feat: AI 自然语言选股(GLM)+ 全市场数据管道 + 远程 PostgreSQL

- 首页双入口(智能选股/策略回测):引入 vue-router,顶部导航
- 智能选股:自然语言 -> LLM 解析结构化条件(智谱 GLM,OpenAI 兼容,/v4 兼容)-> SQL 快照预筛 + pandas 指标过滤(复用 indicators 单一事实源)
- 条件模型:指标 vs 常数/指标(value_indicator,如 DIF>DEA、close<布林下轨)、lookback+match 表达连续N天/近N天任一天、市值/PE/PB/换手率快照条件、默认排除 ST/退市/北交所
- 全市场数据同步:按 trade_date 批量拉取未复权日线(与回测 candles qfq 隔离),交易日历/股票列表本地缓存,daily_basic 仅最新截面,Tushare 限频兜底(分钟级重试/小时级降级)
- 存储:DATABASE_URL 切远程 PostgreSQL(cirry.cn/stock),本地 SQLite 已移除
- .env 入库(私有仓库);smoke_test 扩展选股链路

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-14 14:49:53 +08:00
parent e0b5228008
commit 528357c3f5
29 changed files with 1765 additions and 12 deletions

View File

@@ -3,6 +3,9 @@
Candle 表设计与 TimescaleDB hypertable 完全兼容:将来在目标 PG 库执行
SELECT create_hypertable('candles', 'ts');
即可升级为时序表 + Continuous Aggregates 多周期预聚合,无需改表结构。
智能选股三表stock_basic / market_daily / daily_snapshot与回测 candles(qfq)
完全隔离:选股用未复权日线按 trade_date 全市场批量落地,避免污染回测复权缓存。
"""
from datetime import datetime
@@ -55,3 +58,75 @@ class BacktestRun(Base):
max_drawdown: Mapped[float] = mapped_column(Float, default=0.0)
sharpe: Mapped[float] = mapped_column(Float, default=0.0)
num_trades: Mapped[int] = mapped_column(Integer, default=0)
class StockBasic(Base):
"""A股股票列表stock_basic 快照;选股展示名称、排除 ST/退市/北交所的依据)。"""
__tablename__ = "stock_basic"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
ts_code: Mapped[str] = mapped_column(String(12), unique=True, index=True) # 000001.SZ
symbol: Mapped[str] = mapped_column(String(10), index=True) # 000001
name: Mapped[str] = mapped_column(String(32))
area: Mapped[str | None] = mapped_column(String(32))
industry: Mapped[str | None] = mapped_column(String(32))
market: Mapped[str | None] = mapped_column(String(32)) # 主板/创业板/科创板/北交所
exchange: Mapped[str] = mapped_column(String(8)) # SSE/SZSE/BSE
list_status: Mapped[str] = mapped_column(String(2), index=True) # L上市 D退市 P暂停
list_date: Mapped[str] = mapped_column(String(8), default="")
delist_date: Mapped[str | None] = mapped_column(String(8))
class MarketDaily(Base):
"""全市场未复权日线(选股专用,与回测 candles(qfq) 隔离)。
单位沿用 Tushare 原始vol 手、amount 千元。
"""
__tablename__ = "market_daily"
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)
open: Mapped[float] = mapped_column(Float)
high: Mapped[float] = mapped_column(Float)
low: Mapped[float] = mapped_column(Float)
close: Mapped[float] = mapped_column(Float)
pre_close: Mapped[float] = mapped_column(Float)
change: Mapped[float | None] = mapped_column(Float)
pct_chg: Mapped[float | None] = mapped_column(Float) # 日涨跌幅 %
vol: Mapped[float] = mapped_column(Float) # 手
amount: Mapped[float] = mapped_column(Float) # 千元
__table_args__ = (
UniqueConstraint("ts_code", "trade_date", name="uq_mkt_code_date"),
)
class DailySnapshot(Base):
"""每日指标快照daily_basic。total_mv/circ_mv 单位万元Tushare 原始API 层换算亿元。"""
__tablename__ = "daily_snapshot"
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)
close: Mapped[float | None] = mapped_column(Float)
turnover_rate: Mapped[float | None] = mapped_column(Float) # 换手率 %
turnover_rate_f: Mapped[float | None] = mapped_column(Float) # 自由流通换手率 %
volume_ratio: Mapped[float | None] = mapped_column(Float) # 量比
pe: Mapped[float | None] = mapped_column(Float)
pe_ttm: Mapped[float | None] = mapped_column(Float)
pb: Mapped[float | None] = mapped_column(Float)
total_mv: Mapped[float | None] = mapped_column(Float) # 总市值(万元)
circ_mv: Mapped[float | None] = mapped_column(Float) # 流通市值(万元)
__table_args__ = (
UniqueConstraint("ts_code", "trade_date", name="uq_snap_code_date"),
)
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"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
trade_date: Mapped[str] = mapped_column(String(8), unique=True, index=True) # YYYYMMDD