373 lines
13 KiB
Python
373 lines
13 KiB
Python
"""市场总览聚合 API。"""
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from __future__ import annotations
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import math
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import re
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import time
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from datetime import date
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from typing import Any
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import polars as pl
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from fastapi import APIRouter, Request
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from app.services.ext_data import ExtConfig, ExtConfigStore
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from app.services.screener import ScreenerService
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router = APIRouter(prefix="/api/overview", tags=["overview"])
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_CACHE_TTL = 5.0
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_cache: dict[str, Any] | None = None
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_cache_key: str | None = None
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_cache_ts: float = 0.0
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def invalidate_overview_cache() -> None:
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"""清空总览聚合结果缓存。
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清除数据后调用, 避免看板在 TTL 窗口内继续返回旧的聚合结果。
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"""
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global _cache, _cache_key, _cache_ts
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_cache = None
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_cache_key = None
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_cache_ts = 0.0
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CORE_INDEX_NAMES = {
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"000001.SH": "上证指数",
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"399001.SZ": "深证成指",
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"399006.SZ": "创业板指",
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"000680.SH": "科创综指",
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}
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CORE_INDEX_SYMBOLS = tuple(CORE_INDEX_NAMES.keys())
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_DIMENSION_SEP = re.compile(r"[、,，;；|/\s]+")
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def _dimension_field(config: ExtConfig, kind: str) -> str | None:
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candidates = ["概念", "concept", "theme"] if kind == "concept" else ["行业", "industry", "sector"]
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for candidate in candidates:
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needle = candidate.lower()
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for field in config.fields:
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haystack = f"{field.name} {field.label}".lower()
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if needle in haystack:
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return field.name
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return None
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def _ext_files(data_dir, config: ExtConfig) -> list[str]:
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base = data_dir / "ext_data" / config.id
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if config.mode == "timeseries":
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root = base / "timeseries"
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return [str(p) for p in sorted(root.rglob("*.parquet")) if p.is_file()]
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return [str(p) for p in sorted(base.glob("*.parquet")) if p.is_file()]
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def _read_ext_rows(data_dir, config: ExtConfig, dimension_field: str) -> list[dict]:
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files = _ext_files(data_dir, config)
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if not files:
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return []
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try:
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df = pl.read_parquet(files, hive_partitioning=True)
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except TypeError:
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try:
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df = pl.read_parquet(files)
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except Exception: # noqa: BLE001
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return []
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except Exception: # noqa: BLE001
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return []
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if df.is_empty() or dimension_field not in df.columns:
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return []
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if config.mode == "timeseries" and "date" in df.columns:
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latest = df.get_column("date").max()
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if latest is not None:
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df = df.filter(pl.col("date") == latest)
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symbol_cols = ["symbol", "code", "股票代码", "代码"]
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for mapping in (config.symbol_map, config.code_map):
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if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
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symbol_cols.append(str(mapping["col"]))
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cols = []
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for col in [dimension_field, *symbol_cols]:
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if col in df.columns and col not in cols:
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cols.append(col)
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return df.select(cols).to_dicts()
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def _dimension_values(raw: Any) -> list[str]:
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if raw is None:
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return []
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values = [v.strip() for v in _DIMENSION_SEP.split(str(raw).strip()) if v.strip()]
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return values
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def _symbol_keys(row: dict, config: ExtConfig) -> list[str]:
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fields = ["symbol", "code", "股票代码", "代码"]
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for mapping in (config.symbol_map, config.code_map):
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if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
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fields.append(str(mapping["col"]))
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keys: list[str] = []
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for field in fields:
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raw = row.get(field)
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if raw is None:
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continue
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text = str(raw).strip().upper()
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if not text:
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continue
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keys.append(text)
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if "." in text:
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keys.append(text.split(".", 1)[0])
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return keys
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def _dimension_rank(rows: list[dict], request: Request, kind: str, limit: int = 5, level: int | None = None) -> dict:
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if not rows:
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return {"leading": [], "lagging": []}
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quote_map: dict[str, dict] = {}
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for row in rows:
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symbol = str(row.get("symbol") or "").strip().upper()
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if not symbol:
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continue
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quote_map[symbol] = row
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quote_map[symbol.split(".", 1)[0]] = row
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store = ExtConfigStore(request.app.state.repo.store.data_dir)
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groups: dict[str, dict[str, dict]] = {}
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for config in store.load_all():
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field = _dimension_field(config, kind)
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if not field:
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continue
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for ext_row in _read_ext_rows(request.app.state.repo.store.data_dir, config, field):
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quote = None
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for key in _symbol_keys(ext_row, config):
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quote = quote_map.get(key)
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if quote:
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break
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if not quote:
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continue
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symbol = str(quote.get("symbol") or "")
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for value in _dimension_values(ext_row.get(field)):
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# 行业按 "-" 拆分级: "银行-银行-股份制银行" → level=2 取"银行"(二级)
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if level is not None and "-" in value:
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parts = value.split("-")
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value = parts[level - 1] if level <= len(parts) else parts[-1]
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groups.setdefault(value, {})[symbol] = quote
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items = []
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for name, by_symbol in groups.items():
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stocks = list(by_symbol.values())
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changes = [_finite(s.get("change_pct")) for s in stocks]
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changes = [v for v in changes if v is not None]
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if not changes:
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continue
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leader = max(stocks, key=lambda s: _finite(s.get("change_pct")) or -999)
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items.append({
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"name": name,
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"count": len(stocks),
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"avg_pct": sum(changes) / len(changes),
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"up_count": sum(1 for v in changes if v > 0),
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"down_count": sum(1 for v in changes if v < 0),
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"amount": sum(_finite(s.get("amount")) or 0 for s in stocks),
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"leader": {
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"symbol": leader.get("symbol"),
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"name": leader.get("name"),
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"change_pct": _finite(leader.get("change_pct")),
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},
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})
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leading = sorted(items, key=lambda x: x["avg_pct"], reverse=True)[:limit]
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lagging = sorted(items, key=lambda x: x["avg_pct"])[:limit]
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return {"leading": leading, "lagging": lagging}
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def _finite(v: Any) -> float | None:
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if v is None:
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return None
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try:
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f = float(v)
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except (TypeError, ValueError):
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return None
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return f if math.isfinite(f) else None
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def _json_safe(value: Any) -> Any:
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if isinstance(value, dict):
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return {k: _json_safe(v) for k, v in value.items()}
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if isinstance(value, list):
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return [_json_safe(v) for v in value]
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if isinstance(value, float) and not math.isfinite(value):
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return None
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return value
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def _board(symbol: str) -> str:
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if symbol.endswith(".BJ"):
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return "北交所"
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if symbol.startswith(("300", "301")):
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return "创业板"
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if symbol.startswith(("688", "689")):
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return "科创板"
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if symbol.endswith(".SH"):
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return "沪主板"
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if symbol.endswith(".SZ"):
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return "深主板"
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return "其他"
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def _score(value: float, low: float, high: float) -> int:
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if high <= low:
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return 50
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return max(0, min(100, round((value - low) / (high - low) * 100)))
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def _quote_status(request: Request) -> dict:
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qs = getattr(request.app.state, "quote_service", None)
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if not qs:
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return {"enabled": False, "running": False, "quote_age_ms": None, "is_trading_hours": False}
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return qs.status()
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def _index_quotes(request: Request, as_of: date | None = None) -> list[dict]:
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qs = getattr(request.app.state, "quote_service", None)
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rows: list[dict] = []
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if qs and as_of is None:
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df = qs.get_index_quotes(list(CORE_INDEX_SYMBOLS))
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if not df.is_empty():
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rows = df.to_dicts()
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if not rows:
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repo = getattr(request.app.state, "repo", None)
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if repo:
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placeholders = ", ".join("?" for _ in CORE_INDEX_SYMBOLS)
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try:
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db_rows = repo.execute_all(
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f"""
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WITH ranked AS (
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SELECT symbol, date, close,
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row_number() OVER (PARTITION BY symbol ORDER BY date DESC) AS rn
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FROM kline_index_daily
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WHERE symbol IN ({placeholders})
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AND (? IS NULL OR date <= ?)
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), latest AS (
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SELECT symbol,
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max(CASE WHEN rn = 1 THEN date END) AS date,
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max(CASE WHEN rn = 1 THEN close END) AS last_price,
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max(CASE WHEN rn = 2 THEN close END) AS prev_close
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FROM ranked
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WHERE rn <= 2
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GROUP BY symbol
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)
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SELECT symbol, date, last_price, prev_close
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FROM latest
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""",
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[*CORE_INDEX_SYMBOLS, as_of, as_of],
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)
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except Exception: # noqa: BLE001
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db_rows = []
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for symbol, dt, last_price, prev_close in db_rows:
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change_amount = None
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change_pct = None
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lp = _finite(last_price)
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pc = _finite(prev_close)
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if lp is not None and pc not in (None, 0):
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change_amount = lp - pc
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change_pct = change_amount / pc * 100
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rows.append({
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"symbol": symbol,
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"name": CORE_INDEX_NAMES.get(symbol),
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"date": str(dt) if dt else None,
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"last_price": lp,
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"close": lp,
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"prev_close": pc,
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"change_amount": change_amount,
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"change_pct": change_pct,
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})
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by_symbol = {r.get("symbol"): r for r in rows}
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out = []
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for symbol in CORE_INDEX_SYMBOLS:
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r = by_symbol.get(symbol, {"symbol": symbol})
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out.append({
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"symbol": symbol,
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"name": r.get("name") or CORE_INDEX_NAMES[symbol],
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"last_price": _finite(r.get("last_price") if r.get("last_price") is not None else r.get("close")),
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"change_pct": _finite(r.get("change_pct")),
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"change_amount": _finite(r.get("change_amount")),
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})
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return out
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def _top_rows(rows: list[dict], key: str, descending: bool, limit: int = 8) -> list[dict]:
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filtered = [r for r in rows if _finite(r.get(key)) is not None]
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filtered.sort(key=lambda r: _finite(r.get(key)) or 0, reverse=descending)
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return [
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{
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"symbol": r.get("symbol"),
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"name": r.get("name"),
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"close": _finite(r.get("close")),
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"change_pct": _finite(r.get("change_pct")),
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"amount": _finite(r.get("amount")),
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"turnover_rate": _finite(r.get("turnover_rate")),
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"board": _board(str(r.get("symbol") or "")),
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}
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for r in filtered[:limit]
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]
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def _pct_band_rows(values: list[float]) -> list[dict]:
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bands = [
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("<-5%", None, -0.05),
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("-5~-3%", -0.05, -0.03),
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("-3~-1%", -0.03, -0.01),
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("-1~0%", -0.01, 0),
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("0~1%", 0, 0.01),
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("1~3%", 0.01, 0.03),
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("3~5%", 0.03, 0.05),
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(">5%", 0.05, None),
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]
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total = len(values) or 1
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out = []
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for label, low, high in bands:
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count = 0
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for v in values:
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if low is None and v < high:
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count += 1
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elif high is None and v >= low:
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count += 1
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elif low is not None and high is not None and low <= v < high:
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count += 1
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out.append({"label": label, "count": count, "pct": count / total * 100})
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return out
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def _build_overview(request: Request, as_of: date | None = None) -> dict:
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"""装配市场总览(委托给 services.market_overview_builder,保持行为一致)。
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逻辑已抽离至 build_market_overview,以解耦对 Request 的依赖,
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使大盘复盘等无 Request 的调用方可复用同一装配逻辑。
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"""
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from app.services.market_overview_builder import build_market_overview
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return build_market_overview(
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repo=request.app.state.repo,
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quote_service=getattr(request.app.state, "quote_service", None),
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depth_service=getattr(request.app.state, "depth_service", None),
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as_of=as_of,
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)
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@router.get("/market")
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def market_overview(request: Request, as_of: date | None = None):
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"""总览页单次请求聚合数据，避免前端拉全市场明细后再计算。"""
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global _cache, _cache_key, _cache_ts
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now = time.time()
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cache_key = as_of.isoformat() if as_of else "latest"
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if _cache is not None and _cache_key == cache_key and (now - _cache_ts) < _CACHE_TTL:
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return _cache
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data = _build_overview(request, as_of)
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_cache = data
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_cache_key = cache_key
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_cache_ts = now
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return data
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