dbc2000数据库 python python db2数据库操作

Python操作db2

import ibm_db
conn = ibm_db.connect("database=MICRO_11; "
                           "hostname=localhost; "
                           "port=50000; "
                           "protocol=tcpip; "
                           "uid=administrator; "
                           "pwd=wyz", "", "")
stmt = ibm_db.exec_immediate(conn,"SELECT SYS_ORG_TYPE_CODE,SYS_ORG_TYPE_NAME "
                                  "FROM SYS_ORG_TYPE_TB "
                                  "WHERE SYS_ORG_TYPE_UPID IS NOT NULL")
# if结果集条数为0：result==False
# if结果集条数>0：结果为一个tuple
result = ibm_db.fetch_tuple(stmt)
while result:
    print(result[0], result[1]) # 顺序和select字段顺序一样
    result = ibm_db.fetch_tuple(stmt)

 

一、建连接：

'''
ibm_db.connect() #非持久性连接
ibm_db.pconnect()  #持久性连接，提升性能，连接不关闭
'''
import ibm_db
conn = ibm_db.connect("dsn=name","username","password")
#连接cataloged或非cataloged数据库
ibm_db.connect("DATABASE=name;HOSTNAME=host;PORT=60000;PROTOCOL=TCPIP;UID=username;
                PWD=password;", "", "")

二、执行SQL：

不带参数的

'''
string可以为XQuery表达式，用XMLQuery包装的
如果将用户输入作为SQL变量，可能受到SQL注入攻击
返回的是cursor类型，调用 ibm_db.num_rows()可以得到影响的数据行数
如果执行错误，可通过ibm_db.stmt_error() 或 ibm_db.stmt_errormsg()得到错误信息
'''
import ibm_db
conn = ibm_db.connect("dsn=name","username","password")
stmt = ibm_db.exec_immediate(conn, "UPDATE employee SET bonus = '1000' WHERE job = 'MANAGER'")
print "Number of affected rows: ", ibm_db.num_rows(stmt)
# XQuery
if conn:
    sql = "SELECT XMLSERIALIZE(XMLQUERY('for $i in $t/address where $i/city = \"Olathe\" return <zip>{$i/zip/text()}</zip>' passing c.xmlcol as \"t\") AS CLOB(32k)) FROM xml_test c WHERE id = 1"
    stmt = ibm_db.exec_immediate(conn, sql)
    result = ibm_db.fetch_both(stmt)
    while( result ):
        print "Result from XMLSerialize and XMLQuery:", result[0]
        result = ibm_db.fetch_both(stmt)

 带参数的：

'''
ibm_db.prepare(), ibm_db.bind_param()，ibm_db.execute()三个方法
准备语句可以提高性能，因为数据库服务器为数据检索创建了优化的访问计划，如果再次执行该语句，则可以重用它
'''
import ibm_db
conn = ibm_db.connect("dsn=name","username","password")
sql = "SELECT EMPNO, LASTNAME FROM EMPLOYEE WHERE EMPNO > ? AND EMPNO < ?"
stmt = ibm_db.prepare(conn, sql)
max = 50
min = 0
# 绑定参数
ibm_db.bind_param(stmt, 1, min)
ibm_db.bind_param(stmt, 2, max)
ibm_db.execute(stmt)
# Process results

# Invoke prepared statement again using dynamically bound parameters
param = max, min, 
ibm_db.execute(stmt, param)

 三、检索结果集：ibm_db.fetch_both(stmt,num) 如果指定游标为scrollable类型，【在调用ibm_db.exec_immediate()或ibm_db.prepare()的时候】，num为检索的行数

import ibm_db
#  第一种方式：
conn = ibm_db.connect( "dsn=name", "username", "password" )
sql = "SELECT * FROM EMPLOYEE"
stmt = ibm_db.exec_immediate(conn, sql)
dictionary = ibm_db.fetch_both(stmt)
while dictionary != False:
    print "The ID is : ",  dictionary["EMPNO"]
    print "The Name is : ", dictionary[1]
    dictionary = ibm_db.fetch_both(stmt)
#  第二种方式：
tuple = ibm_db.fetch_tuple(stmt)
while tuple != False:
    print "The ID is : ", tuple[0]
    print "The name is : ", tuple[1]
    tuple = ibm_db.fetch_tuple(stmt)
# 第三种方式：
dictionary = ibm_db.fetch_assoc(stmt)
while dictionary != False:
    print "The ID is : ", dictionary["EMPNO"]
    print "The name is : ", dictionary["FIRSTNME"]
    dictionary = ibm_db.fetch_assoc(stmt)
# 第四种方式：
while ibm_db.fetch_row(stmt) != False:
    print "The Employee number is : ",  ibm_db.result(stmt, 0)
    print "The Name is : ", ibm_db.result(stmt, "NAME")

 四、调用存储过程

import ibm_db

conn = ibm_db.connect("dsn=sample","username","password")
if conn:
      sql = 'CALL match_animal(?, ?, ?)'
      stmt = ibm_db.prepare(conn, sql)
    
      name = "Peaches"
      second_name = "Rickety Ride"
      weight = 0
      ibm_db.bind_param(stmt, 1, name, ibm_db.SQL_PARAM_INPUT)
      ibm_db.bind_param(stmt, 2, second_name, ibm_db.SQL_PARAM_INPUT_OUTPUT)
      ibm_db.bind_param(stmt, 3, weight, ibm_db.SQL_PARAM_OUTPUT)
    
      print "Values of bound parameters _before_ CALL:"
      print "  1: %s 2: %s 3: %d\n" % (name, second_name, weight)
    
      if ibm_db.execute(stmt):
        print "Values of bound parameters _after_ CALL:"
        print "  1: %s 2: %s 3: %d\n" % (name, second_name, weight)

五、开启事务：适合大批量插入数据提升性能

import ibm_db

array = { ibm_db.SQL_ATTR_AUTOCOMMIT : ibm_db.SQL_AUTOCOMMIT_OFF }
conn = ibm_db.pconnect("dsn=SAMPLE", "user", "password", array)
sql = "DELETE FROM EMPLOYEE"
try:
   stmt = ibm_db.exec_immediate(conn, sql)
except:
   print "Transaction couldn't be completed."
   ibm_db.rollback(conn)
else:
   ibm_db.commit(conn)
   print "Transaction complete."

六、错误处理：

第一种：

import ibm_db 
try:
    conn = ibm_db.connect("dsn=sample","user","password")     
except:     
    print "no connection:", ibm_db.conn_errormsg()
else:
    print "The connection was successful"

第二种：

import ibm_db
conn = ibm_db.connect( "dsn=sample", "user", "password")
sql = "DELETE FROM EMPLOYEE"
try:
   stmt = ibm_db.exec_immediate(conn, sql)
except:
   print "Transaction couldn't be completed:" , ibm_db.stmt_errormsg()
else:
   print "Transaction complete."

七、查看元数据

注意：调用元数据函数消耗大量的空间。如果可能的话，考虑缓存调用的结果以便在后续调用中使用。

ibm_db.client_info()	返回包含数据库客户端信息的只读对象.
ibm_db.column_privileges()	返回一个结果集，列出表的column和其关联特权
ibm_db.columns()	返回一个结果集，列出表的column和其关联元数据
ibm_db.foreign_keys()	返回一个结果集，列出表的column和其关联元数据
ibm_db.primary_keys()	返回一个结果集，列出表的外键
ibm_db.procedure_columns()	返回一个结果集，列出一个或多个存储过程的参数
ibm_db.procedures()	返回一个结果集，列出数据库里注册了的的存储过程
ibm_db.server_info()	返回包含数据库服务器信息的只读对象.
ibm_db.special_columns()	返回一个结果集，列出 表的唯一行标识符列
ibm_db.statistics()	返回一个结果集，列出表的索引和统计信息
ibm_db.table_privileges()	返回一个结果集，列出数据库中的表和相关权限。

 

import ibm_db

conn = ibm_db.connect("dsn=sample", "user", "password")
client = ibm_db.client_info(conn)

# DB客户端信息
if client:
    print "DRIVER_NAME: string(%d) \"%s\"" % (len(client.DRIVER_NAME), client.DRIVER_NAME)
    print "DRIVER_VER: string(%d) \"%s\"" % (len(client.DRIVER_VER), client.DRIVER_VER)
    print "DATA_SOURCE_NAME: string(%d) \"%s\"" % (len(client.DATA_SOURCE_NAME), client.DATA_SOURCE_NAME)
    print "DRIVER_ODBC_VER: string(%d) \"%s\"" % (len(client.DRIVER_ODBC_VER), client.DRIVER_ODBC_VER)
    print "ODBC_VER: string(%d) \"%s\"" % (len(client.ODBC_VER), client.ODBC_VER)
    print "ODBC_SQL_CONFORMANCE: string(%d) \"%s\"" % (len(client.ODBC_SQL_CONFORMANCE), client.ODBC_SQL_CONFORMANCE)
    print "APPL_CODEPAGE: int(%s)" % client.APPL_CODEPAGE
    print "CONN_CODEPAGE: int(%s)" % client.CONN_CODEPAGE
    ibm_db.close(conn)
else:
    print "Error."

# DB服务器信息
server = ibm_db.server_info(conn)

if server:
    print "DBMS_NAME: string(%d) \"%s\"" % (len(server.DBMS_NAME), server.DBMS_NAME)
    print "DBMS_VER: string(%d) \"%s\"" % (len(server.DBMS_VER), server.DBMS_VER)
    print "DB_NAME: string(%d) \"%s\"" % (len(server.DB_NAME), server.DB_NAME)
    ibm_db.close(conn)
else:
    print "Error."