recycle-docker/tools/import_machine.py

import csv
import pymysql
from datetime import datetime

# ====== 1. 数据库配置 ======
DB_CONFIG = {
    "host": "127.0.0.1",
    "port": 3306,
    "user": "root",
    "password": "root",
    "database": "recycle",
    "charset": "utf8mb4"
}

CSV_FILE = "t_chxs_machine.csv"  # 请确保文件名正确

def import_machines():
    conn = pymysql.connect(**DB_CONFIG)
    try:
        with conn.cursor() as cur:
            # ====== 2. 读取 CSV ======
            with open(CSV_FILE, mode="r", encoding="gb18030") as f:
                reader = csv.DictReader(f)
                
                data_to_insert = []
                for row in reader:
                    # 处理可能为空的 create_time，如果 CSV 里是空的，就传 None 让数据库用 DEFAULT
                    c_time = row.get("create_time").strip()
                    create_time = c_time if c_time else None
                    
                    # 组装数据元组
                    data_to_insert.append((
                        row["id"],
                        row["code"],
                        row["type_id"],
                        row["type_name"],
                        row["brand_id"],
                        row["brand_name"],
                        row["machine_id"],
                        row["name"],
                        row["shrink_name"],
                        create_time
                    ))

            # ====== 3. 批量插入 SQL ======
            sql = """
                INSERT INTO t_machine 
                (id, code, type_id, type_name, brand_id, brand_name, machine_id, name, shrink_name, create_time)
                VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
            """
            
            # 使用 executemany 比一条条插入快得多
            cur.executemany(sql, data_to_insert)
            
        conn.commit()
        print(f"✅ 成功导入 {len(data_to_insert)} 条数据到 t_machine 表")

    except Exception as e:
        conn.rollback()
        print(f"❌ 导入失败: {e}")
    finally:
        conn.close()

if __name__ == "__main__":
    import_machines()