MySQL Schema设计(三)利用Python操作Schema

弓在箭要射出之前,低声对箭说道,“你的*是我的”。Schema如箭,弓似Python,选择Python,是Schema最大的*。而*应是一个能使自己变得更好的机会。

㈠ MySQLdb部分


表结构:
mysql> use sakila;
mysql> desc actor;
+-------------+----------------------+------+-----+-------------------+-----------------------------+
| Field       | Type                 | Null | Key | Default           | Extra                       |
+-------------+----------------------+------+-----+-------------------+-----------------------------+
| actor_id    | smallint(5) unsigned | NO   | PRI | NULL              | auto_increment              |
| first_name  | varchar(45)          | NO   |     | NULL              |                             |
| last_name   | varchar(45)          | NO   | MUL | NULL              |                             |
| last_update | timestamp            | NO   |     | CURRENT_TIMESTAMP | on update CURRENT_TIMESTAMP |
+-------------+----------------------+------+-----+-------------------+-----------------------------+
4 rows in set (0.00 sec)

数据库连接模块:
[root@DataHacker ~]# cat dbapi.py
#!/usr/bin/env ipython
#coding = utf-8
#Author: linwaterbin@gmail.com
#Time: 2014-1-29

import MySQLdb as dbapi

USER = ‘root‘
PASSWD = ‘oracle‘
HOST = ‘127.0.0.1‘
DB = ‘sakila‘

conn = dbapi.connect(user=USER,passwd=PASSWD,host=HOST,db=DB)

1 打印列的元数据
[root@DataHacker ~]# cat QueryColumnMetaData.py
#!/usr/bin/env ipython

from dbapi import *

cur = conn.cursor()
statement = """select * from actor limit 1"""
cur.execute(statement)

print "output column metadata....."
print
for record in cur.description:
    print record

cur.close()
conn.close()

1.)调用execute()之后,cursor应当设置其description属性

2.)是个tuple,共7列:列名、类型、显示大小、内部大小、精度、范围以及一个是否接受null值的标记
[root@DataHacker ~]# chmod +x QueryColumnMetaData.py
[root@DataHacker ~]# ./QueryColumnMetaData.py
output column metadata.....

(‘actor_id‘, 2, 1, 5, 5, 0, 0)
(‘first_name‘, 253, 8, 45, 45, 0, 0)
(‘last_name‘, 253, 7, 45, 45, 0, 0)
(‘last_update‘, 7, 19, 19, 19, 0, 0)

2 通过列名访问列值

默认情况下,获取方法从数据库作为"行"返回的值是元组
In [1]: from dbapi import *

In [2]: cur = conn.cursor()

In [3]: v_sql = "select actor_id,last_name from actor limit 2"

In [4]: cur.execute(v_sql)
Out[4]: 2L

In [5]: results = cur.fetchone()

In [6]: print results[0]
58

In [7]: print results[1]
AKROYD

我们能够借助cursorclass属性来作为字典返回
In [2]: import MySQLdb.cursors

In [3]: import MySQLdb

In [4]: conn = MySQLdb.connect(user=‘root‘,passwd=‘oracle‘,host=‘127.0.0.1‘,db=‘sakila‘,cursorclass=MySQLdb.cursors.DictCursor)

In [5]: cur = conn.cursor()

In [6]: v_sql = "select actor_id,last_name from actor limit 2"

In [7]: cur.execute(v_sql)
Out[7]: 2L

In [8]: results = cur.fetchone()

In [9]: print results[‘actor_id‘]
58

In [10]: print results[‘last_name‘]
AKROYD


㈡ SQLAlchemy--SQL炼金术师


虽然SQL有国际标准,但遗憾的是,各个数据库厂商对这些标准的解读都不一样,并且都在标准的基础上实现了各自的私有语法。为了隐藏不同SQL“方言”之间到区别,人们开发了诸如SQLAlchemy之类的工具

SQLAlchemy连接模块:
SQLAlchemy连接模块:
[root@DataHacker Desktop]# cat sa.py
import sqlalchemy as sa
engine = sa.create_engine(‘mysql://root:oracle@127.0.0.1/testdb‘,pool_recycle=3600)
metadata = sa.MetaData()

example 1:表定义
In [3]: t = Table(‘t‘,metadata,
     ...:                Column(‘id‘,Integer),
     ...:                Column(‘name‘,VARCHAR(20)),
     ...:                mysql_engine=‘InnoDB‘,
     ...:                mysql_charset=‘utf8‘
     ...:              )

In [4]: t.create(bind=engine)

example 2:表删除
有2种方式,其一:
In [5]: t.drop(bind=engine,checkfirst=True) 
另一种是:
In [5]: metadata.drop_all(bind=engine,checkfirst=True),其中可以借助tables属性指定要删除的对象

example 3: 5种约束
3 .1 primary key
下面2种方式都可以,一个是列级,一个是表级
In [7]: t_pk_col = Table(‘t_pk_col‘,metadata,Column(‘id‘,Integer,primary_key=True),Column(‘name‘,VARCHAR(20)))

In [8]: t_pk_col.create(bind=engine)


In [9]: t_pk_tb = Table(‘t_pk_01‘,metadata,Column(‘id‘,Integer),Column(‘name‘,VARCHAR(20)),PrimaryKeyConstraint(‘id‘,‘name‘,name=‘prikey‘))

In [10]: t_pk_tb.create(bind=engine)


3.2 Foreign Key
In [13]: t_fk = Table(‘t_fk‘,metadata,Column(‘id‘,Integer,ForeignKey(‘t_pk.id‘)))

In [14]: t_fk.create(bind=engine)

In [15]: t_fk_tb = Table(‘t_fk_tb‘,metadata,Column(‘col1‘,Integer),Column(‘col2‘,VARCHAR(10)),ForeignKeyConstraint([‘col1‘,‘col2‘],[‘t_pk.id‘,‘t_pk.name‘]))

In [16]: t_fk_tb.create(bind=engine)



3.3 unique
In [17]: t_uni = Table(‘t_uni‘,metadata,Column(‘id‘,Integer,unique=True))

In [18]: t_uni.create(bind=engine)

In [19]: t_uni_tb = Table(‘t_uni_tb‘,metadata,Column(‘col1‘,Integer),Column(‘col2‘,VARCHAR(10)),UniqueConstraint(‘col1‘,‘col2‘))

In [20]: t_uni_tb.create(bind=engine)



3.4 check
     虽然能成功,但MySQL目前尚未支持check约束。这里就不举例了。
3.5 not null
In [21]: t_null = Table(‘t_null‘,metadata,Column(‘id‘,Integer,nullable=False))

In [22]: t_null.create(bind=engine)


4 默认值

分2类:悲观(值由DB Server提供)和乐观(值由SQLAlshemy提供),其中乐观又可分:insert和update

4.1 例子:insert
In [23]: t_def_inser = Table(‘t_def_inser‘,metadata,Column(‘id‘,Integer),Column(‘name‘,VARCHAR(10),server_default=‘cc‘))

In [24]: t_def_inser.create(bind=engine)

3.2 例子:update
In [25]: t_def_upda = Table(‘t_def_upda‘,metadata,Column(‘id‘,Integer),Column(‘name‘,VARCHAR(10),server_onupdate=‘DataHacker‘))

In [26]: t_def_upda.create(bind=engine)
3.3 例子:Passive 
In [27]: t_def_pass = Table(‘t_def_pass‘,metadata,Column(‘id‘,Integer),Column(‘name‘,VARCHAR(10),DefaultClause(‘cc‘)))

In [28]: t_def_pass.create(bind=engine)


㈢ 隐藏Schema


数据的安全是否暴露在完全可信任的对象面前,这是任何有安全意识的DBA都不会去冒的风险。比较好的方式是尽可能隐藏Schema结构并验证用户输入的数据完整性,这在一定程度上虽然增加了运维成本,但安全无小事。

这里借助开发一个命令行工具来阐述该问题
需求:隐藏表结构,实现动态查询,并将结果模拟mysql \G输出
版本:
[root@DataHacker ~]# ./sesc.py --version
1.0

查看帮助:
[root@DataHacker ~]# ./sesc.py -h
Usage: sesc.py [options] <arg1> <arg2> [<arg3>...]

Options:
  --version             show program‘s version number and exit
  -h, --help            show this help message and exit
  -q TERM               assign where predicate
  -c COL, --column=COL  assign query column
  -t TABLE              assign query table
  -f, --format          -f must match up -o
  -o OUTFILE            assign output file

我们要的效果:
[root@DataHacker ~]# ./sesc.py -t actor -c last_name -q s% -f -o output.txt
[root@DataHacker ~]# cat output.txt
************ 1 row *******************

actor_id: 180
first_name: JEFF
last_name: SILVERSTONE
last_update: 2006-02-15 04:34:33

************ 2 row *******************

actor_id: 195
first_name: JAYNE
last_name: SILVERSTONE
last_update: 2006-02-15 04:34:33
......<此处省略大部分输出>......

请看代码
#!/usr/bin/env python
import optparse
from dbapi import *


#构造OptionParser实例,配置期望的选项
parser = optparse.OptionParser(usage="%prog [options] <arg1> <arg2> [<arg3>...]",version=‘1.0‘,)
#定义命令行选项,用add_option一次增加一个
parser.add_option("-q",action="store",type="string",dest="term",help="assign where predicate")
parser.add_option("-c","--column",action="store",type="string",dest="col",help="assign query column")
parser.add_option("-t",action="store",type="string",dest="table",help="assign query table")
parser.add_option("-f","--format",action="store_true",dest="format",help="-f must match up -o")
parser.add_option("-o",action="store",type="string",dest="outfile",help="assign output file")
#解析命令行
options,args = parser.parse_args()

#把上述dest值赋给我们自定义的变量
table = options.table
column = options.col
term = options.term
format = options.format

#实现动态读查询
statement = "select * from %s where %s like ‘%s‘"%(table,column,term)
cur = conn.cursor()
cur.execute(statement)
results = cur.fetchall()

#模拟 \G 输出形式
if format is True:
  columns_query = "describe %s"%(table)
  cur.execute(columns_query)
  heards = cur.fetchall()
  column_list = []
  for record in heards:
    column_list.append(record[0])
  output = ""
  count = 1
  for record in results:
    output = output + "************ %s row ************\n\n"%(count)
    for field_no in xrange(0, len(column_list)):
      output = output + column_list[field_no]+ ": " + str(record[field_no]) + "\n"
    output = output + "\n"
    count = count + 1
else:
  output = []
  for record in xrange(0,len(results)):
    output.append(results[record])
  output = ‘‘.join(output)

#把输出结果定向到指定文件
if options.outfile:
  outfile = options.outfile
  with open(outfile,‘w‘) as out:
    out.write(output)
else:
  print output

#关闭游标与连接
conn.close()
cur.close()


By DataHacker
2014-2-5
Good Luck!

MySQL Schema设计(三)利用Python操作Schema

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