一、ORM 与 SQLAlchemy 简介
ORM 全称 Object Relational Mapping, 翻译过来叫对象关系映射。简单的说，ORM 将数据库中的表与面向对象语言中的类建立了一种对应关系。这样，我们要操作数据库，数据库中的表或者表中的一条记录就可以直接通过操作类或者类实例来完成。
SQLAlchemy 是Python 社区最知名的 ORM 工具之一，为高效和高性能的数据库访问设计，实现了完整的企业级持久模型。
二、SQLAlchemy的使用
1、创建单表结构：
from sqlalchemy.ext.declarative import declarative_base # 导入基类 from sqlalchemy import Column, Integer, String # 数据类型 # Base = ORM基类 - 要按照ORM的规则定义你的类 Base = declarative_base() class Users(Base): __tablename__ = "user" # 创建ID数据字段 , 那么ID是不是一个数据列呢? 也就是说创建ID字段 == 创建ID数据列 # id = Column(数据类型,索引,主键,外键,等等) id = Column(Integer, primary_key=True, autoincrement=True,index=True) name = Column(String(32), nullable=False) # nullable=False 不能为空 # 打开数据库的连接 -- 创建数据库引擎 from sqlalchemy import create_engine # 创建数据库引擎 # engine = create_engine("mysql://scott:[email protected]/dbname",encoding=‘latin1‘, echo=True) engine = create_engine("mysql pymysql://root:@127.0.0.1:3306/SQLAlchemy_Pro?charset=utf8") Base.metadata.create_all(engine) # Base自动检索所有继承Base的ORM 对象 并且创建所有的数据表
2.单表的增删改查：
from sqlalchemy.orm import sessionmaker from sqlalchemy import create_engine from creatTable import Users # 创建引擎 engine = create_engine("mysql pymysql://root:@127.0.0.1:3306/SQLAlchemy_Pro?charset=utf8") Session = sessionmaker(engine) db_session = Session() # 1. 增加数据add(创建表结构的类名(字段名=添加的数据)) db_session.add(Users(name="ZWQ")) # 相当于建立一条添加数据的sql语句 db_session.commit() # 执行 db_session.close() # 结束关闭 # 批量添加 db_session.add_all([Users(name="清风徐来"), Users(name="水波不兴")]) db_session.commit() db_session.close() # 2.查询 query(表结构的类名) sqlres = db_session.query(Users) print(sqlres) # 直接翻译输出对应的SQL查询语句 res = db_session.query(Users).all() # 返回表中所有数据对象 print(res)# [<creatTable.Users object at 0x00000000038A1B00>,<creatTable.Users object at 0x00000000038A1B70>] for u in res: print(u.id, u.name) res = db_session.query(Users).first() # 取第一个，返回是对象 print(res.id, res.name) res = db_session.query(Users).filter(Users.id == 3).first() # 返回符合条件查询结果 print(res.name) res = db_session.query(Users).filter(Users.id <= 2, Users.name == "ZWQ").all() # filter中的条件可以是模糊条件,多个条件 for u in res: print(u.id,u.name) # 3.更改数据 update({k:v}) res = db_session.query(Users).filter(Users.id == 1).update({"name":"DragonFire"}) print(res) db_session.commit() res = db_session.query(Users).update({"name":"ZWQ"}) # 全部修改，返回修改的数据个数 print(res) db_session.commit() # 4.删除 delete()结合查询条件删除 res = db_session.query(Users).filter(Users.id == 1).delete() # 删除否合条件的数据，返回删除数量 print(res) db_session.commit() res = db_session.query(Users).delete() # 删除表中所有数据，返回删除数量 print(res) db_session.commit()
3.创建外键关联的表结构：
from sqlalchemy.ext.declarative import declarative_base Base = declarative_base() from sqlalchemy import Column,Integer,String,ForeignKey from sqlalchemy.orm import relationship class Student(Base): __tablename__ = "student" id = Column(Integer,primary_key=True) name = Column(String(32),nullable=False) sch_id = Column(Integer,ForeignKey("school.id")) # 关联的表的字段,表间的关系 stu2sch = relationship("School",backref="sch2stu") # 写在哪边那边就是正向查询，对象间的关系，backref(反向查询) class School(Base): __tablename__ = "school" id = Column(Integer,primary_key=True) name = Column(String(32),nullable=False) from sqlalchemy import create_engine engine = create_engine("mysql pymysql://root:@127.0.0.1:3306/SQLAlchemy_Pro?charset=utf8") Base.metadata.create_all(engine)
4、外键关联的表添加与查询操作：
from sqlalchemy.orm import sessionmaker
from creatTableFk import engine from creatTableFk import Student,School # 导入创建表结构的类 Session = sessionmaker(engine) db_session = Session() # 1.添加数据 db_session.add(School(name="NCU")) db_session.commit() # relationship 正向添加 stu = Student(name="清风徐来",stu2sch=School(name="NCU")) db_session.add(stu) db_session.commit() # relationship 反向添加 sch = School(name="NCU") sch.sch2stu = [Student(name="YWB"),Student(name="CT")] db_session.add(sch) db_session.commit() # 2.查询 res = db_session.query(Student).all() for stu in res: print(stu.name,stu.stu2sch.name) # 正向跨表 res = db_session.query(School).all() for sch in res: for stu in sch.sch2stu: print(sch.name,stu.name) # 反向跨表
5.多对多的表的创建
from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, String, Integer, ForeignKey, create_engine from sqlalchemy.orm import relationship Base = declarative_base() # 多对多关联通过第三张表关联，sqlalchemy要自己创建第三张表 class Girl(Base): __tablename__ = "girls" id = Column(Integer, primary_key=True) name = Column(String(32), nullable=False) g2b = relationship("Boy", backref="b2g", secondary="hotels") class Boy(Base): __tablename__ = "boys" id = Column(Integer, primary_key=True) name = Column(String(32), nullable=False) class Hotel(Base): __tablename__ = "hotels" id = Column(Integer, primary_key=True) boy_id = Column(Integer, ForeignKey("boys.id"), nullable=False) girl_id = Column(Integer, ForeignKey("girls.id"), nullable=False) engine = create_engine("mysql pymysql://root:@127.0.0.1:3306/SQLAlchemy_Pro?charset=utf8") Base.metadata.create_all(engine)
6.多对多表数据的添加与查询：
from sqlalchemy.orm import sessionmaker from CreateTableM2M import engine Session = sessionmaker(engine) db_session = Session() from CreateTableM2M import Girl,Boy # 1.增加数据 # relationship 正向添加 g = Girl(name="ZLY",g2b=[Boy(name="ZWQ"),Boy(name="FSF")]) db_session.add(g) db_session.commit() # relationship 反向添加 b = Boy(name="ZS") b.b2g = [Girl(name="罗玉凤"),Girl(name="娟儿"),Girl(name="芙蓉姐姐")] db_session.add(b) db_session.commit() # 2.查询 # relationship 正向 res = db_session.query(Girl).all() for g in res: for b in g.g2b: print(g.name,b.name) # relationship 反向 res = db_session.query(Boy).all() for b in res: for g in b.b2g: print(b.name,g.name)
7. 高级ORM操作
1 from CreateTable import Users,engine 2 from sqlalchemy.orm import sessionmaker 3 from CreateTableForeignKey import Student 4 5 Session = sessionmaker(engine) 6 db_session = Session() 7 8 # 查询数据表操作 9 # and or 10 from sqlalchemy.sql import and_ , or_,desc 11 ret = db_session.query(Users).filter(and_(Users.id > 3, Users.name == ‘DragonFire‘)).all() 12 ret = db_session.query(Users).filter(or_(Users.id < 2, Users.name == ‘DragonFire‘)).all() 13 14 ret = db_session.query(Users).filter( 15 or_( 16 Users.id < 2, 17 and_( 18 Users.name == ‘eric‘, 19 Users.id > 3 20 ), 21 Users.name != "" 22 ) 23 ) 24 print(ret) 25 select * from User where id<2 or (name="eric" and id>3) or extra != "" 26 27 28 # 查询所有数据 29 r1 = db_session.query(User).all() 30 31 查询数据 指定查询数据列 加入别名 32 r2 = db_session.query(Student.name.label(‘username‘), Student.id).first() 33 print(r2.id,r2.username) # 15 NBDragon 34 35 # 表达式筛选条件 36 r3 = db_session.query(User).filter(User.name == "DragonFire").all() 37 38 # 原生SQL筛选条件 39 r4 = db_session.query(User).filter_by(name=‘DragonFire‘).all() 40 r5 = db_session.query(Users).filter_by(name=‘DragonFire‘).first() 41 42 字符串匹配方式筛选条件 并使用 order_by进行排序 43 r6 = db_session.query(Student).order_by(Student.name.desc()).all() 44 for i in r6: 45 print(i.id,i.name) 46 47 原生SQL查询 48 from sqlalchemy.sql import text 49 r7 = db_session.query(User).from_statement(text("SELECT * FROM User where name=:name")).params(name=‘DragonFire‘).all() 50 51 # 筛选查询列 52 # query的时候我们不在使用User ORM对象,而是使用User.name来对内容进行选取 53 user_list = db_session.query(User.name).all() 54 print(user_list) 55 for row in user_list: 56 print(row.name) 57 58 # 别名映射 name as nick 59 user_list = db_session.query(User.name.label("nick")).all() 60 print(user_list) 61 for row in user_list: 62 print(row.nick) # 这里要写别名了 63 64 # 筛选条件格式 65 user_list = db_session.query(User).filter(User.name == "DragonFire").all() 66 user_list = db_session.query(User).filter(User.name == "DragonFire").first() 67 user_list = db_session.query(User).filter_by(name="DragonFire").first() 68 for row in user_list: 69 print(row.nick) 70 71 # 复杂查询 72 from sqlalchemy.sql import text 73 user_list = db_session.query(User).filter(text("id<:value and name=:name")).params(value=3,name="DragonFire") 74 75 # 查询语句 76 from sqlalchemy.sql import text 77 user_list = db_session.query(User).filter(text("select * from User id<:value and name=:name")).params(value=3,name="DragonFire") 78 79 # 排序 : 80 user_list = db_session.query(User).order_by(User.id).all() 81 user_list =