python连接sql server数据库实现增删改查

　　简述

　　python连接微软的sql server数据库用的第三方模块叫做pymssql（document：http://www.pymssql.org/en/stable/index.html）。在官方文档可以看到，pymssql是基于_mssql模块做的封装，是为了遵守python的DBAPI规范接口. 两者之间的关系如下图：

　　1.使用pymssql连接sql server数据库并实现数据库基本操作(官方api http://www.pymssql.org/en/stable/ref/pymssql.html )

1）基本语法

import pymssql 

server = "187.32.43.13"    # 连接服务器地址
user = "root"　　　　　　　　 # 连接帐号
password = "1234"　　　　　　# 连接密码

conn = pymssql.connect(server, user, password, "连接默认数据库名称")  #获取连接

cursor = conn.cursor() # 获取光标

# 创建表
cursor.execute("""
IF OBJECT_ID(\'persons\', \'U\') IS NOT NULL
    DROP TABLE persons
CREATE TABLE persons (
    id INT NOT NULL,
    name VARCHAR(100),
    salesrep VARCHAR(100),
    PRIMARY KEY(id)
)
""")　　

# 插入多行数据
cursor.executemany(
    "INSERT INTO persons VALUES (%d, %s, %s)",
    [(1, \'John Smith\', \'John Doe\'),
     (2, \'Jane Doe\', \'Joe Dog\'),
     (3, \'Mike T.\', \'Sarah H.\')])
# 你必须调用 commit() 来保持你数据的提交如果你没有将自动提交设置为true
conn.commit()

# 查询数据
cursor.execute(\'SELECT * FROM persons WHERE salesrep=%s\', \'John Doe\')

# 遍历数据（存放到元组中） 方式1
row = cursor.fetchone()
while row:
    print("ID=%d, Name=%s" % (row[0], row[1]))
    row = cursor.fetchone()

# 遍历数据（存放到元组中） 方式2
for row in cursor:
    print(\'row = %r\' % (row,))


# 遍历数据（存放到字典中）

# cursor = conn.cursor(as_dict=True)
#
# cursor.execute(\'SELECT * FROM persons WHERE salesrep=%s\', \'John Doe\')
# for row in cursor:
#     print("ID=%d, Name=%s" % (row[\'id\'], row[\'name\']))
#
# conn.close()

# 关闭连接
conn.close()

# 注：在任何时候，在一个连接下，一次正在执行的数据库操作只会出现一个cursor对象

2）同时，如果你可以使用另一种语法：with 来避免手动关闭cursors和connection连接

import pymssql 

server = "187.32.43.13"    # 连接服务器地址
user = "root"　　　　　　　　 # 连接帐号
password = "1234"　　　　　　# 连接密码

with pymssql.connect(server, user, password, "你的连接默认数据库名称") as conn:
    with conn.cursor(as_dict=True) as cursor:   # 数据存放到字典中
        cursor.execute(\'SELECT * FROM persons WHERE salesrep=%s\', \'John Doe\')
        for row in cursor:
            print("ID=%d, Name=%s" % (row[\'id\'], row[\'name\']))

3）调用存储过程：

with pymssql.connect(server, user, password, "tempdb") as conn:
    with conn.cursor(as_dict=True) as cursor:
        cursor.execute("""
        CREATE PROCEDURE FindPerson
            @name VARCHAR(100)
        AS BEGIN
            SELECT * FROM persons WHERE name = @name
        END
        """)
        cursor.callproc(\'FindPerson\', (\'Jane Doe\',))
        for row in cursor:
            print("ID=%d, Name=%s" % (row[\'id\'], row[\'name\']))

　　　　2.使用_mssql连接sql server数据库并实现操作（官方api http://www.pymssql.org/en/stable/ref/_mssql.html）

1）基本语法：

import _mssql
# 创建连接
conn = _mssql.connect(server=\'SQL01\', user=\'user\', password=\'password\', \
    database=\'mydatabase\')
print(conn.timeout)
print(conn.login_timeout)

# 创建table
conn.execute_non_query(\'CREATE TABLE persons(id INT, name VARCHAR(100))\')
# insert数据
conn.execute_non_query("INSERT INTO persons VALUES(1, \'John Doe\')")
conn.execute_non_query("INSERT INTO persons VALUES(2, \'Jane Doe\')")
# 查询操作
conn.execute_query(\'SELECT * FROM persons WHERE salesrep=%s\', \'John Doe\')
for row in conn:
    print "ID=%d, Name=%s" % (row[\'id\'], row[\'name\'])
#查询数量count()
numemployees = conn.execute_scalar("SELECT COUNT(*) FROM employees")
# 查询一条数据
employeedata = conn.execute_row("SELECT * FROM employees WHERE id=%d", 13)
# 带参数查询的几个例子：
conn.execute_query(\'SELECT * FROM empl WHERE id=%d\', 13)
conn.execute_query(\'SELECT * FROM empl WHERE name=%s\', \'John Doe\')
conn.execute_query(\'SELECT * FROM empl WHERE id IN (%s)\', ((5, 6),))
conn.execute_query(\'SELECT * FROM empl WHERE name LIKE %s\', \'J%\')
conn.execute_query(\'SELECT * FROM empl WHERE name=%(name)s AND city=%(city)s\', \
    { \'name\': \'John Doe\', \'city\': \'Nowhere\' } )
conn.execute_query(\'SELECT * FROM cust WHERE salesrep=%s AND id IN (%s)\', \
    (\'John Doe\', (1, 2, 3)))
conn.execute_query(\'SELECT * FROM empl WHERE id IN (%s)\', (tuple(xrange(4)),))
conn.execute_query(\'SELECT * FROM empl WHERE id IN (%s)\', \
    (tuple([3, 5, 7, 11]),))
#关闭连接
conn.close()

pymssql托管在Github上：https://github.com/pymssql