8fbcb72a3f
- 实现查询API (query.py): 支持star_id/unique_id/nickname三种查询方式 - 实现计算模块 (calculator.py): CPM/自然搜索UV/搜索成本计算 - 实现品牌API集成 (brand_api.py): 批量并发调用，10并发限制 - 实现导出服务 (export_service.py): Excel/CSV导出 - 前端组件: QueryForm/ResultTable/ExportButton - 主页面集成: 支持6种页面状态 - 测试: 44个测试全部通过，覆盖率88% Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
from fastapi import APIRouter, Depends
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.schemas.query import QueryRequest, QueryResponse, VideoData
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from app.services.query_service import query_videos
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from app.services.calculator import calculate_metrics
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from app.services.brand_api import get_brand_names
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from app.api.v1.export import set_export_data
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router = APIRouter()
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@router.post("/query", response_model=QueryResponse)
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async def query(
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request: QueryRequest,
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db: AsyncSession = Depends(get_db),
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) -> QueryResponse:
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"""
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批量查询 KOL 视频数据.
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支持三种查询方式:
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- star_id: 按星图ID精准匹配
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- unique_id: 按达人unique_id精准匹配
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- nickname: 按达人昵称模糊匹配
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"""
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try:
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# 1. 查询数据库
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videos = await query_videos(db, request.type, request.values)
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if not videos:
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return QueryResponse(success=True, data=[], total=0)
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# 2. 提取品牌ID并批量获取品牌名称
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brand_ids = [v.brand_id for v in videos if v.brand_id]
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brand_map = await get_brand_names(brand_ids) if brand_ids else {}
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# 3. 转换为响应模型并计算指标
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data = []
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for video in videos:
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video_data = VideoData.model_validate(video)
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# 填充品牌名称
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if video.brand_id:
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video_data.brand_name = brand_map.get(video.brand_id, video.brand_id)
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# 计算预估指标
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metrics = calculate_metrics(
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estimated_video_cost=video.estimated_video_cost,
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natural_play_cnt=video.natural_play_cnt,
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total_play_cnt=video.total_play_cnt,
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after_view_search_uv=video.after_view_search_uv,
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)
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video_data.estimated_natural_cpm = metrics["estimated_natural_cpm"]
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video_data.estimated_natural_search_uv = metrics["estimated_natural_search_uv"]
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video_data.estimated_natural_search_cost = metrics["estimated_natural_search_cost"]
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data.append(video_data)
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# 缓存数据供导出使用
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set_export_data([d.model_dump() for d in data])
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return QueryResponse(success=True, data=data, total=len(data))
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except Exception as e:
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return QueryResponse(success=False, data=[], total=0, error=str(e))
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