Schema是什麼?
不管我們做什麼應用,只要和使用者輸入打交道,就有一個原則--永遠不要相信使用者的輸入資料。意味著我們要對使用者輸入進行嚴格的驗證,web開發時一般輸入資料都以JSON形式傳送到後端API,API要對輸入資料做驗證。一般我都是加很多判斷,各種if,導致程式碼很醜陋,能不能有一種方式比較優雅的驗證使用者資料呢? Schema就派上用場了。本文主要介紹了MySQL資料庫設計之利用Python操作Schema方法詳解,還是比較不錯的,這裡分享給大家,供需要的朋友參考。
㈠ MySQLdb部分
#表格結構:
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)
資料庫連線模組:
[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 列印列的元資料
[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.)呼叫execute()之後,cursor應設定其description屬性
2.)是個tuple,共7列:列名、型別、顯示大小、內部大小、精度、範圍以及一個是否接受null值的標記[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)
預設情況下,取得方法從資料庫作為"行"傳回的值是元組
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
我們能夠借助cursorclass屬性來作為字典傳回
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煉金術師
雖然SQL有國際標準,但遺憾的是,各個資料庫廠商對這些標準的解讀都不一樣,並且都在標準的基礎上實現了各自的私有語法。為了隱藏不同SQL「方言」之間到區別,人們開發了諸如SQLAlchemy之類的工具 #SQLAlchemy連接模組:[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()
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:表格刪除
##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種限制
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 預設值
分為2類:悲觀(值由DB Server提供)和樂觀(值由SQLAlshemy提供),其中樂觀又可分: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 隱藏Schema
需求:隱藏表結構,實作動態查詢,並將結果模擬mysql \G輸出版本: [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>......######請看程式碼#########
#!/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()#########相關推薦:#########關於資料庫中table與schema的區別詳解############MySQL中關於information_schema的詳細介紹############MySQL分散式叢集之MyCAT(二)schema程式碼詳解######
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