223 lines
8.4 KiB
Python
223 lines
8.4 KiB
Python
#统计分析 数据访问层（动态查询 + 聚合）
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from os.path import join
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from typing import Optional
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from sqlalchemy import and_, case, func
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from sqlalchemy.orm import Session
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from model.wl_class_model import Class_
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from model.wl_emp_model import Emp
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from model.wl_score_model import Score
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from model.wl_student_model import Student
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from scheme.wl_statistics_scheme import AgeCompareOp, SortOrder
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# stu_gender 字段的实际取值，确认数据库里存的到底是什么后改这两行即可
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MALE_VALUE = "男"
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FEMALE_VALUE = "女"
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# ---- 2.6.1.1 动态年龄范围查询 ----
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# 比较条件 -> SQLAlchemy 表达式工厂，动态拼接 where 条件
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_AGE_OP_FACTORY = {
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AgeCompareOp.gt: lambda v1, v2: Student.stu_age > v1,
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AgeCompareOp.ge: lambda v1, v2: Student.stu_age >= v1,
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AgeCompareOp.lt: lambda v1, v2: Student.stu_age < v1,
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AgeCompareOp.le: lambda v1, v2: Student.stu_age <= v1,
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AgeCompareOp.eq: lambda v1, v2: Student.stu_age == v1,
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AgeCompareOp.between: lambda v1, v2: Student.stu_age.between(v1, v2),
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}
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class StatisticDao:
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@staticmethod
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def search_students_by_age(db: Session, op: AgeCompareOp,
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value: int, value2: Optional[int] = None):
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if op == AgeCompareOp.between:
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if value2 is None:
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raise ValueError("区间查询（between）需要同时提供上界 value2")
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if value > value2:
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raise ValueError("区间查询的下界不能大于上界")
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condition = _AGE_OP_FACTORY[op](value, value2)
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return db.query(Student) \
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.filter(Student.is_deleted == 0, condition) \
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.order_by(Student.stu_age) \
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.all()
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@staticmethod
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def statistic_classes_count(db: Session):
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"""每个班级的总人数 + 按性别细分的分布（含 0 人的空班级）"""
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result=[]
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for c in db.query(Class_).filter(Class_.is_deleted==0).all():
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students=[s for s in c.students if s.is_deleted == 0]
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result.append({
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"class_id":c.class_id,
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"total":len(students),
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"male_count":sum(1 for s in students if s.stu_gender==MALE_VALUE),
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"female_count":sum(1 for s in students if s.stu_gender==FEMALE_VALUE)
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})
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return result
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# 另一个版本的写法，效率更高
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# male = func.sum(case((Student.stu_gender == MALE_VALUE, 1), else_=0))
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# female = func.sum(case((Student.stu_gender == FEMALE_VALUE, 1), else_=0))
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#
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# return db.query(
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# WlClass.class_id.label("class_id"),
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# func.count(Student.stu_id).label("total"),
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# male.label("male_count"),
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# female.label("female_count"),
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# ).select_from(WlClass) \
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# .outerjoin(
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# Student,
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# # 逻辑删除的过滤条件必须写在 ON 里，写进 where 会把空班级整行滤掉
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# and_(Student.class_id == WlClass.class_id, Student.is_deleted == 0),
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# ) \
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# .filter(WlClass.is_deleted == 0) \
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# .group_by(WlClass.class_id) \
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# .order_by(WlClass.class_id) \
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# .all()
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@staticmethod
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def query_score_by_line(db:Session,score_line:float):
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result=[]
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for s in db.query(Student).filter(Student.is_deleted==0).all():
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if all(sc.score>score_line for sc in s.scores):
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result.append({
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"stu_no":s.stu_no,
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"stu_name":s.stu_name,
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"scores": [{"exam_order":i.exam_order,"score":i.score} for i in s.scores]
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})
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return result
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@staticmethod
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def query_by_fail_count(db:Session,fail_count:int):
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result=[]
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students=db.query(Student).filter(Student.is_deleted==0).all()
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for stu in students:
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if len([sc for sc in stu.scores if sc.score<60])>fail_count:
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result.append({
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"stu_name":stu.stu_name,
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"class_id":stu.class_id,
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"scores":[{"exam_order":i.exam_order,"score":i.score} for i in stu.scores]
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})
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return result
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@staticmethod
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def get_class_avg_score(db: Session, sort_order: SortOrder | None = None):
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"""每次考试每个班级的平均分，支持按平均分动态升/降序"""
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avg_score = func.avg(Score.score).label("avg_score")
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q = db.query(
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Student.class_id.label("class_id"),
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Score.exam_order.label("exam_order"),
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avg_score,
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).select_from(Score) \
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.join(Score.student) \
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.filter(Student.is_deleted == 0, Student.class_id.isnot(None)) \
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.group_by(Student.class_id, Score.exam_order)
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# 动态排序：传了方向就按平均分排，没传则按班级 + 考试序次排
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if sort_order == SortOrder.desc:
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q = q.order_by(avg_score.desc())
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elif sort_order == SortOrder.asc:
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q = q.order_by(avg_score.asc())
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else:
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q = q.order_by(Student.class_id, Score.exam_order)
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return q.all()
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@staticmethod
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def get_info_by_rank(db:Session,rank:int):
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q=(db.query(
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Student.stu_name,
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Student.class_id,
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Emp.offer_time,
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Emp.company_name
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).select_from(Student) \
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.join(Student.emp)) \
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.filter(Student.is_deleted==0) \
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.order_by(Emp.salary.desc())\
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.limit(rank)
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return q.all()
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@staticmethod
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def get_emp_time(db:Session):
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"""每个学生的就业时长（天）= offer下发时间 - 就业开放时间
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"""
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emp_total_time = func.coalesce(
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# 未就业学生左外连接后 Emp 列为 NULL，DATEDIFF 也返回 NULL，统一兜成 0
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func.datediff(Emp.offer_time, Emp.emp_open_time),
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0,
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).label('emp_total_time')
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q=db.query(
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Student.stu_name,
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emp_total_time,
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).select_from(Student) \
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.outerjoin(Student.emp) \
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.filter(Student.is_deleted==0)
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return q.all()
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@staticmethod
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def get_class_avg_emp_time(db:Session, sort_order: SortOrder | None = None):
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"""每个班级的平均就业时长（天）= offer下发时间 - 就业开放时间
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口径：
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- 以班级表为主表左外连接，保证没有任何就业学生的班级也出现在结果里
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- 只统计已进入就业阶段（emp_open_time 非空）且已拿到 offer（offer_time 非空）的学生
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- 该班可统计的人数为 0 时 AVG 返回 NULL，出参里 avg_emp_time 给 None，即"无就业学生"
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"""
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emp_time = func.datediff(Emp.offer_time, Emp.emp_open_time)
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# AVG 和 COUNT(表达式) 都会自动忽略 NULL，所以没 offer 时间的学生不参与分子也不占分母
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avg_emp_time = func.avg(emp_time).label("avg_emp_time")
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# 用 COUNT(表达式) 而不是 COUNT(*)，它正好是平均值的分母
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emp_stu_count = func.count(emp_time).label("emp_stu_count")
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q = db.query(
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Class_.class_id.label("class_id"),
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avg_emp_time,
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emp_stu_count,
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).select_from(Class_) \
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.outerjoin(
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Student,
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# 逻辑删除的过滤条件必须写在 ON 里，写进 where 会把空班级整行滤掉
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and_(Student.class_id == Class_.class_id, Student.is_deleted == 0),
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) \
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.outerjoin(
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Emp,
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and_(
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Emp.stu_id == Student.stu_id,
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Emp.emp_open_time.isnot(None),
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Emp.offer_time.isnot(None),
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),
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) \
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.group_by(Class_.class_id)
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# 动态排序逻辑与 get_class_avg_score 保持一致
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if sort_order == SortOrder.desc:
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# MySQL 里 DESC 时 NULL 排最后，"无就业学生"的班级自然落到末尾
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q = q.order_by(avg_emp_time.desc())
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elif sort_order == SortOrder.asc:
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q = q.order_by(avg_emp_time.asc())
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else:
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q = q.order_by(Class_.class_id)
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return [
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{
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"class_id": r.class_id,
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# AVG 出来是 Decimal，转 float 并按天保留 1 位小数；None 表示该班无就业学生
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"avg_emp_time": round(float(r.avg_emp_time), 1)
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if r.avg_emp_time is not None else None,
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"emp_stu_count": r.emp_stu_count,
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}
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for r in q.all()
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]
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