初始化前后端学生管理系统项目
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# 请求体
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from pydantic import BaseModel, Field
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class ScoreCreate(BaseModel):
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stu_id: int=Field(...,ge=1,description='学生id必须大于等于1')
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exam_id: int=Field(...,ge=1,description='考核序次必须大于等于1')
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score: int=Field(...,ge=0,le=100,description='成绩必须在0-100之间')
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class ScoreUpdate(BaseModel):
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# stu_id: int = Field(None, ge=1, description='学生id必须大于等于1')
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# exam_id: int = Field(None, ge=1, description='考核序次必须大于等于1')
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score: int = Field(None, ge=0, le=100, description='成绩必须在0-100之间')
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from datetime import datetime
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from pydantic import BaseModel,Field
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#引入Pydantic数据校验。
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class AdvisorIn(BaseModel):
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advisor_id: int=Field(...,ge=1,description="顾问ID")
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advisor_name: str=Field(...,min_length=2,max_length=8,description="姓名为2~8个字符")
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class AdvisorOut(BaseModel):
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advisor_id: int
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advisor_name: str
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class Config:
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from_attributes = True
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from pydantic import BaseModel, Field, ConfigDict # BaseModel=模型基类，Field=字段规则，ConfigDict=模型配置
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from datetime import date # Python的日期类型（只有年月日）
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from typing import Optional # Optional[X] 表示"可以是X，也可以是None"
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# ---------------- 请求模型 ----------------
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# 新增班级：class_id、start_time 必填
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# 请求模型 = 前端传过来的数据长什么样，FastAPI自动帮你校验
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class ClassCreate(BaseModel):# 新增班级的入参模型：POST新增时，请求体必须符合这个结构
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class_id: int = Field(..., ge=1, description="班级编号，正整数，不能重复")
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start_time: date = Field(..., description="开班日期，格式 yyyy-MM-dd")
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# description：这行字会显示在Swagger文档里，方便前端看
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# 修改班级：字段可选，前端传哪个改哪个（局部更新）
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class ClassUpdate(BaseModel):
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# class_id: int = Field( ge=1, description="班级编号，可选") 被注释掉 = 不允许修改班级编号
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start_time: Optional[date] = Field(None, description="开班日期，格式 yyyy-MM-dd")
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# Optional[date] = 可以传日期也可以不传；Field(None) = 不传时默认值是None
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# ---------------- 响应模型 ----------------
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# 响应模型：后端返回给前端的数据结构，from_attributes 允许直接从 ORM （Classinfo实例）的属性取值，不用手动一个个赋值
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class ClassResponse(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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class_id: int # 返回字段：班级编号
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start_time: date# 返回字段：开班日期
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#逻辑：**三个模型管三种场景**—— 新增（必填）、修改（可选）、响应（输出）。
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# 前端传错类型 / 缺字段，FastAPI 直接返回 422，不会把脏数据送进数据库。
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# 就业开放时间和offer下发时间校验
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# 导入基类、过滤条件、校验器
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from pydantic import BaseModel, Field, model_validator, field_validator
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# 导入时间模块
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from datetime import date, datetime
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# 导入可选类型、列表类型
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from typing import Optional, List
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# ---------- 请求模型 ----------
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# 修改就业记录
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class EmploymentOfferUpdate(BaseModel):
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offer_time: Optional[date] = None
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# 修改就业基础
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class EmploymentBaseUpdate(BaseModel):
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employment_open_time: Optional[date] = None
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job_time: Optional[date] = None
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company_name: Optional[str] = None
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salary: Optional[float] = None
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# 添加就业基础
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class EmploymentBaseCreate(BaseModel):
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stu_id: int = Field(..., description="学生编号")
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job_time: Optional[date] = Field(None, description="实际去就职时间")
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employment_open_time: date = Field(description="就业开放时间：年-月-日")
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company_name: str = Field(max_length=100, description="就业公司")
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salary: float = Field(..., gt=0, description="就业薪资，保留2位小数")
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# 添加就业记录
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class EmploymentOfferCreate(BaseModel):
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stu_id: int = Field(..., description="学生编号")
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offer_id: int = Field(..., description="offer编号")
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offer_time: date = Field(description="offer下发时间：年-月-日")
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# 多条件组合查询
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class EmploymentQuery(BaseModel):
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stu_id: Optional[int] = None
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company_name: Optional[str] = Field(None, max_length=100, description="公司名称")
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min_salary: Optional[float] = None
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max_salary: Optional[float] = None
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# ---------- 响应模型 ----------
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# 就业记录查询响应
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class EmploymentOfferQueryResponse(BaseModel):
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stu_id: int
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offer_id: int
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offer_time: date
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class Config:
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from_attributes = True
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# 就业基础查询响应
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class EmploymentBaseQueryResponse(BaseModel):
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stu_id: int
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employment_open_time: Optional[date] = None
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job_time: Optional[date] = None
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company_name: Optional[str] = None
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salary: Optional[float] = None
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class Config:
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from_attributes = True
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from pydantic import BaseModel, Field, model_validator
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class StudentAge(BaseModel):
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age_star: int | None = Field(None, gt=0)
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age_end: int | None = Field(None, gt=0)
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age_value: int | None = Field(None, gt=0)
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@model_validator(mode="after")
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def check_age(self):
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if self.age_value is not None:
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if self.age_star is not None or self.age_end is not None:
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raise ValueError('age_value和age_star/age_end区间不能同时存在')
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else:
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if self.age_star is None or self.age_end is None:
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raise ValueError('区间需填写完整')
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if self.age_star is not None and self.age_end is not None:
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if self.age_star > self.age_end:
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raise ValueError('输入起始值不能大于终止值')
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return self
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class ClassCount(BaseModel):
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class_id: int = Field(..., gt=0)
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gender: str | None = Field(None, description="可填男/女")
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class ScoreCount(BaseModel):
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score: int = Field(..., ge=0, le=100)
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num: int | None = Field(None, gt=0)
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class ScoreAvg(BaseModel):
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exam_order: int = Field(...)
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class Employment(BaseModel):
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top: int = Field(...)
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class EmploymentOff(BaseModel):
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class_id: int = Field(...)
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# scheme/student.py
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from pydantic import BaseModel, Field,model_validator
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from datetime import datetime, date
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from typing import Optional
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# ---------- 请求体模型 ----------
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class StudentCreate(BaseModel):
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stu_id: int = Field(..., ge = 1)
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class_id: int = Field(..., ge = 1)
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advisor_id: int = Field(..., ge=1, description="顾问老师id，对应 advisors.advisor_id")
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stu_name: str = Field(..., min_length=1, max_length=10)
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native_place: str = Field(..., min_length=1, max_length=30)
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graduate_school: str = Field(..., min_length=1, max_length=50)
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education: str = Field(..., min_length=1, max_length=10)
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major: str = Field(..., min_length=1, max_length=20)
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age: int = Field(..., ge = 18, le =40)
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gender: str = Field(..., min_length=1, max_length=20)
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graduate_time:date= Field(...)
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enroll_time:date= Field(...)
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# 模型校验，时间判断
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# @model_validator (mode = "after")
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# def check_time(self):
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# # 入学时间不能晚于就业时间
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# if self.graduate_time is not None:
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# if self.graduate_time < self.enroll_time:
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# raise ValueError ("毕业时间不能早于入学时间！！！")
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# # 简历开放时间不能早于入学时间
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# # if self.employment_open_time < self.enroll_time:
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# # raise ValueError("简历开放时间不能早于入学时间")
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# # 简历开放时间不能晚于毕业时间
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# if self.graduate_time is not None:
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# if self.graduate_time < self.employment_open_time:
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# raise ValueError("简历开放时间不能晚于毕业时间！！！")
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# # mode="after" 的校验器必须返回 self，否则 Pydantic v2 会把整个模型变成 None
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# return self
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class StudentUpdate(BaseModel):
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class_id: Optional[int] = Field(None)
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advisor_id: Optional[int] = Field(None, ge=1)
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stu_name: Optional[str] = Field(None, min_length=1, max_length=10)
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native_place: Optional[str] = Field(None, min_length=1, max_length=30)
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graduate_school: Optional[str] = Field(None, min_length=1, max_length=50)
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education: Optional[str] = Field(None, min_length=1, max_length=10)
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major: Optional[str] = Field(None, min_length=1, max_length=20)
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age: Optional[int] = Field(None, ge = 18, le =40)
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gender: Optional[str] = Field(None, min_length=1, max_length=20)
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# ----------响应体模型-------------
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class StudentResponse(BaseModel):
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stu_id: int
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class_id: int # 数据库非空，这里必须是 int
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stu_name: str
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native_place: str
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graduate_school: Optional[str]
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education: str
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major: Optional[str]
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# 敏感字段已在此模型中脱敏
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class Config:
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from_attributes = True #支持orm对象转换,让pydantic可以读取ORM数据库对象(SQLAlchemy模型)
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# 正确
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from pydantic import Field
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from datetime import datetime
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from typing import Optional
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from pydantic import BaseModel, field_validator
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# --------------------请求体模型-----------------------------
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# 用于增加1行数据# 加了软删除标签
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class TeacherAdd(BaseModel):
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teacher_id:int=Field(...,ge=1,description='教师ID是整数类型')
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class_id:int=Field(...,ge=1,description='班级ID是整数类型')
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teacher_name:str=Field(...,description='教师姓名')
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job_name:str=Field(...,min_length=2,description='主讲老师、班主任、助教')
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is_deleted:int=Field(0,ge=0,le=0,description='只能输入0,0代表未删除，1代表已经被软删除')
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@field_validator("job_name")
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@classmethod
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def validate_job_name(cls, v):
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"""校验 job_name 必须是 主讲/班主任/助教 之一"""
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allowed = ["主讲老师", "班主任", "助教"]
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if v not in allowed:
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raise ValueError(f"job_name 必须是 {allowed} 之一，当前值: {v}")
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return v
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# 用于更新数据
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class TeacherUpdate(BaseModel):
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class_id: Optional[int] = Field(None, ge=1, description='班级ID是整数类型') # ge=1 只对非 None 的值生效
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teacher_name: Optional[str] = Field(None, description='教师姓名')
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job_name: Optional[str] = Field(None,min_length=2, description='主讲老师、班主任、助教')
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@field_validator("job_name")
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@classmethod
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def validate_job_name(cls, v):
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"""校验 job_name 必须是 主讲/班主任/助教 之一"""
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allowed = ["主讲老师", "班主任", "助教"]
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if v not in allowed:
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raise ValueError(f"job_name 必须是 {allowed} 之一，当前值: {v}")
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return v
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# --------------------- 响应模型 ----------------------------
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class TeacherResponse(BaseModel):
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teacher_id: int
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class_id: int
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teacher_name: str
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job_name: str
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class Config: # 告诉 Pydantic："可以从任意对象的属性中读取数据，而不只是从字典中读取。"
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from_attributes = True # 支持 ORM 对象转换
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