Simon
9cc4bfccac
- index_weight 表（migration f5e0d1c2b3a4，MySQL 已应用；index_code+date+symbol 唯一） + IndexWeight 实体 + IndexConstituentRepository（members_at：取 <=as_of 最近一期快照， Survivorship-free / 无未来成分；latest_date） - UniverseSpec.index_code + universe.filter_stocks members 交集 + resolve_members； Research/Selection/Signal/Replay 服务注入 index repo（历史成分过滤，选股/回测共用） - tests/test_index_universe.py：快照历史成分（成分变更不入早期结果）、幂等、 空快照期空集、index_code 过滤下 as_of 一致性；全量 pytest 通过
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""信号用例（M8.1）：基于选股评分排序 + 技术条件生成交易信号。
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信号与回测买入逻辑同源（同一评分引擎、同一口径），保证「为什么 BUY/SELL」可解释。
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"""
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from __future__ import annotations
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from datetime import date, timedelta
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import pandas as pd
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from app.domain.entities.selection import SelectionQuery
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from app.domain.entities.signal import SignalResult, SignalRules
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from app.domain.repositories.market import DailyBarRepository, StockRepository
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from app.quant.selection import factor_columns
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from app.quant.service import load_daily_df
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from app.quant.signal import generate_signals
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from app.quant.universe import filter_stocks, resolve_members
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class SignalService:
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def __init__(
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self,
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stock_repo: StockRepository,
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daily_repo: DailyBarRepository,
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index_repo=None,
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) -> None:
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self._stock_repo = stock_repo
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self._daily_repo = daily_repo
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self._index_repo = index_repo
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def signal(self, query: SelectionQuery, rules: SignalRules) -> SignalResult:
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as_of = query.as_of or date.today()
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stocks = filter_stocks(
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self._stock_repo.list(), query.universe, as_of=as_of,
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members=resolve_members(self._index_repo, query.universe, as_of),
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)
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if not stocks:
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return generate_signals(pd.DataFrame(), query, rules, as_of)
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columns = sorted(factor_columns(query))
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daily = load_daily_df(
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self._daily_repo,
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[s.symbol for s in stocks],
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as_of - timedelta(days=query.warmup_days),
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as_of,
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columns,
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adjust=query.price_adjustment,
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)
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return generate_signals(daily, query, rules, as_of)
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