用python操作数据库,特别是做性能测试造存量数据时特别简单方便,比存储过程方便多了。
连接数据库
前提:安装mysql、python,参考:https://www.cnblogs.com/UncleYong/p/10530261.html
数据库qzcsjb的test表中初始化的数据:
安装pymysql模块,pip install pymysql
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor()
# 执行sql语句
sql
=
'select * from test where name = "%s" and id="%s"'
%
(
'qzcsbj1'
,
'1'
)
rows
=
cursor.execute(sql)
# 返回结果是受影响的行数
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
# 判断是否连接成功
if
rows >
=
0
:
print
(
'连接数据库成功'
)
else
:
print
(
'连接数据库失败'
)
|
增加数据
单条
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor()
# 执行sql语句
sql
=
'insert into test(id,name) values(%s,%s)'
rows
=
cursor.execute(sql,(
'4'
,
'qzcsbj4'
))
# 提交
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
|
多条
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor()
# 执行sql语句
sql
=
'insert into test(id,name) values(%s,%s)'
rows
=
cursor.executemany(sql,[(
'5'
,
'qzcsbj5'
),(
'6'
,
'qzcsbj6'
),(
'7'
,
'qzcsbj7'
)])
# 提交
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
|
大批量新增
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
values
=
[]
for
i
in
range
(
100
,
201
):
values.append((i,
'qzcsbj'
+
str
(i)))
sql
=
'insert into test(id,name) values(%s,%s)'
rows
=
cursor.executemany(sql,values)
# 提交
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
|
修改数据
把上面大批量新增的数据删除,delete from test where id>=100;
单条
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor()
# 执行sql语句
sql
=
'update test set name = %s where id = %s'
rows
=
cursor.execute(sql,(
'qzcsbj'
,
'7'
))
# 提交
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
|
多条
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
|
import
pymysql
# 建立数据库连接
conn
=
pymysql.connect(
host
=
'192.168.168.168'
,
port
=
3306
,
user
=
'root'
,
password
=
'mysql'
,
db
=
'qzcsbj'
,
charset
=
'utf8'
)
# 获取游标
cursor
=
conn.cursor()
# 执行sql语句
sql
=
'update test set name = %s where id = %s'
rows
=
cursor.executemany(sql,[(
'全栈测试笔记5'
,
'5'
),(
'全栈测试笔记6'
,
'6'
)])
# 提交
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
|
删除数据
单条
下面脚本和上面增加数据,除了执行sql语句部分不一样,其余都一样
1
2
3
|
# 执行sql语句
sql
=
'delete from test where id = %s'
rows
=
cursor.execute(sql,(
'1'
,))
|
多条
下面脚本和上面增加数据,除了执行sql语句部分不一样,其余都一样
1
2
3
|
# 执行sql语句
sql
=
'delete from test where id = %s'
rows
=
cursor.executemany(sql,[(
'2'
),(
'3'
)])
|
查询数据
fetchone
有点像从管道中取一个,如果再来一个fetchone,会又取下一个,如果取完了再取,就返回None
每条记录为元组格式
下面脚本和上面增加数据,除了执行sql语句部分不一样,其余都一样
1
2
3
4
5
6
7
|
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
|
运行结果:
(4, 'qzcsbj4')
(5, '全栈测试笔记5')
(6, '全栈测试笔记6')
(7, 'qzcsbj')
None
每条记录为字典格式
1
2
3
4
5
6
7
8
9
10
|
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
print
(cursor.fetchone())
|
运行结果:
{'id': 4, 'name': 'qzcsbj4'}
{'id': 5, 'name': '全栈测试笔记5'}
{'id': 6, 'name': '全栈测试笔记6'}
{'id': 7, 'name': 'qzcsbj'}
None
fetchmany
1
2
3
4
5
6
|
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
print
(cursor.fetchmany(
2
))
|
运行结果:
[{'id': 4, 'name': 'qzcsbj4'}, {'id': 5, 'name': '全栈测试笔记5'}]
fetchall
1
2
3
4
5
6
7
|
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
print
(cursor.fetchall())
print
(cursor.fetchall())
|
运行结果:
[{'id': 4, 'name': 'qzcsbj4'}, {'id': 5, 'name': '全栈测试笔记5'}, {'id': 6, 'name': '全栈测试笔记6'}, {'id': 7, 'name': 'qzcsbj'}]
[]
相对绝对位置移动
从头开始跳过n个
1
2
3
4
5
6
7
|
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
cursor.scroll(
3
,mode
=
'absolute'
)
print
(cursor.fetchone())
|
运行结果:
{'id': 7, 'name': 'qzcsbj'}
相对当前位置移动
1
2
3
4
5
6
7
8
|
# 获取游标
cursor
=
conn.cursor(pymysql.cursors.DictCursor)
# 执行sql语句
rows
=
cursor.execute(
'select * from test;'
)
print
(cursor.fetchone())
cursor.scroll(
2
,mode
=
'relative'
)
print
(cursor.fetchone())
|
运行结果:
{'id': 4, 'name': 'qzcsbj4'}
{'id': 7, 'name': 'qzcsbj'}
> > > 1、微信公众号:全栈测试笔记
> > > 2、技术交流Q群:652122175
> > > 3、性能测试从0到实战: https://www.cnblogs.com/uncleyong/p/12311432.html
> > > 4、自动化测试实战: https://www.cnblogs.com/uncleyong/p/12016690.html
> > > 5、测试汇总:
https://www.cnblogs.com/uncleyong/p/10530261.html
> > > 6、声明:本文部分内容可能来源或整理自网络,如有侵权,请联系删除。
================================ END ================================
<div class="clear"></div>
<div id="post_next_prev">
<a href="https://www.cnblogs.com/uncleyong/p/10931195.html" class="p_n_p_prefix">« </a> 上一篇: <a href="https://www.cnblogs.com/uncleyong/p/10931195.html" title="发布于 2019-05-26 15:59">mysql,本地连接看到的数据库不全,远程连接看到的数据库是完整的</a>
<br>
<a href="https://www.cnblogs.com/uncleyong/p/10990062.html" class="p_n_p_prefix">» </a> 下一篇: <a href="https://www.cnblogs.com/uncleyong/p/10990062.html" title="发布于 2019-06-01 10:09">JMeter基础【第六篇】JMeter5.1事务、检查点、集合点、思考时间、其余设置等</a>