SqlAlchemy ORM

時間  2020-05-15
標籤 sqlalchemy orm 欄目 Java 简体版
原文   原文鏈接

SqlAlchemy ORM　　

SQLAlchemy是Python編程語言下的一款ORM框架，該框架創建在數據庫API之上，使用關係對象映射進行數據庫操做，簡言之即是：將對象轉換成SQL，而後使用數據API執行SQL並獲取執行結果html

Dialect用於和數據API進行交流，根據配置文件的不一樣調用不一樣的數據庫API，從而實現對數據庫的操做，如：python

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MySQL - Python
     mysql + mysqldb: / / <user>:<password>@<host>[:<port>] / <dbname>
  
pymysql
     mysql + pymysql: / / <username>:<password>@<host> / <dbname>[?<options>]
  
MySQL - Connector
     mysql + mysqlconnector: / / <user>:<password>@<host>[:<port>] / <dbname>
  
cx_Oracle
     oracle + cx_oracle: / / user: pass @host:port / dbname[?key = value&key = value...]
  
更多詳見：http: / / docs.sqlalchemy.org / en / latest / dialects / index.html

　　

步驟一：mysql

使用 Engine/ConnectionPooling/Dialect 進行數據庫操做，Engine使用ConnectionPooling鏈接數據庫，而後再經過Dialect執行SQL語句。sql

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#!/usr/bin/env python
# -*- coding:utf-8 -*-
  
from sqlalchemy import create_engine
  
  
engine = create_engine( "mysql+mysqldb://root:123@127.0.0.1:3306/s11" , max_overflow = 5 )
  
engine.execute(
     "INSERT INTO ts_test (a, b) VALUES ('2', 'v1')"
)
  
engine.execute(
      "INSERT INTO ts_test (a, b) VALUES (%s, %s)" ,
     (( 555 , "v1" ),( 666 , "v1" ),)
)
engine.execute(
     "INSERT INTO ts_test (a, b) VALUES (%(id)s, %(name)s)" ,
     id = 999 , name = "v1"
)
  
result = engine.execute( 'select * from ts_test' )
result.fetchall()

　　

步驟二：數據庫

使用 Schema Type/SQL Expression Language/Engine/ConnectionPooling/Dialect 進行數據庫操做。Engine使用Schema Type建立一個特定的結構對象，以後經過SQL Expression Language將該對象轉換成SQL語句，而後經過 ConnectionPooling 鏈接數據庫，再而後經過 Dialect 執行SQL，並獲取結果。express

增刪改查編程

 

一個簡單的完整例子ubuntu

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from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String
from  sqlalchemy.orm import sessionmaker
 
Base = declarative_base() #生成一個SqlORM 基類
 
 
engine = create_engine( "mysql+mysqldb://root@localhost:3306/test" ,echo = False )
 
 
class Host(Base):
     __tablename__ = 'hosts'
     id = Column(Integer,primary_key = True ,autoincrement = True )
     hostname = Column(String( 64 ),unique = True ,nullable = False )
     ip_addr = Column(String( 128 ),unique = True ,nullable = False )
     port = Column(Integer,default = 22 )
 
Base.metadata.create_all(engine) #建立全部表結構
 
if __name__ = = '__main__' :
     SessionCls = sessionmaker(bind = engine) #建立與數據庫的會話session class ,注意,這裏返回給session的是個class,不是實例
     session = SessionCls()
     #h1 = Host(hostname='localhost',ip_addr='127.0.0.1')
     #h2 = Host(hostname='ubuntu',ip_addr='192.168.2.243',port=20000)
     #h3 = Host(hostname='ubuntu2',ip_addr='192.168.2.244',port=20000)
     #session.add(h3)
     #session.add_all( [h1,h2])
     #h2.hostname = 'ubuntu_test' #只要沒提交,此時修改也沒問題
     #session.rollback()
     #session.commit() #提交
     res = session.query(Host). filter (Host.hostname.in_([ 'ubuntu2' , 'localhost' ])). all ()
     print (res)

　　

 

更多內容詳見：api

    http://www.jianshu.com/p/e6bba189fcbdsession

    http://docs.sqlalchemy.org/en/latest/core/expression_api.html

注：SQLAlchemy沒法修改表結構，若是須要能夠使用SQLAlchemy開發者開源的另一個軟件Alembic來完成。

步驟三：

使用 ORM/Schema Type/SQL Expression Language/Engine/ConnectionPooling/Dialect 全部組件對數據進行操做。根據類建立對象，對象轉換成SQL，執行SQL。

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#!/usr/bin/env python
# -*- coding:utf-8 -*-
  
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
  
engine = create_engine( "mysql+mysqldb://root:123@127.0.0.1:3306/s11" , max_overflow = 5 )
  
Base = declarative_base()
  
  
class User(Base):
     __tablename__ = 'users'
     id = Column(Integer, primary_key = True )
     name = Column(String( 50 ))
  
# 尋找Base的全部子類，按照子類的結構在數據庫中生成對應的數據表信息
# Base.metadata.create_all(engine)
  
Session = sessionmaker(bind = engine)
session = Session()
  
  
# ########## 增 ##########
# u = User(id=2, name='sb')
# session.add(u)
# session.add_all([
#     User(id=3, name='sb'),
#     User(id=4, name='sb')
# ])
# session.commit()
  
# ########## 刪除 ##########
# session.query(User).filter(User.id > 2).delete()
# session.commit()
  
# ########## 修改 ##########
# session.query(User).filter(User.id > 2).update({'cluster_id' : 0})
# session.commit()
# ########## 查 ##########
# ret = session.query(User).filter_by(name='sb').first()
  
# ret = session.query(User).filter_by(name='sb').all()
# print ret
  
# ret = session.query(User).filter(User.name.in_(['sb','bb'])).all()
# print ret
  
# ret = session.query(User.name.label('name_label')).all()
# print ret,type(ret)
  
# ret = session.query(User).order_by(User.id).all()
# print ret
  
# ret = session.query(User).order_by(User.id)[1:3]
# print ret
# session.commit()

外鍵關聯

A one to many relationship places a foreign key on the child table referencing the parent.relationship() is then specified on the parent, as referencing a collection of items represented by the child

from sqlalchemy import Table, Column, Integer, ForeignKey from sqlalchemy.orm import relationship from sqlalchemy.ext.declarative import declarative_base Base = declarative_base()
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<br> class Parent(Base):
     __tablename__ = 'parent'
     id = Column(Integer, primary_key = True )
     children = relationship( "Child" )
 
class Child(Base):
     __tablename__ = 'child'
     id = Column(Integer, primary_key = True )
     parent_id = Column(Integer, ForeignKey( 'parent.id' ))

To establish a bidirectional relationship in one-to-many, where the 「reverse」 side is a many to one, specify an additional relationship() and connect the two using therelationship.back_populates parameter:

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class Parent(Base):
     __tablename__ = 'parent'
     id = Column(Integer, primary_key = True )
     children = relationship( "Child" , back_populates = "parent" )
 
class Child(Base):
     __tablename__ = 'child'
     id = Column(Integer, primary_key = True )
     parent_id = Column(Integer, ForeignKey( 'parent.id' ))
     parent = relationship( "Parent" , back_populates = "children" )

Child will get a parent attribute with many-to-one semantics.

Alternatively, the backref option may be used on a single relationship() instead of usingback_populates:

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class Parent(Base):
     __tablename__ = 'parent'
     id = Column(Integer, primary_key = True )
     children = relationship( "Child" , backref = "parent" )

　　

　　

附，原生sql join查詢

幾個Join的區別 http://stackoverflow.com/questions/38549/difference-between-inner-and-outer-joins 

  • INNER JOIN: Returns all rows when there is at least one match in BOTH tables
  • LEFT JOIN: Return all rows from the left table, and the matched rows from the right table
  • RIGHT JOIN: Return all rows from the right table, and the matched rows from the left table
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select host.id,hostname,ip_addr,port,host_group. name from host right join host_group on host.id = host_group.host_id

in SQLAchemy

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session.query(Host). join (Host.host_groups).filter(HostGroup. name == 't1' ).group_by( "Host" ). all ()

　　

group by 查詢

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select name , count (host.id) as NumberOfHosts from host right join host_group on host.id= host_group.host_id group by name ;

in SQLAchemy

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from sqlalchemy import func
session.query(HostGroup, func. count (HostGroup. name )).group_by(HostGroup. name ). all ()
 
#another example
session.query(func. count ( User . name ), User . name ).group_by( User . name ). all () SELECT count (users. name ) AS count_1, users. name AS users_name
FROM users GROUP BY users. name
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