正确安装好cx_oracle之后，要使用它来连接到oracle数据库进行操作，具体应该分3步走：
第一步：导入cx_Oracle ，建立连接
>>>
import cx_Oracle #
导入模块
>>>
db = cx_Oracle.connect('hr', 'hrpwd', 'localhost:1521/XE')
建立连接，3
个参数分开写
>>>
db1 = cx_Oracle.connect('hr/hrpwd@localhost:1521/XE')
建立连接，3
个参数连写
>>>
dsn_tns = cx_Oracle.makedsn('localhost', 1521, 'XE')
>>>
print dsn_tns
(DESCRIPTION=(ADDRESS_LIST=(ADDRESS=(PROTOCOL=TCP)(HOST=localhost)(PORT=1521)))
(CONNECT_DATA=(SID=XE)))
>>>
db2 = cx_Oracle.connect('hr', 'hrpwd', dsn_tns)
>>> print db.version
10.2.0.1.0
>>> versioning = db.version.split('.')
>>> print versioning
['10', '2', '0', '1', '0']
>>> if versioning[0]=='10':
... print "Running 10g"
... elif versioning[0]=='9':
... print "Running 9i"
...
Running 10g
>>> print db.dsn
localhost:1521/XE
第二步：建立
Cursor
光标
>>>cursor = db.cursor() 建立一个cursor
之后，我们可以调用这个cursor.execute（‘SQL‘） 来执行SQL语句。比如：
>>>cursor.execute(‘select * from tabs’)
执行完毕以后，可以调用cursor.fetchall()一次取完所有结果，或者cursor.fetchone()一次取一行结果
>>>row=cursor.fetchall()
>>>for x in row:
For y in x:
Print y,
Print
在从oracle取出数据的时候，考虑到它的数据类型了吗？下面就是数据类型的对应表
Datatypes
During the fetch stage, basic Oracle data types get mapped into their Python equivalents. cx_Oracle maintains a separate set of data types that helps in this transition. The Oracle - cx_Oracle - Python mappings are:
|
Oracle
|
cx_Oracle
|
Python
|
|
VARCHAR2
NVARCHAR2
LONG
|
cx_Oracle.STRING
|
str
|
|
CHAR
|
cx_Oracle.FIXED_CHAR
|
|
NUMBER
|
cx_Oracle.NUMBER
|
int
|
|
FLOAT
|
float
|
|
DATE
|
cx_Oracle.DATETIME
|
datetime.datetime
|
|
TIMESTAMP
|
cx_Oracle.TIMESTAMP
|
|
CLOB
|
cx_Oracle.CLOB
|
cx_Oracle.LOB
|
|
BLOB
|
cx_Oracle.BLOB
|
带参数的查询：
>>> named_params = {'dept_id':50, 'sal':1000}
>>> query1 = cursor.execute('SELECT * FROM employees
WHERE department_id=:dept_id AND salary>:sal', named_params)
>>> query2 = cursor.execute('SELECT * FROM employees
WHERE department_id=:dept_id AND salary>:sal', dept_id=50, sal=1000)
这种是名字参数，还可以按位置参数：
r1 = cursor.execute('SELECT * FROM locations
WHERE country_id=:1 AND city=:2', ('US', 'Seattle'))
注意：
当只有一次参数的时候，也要把它写成元组的形式，比如
Cursor.execute(‘select name from user where id=:1’,(login_Id,))
千万要注意，login_id后面还带有一个逗号，如果没有逗号，他其实就是一个数据对象，但是当他后面有个逗号的时候，他就变成了元组的一个数据项，千万要记住啊，我就是在这里徘徊了很久。！
Cursor. Prepare的用法，
这个方法就是在prepare之后，你再去execute的时候，就不用写上sql语句参数了
>>> cursor.prepare('SELECT * FROM jobs WHERE min_salary>:min')
>>> r = cursor.execute(None, {'min':1000}) #注意，第一个参数是None,
一次执行多条sql语句
Large insert operations don't require many separate inserts because Python fully supports inserting many rows at once with the cx_Oracle.Cursor.executemany method. Limiting the number of execute operations improves program performance a lot and should be the first thing to think about when writing applications heavy on INSERTs.
Let's create a table for a Python module list, this time directly from Python. You will drop it later.
>>> create_table = """
CREATE TABLE python_modules (
module_name VARCHAR2(50) NOT NULL,
file_path VARCHAR2(300) NOT NULL
)
"""
>>> from sys import modules
>>> cursor.execute(create_table)
>>> M = []
>>> for m_name, m_info in modules.items():
... try:
... M.append((m_name, m_info.__file__))
... except AttributeError:
... pass
...
>>> len(M)
76
>>> cursor.prepare("INSERT INTO python_modules(module_name, file_path) VALUES (:1, :2)")
>>> cursor.executemany(None, M)
>>> db.commit()
>>> r = cursor.execute("SELECT COUNT(*) FROM python_modules")
>>> print cursor.fetchone()
(76,)
>>> cursor.execute("DROP TABLE python_modules PURGE")
