151 lines
8.7 KiB
Python
151 lines
8.7 KiB
Python
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from datetime import datetime
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from sqlalchemy.orm import Session
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from database import engine, SessionLocal
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from models import Base, Teacher, Class, Student, Score, Employment
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def init_db():
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Base.metadata.create_all(bind=engine)
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def seed_data(db: Session):
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"""Insert sample data if empty"""
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if db.query(Teacher).count() > 0:
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return
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teachers = [
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Teacher(num='T001', name='张伟', age=35, sex=1, home_place='北京', college='清华大学',
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specialty='计算机科学与技术', enrollment_time=datetime(2008, 9, 1),
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graduate_time=datetime(2012, 6, 30), education='本科',
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work_experience='10年Java教学经验', coach_area='应用'),
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Teacher(num='T002', name='李娜', age=32, sex=2, home_place='上海', college='复旦大学',
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specialty='软件工程', enrollment_time=datetime(2010, 9, 1),
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graduate_time=datetime(2014, 6, 30), education='硕士',
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work_experience='8年前端教学经验', coach_area='项目'),
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Teacher(num='T003', name='王强', age=40, sex=1, home_place='广州', college='中山大学',
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specialty='人工智能', enrollment_time=datetime(2004, 9, 1),
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graduate_time=datetime(2008, 6, 30), education='博士',
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work_experience='12年算法教学经验', coach_area='算法'),
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Teacher(num='T004', name='赵敏', age=28, sex=2, home_place='深圳', college='浙江大学',
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specialty='数据科学', enrollment_time=datetime(2014, 9, 1),
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graduate_time=datetime(2018, 6, 30), education='硕士',
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work_experience='5年Python教学经验', coach_area='应用'),
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Teacher(num='T005', name='陈刚', age=38, sex=1, home_place='成都', college='电子科技大学',
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specialty='通信工程', enrollment_time=datetime(2006, 9, 1),
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graduate_time=datetime(2010, 6, 30), education='本科',
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work_experience='11年嵌入式教学经验', coach_area='项目'),
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]
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db.add_all(teachers)
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db.commit()
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for t in teachers:
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db.refresh(t)
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classes = [
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Class(num='C2024001', name='C2024001', class_start_time=datetime(2024, 3, 1),
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head_teacher_id=1, coach_teacher_id=2, tutor_teacher_id=4),
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Class(num='C2024002', name='C2024001', class_start_time=datetime(2024, 4, 1),
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head_teacher_id=2, coach_teacher_id=3, tutor_teacher_id=5),
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Class(num='C2024003', name='C2024003', class_start_time=datetime(2024, 5, 1),
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head_teacher_id=3, coach_teacher_id=1, tutor_teacher_id=4),
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]
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db.add_all(classes)
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db.commit()
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for c in classes:
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db.refresh(c)
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students = [
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Student(num='S2024001', name='刘洋', age=22, sex=1, home_place='北京',
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college='北京大学', specialty='计算机科学与技术',
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enrollment_time=datetime(2020, 9, 1), graduate_time=datetime(2024, 6, 30),
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education='本科', class_id=1, advisor_id=1),
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Student(num='S2024002', name='孙丽', age=23, sex=2, home_place='上海',
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college='上海交通大学', specialty='软件工程',
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enrollment_time=datetime(2019, 9, 1), graduate_time=datetime(2023, 6, 30),
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education='本科', class_id=1, advisor_id=1),
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Student(num='S2024003', name='周杰', age=24, sex=1, home_place='广州',
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college='华南理工大学', specialty='人工智能',
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enrollment_time=datetime(2018, 9, 1), graduate_time=datetime(2022, 6, 30),
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education='硕士', class_id=1, advisor_id=2),
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Student(num='S2024004', name='吴敏', age=21, sex=2, home_place='深圳',
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college='深圳大学', specialty='数据科学',
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enrollment_time=datetime(2021, 9, 1), graduate_time=datetime(2025, 6, 30),
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education='本科', class_id=2, advisor_id=3),
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Student(num='S2024005', name='郑浩', age=25, sex=1, home_place='成都',
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college='四川大学', specialty='通信工程',
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enrollment_time=datetime(2017, 9, 1), graduate_time=datetime(2021, 6, 30),
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education='本科', class_id=2, advisor_id=4),
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Student(num='S2024006', name='冯雪', age=22, sex=2, home_place='杭州',
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college='浙江大学', specialty='计算机科学与技术',
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enrollment_time=datetime(2020, 9, 1), graduate_time=datetime(2024, 6, 30),
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education='本科', class_id=2, advisor_id=5),
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Student(num='S2024007', name='黄磊', age=23, sex=1, home_place='南京',
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college='南京大学', specialty='软件工程',
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enrollment_time=datetime(2019, 9, 1), graduate_time=datetime(2023, 6, 30),
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education='本科', class_id=3, advisor_id=1),
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Student(num='S2024008', name='徐婷', age=24, sex=2, home_place='武汉',
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college='武汉大学', specialty='人工智能',
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enrollment_time=datetime(2018, 9, 1), graduate_time=datetime(2022, 6, 30),
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education='硕士', class_id=3, advisor_id=2),
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Student(num='S2024009', name='马超', age=21, sex=1, home_place='西安',
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college='西安交通大学', specialty='数据科学',
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enrollment_time=datetime(2021, 9, 1), graduate_time=datetime(2025, 6, 30),
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education='本科', class_id=3, advisor_id=3),
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Student(num='S2024010', name='朱琳', age=22, sex=2, home_place='天津',
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college='南开大学', specialty='通信工程',
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enrollment_time=datetime(2020, 9, 1), graduate_time=datetime(2024, 6, 30),
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education='本科', class_id=3, advisor_id=4),
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Student(num='S2026001', name='牧遥', age=22, sex=1, home_place='北京',
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college='北京大学', specialty='计算机科学与技术',
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enrollment_time=datetime(2020, 9, 1), graduate_time=datetime(2024, 6, 30),
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education='本科', class_id=1, advisor_id=1),
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]
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db.add_all(students)
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db.commit()
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for s in students:
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db.refresh(s)
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score_data = [
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# 刘洋 (id=1)
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(1, '第一次考核', 85.50), (1, '第二次考核', 90.00), (1, '第三次考核', 88.00),
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# 孙丽 (id=2)
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(2, '第一次考核', 92.00), (2, '第二次考核', 87.50), (2, '第三次考核', 91.00),
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# 周杰 (id=3)
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(3, '第一次考核', 78.00), (3, '第二次考核', 82.50), (3, '第三次考核', 80.00),
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# 吴敏 (id=4)
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(4, '第一次考核', 95.00), (4, '第二次考核', 93.50), (4, '第三次考核', 96.00),
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# 郑浩 (id=5)
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(5, '第一次考核', 70.00), (5, '第二次考核', 75.50), (5, '第三次考核', 72.00),
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# 冯雪 (id=6)
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(6, '第一次考核', 88.00), (6, '第二次考核', 90.50), (6, '第三次考核', 89.00),
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# 黄磊 (id=7)
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(7, '第一次考核', 82.00), (7, '第二次考核', 85.00), (7, '第三次考核', 83.50),
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# 徐婷 (id=8)
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(8, '第一次考核', 91.00), (8, '第二次考核', 94.00), (8, '第三次考核', 92.50),
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# 马超 (id=9)
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(9, '第一次考核', 76.00), (9, '第二次考核', 79.50), (9, '第三次考核', 77.00),
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# 朱琳 (id=10)
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(10, '第一次考核', 89.00), (10, '第二次考核', 86.50), (10, '第三次考核', 90.00),
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# 牧遥 (id=11) - 有不及格
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(11, '第一次考核', 56.50), (11, '第二次考核', 30.00), (11, '第三次考核', 88.00),
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]
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for sid, num, score in score_data:
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db.add(Score(sid=sid, num=num, score=score))
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db.commit()
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employment_data = [
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(1, 1, datetime(2024, 6, 1), datetime(2024, 7, 15), '字节跳动', 25000.00),
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(2, 1, datetime(2024, 6, 1), datetime(2024, 7, 20), '腾讯', 28000.00),
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(3, 1, datetime(2024, 6, 1), datetime(2024, 8, 1), '阿里巴巴', 30000.00),
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(4, 2, datetime(2024, 7, 1), datetime(2024, 8, 10), '美团', 24000.00),
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(5, 2, datetime(2024, 7, 1), None, None, None),
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(6, 2, datetime(2024, 7, 1), datetime(2024, 8, 15), '京东', 26000.00),
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(7, 3, datetime(2024, 8, 1), datetime(2024, 9, 5), '百度', 27000.00),
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(8, 3, datetime(2024, 8, 1), datetime(2024, 9, 10), '华为', 32000.00),
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(9, 3, datetime(2024, 8, 1), None, None, None),
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(10, 3, datetime(2024, 8, 1), datetime(2024, 9, 20), '小米', 23000.00),
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]
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for sid, cid, open_time, offer_time, company, salary in employment_data:
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db.add(Employment(sid=sid, class_id=cid, employment_open_time=open_time,
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offer_recived_time=offer_time, employment_company=company,
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employment_salary=salary))
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db.commit()
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