259 lines
10 KiB
Plaintext
259 lines
10 KiB
Plaintext
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
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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 BreedingTraitCRUD
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from .schema import (
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TraitCreateSchema,
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TraitOutSchema,
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TraitQueryParam,
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TraitUpdateSchema,
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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_float(v: Any) -> float | 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 float(v)
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except (TypeError, ValueError):
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return None
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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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class TraitService:
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"""性状字典 模块服务层"""
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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[TraitOutSchema]) -> None:
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if not items:
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return
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crud = BreedingTraitCRUD(self.auth, self.db)
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async def detail(self, id: int) -> TraitOutSchema:
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obj = await BreedingTraitCRUD(self.auth, self.db).get(id=id)
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if not obj:
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raise CustomException(msg="该性状字典不存在")
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out = TraitOutSchema.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: TraitQueryParam | None = None,
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order_by: list[dict[str, str]] | None = None,
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) -> list[TraitOutSchema]:
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obj_list = await BreedingTraitCRUD(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 = [TraitOutSchema.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: TraitQueryParam | None = None,
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order_by: list[dict[str, str]] | None = None,
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) -> PageResultSchema[TraitOutSchema]:
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offset = (page_no - 1) * page_size
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result = await BreedingTraitCRUD(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=TraitOutSchema,
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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: TraitCreateSchema) -> TraitOutSchema:
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exist_obj = await BreedingTraitCRUD(self.auth, self.db).get(trait_code=data.trait_code)
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if exist_obj:
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raise CustomException(msg="创建失败，性状编码已存在")
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obj = await BreedingTraitCRUD(self.auth, self.db).create(data=data)
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out = TraitOutSchema.model_validate(obj)
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return out
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async def update(self, id: int, data: TraitUpdateSchema) -> TraitOutSchema:
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obj = await BreedingTraitCRUD(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，该性状字典不存在")
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if data.trait_code is not None:
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exist_obj = await BreedingTraitCRUD(self.auth, self.db).get(trait_code=data.trait_code)
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if exist_obj and exist_obj.id != id:
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raise CustomException(msg="更新失败，性状编码重复")
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obj = await BreedingTraitCRUD(self.auth, self.db).update(id=id, data=data)
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out = TraitOutSchema.model_validate(obj)
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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 BreedingTraitCRUD(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，该性状字典不存在")
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await BreedingTraitCRUD(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 BreedingTraitCRUD(self.auth, self.db).get_list(order_by=[{"id": "asc"}])
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return [{"value": o.id, "label": o.trait_code} 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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"trait_code": "性状编码",
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"trait_name": "性状名称",
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"category": "性状类别",
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"data_type": "数据类型",
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"unit": "单位",
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"is_core": "是否核心性状",
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"scale_json": "量规/分级JSON",
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"valid_min": "有效最小值",
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"valid_max": "有效最大值",
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"ontology_uri": "本体IRI",
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"remark": "备注",
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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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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) -> str:
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header_dict = {
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"性状编码": "trait_code",
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"性状名称": "trait_name",
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"性状类别": "category",
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"数据类型": "data_type",
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"单位": "unit",
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"是否核心性状": "is_core",
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"量规/分级JSON": "scale_json",
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"有效最小值": "valid_min",
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"有效最大值": "valid_max",
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"本体IRI": "ontology_uri",
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"备注": "remark",
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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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mapped_rows = []
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for row in rows:
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mapped_rows.append({en: row.get(ch) for ch, en in header_dict.items()})
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required_fields = ["trait_code", "trait_name"]
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errors = []
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for field in required_fields:
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missing_indices = [i + 1 for i, r in enumerate(mapped_rows) if _is_blank(r.get(field))]
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if missing_indices:
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field_name = next(k for k, v in header_dict.items() if v == field)
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rows_str = "、".join(str(i) for i in missing_indices)
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errors.append(f"{field_name}不能为空，第{rows_str}行")
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if errors:
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raise CustomException(msg=f"导入失败，以下行缺少必要字段：\n{'; '.join(errors)}")
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error_msgs: list[str] = []
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success_count = 0
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crud = BreedingTraitCRUD(self.auth, self.db)
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for i, row in enumerate(mapped_rows, start=1):
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try:
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fields = {
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"trait_code": _none_if_blank(row.get("trait_code")),
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"trait_name": _none_if_blank(row.get("trait_name")),
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"category": _none_if_blank(row.get("category")),
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"data_type": _none_if_blank(row.get("data_type")),
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"unit": _none_if_blank(row.get("unit")),
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"is_core": _none_if_blank(row.get("is_core")),
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"scale_json": _none_if_blank(row.get("scale_json")),
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"valid_min": _to_float(row.get("valid_min")),
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"valid_max": _to_float(row.get("valid_max")),
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"ontology_uri": _none_if_blank(row.get("ontology_uri")),
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"remark": _none_if_blank(row.get("remark")),
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}
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unique_kwargs = {"trait_code": fields["trait_code"]}
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create_data = TraitCreateSchema(**fields)
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exist_obj = await crud.get(**unique_kwargs)
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if exist_obj:
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if update_support:
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await crud.update(id=exist_obj.id, data=TraitUpdateSchema(**fields))
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success_count += 1
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else:
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error_msgs.append(f"第{i}行: 性状编码 {fields['trait_code']} 已存在")
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else:
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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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result = f"成功导入 {success_count} 条数据"
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if error_msgs:
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result += "\n错误信息:\n" + "\n".join(error_msgs)
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return result
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except Exception as e:
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logger.error(f"批量导入性状字典失败: {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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"性状编码",
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"性状名称",
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"性状类别",
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"数据类型",
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"单位",
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"是否核心性状",
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"量规/分级JSON",
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"有效最小值",
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"有效最大值",
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"本体IRI",
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"备注",
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]
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selector_header_list = ["数据类型", "是否核心性状"]
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option_list = [
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{"数据类型": ["numeric", "categorical"]},
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{"是否核心性状": ["1", "0"]},
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]
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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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