'''
读取excel,整篇写入数据库
单行操作效率低下,利用executemany批量处理,可以大大缩减时间
亲测插入10000个数字,executemany只需要0.75s,而execute需要超过4.5s
'''
import sqlite3
import xlrd
import os
class Batch_deal(object):
path = 'XXX'
def load_files(self):
# 获取excel地址
files = os.listdir(self.path) # 返回子目录下所有文件名集合
for file in files:
if file[-3:] == 'xls':
yield self.path + file
else:
pass
def deal_file(self, file):
# 打开excel,循环所有行,获取数据,添加到list
data = xlrd.open_workbook(file) # 读取excel
table = data.sheets()[0]
nrows = table.nrows # 获取总行数
param = []
for row_ in range(1, nrows + 1): # 遍历行数,添加数据到list
param.append([table.cell(row_, 0).value, table.cell(row_, 1).value, table.cell(row_, 2).value])
# 批量数据保存
sql = self.insert_mass()
self.batch_insert(sql, param)
def batch_insert(self, sql, param): # 批量导入,sql为插入语句, param为插入值list
conn = sqlite3.connect('zaofa.db') # sqlite数据库
cursor = conn.cursor() # 建立游标
try:
cursor.executemany(sql, param) # 批量执行
conn.commit()
except Exception as e:
print(e)
conn.rollback() # 数据回滚,若一个插入失败都不做插入
def insert_mass(self):
sql = "insert into zaofa(name, age, phone) values (?, ?, ?)"
return sql
def main(self):
# 循环所有数据,依次执行
files = self.load_files()
for file in files:
self.deal_file(file)
if __name__ == '__main__':
Batch_deal = Batch_deal()
Batch_deal.main()
读取excel,executemany整篇写入数据库
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转载自blog.csdn.net/Luzaofa/article/details/81454026
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