一、前言
最近做web网站的测试,遇到很多需要批量造数据的功能;比如某个页面展示数据条数需要达到10000条进行测试,此时手动构造数据肯定是不可能的,此时只能通过python脚本进行自动构造数据;本次构造数据主要涉及到在某个表里面批量添加数据、在关联的几个表中同步批量添加数据、批量查询某个表中符合条件的数据、批量更新某个表中符合条件的数据等。
二、数据添加
即批量添加数据到某个表中。
insert_data.py
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | import pymysql import random import time from get_userinfo import get_userinfo from get_info import get_info from get_tags import get_tags from get_tuser_id import get_utag class DatabaseAccess(): def __init__( self ): self .__db_host = "xxxxx" self .__db_port = 3307 self .__db_user = "root" self .__db_password = "123456" self .__db_database = "xxxxxx" # 连接数据库 def isConnectionOpen( self ): self .__db = pymysql.connect( host = self .__db_host, port = self .__db_port, user = self .__db_user, password = self .__db_password, database = self .__db_database, charset = 'utf8' ) # 插入数据 def linesinsert( self ,n,user_id,tags_id,created_at): self .isConnectionOpen() # 创建游标 global cursor conn = self .__db.cursor() try : sql1 = ''' INSERT INTO `codeforge_new`.`cf_user_tag`(`id`, `user_id`, `tag_id`, `created_at`, `updated_at`) VALUES ({}, {}, {}, '{}', '{}'); ''' .format(n,user_id,tags_id,created_at,created_at) # 执行SQL conn.execute(sql1,) except Exception as e: print (e) finally : # 关闭游标 conn.close() self .__db.commit() self .__db.close() def get_data( self ): # 生成对应数据 1000条 for i in range( 0 , 1001 ): created_at = time.strftime( '%Y-%m-%d %H:%M:%S' ,time.localtime()) # print(create_at) # 用户id tuserids = [] tuserid_list = get_utag() for tuserid in tuserid_list: tuserids.append(tuserid[ 0 ]) # print(tuserids) userid_list = get_userinfo() user_id = random.choice(userid_list)[ 0 ] if user_id not in tuserids: user_id = user_id # 标签id tagsid_list = get_tags() tags_id = random.choice(tagsid_list)[ 0 ] self .linesinsert(i,user_id,tags_id,created_at) if __name__ = = "__main__" : # 实例化对象 db = DatabaseAccess() db.get_data() |
二、数据批量查询
select_data.py
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import pymysql import pandas as pd import numpy as np def get_tags(): # 连接数据库,地址,端口,用户名,密码,数据库名称,数据格式 conn = pymysql.connect(host = 'xxx.xxx.xxx.xxx' ,port = 3307 ,user = 'root' ,passwd = '123456' ,db = 'xxxx' ,charset = 'utf8' ) cur = conn.cursor() # 表cf_users中获取所有用户id sql = 'select id from cf_tags where id between 204 and 298' # 将user_id列转成列表输出 df = pd.read_sql(sql,con = conn) # 先使用array()将DataFrame转换一下 df1 = np.array(df) # 再将转换后的数据用tolist()转成列表 df2 = df1.tolist() # cur.execute(sql) # data = cur.fetchone() # print(df) # print(df1) # print(df2) return df2 conn.close() |
三、批量更新数据
select_data.py
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import pymysql import pandas as pd import numpy as np def get_tags(): # 连接数据库,地址,端口,用户名,密码,数据库名称,数据格式 conn = pymysql.connect(host = 'xxx.xxx.xxx.xxx' ,port = 3307 ,user = 'root' ,passwd = '123456' ,db = 'xxxx' ,charset = 'utf8' ) cur = conn.cursor() # 表cf_users中获取所有用户id sql = 'select id from cf_tags where id between 204 and 298' # 将user_id列转成列表输出 df = pd.read_sql(sql,con = conn) # 先使用array()将DataFrame转换一下 df1 = np.array(df) # 再将转换后的数据用tolist()转成列表 df2 = df1.tolist() # cur.execute(sql) # data = cur.fetchone() # print(df) # print(df1) # print(df2) return df2 conn.close() |
以上就是python 实现数据库中数据添加、查询与更新的示例代码的详细内容,更多关于python 数据库添加、查询与更新的资料请关注自学编程网其它相关文章!
- 本文固定链接: https://zxbcw.cn/post/201620/
- 转载请注明:必须在正文中标注并保留原文链接
- QQ群: PHP高手阵营官方总群(344148542)
- QQ群: Yii2.0开发(304864863)