Python SqlAlchemy使用方法
1.初始化連接
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
engine = create_engine('mysql://pass@localhost/test'echo=True)
DBSession = sessionmaker(bind=engine)
session = DBSession()
ret=session.execute('desc user')
print ret
# print ret.fetchall()print ret.first()mysql://root:pass/test
root是用戶名 pass密碼 test數據庫
session相當於MySQLdb里面的游標
first 相當於fetchone
echo=True 會輸出所有的sql
2.創建表
from sqlalchemy import Column
from sqlalchemy.types import *
from sqlalchemy.ext.declarative import declarative_base
BaseModel = declarative_base()
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
engine = create_engine('mysql://root:Hs2BitqLYKoruZJbT8SV@localhost/test')
DBSession = sessionmaker(bind=engine)
class User(BaseModel):
__tablename__ = 'user1' # 表名
user_name = Column(CHAR(30), primary_key=True)
pwd = Column(VARCHAR(20), default='aaa', nullable=False)
age = Column(SMALLINT(), server_default='12')
accout = Column(INT())
birthday = Column(TIMESTAMP())
article = Column(TEXT())
height = Column(FLOAT())
def init_db():''' 初始化數據庫 :return: '''
BaseModel.metadata.create_all(engine)
def drop_db():''' 刪除所有數據表 :return: '''
BaseModel.metadata.drop_all(engine)
drop_db()
init_db()和django的 ORM一樣 一旦表被創建了，修改User類不能改變數據庫結構，只能用sql語句或刪除表再創建來修改數據庫結構
sqlalchemy.types里面有所有的數據字段類型，等於sql類型的大寫
default參數是插入數據的時候，sqlalchemy自己處理的，server_default才是讓mysql處理的
3.添加記錄
user1=User(user_name='lujianxing',accout=1245678)
session.add(user1)
session.commit()要commit才能起作用
4.更新記錄
1.更新單條記錄
query = session.query(User)
user = query.get('lujianxing11')
print user.accout
user.accout='987'
session.flush()2.更新多條記錄
query = session.query(User)
query.filter(User.user_name=='lujianxing2').update({User.age: '15'})
query.filter(User.user_name=='lujianxing2').update({'age': '16'})
query.filter(User.pwd=='aaa').update({'age': '17'})5.刪除記錄
query = session.query(User)
user = query.get('lujianxing11')
session.delete(user)
session.flush()6.查詢
query = session.query(User)
print query # 只顯示sql語句，不會執行查詢print query[0] # 執行查詢print query.all() # 執行查詢print query.first() # 執行查詢for user in query: # 執行查詢print user.user_name如果字段的類型是數字型，查詢出來的type也是數字型的，不是字符串
高級一點的查詢：
# 篩選
user = query.get(1) # 根據主鍵獲取print query.filter(User.user_name == 2) # 只顯示sql語句，不會執行查詢print query.filter(User.user_name == 'lujianxing').all() # 執行查詢print query.filter(User.user_name == 'lujianxing', User.accout == 1245678, User.age > 10).all() # 執行查詢print query.filter(User.user_name == 'lujianxing').filter(User.accout == 1245678).all()
print query.filter("user_name = 'lujianxing'").all() # 執行查詢print query.filter("user_name = 'lujianxing' and accout=1245678").all() # 執行查詢
query2 = session.query(User.user_name) # 返回的結果不是User的實例，而是元組print query2.all() # 執行查詢print query2.offset(1).limit(1).all() # 等於 limit 1,1# 排序print query2.order_by(User.user_name).all()
print query2.order_by('user_name').all()
print query2.order_by(User.user_name.desc()).all()
print query2.order_by(User.user_name, User.accout.desc()).all()
print query2.filter("user_name = 'lujianxing' and accout=1245678").count()
# 聚合查詢print session.query(func.count('*')).select_from(User).scalar()
print session.query(func.count('1')).select_from(User).scalar()
print session.query(func.count(User.id)).scalar()
print session.query(func.count('*')).filter(User.id > 0).scalar() # filter() 中包含 User，因此不需要指定表print session.query(func.count('*')).filter(User.name == 'a').limit(1).scalar() == 1 # 可以用 limit() 限制 count() 的返回數print session.query(func.sum(User.id)).scalar()
print session.query(func.now()).scalar() # func 后可以跟任意函數名，只要該數據庫支持print session.query(func.current_timestamp()).scalar()
print session.query(func.md5(User.name)).filter(User.id == 1).scalar()參考文章
英文文檔
Engine Configuration
中文
Python SQLAlchemy基本操作和常用技巧
http://www.jianshu.com/p/152685de2533
SQLAlchemy 教程
SQLAlchemy 是python 操作數據庫的一個庫。能夠進行 orm 映射官方文檔 sqlchemy
SQLAlchemy“采用簡單的Python語言，為高效和高性能的數據庫訪問設計，實現了完整的企業級持久模型”。SQLAlchemy的理念是，SQL數據庫的量級和性能重要於對象集合；而對象集合的抽象又重要於表和行。
一 安裝 SQLAlchemy
pip install sqlalchemy導入如果沒有報錯則安裝成功
>>> import sqlalchemy
>>> sqlalchemy.__version__'0.9.1'>>>二 使用 sqlalchemy對數據庫操作
(1). 定義元信息，綁定到引擎
>>> from sqlalchemy import *>>> from sqlalchemy.orm import *>>> engine = create_engine('sqlite:///./sqlalchemy.db', echo=True) #定義引擎>>> metadata = MetaData(engine) # 綁定元信息 >>>(2).創建表格，初始化數據庫
>>> users_table = Table('users', metadata,
... Column('id', Integer, primary_key=True),
... Column('name', String(40)),
... Column('email', String(120)))
>>>
>>> users_table.create()
2014-01-09 10:03:32,436 INFO sqlalchemy.engine.base.Engine
CREATE TABLE users (
id INTEGER NOT NULL,
name VARCHAR(40),
email VARCHAR(120),
PRIMARY KEY (id)
)
2014-01-09 10:03:32,436 INFO sqlalchemy.engine.base.Engine ()
2014-01-09 10:03:32,575 INFO sqlalchemy.engine.base.Engine COMMIT
>>>執行上述代碼，我們就創建 一個 users 表，有id， name， email 三個字段
(env)ghost@ghost-H61M-S2V-B3:~/project/flask/fsql$ sqlite3 sqlalchemy.db
SQLite version 3.7.13 2012-06-11 02:05:22Enter ".help" for instructions
Enter SQL statements terminated with a ";"
sqlite> .tables
users
sqlite> (3). 基本操作，插入
如果已經table表已經存在， 第二次運行就不許要 create了， 使用 autoload 設置
>>> from sqlalchemy import *
>>> from sqlalchemy.orm import *
>>> engine = create_engine('sqlite:///./sqlalchemy.db', echo=True)
>>> metadata = MetaData(engine)
>>> users_table = Table('users', metadata, autoload=True)
2014-01-09 10:20:01,580 INFO sqlalchemy.engine.base.Engine PRAGMA table_info("users")
2014-01-09 10:20:01,581 INFO sqlalchemy.engine.base.Engine ()
2014-01-09 10:20:01,582 INFO sqlalchemy.engine.base.Engine PRAGMA foreign_key_list("users")
2014-01-09 10:20:01,583 INFO sqlalchemy.engine.base.Engine ()
2014-01-09 10:20:01,583 INFO sqlalchemy.engine.base.Engine PRAGMA index_list("users")
2014-01-09 10:20:01,583 INFO sqlalchemy.engine.base.Engine ()
>>> users_table
Table('users', MetaData(bind=Engine(sqlite:///./sqlalchemy.db)), Column('id', INTEGER(), table=<users>, primary_key=True, nullable=False), Column('name', VARCHAR(length=40), table=<users>), Column('email', VARCHAR(length=120), table=<users>), schema=None)
>>>實例化一個插入句柄
>> i = users_table.insert()
>>> i
<sqlalchemy.sql.dml.Insert object at 0x31bc850>
>>> print i
INSERT INTO users (id, name, email) VALUES (?, ?, ?)
>>> i.execute(name='rsj217', email='rsj21@gmail.com')
2014-01-09 10:24:02,250 INFO sqlalchemy.engine.base.Engine INSERT INTO users (name, email) VALUES (?, ?)
2014-01-09 10:24:02,250 INFO sqlalchemy.engine.base.Engine ('rsj217', 'rsj21@gmail.com')
2014-01-09 10:24:02,251 INFO sqlalchemy.engine.base.Engine COMMIT
<sqlalchemy.engine.result.ResultProxy object at 0x31bce10>
>>> i.execute({'name': 'ghost'},{'name': 'test'})
2014-01-09 10:24:57,537 INFO sqlalchemy.engine.base.Engine INSERT INTO users (name) VALUES (?)
2014-01-09 10:24:57,537 INFO sqlalchemy.engine.base.Engine (('ghost',), ('test',))
2014-01-09 10:24:57,537 INFO sqlalchemy.engine.base.Engine COMMIT
<sqlalchemy.engine.result.ResultProxy object at 0x31bcd50>
>>>數據庫內容為
sqlite> select * from users;
1|rsj217|rsj21@gmail.com
2|ghost|
3|test|
sqlite>查詢 刪除和插入類似 都需要先實例一個 sqlalchemy.sql.dml 對象
三 使用 ORM
使用 orm 就是 將 python class 與 數據庫的 table 映射，免去直接寫 sql 語句
創建映射
>>> class User(object):... def __repr__(self):... return '%s(%r, %r)' % (self.__class__.__name__, self.name, self.email)
... >>> mapper(User, users_table) # 創建映射
<Mapper at 0x31bcfd0; User>
>>> ul = User()
>>> ul.name
>>> print ul
User(None, None)
>>> print ul.name
None
>>>建立會話
查詢
>>> session = create_session()
>>> session
<sqlalchemy.orm.session.Session object at 0x31bef10>
>>> query = session.query(User)
>>> query
<sqlalchemy.orm.query.Query object at 0x31bee50>
>>> u = query.filter_by(name='rsj217').first()
2014-01-09 10:44:23,809 INFO sqlalchemy.engine.base.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email
FROM users
WHERE users.name = ?
LIMIT ? OFFSET ?
2014-01-09 10:44:23,809 INFO sqlalchemy.engine.base.Engine ('rsj217', 1, 0)
>>> u.name
u'rsj217'>>>插入
>>> from sqlalchemy import *
>>> from sqlalchemy.orm import *
>>> engine = create_engine('sqlite:///./sqlalchemy.db')
>>> metadata = MetaData(engine)
>>> users_table = Table('users', metadata, autoload=True)
>>> class User(object): pass
...
>>> mapper(User, users_table)
<Mapper at 0x18185d0; User>
>>> Session = sessionmaker(bind=engine)
>>> session = Session()
>>> u = User()
>>> u.name = 'new'>>> session.add(u)
>>> session.flush()
>>> session.commit()
>>>注意建立會話的方式， sqlalchemy 的版本不同 sessionmaker 的方式更好
剩下刪除 關系 事物等高級操作就參考官方文檔了.