Python 操作 MySQL--（pymysql）
pymysql
pymsql是Python中操作MySQL的模块，其使用方法和MySQLdb几乎相同。
1、下载安装
pip3 install pymysql
2、执行SQL
执行SQL语句的基本语法：
需要注意的是：创建连接后，都由游标来进行与数据库的操作，因而获取数据也需要游标。
#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = 'wyf' import pymysql #创建链接
conn = pymysql.connect(host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test')
#创建游标 cursor = conn.cursor()
#print cursor #执行语句，返回数据结果总数量
effect_new = cursor.execute('select * from A')
#print effect_new
#结果是 7
# 执行SQL，并返回受影响行数
effect_row = cursor.executemany('select * from A where aID=%s',[3,4,5])
print effect_row
#结果是3
# 提交，不然无法保存新建或者修改的数据
conn.commit() # 关闭游标
cursor.close()
# 关闭连接
conn.close()
3.获取新建数据的自增ID
可以获取到最新自增的ID，也就是最后插入的一条数据ID
#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = 'wyf' import pymysql #创建链接
conn = pymysql.connect(host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test')
#创建游标 cursor = conn.cursor()
#print cursor # 执行SQL，并返回受影响行数
effect_row = cursor.executemany('insert into A(aNum) values(%s)',['ggg','hhhh','ffff']) # 提交，不然无法保存新建或者修改的数据
conn.commit()
print cursor.fetchall()
# 关闭游标
cursor.close()
# 关闭连接
conn.close() # 获取最新自增ID,注意是最新的id，多条也是一条
new_id = cursor.lastrowid
print new_id
4、获取查询数据
获取查询数据的三种方式：获取第一行数据，获取前n行数据，获取所有数据 （数据是以元祖的方式存放）
#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = 'wyf' import pymysql #创建链接
conn = pymysql.connect(host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test')
#创建游标 cursor = conn.cursor()
#print cursor #获取所有数据
cursor.execute('select * from A') #获取第一条数据
row_1 = cursor.fetchone()
print 'row_1=',row_1
#获取前N条数据
row_n = cursor.fetchmany(3)
print 'row_n=',row_n
# 获取所有数据
row_all = cursor.fetchall()
print 'row_all=',row_all
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
结果：
aaarticlea/png;base64,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" alt="" />
注：在fetch数据时按照顺序进行，可以使用cursor.scroll(num,mode)来移动游标位置，如：
- cursor.scroll(1,mode='relative') # 相对当前位置移动
- cursor.scroll(2,mode='absolute') # 相对绝对位置移动
示例：
#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = 'wyf' import pymysql #创建链接
conn = pymysql.connect(host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test')
#创建游标 cursor = conn.cursor()
#print cursor #获取所有数据
cursor.execute('select * from A')
#所有查询数据都打印一编，方便对比
print '''row_all= ((1, 'a20050111'), (9, 'sdasdas'), (3, 'a20050113'), (4, 'a20050114'), (5, 'a20050115'), (6, 'a20160928'), (7, 'sdasdasdadasd'), (8, 'sdasdasdadasd'), (17, 'ffff'), (16, 'hhhh'), (15, 'ggg'))'''
cursor.scroll(1, mode='relative') # 相对当前位置移动
row_all_1 = cursor.fetchone()
print 'row_all_1=',row_all_1
cursor.scroll(2, mode='absolute') # 相对绝对位置移动
row_all_2 = cursor.fetchone()
print 'row_all_2=',row_all_2
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
结果：
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alt="" />
总结：
1.当用fetchall的时候游标指针会移动到最后，请在使用scroll的时候注意。
2.结果分析，相对是当前指针的位置，绝对是指针整体位置。
3.(1, mode='relative') 当前指针下移一个的位置，及地第二个，(2, mode='absolute')，最初的指针下移两个，因为这个结果指针最初都是最开始。
5.fetch数据类型
默认拿到的数据是元祖类型，如果是字典的话会更方便操作，那方法来了：
#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = 'wyf' import pymysql #创建链接
conn = pymysql.connect(host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test')
#创建游标 cursor = conn.cursor()
#print cursor # 游标设置为字典类型
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
r = cursor.execute("select * from A")
result = cursor.fetchone()
print 'result=',result
conn.commit()
# 关闭游标
cursor.close()
# 关闭连接
conn.close()
aaarticlea/png;base64,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" alt="" />
6.利用with自动关闭
# 利用with定义函数
@contextlib.contextmanager
def mysql(self, host='192.168.14.88',port=3306,user='root',passwd='',db='hive_test', charset='utf8'):
self.conn = pymysql.connect(host=host, port=port, user=user, passwd=passwd, db=db, charset=charset)
self.cuersor = self.conn.cursor(cursor=pymysql.cursors.DictCursor)
try:
yield self.cuersor
finally:
self.conn.commit()
self.cuersor.close()
self.conn.close()
# 执行
with mysql() as cuersor:
print(cuersor)
# 操作MySQL代码块
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