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- import pandas as pd
- from com.zf.crawl import base_mysql
- def generate_sql_from_excel(excel_file):
- # 读取 Excel 文件
- df = pd.read_excel(excel_file)
- sql_arr = []
- auto_increment = 0
- code = 0
- for index, row in df.iterrows():
- commodity_code = str(row.values[4])
- level = 0
- for i in range(4):
- if not pd.isna(row.values[i]):
- if 0 == i:
- auto_increment += 1
- code = 'C0' + str(auto_increment)
- level = i + 1
- commodity_name = str(row.values[i]).rstrip('*')
- commodity_name = commodity_name.replace('(', '(').replace(')', ')')
- sql = f"INSERT INTO t_yujin_crossborder_prov_commodity_category (code, level,commodity_code, commodity_name, create_time) VALUES ('{code}', {level}, '{commodity_code}', '{commodity_name}', now());"
- sql_arr.append(sql)
- print(sql)
- print(f"√ 成功生成 commodity category SQL 文件 size {len(sql_arr)} ")
- # 解析完后生成sql文件批量入库
- base_mysql.bulk_insert(sql_arr)
- print("trade SQL 存表完成!")
- # 商品书数据初始化
- excel_file = 'C:\\Users\\admin\\Desktop\\海关总署数据梳理.xlsx' # 输入的 Excel 文件
- generate_sql_from_excel(excel_file)
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