汇总三轮未提交的开发(每轮均在本机 MariaDB + 真实浏览器上验证):
1) 股息率案例(全市场股息率最高 n 只,默认 20,每 m 月择股)
- 新增日频估值表 daily_basic + 迁移;股息率因子(dv_ratio / dividend_yield / TTM)
- 名称历史表 stock_name_history:剔除 ST 按**择股日当时名称**判定,消除
「曾高股息后 ST」的股息陷阱(实测 3.70pp 偏差)
- 区间择股/调仓双周期(m 择股 / y 调仓)、指数成分与白名单、停牌近似剔除
- 复权因子口径核对(4,164,742 行、缺失 0.0%)、收盘价成交与涨跌停拦单
- 案例实测:2020-01-01~2026-09-04 总收益 +24.86%(年化 3.52%、回撤 -28.58%)
2) 策略库与前端统一
- strategy 表 + CRUD/PUT 原地更新 + `describe_strategy` 按 spec 真实推导
「一句话说明 + 计算公式 + 执行步骤 + 注意事项」(与引擎实执行规则同源)
- 任何出现股票代码处都成对显示名称且可点击进个股页
- 全站图表基座统一 TradingView Lightweight Charts(ECharts 依赖、
锁文件、组件与文档标注一并清除),买卖点标记只落在真实交易日上
3) 回测存档完整化(可往复查看)
- 同步端点(POST /api/backtests、/api/factor-tests)此前完全不落库 → 现在同样归档,
归档 id 经响应头 X-Experiment-Id 返回(不破坏 response_model)
- data_version 首次真实写入(数据快照指纹:最新交易日 + 各表规模)
- 个股收益曲线默认**全量保存**(此前硬截断 60 只);超出体积预算才裁剪,
并写 archive_meta(机器可读)+ unimplemented(人可读)如实标注
- 列表 kind/q 过滤 + X-Total-Count(此前 limit=50 静默截断)、DELETE 归档
- 只读归档页 /experiments/{id}(Server Component,SSR 直出**选股条件**与
**交易执行依据**);结果视图按 kind 分发(backtest/factor_test/selection),
非回测归档不套用回测口径
- 新增 CLI:prune_experiments(保留策略,默认 dry-run)、
restore_experiment_from_job(从 Job 副本按原 id 重建被删的历史归档,默认 dry-run)
门禁:pytest 388 passed、ruff All checks passed、tsc 0 错误、图表单测 7 passed、
next build 成功、契约脚本 verify_strategy_workspace 59/59(含按 kind 逐类验证归档页)。
90 lines
3.4 KiB
Python
90 lines
3.4 KiB
Python
"""策略 Repository 的 SQLAlchemy 实现(M8.3)。
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config 以 JSON 存(StrategyDefinition.model_dump);读取时重建实体。
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"""
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from __future__ import annotations
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import json
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from datetime import datetime
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from app.domain.entities.strategy import StrategyDefinition
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from app.infrastructure.persistence.sqlalchemy.models.strategy import StrategyModel
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class SqlAlchemyStrategyRepository:
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def __init__(self, session: Session) -> None:
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self._session = session
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def save(self, definition: StrategyDefinition) -> StrategyDefinition:
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if not definition.id:
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raise ValueError("需要 id(由调用方生成)")
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dup = self._session.scalar(
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select(StrategyModel).where(StrategyModel.name == definition.name).limit(1)
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)
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if dup is not None and dup.id != definition.id:
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raise ValueError(f"策略名已存在:{definition.name}")
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now = definition.created_at or datetime.now()
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row = self._session.get(StrategyModel, definition.id)
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config_json = json.dumps(definition.model_dump(exclude={"id", "created_at"}), ensure_ascii=False)
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if row is None:
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self._session.add(
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StrategyModel(
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id=definition.id,
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name=definition.name,
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description=definition.description,
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spec_type=definition.spec_type,
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config_json=config_json,
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version=definition.version,
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created_at=now,
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)
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)
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else:
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row.name = definition.name
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row.description = definition.description
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row.spec_type = definition.spec_type
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row.config_json = config_json
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row.version = definition.version
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self._session.flush()
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return definition
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def get(self, strategy_id: str) -> StrategyDefinition | None:
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row = self._session.get(StrategyModel, strategy_id)
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return _to_entity(row) if row else None
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def get_by_name(self, name: str) -> StrategyDefinition | None:
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row = self._session.scalar(
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select(StrategyModel).where(StrategyModel.name == name).limit(1)
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)
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return _to_entity(row) if row else None
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def list(self) -> list[StrategyDefinition]:
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rows = self._session.scalars(
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select(StrategyModel).order_by(StrategyModel.name)
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).all()
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return [_to_entity(r) for r in rows]
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def delete(self, strategy_id: str) -> bool:
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row = self._session.get(StrategyModel, strategy_id)
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if row is None:
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return False
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self._session.delete(row)
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return True
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def _to_entity(row: StrategyModel) -> StrategyDefinition:
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data = json.loads(row.config_json)
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# 列字段由 DB 行回填,避免与 config_json 重复。
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# description 必须一并回填:它是列字段(String(300)),save() 会写入,
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# 但这里若只从 config_json 里 pop 掉却不回填,读回的策略说明会恒为空串
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# (读写不对称:保存的说明看不到,策略库/编辑页都拿不到)。
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for key in ("name", "version", "description", "spec_type"):
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data.pop(key, None)
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return StrategyDefinition(
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id=row.id, name=row.name, version=row.version, description=row.description,
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created_at=row.created_at, **data,
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)
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