#统计分析 数据访问层（动态查询 + 聚合） from typing import Optional from sqlalchemy import and_, case, func from sqlalchemy.orm import Session from model.wl_class_model import Class_ from model.wl_emp_model import Emp from model.wl_score_model import Score from model.wl_student_model import Student from scheme.wl_statistics_scheme import AgeCompareOp, SortOrder # stu_gender 字段的实际取值 MALE_VALUE = "男" FEMALE_VALUE = "女" # ---- 2.6.1.1 动态年龄范围查询 ---- # 比较条件 -> SQLAlchemy 表达式工厂，动态拼接 where 条件 _AGE_OP_FACTORY = { AgeCompareOp.gt: lambda v1, v2: Student.stu_age > v1, AgeCompareOp.ge: lambda v1, v2: Student.stu_age >= v1, AgeCompareOp.lt: lambda v1, v2: Student.stu_age < v1, AgeCompareOp.le: lambda v1, v2: Student.stu_age <= v1, AgeCompareOp.eq: lambda v1, v2: Student.stu_age == v1, AgeCompareOp.between: lambda v1, v2: Student.stu_age.between(v1, v2), } class StatisticDao: @staticmethod def search_students_by_age(db: Session, op: AgeCompareOp, value: int, value2: Optional[int] = None): """ 输入比较条件动态查询符合条件的学员信息 :param db:数据库会话 :param op:比较条件（如大于、小于、等于、区间等） :param value:对比值1 :param value2:对比值2，选了between后的上界 :return: """ if op == AgeCompareOp.between: if value2 is None: raise ValueError("区间查询（between）需要同时提供上界 value2") if value > value2: raise ValueError("区间查询的下界不能大于上界") condition = _AGE_OP_FACTORY[op](value, value2) return db.query(Student) \ .filter(Student.is_deleted == 0, condition) \ .order_by(Student.stu_age) \ .all() @staticmethod def statistic_classes_count(db: Session): """每个班级的总人数 + 按性别细分的分布（含 0 人的空班级）""" result=[] for c in db.query(Class_).filter(Class_.is_deleted==0).all(): students=[s for s in c.students if s.is_deleted == 0]# 班级里的学生，过滤逻辑删除后的 result.append({ "class_id":c.class_id, "total":len(students), "male_count":sum(1 for s in students if s.stu_gender==MALE_VALUE), "female_count":sum(1 for s in students if s.stu_gender==FEMALE_VALUE) }) return result # 另一个版本的写法，效率更高 # male = func.sum(case((Student.stu_gender == MALE_VALUE, 1), else_=0)) # female = func.sum(case((Student.stu_gender == FEMALE_VALUE, 1), else_=0)) # # return db.query( # WlClass.class_id.label("class_id"), # func.count(Student.stu_id).label("total"), # male.label("male_count"), # female.label("female_count"), # ).select_from(WlClass) \ # .outerjoin( # Student, # # 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 # and_(Student.class_id == WlClass.class_id, Student.is_deleted == 0), # ) \ # .filter(WlClass.is_deleted == 0) \ # .group_by(WlClass.class_id) \ # .order_by(WlClass.class_id) \ # .all() @staticmethod def query_score_by_line(db:Session,score_line:float): """ 查询每次考试都在分数线以上学生信息 :param db: :param score_line: 分数线 :return: """ result=[] for s in db.query(Student).filter(Student.is_deleted==0).all(): if all(sc.score>score_line for sc in s.scores): result.append({ "stu_no":s.stu_no, "stu_name":s.stu_name, "scores": [{"exam_order":i.exam_order,"score":i.score} for i in s.scores] }) return result @staticmethod def query_by_fail_count(db:Session,fail_count:int): """ 查询有指定次数次以上不及格学生的信息 :param db: :param fail_count: 指定次数 :return: """ result=[] students=db.query(Student).filter(Student.is_deleted==0).all() for stu in students: if len([sc for sc in stu.scores if sc.score<60])>fail_count: result.append({ "stu_name":stu.stu_name, "class_id":stu.class_id, "scores":[{"exam_order":i.exam_order,"score":i.score} for i in stu.scores] }) return result @staticmethod def get_class_avg_score(db: Session, sort_order: SortOrder | None = None): """每次考试每个班级的平均分，支持按平均分动态升/降序""" avg_score = func.avg(Score.score).label("avg_score") q = db.query( Student.class_id.label("class_id"), Score.exam_order.label("exam_order"), avg_score, ).select_from(Score) \ .join(Score.student) \ .filter(Student.is_deleted == 0, Student.class_id.isnot(None)) \ .group_by(Student.class_id, Score.exam_order) # 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 if sort_order == SortOrder.desc: q = q.order_by(avg_score.desc()) elif sort_order == SortOrder.asc: q = q.order_by(avg_score.asc()) else: q = q.order_by(Student.class_id, Score.exam_order) return q.all() @staticmethod def get_info_by_rank(db:Session,rank:int): """ 统计就业薪资排名TopN的学生信息 :param db: :param rank: Top N 中的N :return: """ q=(db.query( Student.stu_name, Student.class_id, Emp.offer_time, Emp.company_name, Emp.salary ).select_from(Student) \ .join(Student.emp)) \ .filter(Student.is_deleted==0, Emp.is_deleted==0) \ .order_by(Emp.salary.desc())\ .limit(rank) return q.all() @staticmethod def get_emp_time(db:Session): """统计每个学生的就业时长（天）= offer下发时间 - 就业开放时间 未就业（offer_time，和emp_open_time至少一个为null） """ emp_total_time = func.coalesce( func.datediff(Emp.offer_time, Emp.emp_open_time), '', # 未进入就业阶段或者未拿到offer ).label('emp_total_time') # 每个学生都要统计，所以用外连接 q=db.query( Student.stu_name, emp_total_time, ).select_from(Student) \ .outerjoin(Emp, and_(Student.stu_no == Emp.stu_no, Emp.is_deleted == 0)) \ .filter(Student.is_deleted==0) return q.all() @staticmethod def get_class_avg_emp_time(db:Session, sort_order: SortOrder | None = None): """ 统计每个班级平均就业时长 :param db: :param sort_order:排序（可选） :return: """ emp_time = func.datediff(Emp.offer_time, Emp.emp_open_time) avg_emp_time = func.avg(emp_time).label("avg_emp_time") emp_stu_count = func.count(emp_time).label("emp_stu_count")# 统计有就业时长学生数量 q = db.query( Class_.class_id.label("class_id"), avg_emp_time, emp_stu_count, ).select_from(Class_) \ .outerjoin( Student, and_(Student.class_id == Class_.class_id, Student.is_deleted == 0), ) \ .outerjoin( Emp, and_( Emp.stu_no == Student.stu_no, Emp.is_deleted == 0, Emp.emp_open_time.isnot(None), Emp.offer_time.isnot(None), ), ) \ .group_by(Class_.class_id) if sort_order == SortOrder.desc: q = q.order_by(avg_emp_time.desc()) elif sort_order == SortOrder.asc: q = q.order_by(avg_emp_time.asc()) else: q = q.order_by(Class_.class_id) return [ { "class_id": r.class_id, "avg_emp_time": round(float(r.avg_emp_time), 1) if r.avg_emp_time is not None else None, "emp_stu_count": r.emp_stu_count, } for r in q.all() ]