Files
stock/serve/backend/app/api/screener.py
T
fish 267b8557e8 概念/行业分析添加日期选择功能
- backend: market_snapshot 支持可选 as_of 参数
- frontend: 两页加 DatePicker,按选定日期查询数据

Co-Authored-By: Claude <noreply@anthropic.com>
2026-07-06 14:58:31 +08:00

623 lines
24 KiB
Python

"""Screener API。"""
from __future__ import annotations
import logging
import math
import re
import time
from dataclasses import asdict
from datetime import date, datetime
from typing import Any, Optional
from fastapi import APIRouter, HTTPException, Query, Request
from pydantic import BaseModel
from app.services.screener import PRESET_STRATEGIES, ScreenerService
from app.services import strategy_cache
from app.strategy import config as strategy_config
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/screener", tags=["screener"])
class CustomRequest(BaseModel):
conditions: list[str]
order_by: Optional[str] = None
limit: int = 30
pool: Optional[list[str]] = None
as_of: Optional[date] = None
ext_columns: Optional[str] = None
class PresetRequest(BaseModel):
strategy_id: str
pool: Optional[list[str]] = None
as_of: Optional[date] = None
ext_columns: Optional[str] = None
def _safe(result_dict: dict) -> dict:
"""sanitize for JSON(NaN / Inf → None)."""
rows = result_dict.get("rows", [])
for r in rows:
for k, v in list(r.items()):
if isinstance(v, float) and not math.isfinite(v):
r[k] = None
return result_dict
_EXT_IDENT_RE = re.compile(r"^[A-Za-z0-9_]+$")
def _safe_ext_value(value: Any) -> Any:
if isinstance(value, float) and not math.isfinite(value):
return None
if isinstance(value, (date, datetime)):
return value.isoformat()
return value
def _quote_ident(name: str) -> str:
return '"' + name.replace('"', '""') + '"'
def _load_ext_value_maps(repo, ext_columns: Optional[str]) -> dict[str, dict[str, Any]]:
"""按请求加载扩展列,返回 {输出列名: {symbol: value}}。
策略结果缓存是共享文件,不能被不同 ext_columns 组合污染;因此扩展列只在
返回前通过该投影映射追加到结果副本中。
"""
ext_specs = _parse_ext_columns(ext_columns) if ext_columns else []
if not ext_specs:
return {}
import polars as pl
from app.api.ext_data import _read_ext_dataframe
from app.services.ext_data import ExtConfigStore
db = repo.store.db
data_dir = repo.store.data_dir
ext_store = ExtConfigStore(data_dir)
configs = {c.id: c for c in ext_store.load_all()}
value_maps: dict[str, dict[str, Any]] = {}
for config_id, field_name in ext_specs:
out_col = f"{config_id}__{field_name}"
cfg = configs.get(config_id)
try:
if cfg:
# 时序扩展表只取最新分区,避免历史分区把同一 symbol JOIN 放大。
ext_df, _ = _read_ext_dataframe(cfg, data_dir)
else:
view_name = f"ext_{config_id}"
ext_df = pl.from_arrow(db.query(
f"SELECT symbol, {_quote_ident(field_name)} FROM {view_name}"
).arrow())
if ext_df.is_empty() or "symbol" not in ext_df.columns or field_name not in ext_df.columns:
continue
ext_df = ext_df.select(["symbol", field_name]).unique(subset=["symbol"], keep="last")
value_maps[out_col] = {
str(row["symbol"]): _safe_ext_value(row.get(field_name))
for row in ext_df.to_dicts()
if row.get("symbol")
}
except Exception as e: # noqa: BLE001
logger.debug("screener ext column join skipped for %s.%s: %s", config_id, field_name, e)
return value_maps
def _row_with_ext(row: dict, ext_values: dict[str, dict[str, Any]], symbol: Optional[str] = None) -> dict:
next_row = dict(row)
sym = symbol or next_row.get("symbol")
for out_col, value_map in ext_values.items():
next_row[out_col] = value_map.get(str(sym)) if sym else None
return next_row
def _rows_with_ext(rows: list[dict], ext_values: dict[str, dict[str, Any]]) -> list[dict]:
if not ext_values:
return rows
return [_row_with_ext(r, ext_values) for r in rows]
def _result_with_ext(result_dict: dict, ext_values: dict[str, dict[str, Any]]) -> dict:
if not ext_values:
return result_dict
return {**result_dict, "rows": _rows_with_ext(result_dict.get("rows", []), ext_values)}
def _results_with_ext(results: dict[str, dict], ext_values: dict[str, dict[str, Any]]) -> dict[str, dict]:
if not ext_values:
return results
return {sid: _result_with_ext(r, ext_values) for sid, r in results.items()}
def _cache_payload_with_ext(cached: dict, ext_values: dict[str, dict[str, Any]]) -> dict:
if not ext_values:
return cached
payload = dict(cached)
payload["results"] = _results_with_ext(cached.get("results", {}), ext_values)
ever_rows = cached.get("today_ever_rows")
if isinstance(ever_rows, dict):
enriched_ever: dict[str, dict[str, dict]] = {}
for sid, sym_map in ever_rows.items():
if not isinstance(sym_map, dict):
continue
enriched_ever[sid] = {
sym: _row_with_ext(row, ext_values, symbol=sym)
for sym, row in sym_map.items()
if isinstance(row, dict)
}
payload["today_ever_rows"] = enriched_ever
return payload
def _update_cache_strategy(data_dir, as_of: str, strategy_id: str, safe_data: dict) -> None:
"""单跑后更新缓存中该策略的结果,保持缓存与最新计算一致。"""
from app.services import strategy_cache
cached = strategy_cache.read_cache(data_dir)
if cached and cached.get("as_of") == as_of:
results = cached.get("results", {})
results[strategy_id] = {
"total": safe_data.get("total", 0),
"as_of": as_of,
"rows": safe_data.get("rows", []),
}
strategy_cache.write_cache(data_dir, as_of, results)
@router.get("/strategies")
def strategies(request: Request):
"""策略清单(内置 + 自定义 + AI)。"""
data_dir = request.app.state.repo.store.data_dir
presets = []
seen_ids: set[str] = set()
# 内置策略
for k, v in PRESET_STRATEGIES.items():
overrides = strategy_config.load_override(data_dir, k)
name = (overrides.get("name") or v["name"]) if overrides else v["name"]
desc = (overrides.get("description") or v["description"]) if overrides else v["description"]
presets.append({"id": k, "name": name, "description": desc, "source": "builtin"})
seen_ids.add(k)
# 自定义/AI 策略(不在 PRESET_STRATEGIES 中的)
engine = getattr(request.app.state, "strategy_engine", None)
if engine:
for meta in engine.list_strategies():
sid = meta["id"]
if sid not in seen_ids:
overrides = strategy_config.load_override(data_dir, sid)
name = (overrides.get("name") or meta["name"]) if overrides else meta["name"]
desc = (overrides.get("description") or meta.get("description", "")) if overrides else meta.get("description", "")
presets.append({"id": sid, "name": name, "description": desc, "source": meta.get("source", "custom")})
seen_ids.add(sid)
return {"presets": presets}
@router.post("/run")
def run_custom(req: CustomRequest, request: Request):
repo = request.app.state.repo
svc = ScreenerService(repo)
as_of = req.as_of or svc.latest_date()
if not as_of:
raise HTTPException(status_code=400,
detail="无可用数据日期 — enriched 表为空,请先运行盘后管道")
result = svc.run(
as_of=as_of,
conditions=req.conditions,
order_by=req.order_by,
limit=req.limit,
pool=req.pool,
)
safe_data = _safe(asdict(result))
ext_values = _load_ext_value_maps(repo, req.ext_columns)
return _result_with_ext(safe_data, ext_values)
@router.post("/run_preset")
def run_preset(req: PresetRequest, request: Request):
repo = request.app.state.repo
svc = ScreenerService(repo)
as_of = req.as_of or svc.latest_date()
if not as_of:
raise HTTPException(status_code=400, detail="无可用数据日期")
# 加载用户保存的策略配置
data_dir = request.app.state.repo.store.data_dir
ext_values = _load_ext_value_maps(repo, req.ext_columns)
overrides = strategy_config.load_override(data_dir, req.strategy_id)
bf = overrides.get("basic_filter") if overrides else None
dl = overrides.get("display_limit") if overrides else None
if dl is None and overrides and "display_limit" in overrides:
dl = 0
# 内置策略
if req.strategy_id in PRESET_STRATEGIES:
try:
result = svc.run_preset(req.strategy_id, as_of=as_of, pool=req.pool, basic_filter=bf, display_limit=dl)
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e)) from e
safe_data = _safe(asdict(result))
_update_cache_strategy(data_dir, str(as_of), req.strategy_id, safe_data)
return _result_with_ext(safe_data, ext_values)
# 自定义/AI 策略 — 通过 StrategyEngine 执行
engine = getattr(request.app.state, "strategy_engine", None)
if not engine:
raise HTTPException(status_code=404, detail=f"策略引擎未初始化或策略 {req.strategy_id} 不存在")
try:
result = engine.run(req.strategy_id, as_of, pool=req.pool, overrides=overrides or None)
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e)) from e
data = asdict(result)
if dl is not None and dl > 0:
data["rows"] = data["rows"][:dl]
data["total"] = min(data["total"], dl)
# 单跑后更新缓存中该策略的结果(保持缓存最新)
safe_data = _safe(data)
_update_cache_strategy(data_dir, str(as_of), req.strategy_id, safe_data)
return _result_with_ext(safe_data, ext_values)
@router.get("/cached")
def get_cached(
request: Request,
ext_columns: Optional[str] = Query(None, description="逗号分隔: config_id.field_name"),
):
"""读取策略结果缓存。
- 盘后缓存 (strategy_cache.json): run_all 写入, 页面秒加载用。
"""
data_dir = request.app.state.repo.store.data_dir
cached = strategy_cache.read_cache(data_dir)
if cached is None:
cached = {"as_of": None, "results": {}, "updated_at": None}
# 无任何数据 → 返回空标记, 前端据此提示
if not cached.get("results") and cached.get("as_of") is None:
return {"as_of": None, "results": {}, "updated_at": None}
ext_values = _load_ext_value_maps(request.app.state.repo, ext_columns)
return _cache_payload_with_ext(cached, ext_values)
@router.get("/market-snapshot")
def market_snapshot(request: Request, as_of: date | None = None):
"""全市场轻量行情快照(可选指定日期),供板块/概念聚合分析使用。"""
import polars as pl
repo = request.app.state.repo
svc = ScreenerService(repo)
if as_of is None:
as_of = svc.latest_date()
if not as_of:
return {"as_of": None, "rows": []}
df = svc._load_enriched_for_date(as_of)
if df.is_empty():
return {"as_of": str(as_of), "rows": []}
if "close" in df.columns and "total_shares" in df.columns and "market_cap" not in df.columns:
df = df.with_columns((pl.col("close") * pl.col("total_shares")).alias("market_cap"))
if "close" in df.columns and "float_shares" in df.columns and "float_market_cap" not in df.columns:
df = df.with_columns((pl.col("close") * pl.col("float_shares")).alias("float_market_cap"))
cols = [
"symbol", "name", "close", "change_pct", "amount", "volume",
"turnover_rate", "vol_ratio_5d", "total_shares", "float_shares",
"market_cap", "float_market_cap", "consecutive_limit_ups",
]
df = df.select([c for c in cols if c in df.columns])
rows = df.to_dicts()
for r in rows:
for k, v in list(r.items()):
if isinstance(v, float) and not math.isfinite(v):
r[k] = None
return {"as_of": str(as_of), "rows": rows}
@router.post("/run_all")
def run_all(request: Request, body: Optional[dict] = None):
"""批量运行指定策略,只返回每个策略的命中数。
优化: 从 enriched 读取一次目标日期数据, 所有策略共享。
body.strategy_ids: 只跑指定的策略 ID 列表, 为空则跑全部。
"""
from datetime import date as date_type
t_total = time.perf_counter()
body = body or {}
repo = request.app.state.repo
svc = ScreenerService(repo)
# 解析日期
raw_date = body.get("as_of")
if raw_date:
as_of = date_type.fromisoformat(str(raw_date)) if isinstance(raw_date, str) else raw_date
else:
as_of = svc.latest_date()
if not as_of:
return {"as_of": None, "results": {}}
# 一次读取目标日期的全部数据
t0 = time.perf_counter()
precomputed = svc._load_enriched_for_date(as_of)
logger.info("run_all: _load_enriched_for_date took %.1fms", (time.perf_counter() - t0) * 1000)
results: dict[str, dict] = {}
data_dir = request.app.state.repo.store.data_dir
# 收集需要运行的策略 ID (如果指定了 strategy_ids 则只跑这些)
requested_ids = body.get("strategy_ids")
all_ids = list(PRESET_STRATEGIES.keys())
engine = getattr(request.app.state, "strategy_engine", None)
if engine:
for meta in engine.list_strategies():
sid = meta["id"]
if sid not in PRESET_STRATEGIES:
all_ids.append(sid)
if requested_ids and isinstance(requested_ids, list):
id_set = set(requested_ids)
all_ids = [sid for sid in all_ids if sid in id_set]
if not all_ids:
return {"as_of": str(as_of), "results": {}}
# 批量预加载所有 override 配置
t0 = time.perf_counter()
all_overrides = strategy_config.list_overrides(data_dir)
logger.info("run_all: list_overrides took %.1fms (%d overrides)", (time.perf_counter() - t0) * 1000, len(all_overrides))
# 历史策略: 只在需要时加载 (只加载 all_ids 中包含的 filter_history 策略)
t0 = time.perf_counter()
shared_history = None
id_set = set(all_ids)
if engine:
history_strats = [
(sid, s) for sid, s in engine._strategies.items()
if s.filter_history_fn and sid in id_set
]
if history_strats:
max_lb = min(max(s.lookback_days for _, s in history_strats), 30)
shared_history = svc._load_enriched_history(as_of, max(1, max_lb))
else:
history_strats = []
logger.info("run_all: _load_enriched_history took %.1fms (history_strats=%d)", (time.perf_counter() - t0) * 1000, len(history_strats))
for sid in all_ids:
try:
overrides = all_overrides.get(sid, {})
bf = overrides.get("basic_filter") if overrides else None
dl = overrides.get("display_limit") if overrides else None
if dl is None and overrides and "display_limit" in overrides:
dl = 0
if sid in PRESET_STRATEGIES:
r = svc.run_preset(sid, as_of=as_of, precomputed=precomputed, basic_filter=bf, display_limit=dl)
else:
r = engine.run(
sid, as_of, overrides=overrides or None,
precomputed=precomputed, precomputed_history=shared_history,
)
if dl is not None and dl > 0:
r.rows = r.rows[:dl]
r.total = min(r.total, dl)
safe_rows = _safe(asdict(r)).get("rows", [])
results[sid] = {"total": r.total, "as_of": str(as_of), "rows": safe_rows}
except (ValueError, Exception):
continue
elapsed = (time.perf_counter() - t_total) * 1000
logger.info("run_all: total took %.1fms (%d strategies)", elapsed, len(all_ids))
# 写入策略缓存 (供页面秒加载)
if results:
try:
strategy_cache.write_cache(data_dir, str(as_of), results)
except Exception: # noqa: BLE001
pass
ext_values = _load_ext_value_maps(repo, body.get("ext_columns"))
return {"as_of": str(as_of), "results": _results_with_ext(results, ext_values)}
@router.get("/limit-ladder")
def limit_ladder(
request: Request,
as_of: Optional[date] = None,
direction: str = Query("up", description="up=涨停梯队 | down=跌停梯队"),
ext_columns: Optional[str] = Query(None, description="逗号分隔: config_id.field_name"),
):
"""连板/连跌梯队 — 按连板数分组, 含三状态。
返回: tiers = [{ boards, count, stocks: [{symbol,name,change_pct,status,...}] }]
direction=up (默认):
status: limit_up=涨停 | broken=炸板(摸板未封) | failed=断板(晋级失败)
direction=down:
status: limit_down=跌停 | recovery=翘板(跌停后回升,含收阳条件) | failed=止跌(昨日跌停今日未跌停也未翘板)
ext_columns: 动态 JOIN 扩展数据, 如 "concept.concept,industry.industry"
"""
from datetime import timedelta
import polars as pl
is_down = direction == "down"
# 按 direction 参数化字段映射
if is_down:
sig_col = "signal_limit_down"
consec_col = "consecutive_limit_downs"
broken_col = "signal_limit_down_recovery"
status_main, status_broken, status_failed = "limit_down", "recovery", "failed"
else:
sig_col = "signal_limit_up"
consec_col = "consecutive_limit_ups"
broken_col = "signal_broken_limit_up"
status_main, status_broken, status_failed = "limit_up", "broken", "failed"
repo = request.app.state.repo
svc = ScreenerService(repo)
as_of = as_of or svc.latest_date()
if not as_of:
raise HTTPException(status_code=400, detail="无可用数据日期")
df = svc._load_enriched_for_date(as_of)
if df.is_empty():
return {"as_of": str(as_of), "tiers": [], "counts": {"up": 0, "down": 0}}
# 双方向涨跌停计数(不论当前 direction, 前端始终同时显示)
count_up_raw = int(df.filter(pl.col("signal_limit_up").fill_null(False)).height) if "signal_limit_up" in df.columns else 0
count_down_raw = int(df.filter(pl.col("signal_limit_down").fill_null(False)).height) if "signal_limit_down" in df.columns else 0
count_up = count_up_raw
count_down = count_down_raw
# 加载前一日数据获取 prev consecutive_limit_ups/downs
prev_consec: pl.DataFrame = pl.DataFrame()
for delta in range(1, 10):
candidate = as_of - timedelta(days=delta)
df_prev = svc._load_enriched_for_date(candidate)
if not df_prev.is_empty() and consec_col in df_prev.columns:
prev_consec = df_prev.select(
"symbol",
pl.col(consec_col).alias("prev_consec"),
)
break
if not prev_consec.is_empty():
df = df.join(prev_consec, on="symbol", how="left")
else:
df = df.with_columns(pl.lit(0).cast(pl.UInt32).alias("prev_consec"))
# 表达式
is_limit = pl.col(sig_col).fill_null(False) if sig_col in df.columns else pl.lit(False)
is_broken = pl.col(broken_col).fill_null(False) if broken_col in df.columns else pl.lit(False)
consec = pl.col(consec_col).fill_null(0) if consec_col in df.columns else pl.lit(0)
prev_c = pl.col("prev_consec").fill_null(0)
# 计算 status + boards (结构涨跌停对称, 仅字段与字面量不同)
is_failed = ~is_limit & ~is_broken & (prev_c > 0)
df = df.with_columns([
pl.when(is_limit).then(pl.lit(status_main))
.when(is_broken).then(pl.lit(status_broken))
.when(is_failed).then(pl.lit(status_failed))
.otherwise(None).alias("status"),
pl.when(is_limit).then(consec)
.when(is_broken | is_failed).then(prev_c + 1)
.otherwise(0).cast(pl.UInt32).alias("boards"),
])
df = df.filter(pl.col("status").is_not_null() & (pl.col("boards") > 0))
# Add null columns for sealed_status and sealed_vol (no longer used)
df = df.with_columns(
pl.lit(None).alias("sealed_status"),
pl.lit(None).alias("sealed_vol"),
)
# 动态 JOIN 扩展数据
ext_specs = _parse_ext_columns(ext_columns) if ext_columns else []
ext_col_names: list[str] = []
if ext_specs:
db = repo.store.db
data_dir = repo.store.data_dir
from app.services.ext_data import ExtConfigStore
ext_store = ExtConfigStore(data_dir)
configs = {c.id: c for c in ext_store.load_all()}
for config_id, field_name in ext_specs:
view_name = f"ext_{config_id}"
ext_col_name = f"{config_id}__{field_name}"
try:
ext_df = pl.from_arrow(db.query(
f"SELECT symbol, \"{field_name}\" FROM {view_name}"
).arrow())
if not ext_df.is_empty() and "symbol" in ext_df.columns:
ext_df = ext_df.rename({field_name: ext_col_name})
df = df.join(ext_df.select(["symbol", ext_col_name]), on="symbol", how="left")
ext_col_names.append(ext_col_name)
except Exception:
cfg = configs.get(config_id)
if cfg:
try:
from app.api.ext_data import _parquet_glob
glob = _parquet_glob(cfg, data_dir)
ext_df = pl.read_parquet(glob)
if not ext_df.is_empty() and "symbol" in ext_df.columns and field_name in ext_df.columns:
ext_df = ext_df.select(["symbol", field_name]).rename({field_name: ext_col_name})
df = df.join(ext_df, on="symbol", how="left")
ext_col_names.append(ext_col_name)
except Exception:
pass
# 选择输出列
cols = ["symbol", "name", "close", "change_pct", "boards", "status", consec_col, "sealed_status", "sealed_vol"] + ext_col_names
df = df.select([c for c in cols if c in df.columns])
# 排序: boards 降序, status 按主状态→炸/翘→断/止
status_order = pl.when(pl.col("status") == status_main).then(0)
status_order = status_order.when(pl.col("status") == status_broken).then(1)
status_order = status_order.otherwise(2).alias("_status_order")
df = df.with_columns(status_order).sort(["boards", "_status_order"], descending=[True, False]).drop("_status_order")
rows = df.to_dicts()
for r in rows:
for k, v in list(r.items()):
if isinstance(v, float) and not math.isfinite(v):
r[k] = None
# 按 boards 分组
tiers: dict[int, list] = {}
for r in rows:
n = int(r.get("boards") or 0)
tiers.setdefault(n, []).append(r)
tier_list = [
{"boards": n, "count": len(stocks), "stocks": stocks}
for n, stocks in sorted(tiers.items(), key=lambda x: -x[0])
]
return {
"as_of": str(as_of),
"tiers": tier_list,
"counts": {"up": count_up, "down": count_down},
"counts_raw": {"up": count_up_raw, "down": count_down_raw},
}
def _parse_ext_columns(ext_columns: str) -> list[tuple[str, str]]:
"""解析 'config_id1.field1,config_id2.field2' 为 [(config_id, field_name), ...]。"""
result = []
for part in ext_columns.split(","):
part = part.strip()
if "." not in part:
continue
config_id, field_name = part.split(".", 1)
config_id = config_id.strip()
field_name = field_name.strip()
if not config_id or not field_name:
continue
if not _EXT_IDENT_RE.match(config_id) or "\x00" in field_name:
continue
result.append((config_id, field_name))
return result