from sqlalchemy import func, case
from sqlalchemy_fastapi_demo_1.model.students import Student
from sqlalchemy_fastapi_demo_1.model.Score import Score
from sqlalchemy_fastapi_demo_1.model.employment import EmploymentBase,EmploymentOffer
from sqlalchemy_fastapi_demo_1.model.c_lass import Classinfo

def students_age(db,op:str,
                 age_value: int = None,
                 age_min: int = None,
                 age_max: int = None):

    a=db.query(Student).filter(Student.is_deleted == 0)
    if op == ">":
        a=a.filter(Student.age > age_value)
    elif op == "<":
        a=a.filter(Student.age < age_value)
    elif op == "=":
        a=a.filter(Student.age == age_value)
    elif op == ">=":
        a=a.filter(Student.age >= age_value)
    elif op == "<=":
        a=a.filter(Student.age <= age_value)
    elif op == "between":
        if age_min is None or age_max is None:
            raise ValueError("区间查询必须提供 age_min和age_max")
        a=a.filter(Student.age.between(age_min, age_max))
    else:
        raise ValueError("请使用 >, <, =, >=, <=, between")
    return a.all()
# 多维度班级统计**：统计每个班级的总人数，以及按性别（男、女）细分的人数分布。
def class_statistics(db):
    a = (db.query(Student.class_id,func.count(Student.stu_id).label("total"),
            func.sum(case((Student.gender == "男", 1), else_=0)).label("male"),
            func.sum(case((Student.gender == "女", 1), else_=0)
            ).label("female"))
        .filter(Student.is_deleted==0).group_by(Student.class_id).all())
    list1 = []
    for i in a:
        list1.append({"class_id": i.class_id,"total": i.total,"male": i.male,"female": i.female})
    return list1

# - 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。
def score_above(db,score_input):
    result = []
    for stu in db.query(Student).filter(Student.is_deleted == 0).all():
        if stu.score and all(s.score >= score_input for s in stu.score):
            for s in stu.score:
                result.append((stu.stu_id, stu.stu_name, s.exam_id, s.score))
    return result
# - 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。
def score_fail(db, fail_times, fail_score=60):
    result = []
    for stu in db.query(Student).filter(Student.is_deleted == 0).all():
        fails = [s for s in stu.score if s.score < fail_score]
        if len(fails) >= fail_times:
            for s in fails:
                result.append((stu.stu_name, stu.class_id,  s.score))
    return result

# - 统计每次考试每个班级的平均分，并支持按分数从高到低或从低到高动态排序。
def avg_scores(db, order="desc"):
    avg = func.avg(Score.score).label("avg_score")
    a = (db.query(Score.exam_id,Student.class_id,avg)
        .join(Score.student).filter(Student.is_deleted == 0)
        .group_by(Score.exam_id,Student.class_id))
    a = a.order_by(avg.desc() if order == "desc" else avg.asc())
    return a.all()

# - 统计就业薪资排名 Top N（动态输入 N）的学生的姓名、班级、就业时间和就业公司。
def top_salary(db, n):
    a = (db.query(Student.stu_name,
            Student.class_id,
            EmploymentBase.job_time,
            EmploymentBase.company_name,
            EmploymentBase.salary).join(Student, EmploymentBase.stu_id == Student.stu_id)
        .filter(EmploymentBase.is_deleted == 0, Student.is_deleted == 0)
        .order_by(EmploymentBase.salary.desc()).offset(n-1).limit(1).first())
    if not a:
        return None
    return {"name": a.stu_name,"class_id": a.class_id,"job_time": str(a.job_time) if a.job_time else None,
        "company": a.company_name,"salary": a.salary}

# - 统计每个学生的就业时长（计算公式：offer下发时间 - 就业开放时间）。
def stu_every(db):
    a = (db.query(Student.stu_id,
            Student.stu_name,
            EmploymentBase.employment_open_time,
            EmploymentOffer.offer_time)
        .join(EmploymentBase, EmploymentBase.stu_id == Student.stu_id)
        .join(EmploymentOffer, EmploymentOffer.stu_id == Student.stu_id)
        .filter(Student.is_deleted == 0,EmploymentBase.is_deleted == 0,
            EmploymentOffer.is_deleted == 0).all())
    return [{"stu_id": sid,"name": name,
            "days": (offer_t - open_t).days if open_t and offer_t else None}
        for sid, name, open_t, offer_t in a]

# - 统计每个班级的平均就业时长（仅统计进入就业阶段，即有就业开放时间的学生）。
def class_avg(db):
    days = func.datediff(EmploymentOffer.offer_time,
        EmploymentBase.employment_open_time).label("days")
    a = (db.query(Student.class_id,
            func.avg(days).label("avg_days"),
            func.count().label("count"))
        .join(EmploymentBase, EmploymentBase.stu_id == Student.stu_id)
        .join(EmploymentOffer, EmploymentOffer.stu_id == Student.stu_id)
        .filter(Student.is_deleted == 0,
                EmploymentBase.is_deleted == 0,
                EmploymentOffer.is_deleted == 0,
            EmploymentBase.employment_open_time.isnot(None)).group_by(Student.class_id).all())
    return [{"class_id": i.class_id, "avg_days": round(float(i.avg_days), 2)} for i in a]