python连接sql server数据库实现增删改查

python连接sql server数据库实现增删改查

 摘自https://www.cnblogs.com/malcolmfeng/p/6909293.html

　　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