内容简介:SQLAlchemy框架用法详解
介绍
SQLAlchemy是一个基于 Python 实现的ORM框架。该框架建立在 DBAPI之上,使用关系对象映射进行数据库操作,简言之便是:将类和对象转换成SQL,然后使用数据API执行 SQL 并获取执行结果。
pip3 install sqlalchemy
什么是ORM?
ORM就是运用面向对象的知识,将数据库中的每个表对应一个类,将数据库表中的记录对应一个类的对象。将复杂的sql语句转换成类和对象的操作。
SQLAlchemy本身无法操作数据库,其必须以来pymsql等第三方插件,Dialect用于和数据API进行交流,根据配置文件的不同调用不同的数据库API,从而实现对数据库的操作,如:
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:http://docs.sqlalchemy.org/en/latest/dialects/index.html
使用
1. 执行原生SQL语句
import time import threading import sqlalchemy from sqlalchemy import create_engine from sqlalchemy.engine.base import Engine engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/t1?charset=utf8", max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间,否则报错 pool_recycle=-1 # 多久之后对线程池中的线程进行一次连接的回收(重置) ) def task(arg): conn = engine.raw_connection() cursor = conn.cursor() cursor.execute( "select * from t1" ) result = cursor.fetchall() cursor.close() conn.close() for i in range(20): t = threading.Thread(target=task, args=(i,)) t.start()
创建数据库表
import datetime from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, Text, ForeignKey, DateTime, UniqueConstraint, Index Base = declarative_base() class Users(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String(32), index=True, nullable=False) # email = Column(String(32), unique=True) # ctime = Column(DateTime, default=datetime.datetime.now) # extra = Column(Text, nullable=True) __table_args__ = ( # UniqueConstraint('id', 'name', name='uix_id_name'), # Index('ix_id_name', 'name', 'email'), ) def init_db(): """ 根据类创建数据库表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间,否则报错 pool_recycle=-1 # 多久之后对线程池中的线程进行一次连接的回收(重置) ) Base.metadata.create_all(engine) def drop_db(): """ 根据类删除数据库表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间,否则报错 pool_recycle=-1 # 多久之后对线程池中的线程进行一次连接的回收(重置) ) Base.metadata.drop_all(engine) if __name__ == '__main__': drop_db() init_db() View Code
import datetime from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, Text, ForeignKey, DateTime, UniqueConstraint, Index from sqlalchemy.orm import relationship Base = declarative_base() # ##################### 单表示例 ######################### class Users(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String(32), index=True) age = Column(Integer, default=18) email = Column(String(32), unique=True) ctime = Column(DateTime, default=datetime.datetime.now) extra = Column(Text, nullable=True) __table_args__ = ( # UniqueConstraint('id', 'name', name='uix_id_name'), # Index('ix_id_name', 'name', 'extra'), ) class Hosts(Base): __tablename__ = 'hosts' id = Column(Integer, primary_key=True) name = Column(String(32), index=True) ctime = Column(DateTime, default=datetime.datetime.now) # ##################### 一对多示例 ######################### class Hobby(Base): __tablename__ = 'hobby' id = Column(Integer, primary_key=True) caption = Column(String(50), default='篮球') class Person(Base): __tablename__ = 'person' nid = Column(Integer, primary_key=True) name = Column(String(32), index=True, nullable=True) hobby_id = Column(Integer, ForeignKey("hobby.id")) # 与生成表结构无关,仅用于查询方便 hobby = relationship("Hobby", backref='pers') # ##################### 多对多示例 ######################### class Server2Group(Base): __tablename__ = 'server2group' id = Column(Integer, primary_key=True, autoincrement=True) server_id = Column(Integer, ForeignKey('server.id')) group_id = Column(Integer, ForeignKey('group.id')) class Group(Base): __tablename__ = 'group' id = Column(Integer, primary_key=True) name = Column(String(64), unique=True, nullable=False) # 与生成表结构无关,仅用于查询方便 servers = relationship('Server', secondary='server2group', backref='groups') class Server(Base): __tablename__ = 'server' id = Column(Integer, primary_key=True, autoincrement=True) hostname = Column(String(64), unique=True, nullable=False) def init_db(): """ 根据类创建数据库表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间,否则报错 pool_recycle=-1 # 多久之后对线程池中的线程进行一次连接的回收(重置) ) Base.metadata.create_all(engine) def drop_db(): """ 根据类删除数据库表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间,否则报错 pool_recycle=-1 # 多久之后对线程池中的线程进行一次连接的回收(重置) ) Base.metadata.drop_all(engine) if __name__ == '__main__': drop_db() init_db() 创建含Fk,M2M表
数据库表的操作
from sqlalchemy.orm import sessionmaker from sqlalchemy import create_engine from models import Users engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) # 每次执行数据库操作时,都需要创建一个session session = Session() # ############# 执行ORM操作 ############# obj1 = Users(name="alex1") session.add(obj1) # 提交事务 session.commit() # 关闭session session.close()
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from db import Users engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) def task(arg): session = Session() obj1 = Users(name="alex1") session.add(obj1) session.commit() for i in range(10): t = threading.Thread(target=task, args=(i,)) t.start() 多线程执行实例
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from sqlalchemy.sql import text from db import Users, Hosts engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) session = Session() # ################ 添加 ################ """ obj1 = Users(name="wupeiqi") session.add(obj1) session.add_all([ Users(name="wupeiqi"), Users(name="alex"), Hosts(name="c1.com"), ]) session.commit() """ # ################ 删除 ################ """ session.query(Users).filter(Users.id > 2).delete() session.commit() """ # ################ 修改 ################ """ session.query(Users).filter(Users.id > 0).update({"name" : "099"}) session.query(Users).filter(Users.id > 0).update({Users.name: Users.name + "099"}, synchronize_session=False) session.query(Users).filter(Users.id > 0).update({"age": Users.age + 1}, synchronize_session="evaluate") session.commit() """ # ################ 查询 ################ """ r1 = session.query(Users).all() r2 = session.query(Users.name.label('xx'), Users.age).all() r3 = session.query(Users).filter(Users.name == "alex").all() r4 = session.query(Users).filter_by(name='alex').all() r5 = session.query(Users).filter_by(name='alex').first() r6 = session.query(Users).filter(text("id<:value and name=:name")).params(value=224, name='fred').order_by(Users.id).all() r7 = session.query(Users).from_statement(text("SELECT * FROM users where name=:name")).params(name='ed').all() """ session.close() 基本的增删改查
# 条件 ret = session.query(Users).filter_by(name='alex').all() ret = session.query(Users).filter(Users.id > 1, Users.name == 'eric').all() ret = session.query(Users).filter(Users.id.between(1, 3), Users.name == 'eric').all() ret = session.query(Users).filter(Users.id.in_([1,3,4])).all() ret = session.query(Users).filter(~Users.id.in_([1,3,4])).all() ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name='eric'))).all() from sqlalchemy import and_, or_ ret = session.query(Users).filter(and_(Users.id > 3, Users.name == 'eric')).all() ret = session.query(Users).filter(or_(Users.id < 2, Users.name == 'eric')).all() ret = session.query(Users).filter( or_( Users.id < 2, and_(Users.name == 'eric', Users.id > 3), Users.extra != "" )).all() # 通配符 ret = session.query(Users).filter(Users.name.like('e%')).all() ret = session.query(Users).filter(~Users.name.like('e%')).all() # 限制 ret = session.query(Users)[1:2] # 排序 ret = session.query(Users).order_by(Users.name.desc()).all() ret = session.query(Users).order_by(Users.name.desc(), Users.id.asc()).all() # 分组 from sqlalchemy.sql import func ret = session.query(Users).group_by(Users.extra).all() ret = session.query( func.max(Users.id), func.sum(Users.id), func.min(Users.id)).group_by(Users.name).all() ret = session.query( func.max(Users.id), func.sum(Users.id), func.min(Users.id)).group_by(Users.name).having(func.min(Users.id) >2).all() # 连表 ret = session.query(Users, Favor).filter(Users.id == Favor.nid).all() ret = session.query(Person).join(Favor).all() ret = session.query(Person).join(Favor, isouter=True).all() # 组合 q1 = session.query(Users.name).filter(Users.id > 2) q2 = session.query(Favor.caption).filter(Favor.nid < 2) ret = q1.union(q2).all() q1 = session.query(Users.name).filter(Users.id > 2) q2 = session.query(Favor.caption).filter(Favor.nid < 2) ret = q1.union_all(q2).all() 常用操作
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from sqlalchemy.sql import text from sqlalchemy.engine.result import ResultProxy from db import Users, Hosts engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) session = Session() # 查询 # cursor = session.execute('select * from users') # result = cursor.fetchall() # 添加 cursor = session.execute('insert into users(name) values(:value)',params={"value":'wupeiqi'}) session.commit() print(cursor.lastrowid) session.close() 原生sql语句
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from sqlalchemy.sql import text from sqlalchemy.engine.result import ResultProxy from db import Users, Hosts, Hobby, Person engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) session = Session() # 添加 """ session.add_all([ Hobby(caption='乒乓球'), Hobby(caption='羽毛球'), Person(name='张三', hobby_id=3), Person(name='李四', hobby_id=4), ]) person = Person(name='张九', hobby=Hobby(caption='姑娘')) session.add(person) hb = Hobby(caption='人妖') hb.pers = [Person(name='文飞'), Person(name='博雅')] session.add(hb) session.commit() """ # 使用relationship正向查询 """ v = session.query(Person).first() print(v.name) print(v.hobby.caption) """ # 使用relationship反向查询 """ v = session.query(Hobby).first() print(v.caption) print(v.pers) """ session.close() 基于relationship操作ForeignKey
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from sqlalchemy.sql import text from sqlalchemy.engine.result import ResultProxy from db import Users, Hosts, Hobby, Person, Group, Server, Server2Group engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) session = Session() # 添加 """ session.add_all([ Server(hostname='c1.com'), Server(hostname='c2.com'), Group(name='A组'), Group(name='B组'), ]) session.commit() s2g = Server2Group(server_id=1, group_id=1) session.add(s2g) session.commit() gp = Group(name='C组') gp.servers = [Server(hostname='c3.com'),Server(hostname='c4.com')] session.add(gp) session.commit() ser = Server(hostname='c6.com') ser.groups = [Group(name='F组'),Group(name='G组')] session.add(ser) session.commit() """ # 使用relationship正向查询 """ v = session.query(Group).first() print(v.name) print(v.servers) """ # 使用relationship反向查询 """ v = session.query(Server).first() print(v.hostname) print(v.groups) """ session.close() 基于relationship操作m2m
import time import threading from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index from sqlalchemy.orm import sessionmaker, relationship from sqlalchemy import create_engine from sqlalchemy.sql import text, func from sqlalchemy.engine.result import ResultProxy from db import Users, Hosts, Hobby, Person, Group, Server, Server2Group engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5) Session = sessionmaker(bind=engine) session = Session() # 关联子查询 subqry = session.query(func.count(Server.id).label("sid")).filter(Server.id == Group.id).correlate(Group).as_scalar() result = session.query(Group.name, subqry) """ SELECT `group`.name AS group_name, (SELECT count(server.id) AS sid FROM server WHERE server.id = `group`.id) AS anon_1 FROM `group` """ # 原生SQL """ # 查询 cursor = session.execute('select * from users') result = cursor.fetchall() # 添加 cursor = session.execute('insert into users(name) values(:value)',params={"value":'wupeiqi'}) session.commit() print(cursor.lastrowid) """ session.close() 其它
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持 码农网
猜你喜欢:- Elasticsearch SQL 用法详解
- SQL中Merge用法详解
- Linux sort命令用法详解
- golang包time用法详解
- Python中with用法详解
- EventBus3.1用法详解
本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
Spark SQL内核剖析
朱锋、张韶全、黄明 / 电子工业出版社 / 2018-8 / 69.00元
Spark SQL 是 Spark 技术体系中较有影响力的应用(Killer application),也是 SQL-on-Hadoop 解决方案 中举足轻重的产品。《Spark SQL内核剖析》由 11 章构成,从源码层面深入介绍 Spark SQL 内部实现机制,以及在实际业务场 景中的开发实践,其中包括 SQL 编译实现、逻辑计划的生成与优化、物理计划的生成与优化、Aggregation 算......一起来看看 《Spark SQL内核剖析》 这本书的介绍吧!