mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
synced 2026-09-12 21:24:16 +08:00
kevin9327
e12e0c7d02
import-csv / import-image 原先 `await file.read()` 之后才比较长度, 上限只在 整个文件进入内存之后生效, 与 issue #204 修复前的扩展数据上传同类。新增 _read_upload_capped 分块读取, 累计超过上限的那一块立即返回 400 并停止读取, 状态码与文案不变; 内存占用不超过上限 + 一块。 测试: 新增 5 例 (含「越限后不再继续读取」的字节计数断言); test_watchlist_csv 的上传 mock 改为像真实 UploadFile 一样读尽返回 b""。
548 lines
21 KiB
Python
548 lines
21 KiB
Python
"""自选股 API。"""
|
||
from __future__ import annotations
|
||
|
||
import logging
|
||
import math
|
||
import time
|
||
from datetime import date
|
||
from typing import Callable
|
||
|
||
import anyio
|
||
import polars as pl
|
||
from fastapi import APIRouter, File, HTTPException, Query, Request, UploadFile
|
||
from pydantic import BaseModel
|
||
|
||
from app.db_safe import is_valid_ext_ident, quote_ident
|
||
from app.services import watchlist
|
||
from app.services.watchlist_csv import import_watchlist_codes, import_watchlist_csv
|
||
from app.services.watchlist_ocr import import_watchlist_image
|
||
from app.services.watchlist_ocr.provider import get_ocr_provider
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
router = APIRouter(prefix="/api/watchlist", tags=["watchlist"])
|
||
|
||
_MAX_IMPORT_IMAGE_BYTES = 12 * 1024 * 1024 # 12MB
|
||
_IMPORT_IMAGE_TYPES = {
|
||
"image/jpeg",
|
||
"image/jpg",
|
||
"image/png",
|
||
"image/webp",
|
||
"image/bmp",
|
||
"image/gif",
|
||
}
|
||
# OCR 独立并发上限：避免多张大图同时解码 + 多 Tesseract 子进程
|
||
_OCR_LIMITER = anyio.CapacityLimiter(2)
|
||
# CSV/TXT 导入：文本远小于截图，上限 5MB 足够
|
||
_MAX_IMPORT_CSV_BYTES = 5 * 1024 * 1024
|
||
_IMPORT_CSV_TYPES = {
|
||
"text/csv",
|
||
"text/plain",
|
||
"application/csv",
|
||
}
|
||
# 上传分块读取粒度 (与 ext_data 上传一致)
|
||
_UPLOAD_CHUNK_BYTES = 1024 * 1024
|
||
|
||
|
||
async def _read_upload_capped(file: UploadFile, max_bytes: int, too_large: str) -> bytes:
|
||
"""分块读取上传内容, 累计超过 max_bytes 立即拒绝(400), 返回完整字节。
|
||
|
||
与 ext_data._write_upload_capped 同类保护: 一次性 `await file.read()` 会先把整个
|
||
文件读入内存再比较长度, 上限在那之后才生效, 一个远超上限的上传照样把进程内存
|
||
顶满; 分块读取在越过上限的那一块就停止, 内存占用不超过上限 + 一块。
|
||
"""
|
||
chunks: list[bytes] = []
|
||
total = 0
|
||
while True:
|
||
chunk = await file.read(_UPLOAD_CHUNK_BYTES)
|
||
if not chunk:
|
||
break
|
||
total += len(chunk)
|
||
if total > max_bytes:
|
||
raise HTTPException(400, too_large)
|
||
chunks.append(chunk)
|
||
return b"".join(chunks)
|
||
|
||
|
||
class AddRequest(BaseModel):
|
||
symbol: str
|
||
note: str = ""
|
||
group_id: str | None = None
|
||
|
||
|
||
class BatchAddRequest(BaseModel):
|
||
symbols: list[str]
|
||
note: str = ""
|
||
group_id: str | None = None
|
||
group_ids: list[str] | None = None
|
||
|
||
|
||
class GroupNameRequest(BaseModel):
|
||
name: str
|
||
color: str | None = None
|
||
|
||
|
||
class GroupReorderRequest(BaseModel):
|
||
ordered_ids: list[str]
|
||
|
||
|
||
class GroupAssignRequest(BaseModel):
|
||
group_id: str | None = None
|
||
|
||
|
||
class ImportCodesRequest(BaseModel):
|
||
text: str
|
||
|
||
|
||
def _with_names(rows: list[dict], request: Request) -> list[dict]:
|
||
if not rows:
|
||
return rows
|
||
try:
|
||
# 股票 + ETF 名称统一由 repo.get_name_map 解析, 自选列表可混合持有
|
||
name_by_symbol = request.app.state.repo.get_name_map([r.get("symbol") for r in rows])
|
||
if not name_by_symbol:
|
||
return rows
|
||
return [{**row, "name": name_by_symbol.get(row.get("symbol"))} for row in rows]
|
||
except Exception as e: # noqa: BLE001
|
||
logger.debug("attach watchlist names failed: %s", e)
|
||
return rows
|
||
|
||
|
||
@router.get("")
|
||
def list_all(request: Request):
|
||
return {"symbols": _with_names(watchlist.list_symbols(), request)}
|
||
|
||
|
||
@router.post("")
|
||
def add_one(req: AddRequest, request: Request):
|
||
try:
|
||
rows = watchlist.add(req.symbol, req.note, req.group_id)
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.post("/batch")
|
||
def add_batch(req: BatchAddRequest, request: Request):
|
||
try:
|
||
rows, added = watchlist.add_batch(
|
||
req.symbols,
|
||
req.note,
|
||
group_id=req.group_id,
|
||
group_ids=req.group_ids,
|
||
)
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"symbols": _with_names(rows, request), "added": added}
|
||
|
||
|
||
@router.get("/groups")
|
||
def list_groups():
|
||
return {"groups": watchlist.list_groups()}
|
||
|
||
|
||
@router.post("/groups")
|
||
def create_group(req: GroupNameRequest):
|
||
try:
|
||
groups, group = watchlist.create_group(req.name, req.color)
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"groups": groups, "group": group}
|
||
|
||
|
||
@router.put("/groups/reorder")
|
||
def reorder_groups(req: GroupReorderRequest):
|
||
"""重排分组前后顺序 (json 数组顺序即定义顺序, 侧边栏/标签栏/分组视图共用)。"""
|
||
try:
|
||
groups = watchlist.reorder_groups(req.ordered_ids)
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"groups": groups}
|
||
|
||
|
||
@router.put("/groups/{group_id}")
|
||
def rename_group(group_id: str, req: GroupNameRequest):
|
||
try:
|
||
groups = watchlist.rename_group(group_id, req.name, req.color)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选分组不存在") from e
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"groups": groups}
|
||
|
||
|
||
@router.delete("/groups/{group_id}")
|
||
def delete_group(group_id: str, request: Request):
|
||
try:
|
||
groups, rows = watchlist.delete_group(group_id)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选分组不存在") from e
|
||
return {"groups": groups, "symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.post("/groups/{group_id}/clear")
|
||
def clear_group(group_id: str, request: Request):
|
||
"""清空分组成员:把该分组内所有股票转为未分组,保留分组定义。"""
|
||
try:
|
||
rows = watchlist.clear_group(group_id)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选分组不存在") from e
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.get("/ocr-status")
|
||
def ocr_status():
|
||
"""当前 OCR 引擎是否可用（前端可据此提示安装依赖）。"""
|
||
provider = get_ocr_provider()
|
||
return {"provider": provider.name, "available": provider.available()}
|
||
|
||
|
||
@router.post("/import-image")
|
||
async def import_from_image(request: Request, file: UploadFile = File(...)):
|
||
"""从自选截图识别股票代码，返回候选列表（不自动写入自选）。"""
|
||
content_type = (file.content_type or "").split(";")[0].strip().lower()
|
||
filename = (file.filename or "").lower()
|
||
# 严格白名单：不接受任意 image/*（如 image/svg+xml）
|
||
ok_type = content_type in _IMPORT_IMAGE_TYPES
|
||
ok_ext = filename.endswith((".jpg", ".jpeg", ".png", ".webp", ".bmp", ".gif"))
|
||
if not ok_type and not ok_ext:
|
||
raise HTTPException(400, "仅支持 JPG / PNG / WebP / BMP / GIF 图片")
|
||
|
||
data = await _read_upload_capped(file, _MAX_IMPORT_IMAGE_BYTES, "图片过大（上限 12MB）")
|
||
if not data:
|
||
raise HTTPException(400, "空文件")
|
||
|
||
existing = {r["symbol"] for r in watchlist.list_symbols()}
|
||
data_dir = request.app.state.repo.store.data_dir
|
||
try:
|
||
# OCR 为同步 CPU/子进程；独立 limiter 限制并发，避免卡住事件循环（行情 SSE 等）
|
||
result = await anyio.to_thread.run_sync(
|
||
lambda: import_watchlist_image(data, data_dir, existing_symbols=existing),
|
||
limiter=_OCR_LIMITER,
|
||
)
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
except RuntimeError as e:
|
||
raise HTTPException(503, str(e)) from e
|
||
except Exception as e: # noqa: BLE001
|
||
logger.exception("watchlist import-image failed")
|
||
raise HTTPException(500, f"识别失败: {e}") from e
|
||
|
||
# 响应不回传整段 raw_text（可能很长）；调试时可开 query，这里默认省略
|
||
result.pop("raw_text", None)
|
||
return result
|
||
|
||
|
||
def _run_candidate_import(parse: Callable[[], dict], empty_msg: str) -> dict:
|
||
"""执行候选解析：ValueError→400、其他→500、空候选→400、剥离 raw_text。"""
|
||
try:
|
||
result = parse()
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
except Exception as e: # noqa: BLE001
|
||
logger.exception("watchlist import failed")
|
||
raise HTTPException(500, f"解析失败: {e}") from e
|
||
if not result["candidates"]:
|
||
raise HTTPException(400, empty_msg)
|
||
result.pop("raw_text", None)
|
||
return result
|
||
|
||
|
||
@router.post("/import-csv")
|
||
async def import_from_csv(request: Request, file: UploadFile = File(...)):
|
||
"""从 CSV / TXT 导入自选候选列表（不自动写入自选）。
|
||
|
||
兼容同花顺/东财/通达信导出（逗号或 Tab 分隔、UTF-8 或 GBK 编码）。目标分组
|
||
在候选确认时由前端传入 batch 接口，本端点只做解析与主数据校验。
|
||
"""
|
||
content_type = (file.content_type or "").split(";")[0].strip().lower()
|
||
filename = (file.filename or "").lower()
|
||
ok_type = content_type in _IMPORT_CSV_TYPES
|
||
ok_ext = filename.endswith((".csv", ".txt"))
|
||
if not ok_type and not ok_ext:
|
||
raise HTTPException(400, "仅支持 CSV / TXT 文件")
|
||
|
||
data = await _read_upload_capped(file, _MAX_IMPORT_CSV_BYTES, "文件过大（上限 5MB）")
|
||
if not data:
|
||
raise HTTPException(400, "空文件")
|
||
|
||
data_dir = request.app.state.repo.store.data_dir
|
||
# 解码与自选/instruments parquet 读取为同步 CPU/IO，挪线程池避免卡事件循环
|
||
return await anyio.to_thread.run_sync(
|
||
lambda: _run_candidate_import(
|
||
lambda: import_watchlist_csv(
|
||
data,
|
||
data_dir,
|
||
existing_symbols={r["symbol"] for r in watchlist.list_symbols()},
|
||
),
|
||
"文件中未识别到股票代码或名称",
|
||
)
|
||
)
|
||
|
||
|
||
@router.post("/import-codes")
|
||
def import_from_codes(req: ImportCodesRequest, request: Request):
|
||
"""从粘贴的证券代码导入自选候选列表（不自动写入自选）。"""
|
||
text = req.text.strip()
|
||
if not text:
|
||
raise HTTPException(400, "请输入要导入的股票代码")
|
||
|
||
existing = {r["symbol"] for r in watchlist.list_symbols()}
|
||
data_dir = request.app.state.repo.store.data_dir
|
||
return _run_candidate_import(
|
||
lambda: import_watchlist_codes(text, data_dir, existing_symbols=existing),
|
||
"未识别到股票代码",
|
||
)
|
||
|
||
|
||
@router.post("/{symbol}/top")
|
||
def move_one_to_top(symbol: str, request: Request):
|
||
rows = watchlist.move_to_top(symbol)
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.put("/{symbol}/group")
|
||
def assign_group(symbol: str, req: GroupAssignRequest, request: Request):
|
||
"""互斥设定分组(仅保留此组; None=移出全部分组)。多组操作用 members 端点。"""
|
||
try:
|
||
rows = watchlist.set_group(symbol, req.group_id)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选标的不存在") from e
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.post("/groups/{group_id}/members/{symbol}")
|
||
def add_member(group_id: str, symbol: str, request: Request):
|
||
"""把标的加入分组(多组成员关系: 不影响其他分组)。"""
|
||
try:
|
||
rows = watchlist.add_to_group(symbol, group_id)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选标的不存在") from e
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.delete("/groups/{group_id}/members/{symbol}")
|
||
def remove_member(group_id: str, symbol: str, request: Request):
|
||
"""把标的移出分组(仅摘本组标签; 标的仍在自选, 可能落入未分组)。"""
|
||
try:
|
||
rows = watchlist.remove_from_group(symbol, group_id)
|
||
except KeyError as e:
|
||
raise HTTPException(404, "自选标的不存在") from e
|
||
except ValueError as e:
|
||
raise HTTPException(400, str(e)) from e
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.delete("/{symbol}")
|
||
def remove_one(symbol: str, request: Request):
|
||
rows = watchlist.remove(symbol)
|
||
return {"symbols": _with_names(rows, request)}
|
||
|
||
|
||
@router.delete("")
|
||
def clear_all():
|
||
"""清空自选列表。"""
|
||
count = watchlist.clear()
|
||
return {"removed": count}
|
||
|
||
|
||
# 自选页需要的列
|
||
_WATCHLIST_COLS = [
|
||
"symbol", "close", "open", "high", "low", "change_pct", "change_amount", "amount",
|
||
"turnover_rate",
|
||
"amplitude", "annual_vol_20d",
|
||
"vol_ratio_5d",
|
||
"ma5", "ma10", "ma20", "ma60",
|
||
"vol_ma5", "vol_ma10",
|
||
"high_60d", "low_60d",
|
||
"rsi_6", "rsi_14", "rsi_24",
|
||
"macd_dif", "macd_dea", "macd_hist",
|
||
"kdj_k", "kdj_d", "kdj_j",
|
||
"boll_upper", "boll_lower",
|
||
"atr_14",
|
||
"momentum_5d", "momentum_10d", "momentum_20d", "momentum_30d", "momentum_60d",
|
||
"deviate_3d", "deviate_10d", "deviate_30d",
|
||
"consecutive_limit_ups", "consecutive_limit_downs",
|
||
"signal_limit_up", "signal_limit_down", "signal_volume_surge",
|
||
"signal_ma_golden_5_20", "signal_macd_golden", "signal_n_day_high",
|
||
"signal_boll_breakout_upper", "signal_ma20_breakout",
|
||
"signal_ma_dead_5_20", "signal_macd_dead", "signal_n_day_low",
|
||
"signal_boll_breakdown_lower", "signal_ma20_breakdown",
|
||
]
|
||
|
||
|
||
@router.get("/enriched")
|
||
def watchlist_enriched(
|
||
request: Request,
|
||
ext_columns: str | None = Query(None, description="逗号分隔的 ext 列: config_id.field_name"),
|
||
):
|
||
"""自选股 enriched 数据 — 直接从 enriched 最新日读取, 无即时计算。
|
||
|
||
ext_columns 参数示例: "industry_rating.score,fund_flow.net_inflow"
|
||
会动态 LEFT JOIN 对应的 ext_{config_id} DuckDB view。
|
||
"""
|
||
t0 = time.perf_counter()
|
||
|
||
repo = request.app.state.repo
|
||
symbols = [r["symbol"] for r in watchlist.list_symbols()]
|
||
if not symbols:
|
||
return {"rows": [], "as_of": None, "elapsed_ms": 0}
|
||
|
||
# 按资产拆分自选 symbol; ETF enriched 是独立缓存, 仅自选真的含 ETF 才去加载
|
||
# (避免无 ETF 用户在缓存冷启动时触发 ETF 全量懒加载)
|
||
etf_set = repo.get_etf_symbol_set()
|
||
index_set = repo.get_index_symbol_set()
|
||
etf_symbols = [s for s in symbols if s in etf_set]
|
||
index_symbols = [s for s in symbols if s not in etf_set and s in index_set]
|
||
stock_symbols = [s for s in symbols if s not in etf_set and s not in index_set]
|
||
|
||
df_e, cache_date = repo.get_enriched_latest()
|
||
|
||
# 以自选列表为主表 LEFT JOIN enriched, 保证自选的每一只都返回一行;
|
||
# 不在 enriched 缓存里的标的 (新股/冷门股/新用户未同步) 指标为 null, 前端渲染为 "—".
|
||
# 旧实现是 df_e.filter(is_in(stock_symbols)), 方向反了 (以 enriched 为主),
|
||
# 会把不在缓存 universe 里的自选股静默丢弃.
|
||
if stock_symbols:
|
||
watchlist_df = pl.DataFrame({"symbol": stock_symbols})
|
||
if df_e.is_empty():
|
||
df = watchlist_df
|
||
else:
|
||
df = watchlist_df.join(df_e, on="symbol", how="left")
|
||
else:
|
||
df = pl.DataFrame()
|
||
|
||
# ETF 行合并; 缺失列 (换手率/涨跌停信号等) 为 null
|
||
etf_date = None
|
||
if etf_symbols:
|
||
df_etf_all, etf_date = repo.get_enriched_latest_asset("etf")
|
||
etf_watchlist_df = pl.DataFrame({"symbol": etf_symbols})
|
||
if not df_etf_all.is_empty():
|
||
# ETF 同样以自选为主表 LEFT JOIN, 缺失标的指标为 null
|
||
df_etf = etf_watchlist_df.join(df_etf_all, on="symbol", how="left")
|
||
else:
|
||
df_etf = etf_watchlist_df
|
||
df = df_etf if df.is_empty() else pl.concat([df, df_etf], how="diagonal_relaxed")
|
||
|
||
# 指数行合并 (镜像 ETF 分支); 缺失列 (换手率/涨跌停信号等) 为 null
|
||
index_date = None
|
||
if index_symbols:
|
||
df_idx_all, index_date = repo.get_enriched_latest_asset("index")
|
||
idx_watchlist_df = pl.DataFrame({"symbol": index_symbols})
|
||
if not df_idx_all.is_empty():
|
||
df_idx = idx_watchlist_df.join(df_idx_all, on="symbol", how="left")
|
||
else:
|
||
df_idx = idx_watchlist_df
|
||
df = df_idx if df.is_empty() else pl.concat([df, df_idx], how="diagonal_relaxed")
|
||
|
||
# as_of 取三类缓存中较旧者
|
||
dates = [d for d in (cache_date if stock_symbols else None, etf_date, index_date) if d is not None]
|
||
as_of = min(dates) if dates else None
|
||
if df.is_empty():
|
||
return {"rows": [], "as_of": str(as_of) if as_of else None, "elapsed_ms": 0}
|
||
|
||
# JOIN float_shares (仅股票有) + 名称 (股票/ETF 统一走 get_name_map)
|
||
df_i = repo.get_instruments()
|
||
if not df_i.is_empty() and "float_shares" in df_i.columns:
|
||
df = df.join(df_i.select(["symbol", "float_shares"]), on="symbol", how="left")
|
||
name_map = repo.get_name_map(df["symbol"].to_list())
|
||
df = df.with_columns(
|
||
pl.col("symbol").replace_strict(name_map, default=None, return_dtype=pl.Utf8).alias("name")
|
||
)
|
||
|
||
# 标注资产类型: 前端据此渲染徽标/豁免板块筛选/分时列降级
|
||
asset_map = {**{s: "etf" for s in etf_symbols}, **{s: "index" for s in index_symbols}}
|
||
df = df.with_columns(
|
||
pl.col("symbol").replace_strict(asset_map, default="stock", return_dtype=pl.Utf8).alias("asset_type")
|
||
)
|
||
|
||
# 选择内置需要的列
|
||
keep = [c for c in _WATCHLIST_COLS + ["name", "float_shares", "asset_type"] if c in df.columns]
|
||
df = df.select(keep)
|
||
|
||
# 动态 JOIN 扩展数据表
|
||
ext_specs = _parse_ext_columns(ext_columns) if ext_columns else []
|
||
if ext_specs:
|
||
db = repo.store.db
|
||
data_dir = repo.store.data_dir
|
||
from app.services.ext_data import ExtConfigStore
|
||
from app.api.ext_data import _read_ext_dataframe
|
||
|
||
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:
|
||
# 扩展时序数据必须只取最新分区；否则一个 symbol 会按历史分区数被 JOIN 放大。
|
||
cfg = configs.get(config_id)
|
||
if cfg:
|
||
ext_df, _ = _read_ext_dataframe(cfg, data_dir)
|
||
else:
|
||
ext_df = pl.from_arrow(db.query(
|
||
f"SELECT symbol, {quote_ident(field_name)} FROM {view_name}"
|
||
).arrow())
|
||
if not ext_df.is_empty() and "symbol" in ext_df.columns:
|
||
ext_df = (
|
||
ext_df
|
||
.select(["symbol", field_name])
|
||
.unique(subset=["symbol"], keep="last")
|
||
.rename({field_name: ext_col_name})
|
||
)
|
||
df = df.join(ext_df.select(["symbol", ext_col_name]), on="symbol", how="left")
|
||
except Exception:
|
||
# view 不存在或字段不存在，尝试直接读 parquet
|
||
cfg = configs.get(config_id)
|
||
if cfg:
|
||
try:
|
||
ext_df, _ = _read_ext_dataframe(cfg, data_dir)
|
||
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])
|
||
.unique(subset=["symbol"], keep="last")
|
||
.rename({field_name: ext_col_name})
|
||
)
|
||
df = df.join(ext_df, on="symbol", how="left")
|
||
except Exception as e2:
|
||
logger.debug("ext join fallback failed for %s.%s: %s", config_id, field_name, e2)
|
||
|
||
# sanitize NaN / Inf
|
||
float_cols = [c for c in df.columns if df[c].dtype.is_float()]
|
||
if float_cols:
|
||
df = df.with_columns([
|
||
pl.when(pl.col(c).is_nan() | pl.col(c).is_infinite())
|
||
.then(None)
|
||
.otherwise(pl.col(c))
|
||
.alias(c)
|
||
for c in float_cols
|
||
])
|
||
|
||
# 按自选添加顺序（新加的在前）重排行
|
||
order_map = {s: i for i, s in enumerate(symbols)}
|
||
df = df.with_columns(pl.col("symbol").map_elements(lambda s: order_map.get(s, len(symbols)), return_dtype=pl.Int32).alias("_sort_order"))
|
||
df = df.sort("_sort_order").drop("_sort_order")
|
||
|
||
rows = df.to_dicts()
|
||
elapsed = (time.perf_counter() - t0) * 1000
|
||
return {"rows": rows, "as_of": str(as_of) if as_of else None, "elapsed_ms": elapsed}
|
||
|
||
|
||
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 config_id and field_name and is_valid_ext_ident(config_id):
|
||
result.append((config_id, field_name))
|
||
return result
|