246 lines
11 KiB
Python
246 lines
11 KiB
Python
"""Theme and industry-chain mapping.
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The first version is intentionally deterministic and editable. It gives the
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research layer a stable vocabulary before LLM-assisted updates are introduced.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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import json
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from typing import Any
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from sqlalchemy import text
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from app.db import tables
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from app.db.database import get_db
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@dataclass(frozen=True)
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class ThemeChain:
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theme: str
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aliases: tuple[str, ...]
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nodes: tuple[str, ...]
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logic: str
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stage: str = "mid"
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lifecycle_status: str = "观察期"
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THEME_CHAINS: tuple[ThemeChain, ...] = (
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ThemeChain("AI算力", ("AI", "算力", "人工智能", "光模块", "服务器", "液冷", "PCB", "CPO"), ("光模块", "PCB", "服务器", "液冷", "IDC", "电源", "铜缆高速连接"), "AI 基础设施扩张带动上游硬件和数据中心链条。"),
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ThemeChain("机器人", ("机器人", "人形机器人", "机器人装备", "减速器", "伺服", "控制器"), ("减速器", "伺服系统", "控制器", "传感器", "本体制造", "机器视觉"), "人形机器人产业趋势扩散，重点观察核心零部件和前排整机。"),
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ThemeChain("低空经济", ("低空", "飞行汽车", "eVTOL", "通航", "无人机"), ("整机", "飞控", "电池", "空管", "材料", "运营服务"), "政策驱动低空基础设施和飞行器产业链加速。"),
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ThemeChain("创新药", ("创新药", "医药", "CXO", "生物医药", "减肥药"), ("创新药企", "CXO", "原料药", "医疗器械", "商业化平台"), "政策、临床进展和出海订单共同驱动医药成长线。"),
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ThemeChain("军工", ("军工", "航天", "航空", "卫星", "船舶"), ("航空装备", "航天电子", "卫星互联网", "船舶", "军工材料"), "订单周期、装备升级和地缘扰动共同驱动军工链。"),
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ThemeChain("固态电池", ("固态电池", "锂电", "电池", "新能源车"), ("电解质", "正极材料", "负极材料", "隔膜", "设备", "整车验证"), "电池技术迭代推动材料和设备环节重估。"),
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ThemeChain("半导体", ("半导体", "芯片", "集成电路", "存储", "先进封装"), ("设备", "材料", "设计", "制造", "封测", "存储"), "国产替代和周期复苏共同影响半导体链。"),
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ThemeChain("传媒游戏", ("传媒", "游戏", "短剧", "影视", "AIGC"), ("游戏", "影视院线", "短剧", "营销", "版权IP", "AIGC应用"), "内容供给、AI 应用和监管周期变化驱动传媒弹性。"),
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ThemeChain("化工材料", ("化工", "材料", "有机硅", "氟化工", "化纤"), ("基础化工", "新材料", "氟化工", "有机硅", "化纤", "电子化学品"), "价格周期和新材料需求共同影响化工材料链。"),
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ThemeChain("有色金属", ("有色", "铜", "铝", "黄金", "稀土", "锂"), ("铜铝", "贵金属", "稀土", "锂资源", "加工材"), "通胀预期、供需缺口和新能源需求影响资源品。"),
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ThemeChain("新能源", ("光伏", "风电", "储能", "新能源", "逆变器"), ("光伏组件", "逆变器", "储能", "风电设备", "电网设备"), "装机需求和价格出清影响新能源链条。"),
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ThemeChain("消费电子", ("消费电子", "苹果", "MR", "折叠屏", "智能穿戴"), ("结构件", "面板", "光学", "声学", "组装", "芯片"), "终端创新周期带动零部件弹性。"),
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)
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def resolve_theme(name: str) -> ThemeChain | None:
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normalized = name or ""
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for theme in THEME_CHAINS:
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if theme.theme in normalized or any(alias in normalized for alias in theme.aliases):
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return theme
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return None
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async def ensure_theme_knowledge_seeded() -> None:
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"""Seed editable theme knowledge from the built-in v1 map when empty."""
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async with get_db() as db:
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result = await db.execute(text("SELECT COUNT(*) AS count FROM theme_knowledge"))
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count = int(result.fetchone()._mapping["count"])
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if count:
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return
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now_values = []
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for index, theme in enumerate(THEME_CHAINS):
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now_values.append({
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"theme_name": theme.theme,
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"aliases_json": json.dumps(list(theme.aliases), ensure_ascii=False),
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"logic_summary": theme.logic,
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"lifecycle_status": theme.lifecycle_status,
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"stage": theme.stage,
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"is_active": True,
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"sort_order": index,
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})
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await db.execute(tables.theme_knowledge_table.insert(), now_values)
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node_values = []
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for theme_index, theme in enumerate(THEME_CHAINS):
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for node_index, node in enumerate(theme.nodes):
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node_values.append({
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"theme_name": theme.theme,
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"chain_node": node,
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"related_stocks": "[]",
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"leader_stocks": "[]",
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"node_role": "",
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"is_active": True,
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"sort_order": theme_index * 100 + node_index,
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})
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if node_values:
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await db.execute(tables.theme_chain_knowledge_table.insert(), node_values)
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await db.commit()
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async def load_theme_chain_library() -> list[dict[str, Any]]:
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await ensure_theme_knowledge_seeded()
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async with get_db() as db:
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themes_result = await db.execute(
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text(
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"SELECT * FROM theme_knowledge "
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"WHERE is_active = 1 ORDER BY sort_order ASC, id ASC"
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)
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)
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nodes_result = await db.execute(
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text(
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"SELECT * FROM theme_chain_knowledge "
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"WHERE is_active = 1 ORDER BY sort_order ASC, id ASC"
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)
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)
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node_map: dict[str, list[dict[str, Any]]] = {}
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for row in nodes_result.fetchall():
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item = dict(row._mapping)
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node_map.setdefault(str(item.get("theme_name") or ""), []).append(item)
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library = []
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for row in themes_result.fetchall():
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item = dict(row._mapping)
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theme_name = str(item.get("theme_name") or "")
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nodes = node_map.get(theme_name, [])
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library.append({
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"theme": theme_name,
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"aliases": _safe_json_list(item.get("aliases_json")),
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"logic": item.get("logic_summary") or "",
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"stage": item.get("stage") or "mid",
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"lifecycle_status": item.get("lifecycle_status") or "观察期",
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"chain_nodes": [node.get("chain_node") for node in nodes if node.get("chain_node")] or ["未归类"],
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"chain_items": [
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{
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"chain_node": node.get("chain_node") or "",
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"related_stocks": _safe_json_list(node.get("related_stocks")),
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"leader_stocks": _safe_json_list(node.get("leader_stocks")),
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"node_role": node.get("node_role") or "",
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}
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for node in nodes
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],
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})
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return library
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def resolve_theme_from_library(name: str, library: list[dict[str, Any]]) -> dict[str, Any] | None:
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normalized = name or ""
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for theme in library:
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theme_name = str(theme.get("theme") or "")
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aliases = [str(alias) for alias in theme.get("aliases", [])]
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if theme_name in normalized or any(alias and alias in normalized for alias in aliases):
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return theme
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return None
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def map_sector_to_chain(sector_name: str, leading_stocks: list[dict[str, Any]] | None = None) -> dict[str, Any]:
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theme = resolve_theme(sector_name)
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if not theme:
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return {
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"theme": sector_name or "未归类",
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"logic": "暂未命中内置产业链图谱，保留为未归类主题等待后续研究补全。",
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"chain_nodes": ["未归类"],
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"leader_stocks": leading_stocks or [],
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}
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return {
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"theme": theme.theme,
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"logic": theme.logic,
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"chain_nodes": list(theme.nodes),
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"chain_items": [
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{"chain_node": node, "related_stocks": [], "leader_stocks": [], "node_role": ""}
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for node in theme.nodes
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],
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"leader_stocks": leading_stocks or [],
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}
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def map_sector_to_chain_from_library(
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sector_name: str,
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leading_stocks: list[dict[str, Any]] | None,
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library: list[dict[str, Any]],
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) -> dict[str, Any]:
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theme = resolve_theme_from_library(sector_name, library)
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if not theme:
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return map_sector_to_chain(sector_name, leading_stocks)
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return {
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"theme": theme["theme"],
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"logic": theme["logic"] or "主题逻辑待补充。",
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"chain_nodes": theme["chain_nodes"],
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"chain_items": theme.get("chain_items", []),
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"leader_stocks": leading_stocks or [],
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"stage": theme.get("stage") or "mid",
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"lifecycle_status": theme.get("lifecycle_status") or "观察期",
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}
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def infer_chain_node(theme_name: str, stock_name: str = "", sector_name: str = "") -> str:
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theme = resolve_theme(theme_name) or resolve_theme(sector_name)
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if not theme:
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return "未归类"
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text = f"{stock_name}{sector_name}{theme_name}"
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for node in theme.nodes:
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if node in text:
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return node
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return theme.nodes[0] if theme.nodes else "未归类"
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def infer_chain_position_from_theme_view(theme_view: dict[str, Any], ts_code: str = "", stock_name: str = "") -> dict[str, str]:
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"""Infer a candidate's industry-chain node and role from editable theme knowledge."""
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chain_items = theme_view.get("chain_items") or []
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for item in chain_items:
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node = str(item.get("chain_node") or "")
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node_role = str(item.get("node_role") or "")
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if _stock_in_list(ts_code, stock_name, item.get("leader_stocks") or []):
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return {"chain_node": node or "未归类", "stock_role": node_role or "核心股"}
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if _stock_in_list(ts_code, stock_name, item.get("related_stocks") or []):
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return {"chain_node": node or "未归类", "stock_role": node_role or "相关股"}
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text_value = f"{stock_name}{theme_view.get('raw_sector', '')}{theme_view.get('theme', '')}"
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for item in chain_items:
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node = str(item.get("chain_node") or "")
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if node and node in text_value:
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return {"chain_node": node, "stock_role": str(item.get("node_role") or "环节标的")}
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nodes = theme_view.get("chain_nodes") or []
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fallback_node = str(nodes[0]) if nodes else infer_chain_node(str(theme_view.get("theme") or ""), stock_name, str(theme_view.get("raw_sector") or ""))
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return {"chain_node": fallback_node or "未归类", "stock_role": "待归类"}
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def _safe_json_list(value: Any) -> list[Any]:
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if isinstance(value, list):
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return value
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if not value:
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return []
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try:
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parsed = json.loads(str(value))
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return parsed if isinstance(parsed, list) else []
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except Exception:
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return []
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def _stock_in_list(ts_code: str, stock_name: str, values: list[Any]) -> bool:
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code = (ts_code or "").upper()
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name = stock_name or ""
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for value in values:
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if isinstance(value, dict):
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raw_code = str(value.get("ts_code") or value.get("code") or "").upper()
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raw_name = str(value.get("name") or "")
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if raw_code and raw_code == code:
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return True
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if raw_name and raw_name == name:
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return True
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else:
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text_value = str(value)
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if text_value and (text_value.upper() == code or text_value == name):
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return True
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return False
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