131 lines
4.4 KiB
Python
131 lines
4.4 KiB
Python
# scheme/statistics.py
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# 统计分析模块的请求/响应模型（含 2.7 通用高级筛选器）
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from typing import Any, List, Literal, Union
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from pydantic import BaseModel, Field
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# ============================================================
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# 2.7.1 通用高级筛选器：支持 AND/OR 逻辑组合与嵌套 sub_rules
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# ============================================================
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class FilterRule(BaseModel):
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"""单条筛选规则"""
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field: str = Field(..., description="字段名，如 age/gender/salary/class_name")
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operator: Literal[">", "<", "=", "!=", ">=", "<=", "like", "in"] = Field(
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..., description="比较操作符"
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)
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value: Any = Field(..., description="比较值；operator=in 时必须是列表")
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class FilterGroup(BaseModel):
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"""逻辑组合规则：可嵌套 sub_rules 实现任意深度的 AND/OR 组合"""
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logic: Literal["AND", "OR"] = Field("AND", description="组合方式")
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sub_rules: List[Union["FilterGroup", "FilterRule"]] = Field(
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..., min_length=1, description="子规则（可继续嵌套 FilterGroup）"
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)
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# Pydantic v2 递归模型需要显式 rebuild
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FilterGroup.model_rebuild()
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class FilterRequest(BaseModel):
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"""高级筛选请求体"""
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model: Literal["student"] = Field(..., description="目标模型（当前支持 student）")
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rules: List[Union[FilterGroup, FilterRule]] = Field(
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..., min_length=1, description="筛选规则列表（顶层默认 AND 连接）"
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)
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class FilterResponse(BaseModel):
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total: int
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items: List[dict] = Field(..., description="命中的学生记录")
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# ============================================================
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# 2.6 统计分析响应模型
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# ============================================================
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class ClassGenderStat(BaseModel):
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"""2.6.1 多维度班级统计：总人数 + 性别分布"""
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class_id: int
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class_name: str
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total: int
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male: int
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female: int
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class AllAboveStudent(BaseModel):
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"""2.6.2 每次考试都在分数线以上的学生"""
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stu_id: int
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stu_name: str
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class_name: str
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exam_count: int = Field(..., description="参加考核次数")
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min_score: float = Field(..., description="最低分（>= 分数线）")
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scores: List[dict] = Field(..., description="各次成绩明细 [{exam_id, score}]")
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class FailStudent(BaseModel):
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"""2.6.2 不及格次数 >= N 的学生"""
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stu_id: int
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stu_name: str
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class_name: str
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fail_count: int = Field(..., description="不及格次数")
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fail_details: List[dict] = Field(..., description="不及格成绩明细 [{exam_id, score}]")
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class ClassExamAvg(BaseModel):
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"""2.6.2 每次考试每个班级的平均分（支持动态排序）"""
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exam_id: int
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class_id: int
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class_name: str
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avg_score: float
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class TopSalaryStudent(BaseModel):
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"""2.6.3 薪资 Top N"""
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stu_id: int
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stu_name: str
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class_name: str
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job_time: Any = Field(None, description="offer 下发时间")
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company_name: str
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salary: float
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class EmploymentDuration(BaseModel):
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"""2.6.3 单个学生就业时长（天）"""
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stu_id: int
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stu_name: str
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class_name: str
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employment_open_time: Any
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job_time: Any = Field(None, description="未拿到 offer 为 null")
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duration_days: int = Field(..., description="offer下发时间 - 就业开放时间；未拿到 offer 为 -1")
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class ClassAvgDuration(BaseModel):
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"""2.6.3 每个班级平均就业时长"""
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class_id: int
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class_name: str
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opened_count: int = Field(..., description="进入就业阶段人数（有开放时间）")
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offered_count: int = Field(..., description="已拿到 offer 人数")
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avg_duration_days: float = Field(..., description="平均就业时长（仅统计已拿到 offer 的学生）")
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class ScoreVolatility(BaseModel):
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"""2.7.2 成绩波动分析：最大分差 Top N"""
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stu_id: int
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stu_name: str
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class_name: str
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max_score: float
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min_score: float
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diff: float = Field(..., description="最大分差 = 最高分 - 最低分")
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class EmploymentFunnel(BaseModel):
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"""2.7.2 班级就业漏斗：总人数 -> 已就业 -> 高薪(>10k) -> 就业率"""
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class_id: int
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class_name: str
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total: int = Field(..., description="班级总人数")
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employed: int = Field(..., description="已就业人数")
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high_salary: int = Field(..., description="高薪人数（薪资 > 10000）")
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employment_rate: float = Field(..., description="就业率（百分比，保留2位）")
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