246 lines
9.6 KiB
Python
246 lines
9.6 KiB
Python
import json
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from typing import Any
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from fastapi import UploadFile
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.base_schema import AuthSchema, PageResultSchema, ImportResultSchema
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from app.core.exceptions import CustomException
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from app.core.logger import logger
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from app.utils.common_util import search_to_dict
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from app.utils.excel_util import ExcelUtil
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from .crud import BreedingAnalysisDatasetCRUD
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from .schema import (
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AnalysisDatasetCreateSchema,
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AnalysisDatasetOutSchema,
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AnalysisDatasetQueryParam,
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AnalysisDatasetUpdateSchema,
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)
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def _is_blank(v: Any) -> bool:
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return v is None or (isinstance(v, str) and v.strip() == "")
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def _none_if_blank(v: Any) -> Any:
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if _is_blank(v):
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return None
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return str(v).strip() if isinstance(v, str) else v
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def _to_int(v: Any) -> int | None:
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if _is_blank(v):
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return None
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try:
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return int(float(v))
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except (TypeError, ValueError):
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return None
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def _parse_str_list(v: Any) -> list[str] | None:
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"""导入用：逗号分隔/数组 → 字符串列表；空返回 None。"""
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if _is_blank(v):
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return None
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if isinstance(v, (list, tuple)):
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out = [str(x).strip() for x in v if not _is_blank(x)]
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return out or None
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out = [s.strip() for s in str(v).split(",") if s.strip()]
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return out or None
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def _parse_int_list(v: Any) -> list[int] | None:
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"""导入用：逗号分隔/数组 → 整数列表；空返回 None。"""
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if _is_blank(v):
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return None
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if isinstance(v, (list, tuple)):
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out = [x for x in (_to_int(i) for i in v) if x is not None]
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return out or None
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out = [x for x in (_to_int(s) for s in str(v).split(",") if s.strip()) if x is not None]
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return out or None
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def _parse_config(v: Any) -> dict | None:
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"""导入用：JSON 字符串/字典 → 对象；无法解析返回 None。"""
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if _is_blank(v):
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return None
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if isinstance(v, dict):
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return v
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try:
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parsed = json.loads(str(v))
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return parsed if isinstance(parsed, dict) else None
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except (TypeError, ValueError):
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return None
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class AnalysisDatasetService:
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"""分析数据集 模块服务层（纯元数据，无外键联表）。"""
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def __init__(self, auth: AuthSchema, db: AsyncSession) -> None:
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self.auth = auth
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self.db = db
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async def _attach_fk_labels(self, items: list[AnalysisDatasetOutSchema]) -> None:
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"""本模块无外键联表字段 —— 保持签名与其它模块一致，避免导出/详情路径报错。"""
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return
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async def detail(self, id: int) -> AnalysisDatasetOutSchema:
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obj = await BreedingAnalysisDatasetCRUD(self.auth, self.db).get(id=id)
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if not obj:
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raise CustomException(msg="该分析数据集不存在")
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out = AnalysisDatasetOutSchema.model_validate(obj)
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await self._attach_fk_labels([out])
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return out
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async def get_list(
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self,
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search: AnalysisDatasetQueryParam | None = None,
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order_by: list[dict[str, str]] | None = None,
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) -> list[AnalysisDatasetOutSchema]:
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obj_list = await BreedingAnalysisDatasetCRUD(self.auth, self.db).get_list(
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search=search_to_dict(search), order_by=order_by
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)
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outs = [AnalysisDatasetOutSchema.model_validate(obj) for obj in obj_list]
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await self._attach_fk_labels(outs)
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return outs
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async def page(
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self,
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page_no: int,
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page_size: int,
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search: AnalysisDatasetQueryParam | None = None,
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order_by: list[dict[str, str]] | None = None,
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) -> PageResultSchema[AnalysisDatasetOutSchema]:
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offset = (page_no - 1) * page_size
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result = await BreedingAnalysisDatasetCRUD(self.auth, self.db).page(
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offset=offset,
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limit=page_size,
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order_by=order_by or [{"id": "asc"}],
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search=search_to_dict(search, {}),
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out_schema=AnalysisDatasetOutSchema,
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)
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await self._attach_fk_labels(result.items)
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return result
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async def create(self, data: AnalysisDatasetCreateSchema) -> AnalysisDatasetOutSchema:
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if _is_blank(data.name):
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raise CustomException(msg="数据集名称不能为空")
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obj = await BreedingAnalysisDatasetCRUD(self.auth, self.db).create(data=data)
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out = AnalysisDatasetOutSchema.model_validate(obj)
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await self._attach_fk_labels([out])
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return out
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async def update(self, id: int, data: AnalysisDatasetUpdateSchema) -> AnalysisDatasetOutSchema:
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obj = await BreedingAnalysisDatasetCRUD(self.auth, self.db).get(id=id)
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if not obj:
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raise CustomException(msg="更新失败，该分析数据集不存在")
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if data.name is not None and _is_blank(data.name):
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raise CustomException(msg="数据集名称不能为空")
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obj = await BreedingAnalysisDatasetCRUD(self.auth, self.db).update(id=id, data=data)
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out = AnalysisDatasetOutSchema.model_validate(obj)
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await self._attach_fk_labels([out])
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return out
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async def delete(self, ids: list[int]) -> None:
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if not ids:
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raise CustomException(msg="删除失败，删除对象不能为空")
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objs = await BreedingAnalysisDatasetCRUD(self.auth, self.db).get_list(search={"id": ("in", ids)})
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obj_map = {o.id: o for o in objs}
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for id_ in ids:
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if id_ not in obj_map:
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raise CustomException(msg="删除失败，该分析数据集不存在")
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await BreedingAnalysisDatasetCRUD(self.auth, self.db).delete(ids=ids)
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async def list_options(self) -> list[dict[str, Any]]:
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"""供前端下拉选择使用：返回 [{value, label}]。"""
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obj_list = await BreedingAnalysisDatasetCRUD(self.auth, self.db).get_list(order_by=[{"id": "asc"}])
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return [{"value": o.id, "label": o.name} for o in obj_list]
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@staticmethod
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def batch_export(obj_list: list[dict[str, Any]]) -> bytes:
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mapping_dict = {
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"name": "数据集名称",
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"description": "数据集描述",
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"trait_codes": "性状编码",
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"sample_ids": "样本ID",
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"config": "分析配置",
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"status": "状态",
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"created_time": "创建时间",
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"created_by": "创建者",
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}
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data = [dict(item) for item in obj_list]
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for item in data:
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creator = item.get("created_by")
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item["created_by"] = creator.get("name", "未知") if isinstance(creator, dict) else "未知"
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if isinstance(item.get("trait_codes"), (list, tuple)):
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item["trait_codes"] = ",".join(str(x) for x in item["trait_codes"])
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if isinstance(item.get("sample_ids"), (list, tuple)):
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item["sample_ids"] = ",".join(str(x) for x in item["sample_ids"])
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if isinstance(item.get("config"), (dict, list)):
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item["config"] = json.dumps(item["config"], ensure_ascii=False)
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return ExcelUtil.export_list2excel(list_data=data, mapping_dict=mapping_dict)
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async def batch_import(self, file: UploadFile, update_support: bool = False) -> ImportResultSchema:
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header_dict = {
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"数据集名称": "name",
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"数据集描述": "description",
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"性状编码": "trait_codes",
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"样本ID": "sample_ids",
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"分析配置": "config",
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"状态": "status",
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}
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try:
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contents = await file.read()
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rows = ExcelUtil.read_excel_to_dicts(contents)
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await file.close()
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if not rows:
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raise CustomException(msg="导入文件为空")
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missing_headers = [h for h in header_dict if h not in rows[0]]
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if missing_headers:
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raise CustomException(msg=f"导入文件缺少必要的列: {', '.join(missing_headers)}")
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error_msgs: list[str] = []
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success_count = 0
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crud = BreedingAnalysisDatasetCRUD(self.auth, self.db)
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for i, row in enumerate(rows, start=1):
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try:
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fields = {
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"name": _none_if_blank(row.get("name")),
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"description": _none_if_blank(row.get("description")),
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"trait_codes": _parse_str_list(row.get("trait_codes")),
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"sample_ids": _parse_int_list(row.get("sample_ids")),
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"config": _parse_config(row.get("config")),
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"status": _none_if_blank(row.get("status")) or "draft",
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}
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create_data = AnalysisDatasetCreateSchema(**fields)
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await crud.create(data=create_data)
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success_count += 1
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except Exception as e:
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error_msgs.append(f"第{i}行: {e!s}")
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continue
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return ImportResultSchema(
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valid_count=success_count,
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invalid_count=len(error_msgs),
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message_list=error_msgs,
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)
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except Exception as e:
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logger.error(f"批量导入分析数据集失败: {e!s}")
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raise CustomException(msg=f"导入失败: {e!s}")
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@staticmethod
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def import_template_download() -> bytes:
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header_list = [
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"数据集名称",
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"数据集描述",
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"性状编码",
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"样本ID",
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"分析配置",
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"状态",
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]
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selector_header_list = []
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option_list = []
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return ExcelUtil.get_excel_template(
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header_list=header_list,
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selector_header_list=selector_header_list,
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option_list=option_list,
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)
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