195 lines
8.3 KiB
Python
195 lines
8.3 KiB
Python
"""市场主线主题归一层。
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不同数据源的板块体系不一致：
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- 东方财富行业/概念
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- Tushare/同花顺行业/概念
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- 股票基础行业
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这里先用可维护的 alias 规则把它们归一成系统自己的 MarketTheme。
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后续可以把 alias 挪到数据库或配置，并让 LLM 根据复盘结果辅助维护。
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"""
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from __future__ import annotations
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import re
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from app.data.models import SectorInfo
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THEME_ALIASES: dict[str, list[str]] = {
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"power_energy": ["公用事业", "电力", "绿色电力", "风力发电", "水电", "火电", "核电", "电力行业"],
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"baijiu_consumer": ["白酒", "白酒Ⅱ", "酿酒", "酿酒概念", "食品饮料", "啤酒", "乳业"],
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"ship_military": ["航海装备", "航海装备Ⅱ", "船舶", "船舶制造", "国防军工", "军工"],
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"coal_energy": ["煤炭", "煤炭行业", "煤炭概念", "煤炭开采加工", "焦炭", "煤化工"],
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"ai_compute": ["人工智能", "算力", "服务器", "数据中心", "CPO", "液冷", "东数西算"],
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"semiconductor": ["半导体", "芯片", "集成电路", "先进封装", "存储芯片", "光刻机"],
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"robotics": ["机器人", "人形机器人", "减速器", "工业母机", "自动化设备", "专用机械"],
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"auto_chain": ["汽车", "汽车零部件", "汽车配件", "新能源车", "智能驾驶", "无人驾驶"],
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"battery_lithium": ["锂电池", "固态电池", "钠离子电池"],
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"nonferrous_metals": ["有色金属", "小金属", "贵金属", "黄金"],
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"media_games": ["传媒", "影视", "影视音像", "游戏", "短剧", "文化传媒"],
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"tourism_services": ["旅游", "酒店", "景点", "餐饮", "免税"],
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"chemical_materials": ["化工", "化学制品", "化工原料", "氟化工", "磷化工"],
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"medicine_health": ["医药", "医疗", "创新药", "中药", "医疗器械", "生物制品"],
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}
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THEME_NAMES: dict[str, str] = {
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"power_energy": "电力能源",
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"baijiu_consumer": "白酒消费",
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"ship_military": "船舶军工",
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"coal_energy": "煤炭能源",
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"ai_compute": "AI算力",
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"semiconductor": "半导体",
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"robotics": "机器人装备",
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"auto_chain": "汽车产业链",
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"battery_lithium": "锂电池",
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"nonferrous_metals": "有色金属",
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"media_games": "传媒游戏",
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"tourism_services": "旅游服务",
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"chemical_materials": "化工材料",
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"medicine_health": "医药健康",
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}
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EXCLUDED_THEME_KEYWORDS = (
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"昨日",
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"连板",
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"首板",
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"炸板",
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"涨停",
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"跌停",
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"情绪",
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"微盘",
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"昨日触板",
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"昨日涨停",
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"昨日首板",
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)
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def _unique_ordered(items: list[str]) -> list[str]:
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seen: set[str] = set()
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result: list[str] = []
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for item in items:
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value = str(item or "").strip()
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if not value or value in seen:
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continue
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seen.add(value)
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result.append(value)
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return result
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def _clean_name(name: str) -> str:
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cleaned = (name or "")
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cleaned = cleaned.replace("行业", "").replace("板块", "").replace("概念", "")
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cleaned = cleaned.replace("Ⅰ", "").replace("Ⅱ", "").replace("Ⅲ", "").replace("IV", "")
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return re.sub(r"[\s_\-]+", "", cleaned)
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def resolve_theme(name: str) -> tuple[str, str, list[str]]:
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clean = _clean_name(name)
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for theme_id, aliases in THEME_ALIASES.items():
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for alias in aliases:
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alias_clean = _clean_name(alias)
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if clean == alias_clean:
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return theme_id, THEME_NAMES[theme_id], aliases
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fallback_id = f"raw_{clean}" if clean else "unknown"
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return fallback_id, name or "未归一主题", [name] if name else []
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def apply_theme(sector: SectorInfo) -> SectorInfo:
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theme_id, theme_name, aliases = resolve_theme(sector.sector_name)
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sector.theme_id = theme_id
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sector.theme_name = theme_name
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sector.theme_aliases = [sector.sector_name] if sector.sector_name else []
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return sector
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def is_excluded_theme_name(name: str) -> bool:
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value = str(name or "").strip()
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return any(keyword in value for keyword in EXCLUDED_THEME_KEYWORDS)
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def is_valid_theme(sector: SectorInfo) -> bool:
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if not sector.theme_id:
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return False
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if sector.theme_id.startswith("raw_"):
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return False
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return not is_excluded_theme_name(sector.sector_name)
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def merge_sectors_to_themes(sectors: list[SectorInfo], limit: int = 20) -> list[SectorInfo]:
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"""把行业/概念板块合并成主题级列表。
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返回仍使用 SectorInfo，便于兼容现有推荐链路；但 sector_name 会变成主题名，
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theme_aliases 里保留原始 alias 关系，leading_stocks 合并去重。
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"""
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grouped: dict[str, SectorInfo] = {}
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for raw in sectors:
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if is_excluded_theme_name(raw.sector_name):
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continue
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sector = apply_theme(raw)
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if not is_valid_theme(sector):
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continue
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key = sector.theme_id or sector.sector_name
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pct = float(sector.realtime_pct_change if sector.realtime_pct_change is not None else sector.pct_change)
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existing = grouped.get(key)
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if existing is None:
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sector.sector_name = sector.theme_name or sector.sector_name
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sector.board_type = "theme"
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sector.sector_code = sector.theme_id or sector.sector_code
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sector.theme_aliases = _unique_ordered([raw.sector_name])
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grouped[key] = sector
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continue
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existing_pct = float(existing.realtime_pct_change if existing.realtime_pct_change is not None else existing.pct_change)
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existing.realtime_pct_change = max(existing_pct, pct) if existing.realtime_pct_change is not None or sector.realtime_pct_change is not None else None
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existing.pct_change = max(existing.pct_change, sector.pct_change)
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existing.heat_score = max(existing.heat_score, sector.heat_score)
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existing.capital_inflow += sector.capital_inflow
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existing.limit_up_count += sector.limit_up_count
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existing.member_count += sector.member_count
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existing.days_continuous = max(existing.days_continuous, sector.days_continuous)
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existing.turnover_avg = max(existing.turnover_avg, sector.turnover_avg)
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existing.main_force_ratio = max(existing.main_force_ratio, sector.main_force_ratio)
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existing.realtime_amount = (existing.realtime_amount or 0) + (sector.realtime_amount or 0)
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existing.realtime_up_count = (existing.realtime_up_count or 0) + (sector.realtime_up_count or 0)
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existing.realtime_down_count = (existing.realtime_down_count or 0) + (sector.realtime_down_count or 0)
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existing.theme_aliases = _unique_ordered([*(existing.theme_aliases or []), raw.sector_name])
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existing.is_realtime = existing.is_realtime or sector.is_realtime
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if existing.data_mode == "daily_snapshot" and sector.data_mode != "daily_snapshot":
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existing.data_mode = sector.data_mode
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if existing.data_status != "fresh" and sector.data_status == "fresh":
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existing.data_status = "fresh"
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existing.source_detail = sector.source_detail
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elif existing.data_status == "fresh" and sector.data_status != "fresh":
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pass
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elif existing.data_status != sector.data_status:
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existing.data_status = "mixed"
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existing.source_detail = "mixed_status"
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if existing.source != sector.source:
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existing.source = "mixed"
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leaders = {}
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for item in (existing.leading_stocks_realtime or existing.leading_stocks or []):
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if item.get("ts_code"):
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leaders[item["ts_code"]] = item
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for item in (sector.leading_stocks_realtime or sector.leading_stocks or []):
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if item.get("ts_code"):
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leaders[item["ts_code"]] = item
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merged_leaders = sorted(leaders.values(), key=lambda item: float(item.get("pct_chg", 0) or 0), reverse=True)[:5]
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existing.leading_stocks_realtime = merged_leaders
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existing.leading_stocks = merged_leaders
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if existing.stage == "end" or (existing.stage == "late" and sector.stage in ("early", "mid")):
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existing.stage = sector.stage
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result = list(grouped.values())
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result.sort(
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key=lambda item: (
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float(item.realtime_pct_change if item.realtime_pct_change is not None else item.pct_change),
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float(item.realtime_amount or 0),
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),
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reverse=True,
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)
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return result[:limit]
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