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refactor: Reorganize datamate-python (#34)
refactor: Reorganize datamate-python (previously label-studio-adapter) into a DDD style structure.
This commit is contained in:
Jason Wang
GitHub
@@ -0,0 +1,353 @@
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from typing import Optional
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import math
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.db.session import get_db
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from app.module.shared.schema import StandardResponse, PaginatedData
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from app.module.dataset import DatasetManagementService
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from app.core.logging import get_logger
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from app.core.config import settings
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from ..client import LabelStudioClient
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from ..service.mapping import DatasetMappingService
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from ..schema import (
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DatasetMappingCreateRequest,
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DatasetMappingCreateResponse,
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DeleteDatasetResponse,
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DatasetMappingResponse,
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)
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router = APIRouter(
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prefix="/project",
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tags=["annotation/project"]
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)
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logger = get_logger(__name__)
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@router.post("/", response_model=StandardResponse[DatasetMappingCreateResponse], status_code=201)
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async def create_mapping(
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request: DatasetMappingCreateRequest,
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db: AsyncSession = Depends(get_db)
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):
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"""
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创建数据集映射
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根据指定的DM程序中的数据集，创建Label Studio中的数据集，
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在数据库中记录这一关联关系，返回Label Studio数据集的ID
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注意：一个数据集可以创建多个标注项目
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"""
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try:
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dm_client = DatasetManagementService(db)
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ls_client = LabelStudioClient(base_url=settings.label_studio_base_url,
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token=settings.label_studio_user_token)
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service = DatasetMappingService(db)
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logger.info(f"Create dataset mapping request: {request.dataset_id}")
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# 从DM服务获取数据集信息
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dataset_info = await dm_client.get_dataset(request.dataset_id)
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if not dataset_info:
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raise HTTPException(
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status_code=404,
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detail=f"Dataset not found in DM service: {request.dataset_id}"
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)
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# 确定数据类型（基于数据集类型）
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data_type = "image" # 默认值
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if dataset_info.type and dataset_info.type.code:
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type_code = dataset_info.type.code.lower()
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if "audio" in type_code:
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data_type = "audio"
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elif "video" in type_code:
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data_type = "video"
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elif "text" in type_code:
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data_type = "text"
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project_name = f"{dataset_info.name}"
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# 在Label Studio中创建项目
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project_data = await ls_client.create_project(
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title=project_name,
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description=dataset_info.description or f"Imported from DM dataset {dataset_info.id}",
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data_type=data_type
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)
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if not project_data:
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raise HTTPException(
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status_code=500,
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detail="Fail to create Label Studio project."
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)
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project_id = project_data["id"]
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# 配置本地存储：dataset/<id>
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local_storage_path = f"{settings.label_studio_local_storage_dataset_base_path}/{request.dataset_id}"
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storage_result = await ls_client.create_local_storage(
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project_id=project_id,
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path=local_storage_path,
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title="Dataset_BLOB",
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use_blob_urls=True,
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description=f"Local storage for dataset {dataset_info.name}"
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)
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if not storage_result:
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# 本地存储配置失败，记录警告但不中断流程
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logger.warning(f"Failed to configure local storage for project {project_id}")
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else:
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logger.info(f"Local storage configured for project {project_id}: {local_storage_path}")
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# 创建映射关系，包含项目名称
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mapping = await service.create_mapping(
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request,
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str(project_id),
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project_name
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)
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response_data = DatasetMappingCreateResponse(
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id=mapping.id,
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labeling_project_id=str(mapping.labeling_project_id),
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labeling_project_name=mapping.name or project_name,
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message="Dataset mapping created successfully"
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)
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return StandardResponse(
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code=201,
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message="success",
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data=response_data
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error while creating dataset mapping: {e}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.get("/", response_model=StandardResponse[PaginatedData[DatasetMappingResponse]])
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async def list_mappings(
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page: int = Query(1, ge=1, description="页码（从1开始）"),
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page_size: int = Query(20, ge=1, le=100, description="每页记录数"),
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db: AsyncSession = Depends(get_db)
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):
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"""
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查询所有映射关系（分页）
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返回所有有效的数据集映射关系（未被软删除的），支持分页查询
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"""
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try:
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service = DatasetMappingService(db)
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# 计算 skip
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skip = (page - 1) * page_size
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logger.info(f"Listing mappings, page={page}, page_size={page_size}")
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# 获取数据和总数
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mappings, total = await service.get_all_mappings_with_count(
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skip=skip,
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limit=page_size
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)
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# 计算总页数
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total_pages = math.ceil(total / page_size) if total > 0 else 0
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# 构造分页响应
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paginated_data = PaginatedData(
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page=page,
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size=page_size,
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total_elements=total,
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total_pages=total_pages,
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content=mappings
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)
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logger.info(f"Found {len(mappings)} mappings on page {page}, total: {total}")
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return StandardResponse(
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code=200,
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message="success",
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data=paginated_data
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)
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except Exception as e:
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logger.error(f"Error listing mappings: {e}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.get("/{mapping_id}", response_model=StandardResponse[DatasetMappingResponse])
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async def get_mapping(
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mapping_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""
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根据 UUID 查询单个映射关系
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"""
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try:
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service = DatasetMappingService(db)
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logger.info(f"Get mapping: {mapping_id}")
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mapping = await service.get_mapping_by_uuid(mapping_id)
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if not mapping:
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raise HTTPException(
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status_code=404,
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detail=f"Mapping not found: {mapping_id}"
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)
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logger.info(f"Found mapping: {mapping.id}")
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return StandardResponse(
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code=200,
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message="success",
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data=mapping
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error getting mapping: {e}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.get("/by-source/{dataset_id}", response_model=StandardResponse[PaginatedData[DatasetMappingResponse]])
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async def get_mappings_by_source(
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dataset_id: str,
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page: int = Query(1, ge=1, description="页码（从1开始）"),
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page_size: int = Query(20, ge=1, le=100, description="每页记录数"),
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db: AsyncSession = Depends(get_db)
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):
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"""
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根据源数据集 ID 查询所有映射关系（分页）
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返回该数据集创建的所有标注项目（不包括已删除的），支持分页查询
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"""
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try:
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service = DatasetMappingService(db)
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# 计算 skip
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skip = (page - 1) * page_size
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logger.info(f"Get mappings by source dataset id: {dataset_id}, page={page}, page_size={page_size}")
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# 获取数据和总数
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mappings, total = await service.get_mappings_by_source_with_count(
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dataset_id=dataset_id,
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skip=skip,
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limit=page_size
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)
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# 计算总页数
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total_pages = math.ceil(total / page_size) if total > 0 else 0
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# 构造分页响应
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paginated_data = PaginatedData(
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page=page,
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size=page_size,
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total_elements=total,
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total_pages=total_pages,
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content=mappings
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)
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logger.info(f"Found {len(mappings)} mappings on page {page}, total: {total}")
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return StandardResponse(
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code=200,
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message="success",
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data=paginated_data
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error getting mappings: {e}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.delete("/", response_model=StandardResponse[DeleteDatasetResponse])
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async def delete_mapping(
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m: Optional[str] = Query(None, description="映射UUID"),
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proj: Optional[str] = Query(None, description="Label Studio项目ID"),
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db: AsyncSession = Depends(get_db)
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):
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"""
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删除映射关系和对应的 Label Studio 项目
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可以通过以下任一方式指定要删除的映射：
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- m: 映射UUID
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- proj: Label Studio项目ID
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- 两者都提供（优先使用 m）
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此操作会：
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1. 删除 Label Studio 中的项目
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2. 软删除数据库中的映射记录
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"""
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try:
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# 至少需要提供一个参数
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if not m and not proj:
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raise HTTPException(
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status_code=400,
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detail="Either 'm' (mapping UUID) or 'proj' (project ID) must be provided"
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)
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ls_client = LabelStudioClient(base_url=settings.label_studio_base_url,
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token=settings.label_studio_user_token)
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service = DatasetMappingService(db)
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# 优先使用 mapping_id 查询
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if m:
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logger.debug(f"Deleting by mapping UUID: {m}")
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mapping = await service.get_mapping_by_uuid(m)
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# 如果没有提供 m，使用 proj 查询
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elif proj:
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logger.debug(f"Deleting by project ID: {proj}")
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mapping = await service.get_mapping_by_labeling_project_id(proj)
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else:
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mapping = None
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if not mapping:
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raise HTTPException(
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status_code=404,
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detail=f"Mapping either not found or not specified."
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)
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id = mapping.id
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labeling_project_id = mapping.labeling_project_id
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labeling_project_name = mapping.name
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logger.debug(f"Found mapping: {id}, Label Studio project ID: {labeling_project_id}")
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# 1. 删除 Label Studio 项目
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try:
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delete_success = await ls_client.delete_project(int(labeling_project_id))
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if delete_success:
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logger.debug(f"Successfully deleted Label Studio project: {labeling_project_id}")
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else:
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logger.warning(f"Failed to delete Label Studio project or project not found: {labeling_project_id}")
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except Exception as e:
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logger.error(f"Error deleting Label Studio project: {e}")
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# 继续执行，即使 Label Studio 项目删除失败也要删除映射记录
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# 2. 软删除映射记录
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soft_delete_success = await service.soft_delete_mapping(id)
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if not soft_delete_success:
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raise HTTPException(
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status_code=500,
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detail="Failed to delete mapping record"
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)
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logger.info(f"Successfully deleted mapping: {id}, Label Studio project: {labeling_project_id}")
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return StandardResponse(
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code=200,
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message="success",
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data=DeleteDatasetResponse(
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id=id,
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status="success",
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message=f"Successfully deleted mapping and Label Studio project '{labeling_project_name}'"
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)
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error deleting mapping: {e}")
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raise HTTPException(status_code=500, detail="Internal server error")
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