69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
# scheme/statistics_scheme.py
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from pydantic import BaseModel, Field, EmailStr
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from datetime import datetime, date
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from typing import Optional, List
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# ---------- 请求模型 ----------
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class StatsScoreRequest(BaseModel):
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choose: int = Field(..., ge=0, le=3)
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email: EmailStr
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full_name: Optional[str] = Field(None, max_length=100)
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# ---------- 响应模型 ----------
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# 多维度班级统计
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class StatsResponse(BaseModel):
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cls_id: str
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total_cnt: int
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man_cnt: int
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female_cnt: int
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class ExamScoreItem(BaseModel):
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exam_attempt: int
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exam_score: float
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# 查询每次考试成绩都在输入分数线（如80分）以上的学生的编号、姓名和成绩。
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class StuInfoAllExamAboveScore(BaseModel):
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stu_id: str
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stu_name: str
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stu_score: List[ExamScoreItem]
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# 查询有输入指定次数（如两次）以上不及格的学生的姓名、班级和不及格成绩明细。
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class FailingStudentItem(BaseModel):
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stu_name: str
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stu_cls_id: str
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stu_fail_cnt: int
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stu_score: List[ExamScoreItem]
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# 查询有输入指定次数（如两次）以上不及格的学生的姓名、班级和不及格成绩明细。
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class ClassExamAvgScoreItem(BaseModel):
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exam_attempt: int
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cls_id: str
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avg_score: float
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stu_cnt: int
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class TopSalaryStudentItem(BaseModel):
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stu_name: str
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cls_id: str
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offer_time: date
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emp_company_name: str
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salary: float
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class StudentEmpDurationItem(BaseModel):
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stu_id: str
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stu_name: str
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cls_id: str
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offer_time: int
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class ClassAvgEmpDurationItem(BaseModel):
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cls_id: str
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avg_duration_days: float
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employed_cnt: int
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class StudentAgeDetailItem(BaseModel):
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stu_id: str
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stu_name: str
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cls_id: str
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gender: str
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age: int |