68 lines
3.4 KiB
Python
68 lines
3.4 KiB
Python
from sqlalchemy.orm import Session
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from database import SessionLocal, engine, Base
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import models
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import crud
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def init_dimensions():
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# 创建会话
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db = SessionLocal()
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try:
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# 检查是否已经存在维度数据
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existing_dimensions = db.query(models.Dimension).count()
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if existing_dimensions == 0:
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print("初始化维度数据...")
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# 教师科研人才评估维度
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talent_dimensions = [
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{"name": "教育和工作经历", "weight": 10, "category": "talent", "description": "教育背景和工作经历评估"},
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{"name": "研究方向前沿性", "weight": 8, "category": "talent", "description": "研究是否处于学科前沿"},
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{"name": "主持科研项目情况", "weight": 12, "category": "talent", "description": "项目规模、数量及影响力"},
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{"name": "科研成果质量", "weight": 16, "category": "talent", "description": "论文、专利等成果的质量与影响"},
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{"name": "教学能力与效果", "weight": 14, "category": "talent", "description": "教学水平及学生评价"},
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{"name": "学术服务与影响力", "weight": 40, "category": "talent", "description": "学术服务与社会影响力"}
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]
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# 工程研究中心评估维度
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lab_dimensions = [
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{"name": "工程技术研发能力与水平", "weight": 30, "category": "lab", "description": "工程研究中心整体工程技术研发水平"},
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{"name": "创新水平", "weight": 10, "category": "lab", "description": "工程研究中心科研创新程度"},
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{"name": "人才与队伍", "weight": 10, "category": "lab", "description": "工程研究中心人才梯队建设情况"},
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{"name": "装备与场地", "weight": 10, "category": "lab", "description": "工程研究中心设备和场地条件"},
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{"name": "成果转化与行业贡献", "weight": 30, "category": "lab", "description": "成果产业化情况与行业贡献"},
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{"name": "学科发展与人才培养", "weight": 20, "category": "lab", "description": "对学科发展与人才培养的贡献"},
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{"name": "开放与运行管理", "weight": 20, "category": "lab", "description": "工程研究中心开放程度与管理水平"}
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]
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# 添加教师科研人才评估维度
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for dim in talent_dimensions:
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crud.create_dimension(
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db,
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name=dim["name"],
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weight=dim["weight"],
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category=dim["category"],
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description=dim["description"]
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)
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# 添加工程研究中心评估维度
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for dim in lab_dimensions:
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crud.create_dimension(
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db,
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name=dim["name"],
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weight=dim["weight"],
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category=dim["category"],
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description=dim["description"]
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)
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print("维度数据初始化完成！")
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else:
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print("数据库中已存在维度数据，跳过初始化。")
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finally:
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db.close()
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if __name__ == "__main__":
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# 确保表已创建
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Base.metadata.create_all(bind=engine)
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# 初始化维度数据
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init_dimensions() |