426cf4d2cd
- Add src/university_scraper module with scraper, analyzer, and CLI - Add backend FastAPI service with API endpoints and database models - Add frontend React app with university management pages - Add configs for Harvard, Manchester, and UCL universities - Add artifacts with various scraper implementations - Add Docker compose configuration for deployment - Update .gitignore to exclude generated files 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
68 lines
1.3 KiB
Python
68 lines
1.3 KiB
Python
"""爬取结果相关的Pydantic模型"""
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from datetime import datetime
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from typing import Optional, List, Dict, Any
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from pydantic import BaseModel
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class FacultyData(BaseModel):
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"""导师数据"""
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name: str
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url: str
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title: Optional[str] = None
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email: Optional[str] = None
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department: Optional[str] = None
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class ProgramData(BaseModel):
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"""项目数据"""
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name: str
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url: str
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degree_type: Optional[str] = None
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description: Optional[str] = None
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faculty_page_url: Optional[str] = None
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faculty_count: int = 0
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faculty: List[FacultyData] = []
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class SchoolData(BaseModel):
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"""学院数据"""
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name: str
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url: str
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description: Optional[str] = None
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program_count: int = 0
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programs: List[ProgramData] = []
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class ResultResponse(BaseModel):
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"""完整结果响应"""
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id: int
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university_id: int
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job_id: Optional[int] = None
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# 统计
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schools_count: int
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programs_count: int
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faculty_count: int
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# 完整数据
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result_data: Dict[str, Any]
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created_at: datetime
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class Config:
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from_attributes = True
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class ResultSummary(BaseModel):
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"""结果摘要"""
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id: int
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university_id: int
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schools_count: int
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programs_count: int
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faculty_count: int
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created_at: datetime
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class Config:
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from_attributes = True
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