Simon
ef09d5b419
- DailyBarRepository.get_range_many / stream_range_many_columns 增加 adjust 参数 （默认 'none'）→ SQL 层过滤口径，消除 stock_daily 混 source/adjust 污染因子的风险 - ResearchSpec / SelectionQuery 增加 price_adjustment（none|qfq），随 config_snapshot 落库可溯源；ResearchService._load_daily 与 SelectionService 装配按口径取数 - tests/test_price_adjustment.py：repo 读取按 adjust 过滤（none/qfq 各自命中）、 spec 默认与字段记录；全量 pytest 通过
112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
"""Repository Protocol（Phase 1 数据层）。
|
||
|
||
业务层只依赖这些 Protocol；具体实现位于 infrastructure/persistence。
|
||
实体一律以 domain.entities 类型进出，禁止把 ORM Model 泄漏到上层。
|
||
"""
|
||
|
||
from __future__ import annotations
|
||
|
||
from collections.abc import Iterator, Sequence
|
||
from datetime import date
|
||
from typing import Protocol
|
||
|
||
from app.domain.entities.market import (
|
||
AdjustFactor,
|
||
DailyBar,
|
||
FinancialIndicator,
|
||
Stock,
|
||
SyncLog,
|
||
TradingCalendar,
|
||
)
|
||
|
||
|
||
class StockRepository(Protocol):
|
||
def get_by_symbol(self, symbol: str) -> Stock | None: ...
|
||
|
||
def list(self) -> list[Stock]: ...
|
||
|
||
def upsert_many(self, stocks: Sequence[Stock]) -> int:
|
||
"""批量写入，以 symbol 为幂等键，返回写入/更新的行数。"""
|
||
|
||
|
||
class TradingCalendarRepository(Protocol):
|
||
def upsert_many(self, days: Sequence[TradingCalendar]) -> int: ...
|
||
|
||
def list_range(self, start: date, end: date) -> list[TradingCalendar]: ...
|
||
|
||
def is_open(self, day: date) -> bool: ...
|
||
|
||
|
||
class DailyBarRepository(Protocol):
|
||
def upsert_many(self, bars: Sequence[DailyBar]) -> int: ...
|
||
|
||
def get_range(self, symbol: str, start: date, end: date) -> list[DailyBar]: ...
|
||
|
||
def get_range_many(
|
||
self,
|
||
symbols: Sequence[str],
|
||
start: date,
|
||
end: date,
|
||
adjust: str = "none",
|
||
) -> list[DailyBar]:
|
||
"""批量区间查询（研究装配面板用）；adjust 指定行情口径（none 不复权 / qfq）。"""
|
||
|
||
def stream_range_many_columns(
|
||
self,
|
||
symbols: Sequence[str],
|
||
start: date,
|
||
end: date,
|
||
columns: Sequence[str],
|
||
adjust: str = "none",
|
||
) -> Iterator[tuple]:
|
||
"""流式（分批 yield）返回 symbol, trade_date(iso str), 数值列(float) 元组。
|
||
|
||
研究装配大数据面板专用：只 SELECT 所需列并在 SQL 侧转 REAL，
|
||
避免 ORM 对象 / Decimal 全量物化（内存大头，见内存优化专项）。
|
||
实现可选——ResearchService 会对缺失该方法的老实现回退到 get_range_many。
|
||
"""
|
||
|
||
def latest_date(self, symbol: str) -> date | None:
|
||
"""断点续传用：该股票本地已有数据的最新交易日。"""
|
||
|
||
|
||
class AdjustFactorRepository(Protocol):
|
||
def upsert_many(self, factors: Sequence[AdjustFactor]) -> int: ...
|
||
|
||
def get_range(self, symbol: str, start: date, end: date) -> list[AdjustFactor]: ...
|
||
|
||
|
||
class FinancialRepository(Protocol):
|
||
def upsert_many(self, rows: Sequence[FinancialIndicator]) -> int: ...
|
||
|
||
def list_symbol(self, symbol: str) -> list[FinancialIndicator]:
|
||
"""该股票本地全部财务行（增量判断 / 新浪校验重叠用，量级小）。"""
|
||
|
||
def has_report_period(self, symbol: str, report_date: date) -> bool:
|
||
"""本地是否已含该报告期（最新应披露报告期是否已入库）。"""
|
||
|
||
def list_announced(
|
||
self,
|
||
symbol: str,
|
||
as_of_date: date,
|
||
report_start: date | None = None,
|
||
) -> list[FinancialIndicator]:
|
||
"""只返回 announce_date <= as_of_date 的记录 —— 未来函数红线。"""
|
||
|
||
def list_announced_many(
|
||
self,
|
||
symbols: Sequence[str],
|
||
as_of_date: date,
|
||
) -> list[FinancialIndicator]:
|
||
"""批量版：返回这些股票 announce_date <= as_of_date 的全部记录。
|
||
|
||
供选股/截面研究一次性取财务字段（调用方按需取每 symbol 最新一版）。
|
||
实现可选 —— 未提供时 SelectionService 回退逐只 list_announced。
|
||
"""
|
||
|
||
|
||
class SyncLogRepository(Protocol):
|
||
def add(self, log: SyncLog) -> SyncLog: ...
|
||
|
||
def recent(self, source: str | None = None, limit: int = 20) -> list[SyncLog]: ...
|