbd7 改进: 并发韧性 + 数据性能 + 死代码清理 + 前端 UX + ST/Sharpe 修复 (#78)
* fix(concurrency): 共享缓存/任务表加锁, 全局限速, depth 原子写, 认证热路径缓存

修复多线程下的竞态与阻塞:
- overview/strategy_cache/PanelCache/StrategyMonitor._watching 四处共享状态加锁,
  消除 "dict/OrderedDict mutated" 与丢更新/半写读取
- strategy_cache/depth parquet 改临时文件 + os.replace 原子写
- rate_limits 改进程级共享时间轴限速, 并发同步不再聚合超过单能力 rpm;
  scheduler 令牌账目与 sleep 分离, sleep 不再独占锁串行化其他请求
- auth.is_configured() 内存缓存, 认证中间件不再每请求读盘阻塞事件循环
- api/backtest 任务清理/取消全程持 _jobs_lock, 并用 Semaphore(2) 限并发重回测

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* perf(data): limit_ladder 去 N+1 全市场重算, 指标裁剪, factor 向量化

- limit_ladder 前一日 consecutive 改窄读单日 parquet 存储列 (谓词/投影下推),
  替代 range(1,10) 逐日 _load_enriched_for_date 全市场指标重算 (最坏 9x)
- compute_indicators 新增可选 needed 裁剪 (默认 None 行为逐位不变, 已对照验证),
  factor 只算所需因子列
- factor._calc_period_return 用 Polars join 替代 Python 逐行 price_map 循环,
  _add_groups 去 map_elements 改纯表达式 (输出逐位一致)
- screener ext value_map 按 parquet mtime 记忆化, 免每请求磁盘重读
  (DuckDB 过滤仍用隔离 :memory: 连接, 不扩大注入面)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(backend): 报表存储去重, 删死代码, DuckDB 视图重建收敛, 管道失败如实标记

- 三份近乎逐字复制的 *_reports.py 收敛到共享 JsonReportStore (原子写 + 锁),
  各模块公有 API/id 格式/上限/落盘 schema 完全保持不变
- 删除 ext_pull.py 中字节相同的死 _run_loop (Python 只绑第二个) 及无用 import
- 13 张 DuckDB 视图重建收敛为唯一权威 repository.rebuild_views(),
  daily_pipeline 与 /api/data/clear 改为调用 (修好 clear 路径漏挂视图的漂移)
- daily_pipeline 累积 stage_errors 并在末尾抛出, 部分失败不再误报成功;
  free/None 模式的能力门控跳过不计入失败

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* feat(frontend): SSE 连接态, 路由代码分割, 查询失效修复, 三态与无障碍

- 实时行情 SSE: 连接态 store + 指数退避 + 断线徽标/toast (避免静默丢告警);
  回测 SSE 断线有界重连 + 可重试, 不再永久卡住进度条
- router 全部 React.lazy + Suspense, vite manualChunks 拆图表库
  (echarts 变独立 1MB 懒加载 chunk, 首屏包显著减小)
- 修 Data 清库后其它页显示旧数据 (改回广域失效); 修 Watchlist kline 失效键
  永不匹配; query key 收敛到 QK 工厂 (新增 strategyDetail)
- Monitor/Analysis/StockAnalysis/ExtPages/CustomSignals 补 loading 门控与
  error/empty 三态区分
- 新增共享 Modal 原语 (焦点陷阱/ESC/焦点还原/aria), 改造 3 个高频弹窗;
  Toast/AlertToast 加 aria-live 与键盘可达; Watchlist/LimitUpLadder 卡片 memo

修复本轮 review 发现的缺陷:
- Modal 焦点 effect 依赖 onClose 致每次输入抢焦点 → 改 ref 只装一次
- StrategySettingsDialog 删除确认框被 Modal 面板裁剪 → 移出作兄弟节点

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(quant): 修正 ST 板块限价套错 与 因子 Sharpe 年化频率

两个不报错但会算错数的领域 bug:

1. ST 5% 涨跌停限幅被无条件套到创业板/科创板 ST 股:
   注册制改革后 创业板(300/301)、科创板(688/689) 的风险警示股仍执行 20%,
   北交所 30%, 只有主板 ST 才是 5%。原代码 _is_st 先判且覆盖板块限幅, 导致
   创业板/科创板 ST 的涨停价按 5% 计算 → +5% 被误报涨停、真 +20% 涨停被漏报,
   污染 signal_limit_up / consecutive_limit_ups / 连板梯队 / near_limit_up。
   修正: ST 5% 仅在 ~(创业板|科创板|北交所) 时生效 (EOD + 盘中两条路径 + near_limit_up)。

2. 因子回测 Sharpe 一律乘 √252, 但 group_nav 每点是一个调仓周期收益:
   月频调仓下是月收益, 乘 √252 会把 Sharpe 高估 √(252/12) ≈ 4.6x (周频 ≈2.2x),
   使无效因子显示成明星因子, 废掉"先筛无效指标"的用途。
   修正: 年化系数按 config.rebalance 取 √252/√52/√12。

新增 tests/test_st_limit_and_sharpe.py (5 例) 覆盖两处修正。

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-08 18:10:19 +08:00

514 lines
18 KiB
Python

"""回测 API — 信号回测 + 因子回测 + 策略回测。"""
from __future__ import annotations
import asyncio
import json
import queue
import threading
from dataclasses import asdict
from datetime import date, timedelta
from typing import Literal
from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
from app.config import settings
from app.services.backtest import (
BacktestConfig,
BacktestService,
VectorbtUnavailable,
is_available,
)
router = APIRouter(prefix="/api/backtest", tags=["backtest"])
FACTOR_DEFAULT_DAYS = 180
STRATEGY_DEFAULT_DAYS = 365 * 3
BACKTEST_MAX_SERVER_DAYS = 186
FACTOR_MAX_SYMBOLS = 1000
BACKTEST_SERVER_GUARD_MESSAGE = (
"当前服务器内存约 1.8GB,回测区间最多支持 6 个月;"
"更长周期容易触发 OOM,建议在 8GB 以上内存环境或本机运行。"
)
def _get_engine(request: Request):
"""获取或创建 BacktestEngine (单例,PanelCache 跨请求生效)。"""
from app.backtest.engine import BacktestEngine
engine = getattr(request.app.state, "backtest_engine", None)
if engine is None:
engine = BacktestEngine(request.app.state.repo)
request.app.state.backtest_engine = engine
return engine
def _resolve_start(req: BaseModel, end: date, default_days: int) -> date:
"""未传 start 使用默认区间;显式传 null/空值表示全部历史。"""
start = getattr(req, "start")
if start is not None:
return start
if "start" in req.model_fields_set:
return date(1900, 1, 1)
return end - timedelta(days=default_days)
def _guard_server_backtest_range(start: date, end: date):
if not settings.backtest_range_guard:
return
days = (end - start).days + 1
if days > BACKTEST_MAX_SERVER_DAYS:
raise HTTPException(status_code=400, detail=BACKTEST_SERVER_GUARD_MESSAGE)
# ================================================================
# 状态
# ================================================================
@router.get("/status")
def status():
"""前端可用此接口判断回测页是否要灰显。"""
return {"available": True}
# ================================================================
# 信号回测 (现有接口,保持不变)
# ================================================================
class BacktestRequest(BaseModel):
symbols: list[str] = Field(..., min_length=1)
start: date | None = None
end: date | None = None
entries: list[str] = []
exits: list[str] = []
stop_loss_pct: float | None = None
max_hold_days: int | None = None
fees_pct: float = 0.0002
slippage_bps: float = 5
matching: Literal["close_t", "open_t+1"] = "close_t"
asset_type: str = "stock"
@router.post("/run")
def run(req: BacktestRequest, request: Request):
"""信号回测 — 现有接口,向后兼容。"""
repo = request.app.state.repo
svc = BacktestService(repo)
end = req.end or date.today()
start = req.start or (end - timedelta(days=365 * 3))
cfg = BacktestConfig(
symbols=req.symbols,
start=start,
end=end,
entries=req.entries,
exits=req.exits,
stop_loss_pct=req.stop_loss_pct,
max_hold_days=req.max_hold_days,
fees_pct=req.fees_pct,
slippage_bps=req.slippage_bps,
matching=req.matching,
asset_type=req.asset_type,
)
try:
result = svc.run(cfg)
except VectorbtUnavailable as e:
raise HTTPException(status_code=503, detail=str(e)) from e
return asdict(result)
# ================================================================
# 因子回测
# ================================================================
class FactorColumnsResponse(BaseModel):
columns: list[dict]
@router.get("/factor/columns")
def factor_columns():
"""返回可用的因子列列表。"""
from app.backtest.factor import FACTOR_COLUMNS
return {"columns": FACTOR_COLUMNS}
class FactorBacktestRequest(BaseModel):
factor_name: str
symbols: list[str] | None = None
start: date | None = None
end: date | None = None
n_groups: int = 5
rebalance: Literal["daily", "weekly", "monthly"] = "monthly"
weight: Literal["equal", "factor_weight"] = "equal"
fees_pct: float = 0.0002
slippage_bps: float = 5.0
asset_type: str = "stock"
@router.post("/factor/run")
def factor_run(req: FactorBacktestRequest, request: Request):
"""因子回测 — IC/IR 分析 + 分层回测。"""
from app.backtest.factor import FactorBacktestService, FactorConfig
engine = _get_engine(request)
svc = FactorBacktestService(engine)
end = req.end or date.today()
start = _resolve_start(req, end, STRATEGY_DEFAULT_DAYS)
_guard_server_backtest_range(start, end)
symbols = req.symbols if req.symbols else None
if symbols is not None and len(symbols) > FACTOR_MAX_SYMBOLS:
raise HTTPException(
status_code=400,
detail=f"指定标的最多支持 {FACTOR_MAX_SYMBOLS} 只,请缩小标的范围。",
)
cfg = FactorConfig(
factor_name=req.factor_name,
symbols=symbols,
start=start,
end=end,
n_groups=req.n_groups,
rebalance=req.rebalance,
weight=req.weight,
fees_pct=req.fees_pct,
slippage_bps=req.slippage_bps,
asset_type=req.asset_type,
)
result = svc.run(cfg)
return asdict(result)
# ================================================================
# 策略回测
# ================================================================
class StrategyBacktestRequest(BaseModel):
strategy_id: str
symbols: list[str] | None = None
start: date | None = None
end: date | None = None
params: dict | None = None
overrides: dict | None = None
# matching 向后兼容; 显式传 entry_fill/exit_fill 时以二者为准。
matching: Literal["close_t", "open_t+1"] = "open_t+1"
entry_fill: Literal["close_t", "open_t+1"] | None = None
exit_fill: Literal["close_t", "open_t+1"] | None = None
fees_pct: float = 0.0002
commission_pct: float | None = None
stamp_tax_pct: float | None = None
slippage_bps: float = 5.0
max_positions: int = 10
max_exposure_pct: float = 1.0
initial_capital: float = 1_000_000.0
position_sizing: Literal["equal", "score_weight"] = "equal"
mode: Literal["position", "full"] = "position"
holding_days: int = 5
asset_type: str = "stock"
@router.post("/strategy/run")
def strategy_run(req: StrategyBacktestRequest, request: Request):
"""策略回测 — 复用 StrategyDef 体系做全周期回测。"""
from app.backtest.strategy import StrategyBacktestService, StrategyBacktestConfig
engine = _get_engine(request)
strategy_engine = request.app.state.strategy_engine
svc = StrategyBacktestService(engine, strategy_engine)
end = req.end or date.today()
start = _resolve_start(req, end, FACTOR_DEFAULT_DAYS)
_guard_server_backtest_range(start, end)
cfg = StrategyBacktestConfig(
strategy_id=req.strategy_id,
symbols=req.symbols if req.symbols else None,
start=start,
end=end,
params=req.params,
overrides=req.overrides,
matching=req.matching,
entry_fill=req.entry_fill,
exit_fill=req.exit_fill,
fees_pct=req.fees_pct,
commission_pct=req.commission_pct,
stamp_tax_pct=req.stamp_tax_pct,
slippage_bps=req.slippage_bps,
max_positions=req.max_positions,
max_exposure_pct=req.max_exposure_pct,
initial_capital=req.initial_capital,
position_sizing=req.position_sizing,
mode=req.mode,
holding_days=req.holding_days,
asset_type=req.asset_type,
)
result = svc.run(cfg)
return asdict(result)
# ── SSE 流式回测 (实时进度 + 可取消 + 支持重连) ───────────────────
import time
import hashlib
class _BacktestJob:
"""单个回测任务的状态, 存模块级供重连使用。"""
__slots__ = ("key", "cancel_event", "progress", "result", "error", "done", "finish_ts")
def __init__(self, key: str):
self.key = key
self.cancel_event = threading.Event()
self.progress: list[dict] = [] # 进度历史 (新连接可回放)
self.result = None # 完成后的结果
self.error: str | None = None
self.done = False
self.finish_ts: float = 0.0
# 模块级任务表: key -> _BacktestJob
_running_jobs: dict[str, _BacktestJob] = {}
_jobs_lock = threading.Lock()
_JOB_TTL = 300 # 完成后保留 5 分钟
# 并发回测上限: 多个重回测同时跑会 OOM (服务器内存约 1.8GB)。用信号量限并发,
# 超出的任务在 _run_backtest 里排队, SSE 连接照常保持, run 一开始就有进度。
_backtest_semaphore = threading.Semaphore(2)
def _cleanup_stale_jobs():
"""清理过期任务 (完成超过 TTL 的)。全程持 _jobs_lock: 迭代+pop 与其他访问互斥。"""
now = time.time()
with _jobs_lock:
stale = [k for k, j in _running_jobs.items() if j.done and now - j.finish_ts > _JOB_TTL]
for k in stale:
_running_jobs.pop(k, None)
def _make_job_key(
strategy_id: str, symbols: str | None, start: str | None, end: str | None,
matching: str, entry_fill: str | None, exit_fill: str | None,
fees_pct: float, slippage_bps: float,
max_positions: int, max_exposure_pct: float, initial_capital: float, position_sizing: str,
params: str | None, overrides: str | None,
mode: str = "position", holding_days: int = 5,
commission_pct: float | None = None, stamp_tax_pct: float | None = None,
asset_type: str = "stock",
) -> str:
raw = f"{strategy_id}|{symbols}|{start}|{end}|{matching}|{entry_fill}|{exit_fill}|{fees_pct}|{slippage_bps}|{max_positions}|{max_exposure_pct}|{initial_capital}|{position_sizing}|{params}|{overrides}|{mode}|{holding_days}|{commission_pct}|{stamp_tax_pct}|{asset_type}"
return hashlib.md5(raw.encode()).hexdigest()[:12]
@router.get("/strategy/stream")
async def strategy_stream(
request: Request,
strategy_id: str,
symbols: str | None = None,
start: str | None = None,
end: str | None = None,
matching: str = "open_t+1",
entry_fill: str | None = None,
exit_fill: str | None = None,
fees_pct: float = 0.0002,
commission_pct: float | None = None,
stamp_tax_pct: float | None = None,
slippage_bps: float = 5.0,
max_positions: int = 10,
max_exposure_pct: float = 1.0,
initial_capital: float = 1_000_000.0,
position_sizing: str = "equal",
params: str | None = None,
overrides: str | None = None,
mode: str = "position",
holding_days: int = 5,
asset_type: str = "stock",
):
"""SSE 流式策略回测: 实时推送进度, 完成后推送结果, 支持重连 (刷新/切页后恢复)。
- 相同参数的任务只启动一次, 多次连接订阅同一个任务
- 断开连接不会取消任务 (除非显式调用 cancel)
- 结果保留 5 分钟供重连
事件类型:
- progress: {day, total, date, equity}
- done: {result} (完整回测结果)
- error: {message}
"""
from app.backtest.strategy import StrategyBacktestService, StrategyBacktestConfig
engine = _get_engine(request)
strategy_engine = request.app.state.strategy_engine
svc = StrategyBacktestService(engine, strategy_engine)
end_date = date.fromisoformat(end) if end else date.today()
if start:
start_date = date.fromisoformat(start)
else:
# 空 start = 全部历史: 用本地最早日K日期, 查不到再回退到默认窗口
earliest = request.app.state.repo.earliest_daily_date()
start_date = earliest or (end_date - timedelta(days=FACTOR_DEFAULT_DAYS))
# 服务端范围保护
guard_violated = False
if settings.backtest_range_guard:
days = (end_date - start_date).days + 1
if days > BACKTEST_MAX_SERVER_DAYS:
guard_violated = True
job_key = _make_job_key(
strategy_id, symbols, start, end,
matching, entry_fill, exit_fill,
fees_pct, slippage_bps, max_positions, max_exposure_pct, initial_capital, position_sizing,
params, overrides,
mode, holding_days,
commission_pct, stamp_tax_pct,
asset_type=asset_type,
)
_cleanup_stale_jobs()
# 获取或创建任务
with _jobs_lock:
job = _running_jobs.get(job_key)
if job is None:
job = _BacktestJob(job_key)
_running_jobs[job_key] = job
is_new = True
else:
is_new = False
async def event_generator():
# 范围保护: 直接报错
if guard_violated:
yield f"event: error\ndata: {json.dumps({'message': BACKTEST_SERVER_GUARD_MESSAGE}, ensure_ascii=False)}\n\n"
return
# 如果是新任务, 启动回测线程
if is_new and not job.done:
cfg = StrategyBacktestConfig(
strategy_id=strategy_id,
symbols=[s.strip() for s in symbols.split(",") if s.strip()] if symbols else None,
start=start_date,
end=end_date,
params=json.loads(params) if params else None,
overrides=json.loads(overrides) if overrides else None,
matching=matching,
entry_fill=entry_fill,
exit_fill=exit_fill,
fees_pct=fees_pct,
commission_pct=commission_pct,
stamp_tax_pct=stamp_tax_pct,
slippage_bps=slippage_bps,
max_positions=int(max_positions),
max_exposure_pct=float(max_exposure_pct),
initial_capital=float(initial_capital),
position_sizing=position_sizing,
mode=mode,
holding_days=int(holding_days),
asset_type=asset_type,
)
def _run_backtest():
# 信号量限并发: 超额任务在此阻塞排队, 不并发吃满内存 (等待期间 cancel_event
# 仍可置位, svc.run 会据此提前返回 cancelled)。持槽跑完在 finally 释放。
_backtest_semaphore.acquire()
try:
result = svc.run(cfg, lambda d: job.progress.append(d), job.cancel_event)
job.result = result
job.done = True
job.finish_ts = time.time()
except Exception as e:
job.error = str(e)
job.done = True
job.finish_ts = time.time()
finally:
_backtest_semaphore.release()
# 启动后台线程 (不阻塞事件循环)
threading.Thread(target=_run_backtest, daemon=True).start()
# 订阅进度: 用读指针读 job.progress 列表 (多连接互不干扰)
cursor = 0
tick = 0
try:
while True:
# 已完成: 推送最终结果/错误并退出
if job.done:
if job.error:
yield f"event: error\ndata: {json.dumps({'message': job.error}, ensure_ascii=False)}\n\n"
elif job.result is not None:
r = job.result
if hasattr(r, "error") and r.error == "cancelled":
yield f"event: error\ndata: {json.dumps({'message': '回测已取消'}, ensure_ascii=False)}\n\n"
elif hasattr(r, "error") and r.error:
yield f"event: error\ndata: {json.dumps({'message': r.error}, ensure_ascii=False)}\n\n"
else:
yield f"event: done\ndata: {json.dumps(asdict(r), ensure_ascii=False, default=str)}\n\n"
return
# 断开检测: 每 4 轮检查一次 (降低 GIL 抢占频率)
tick += 1
if tick % 4 == 0 and await request.is_disconnected():
break
# 推送新进度 (从 cursor 开始读)
prog_list = job.progress
while cursor < len(prog_list):
msg = prog_list[cursor]
cursor += 1
yield f"event: progress\ndata: {json.dumps(msg, ensure_ascii=False, default=str)}\n\n"
await asyncio.sleep(0.5)
except asyncio.CancelledError:
raise
return StreamingResponse(event_generator(), media_type="text/event-stream")
@router.post("/strategy/cancel")
async def strategy_cancel(request: Request):
"""取消正在运行的回测任务 (前端传 query string, 后端算 job_key)。"""
body = await request.json()
qs = body.get("qs", "")
# 解析 qs 得到参数
from urllib.parse import parse_qs
p = parse_qs(qs)
def _get(key: str, default: str = "") -> str:
return p.get(key, [default])[0]
def _get_opt_float(key: str) -> float | None:
# 可选成本参数: 缺省或空串 → None (与 stream 侧 float | None 口径一致, 保证 job_key 对齐)。
v = _get(key)
return float(v) if v else None
job_key = _make_job_key(
_get("strategy_id"),
_get("symbols") or None,
_get("start") or None,
_get("end") or None,
_get("matching", "open_t+1"),
_get("entry_fill") or None,
_get("exit_fill") or None,
float(_get("fees_pct", "0.0002")),
float(_get("slippage_bps", "5")),
int(_get("max_positions", "10")),
float(_get("max_exposure_pct", "1")),
float(_get("initial_capital", "1000000")),
_get("position_sizing", "equal"),
_get("params") or None,
_get("overrides") or None,
_get("mode", "position"),
int(_get("holding_days", "5")),
commission_pct=_get_opt_float("commission_pct"),
stamp_tax_pct=_get_opt_float("stamp_tax_pct"),
asset_type=_get("asset_type", "stock"),
)
# 持锁读任务表: 与 _cleanup_stale_jobs 的 pop、stream 的写入互斥
with _jobs_lock:
job = _running_jobs.get(job_key)
if job and not job.done:
job.cancel_event.set()
return {"ok": True}
return {"ok": False, "message": "任务不存在或已完成"}