安装介绍
- SQLAlchemy 是Python的一款Orm框架
创建
from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String #创建基类,相当于Django中的 models.Model,被各个数据表类所继承 Base = declarative_base() # ##################### 单表示例 ######################### # 创建一张数据表 class Users(Base): __tablename__ = ‘users‘ id = Column(Integer, primary_key=True) name = Column(String(32), index=True) __table_args__ = ( # UniqueConstraint(‘id‘, ‘name‘, name=‘uix_id_name‘), # Index(‘ix_id_name‘, ‘name‘, ‘extra‘), ) # 创建另一张数据表 class School(Base): __tablename__ = "school" id = Column(Integer,primary_key=True,autoincrement=True) name = Column(String,unique=True) # 创建数据库链接 engine = create_engine( "mysql+pymysql://root:[email protected]:3306/dragon?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） ) # 通过Base.metadata找到所有继承 Base 的数据表class Base.metadata.create_all(engine) # SQLAlchemy数据表进行修改后,无法直接进行更新,只能删除表后进行操作,重新进行操作
增删改查相关操作
from CreateDB import Users, School # 1. 创建一个用户添加到数据库 # 创建连接 from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker engine = create_engine("mysql+pymysql://root:[email protected]:3306/dragon?charset=utf8", ) # 创建数据表操作对象 sessionmaker DB_session = sessionmaker(engine) db_session = DB_session() # 1.增加 操作数据表 # 单行操作 # obj1 = Users(name="123") # 通过 Users数据表类创建一条数据 # db_session.add(obj1) # 将创建好的数据添加到 数据表操作对象的内存中,此时数据库还并不知道要添加数据 # db_session.commit() # 将数据表操作对象内存中的所有数据及操作提交到数据库中 # 多行操作 # db_session.add_all([ # Users(name="zhangsan"), # Users(name="lisi"), # ]) # db_session.commit() # 2.查询 数据表操作 # user_list = db_session.query(Users).all() # 查询所有数据 # user_list = db_session.query(Users).filter(Users.id >=2 ) # 查询带有条件的数据 表达式 返回sql语句,循环依然可以获取到数据 # user_list = db_session.query(Users).filter(Users.id >=2 ).all() # 查询带有条件的数据 表达式 返回数据列表 # print(user_list) # for row in user_list: # print(row.id,row.name) # 3.删除数据 数据表操作 # db_session.query(Users).filter(Users.id == 1).delete() # 删除带有条件的数据 # db_session.commit() # 4.修改 # db_session.query(Users).filter(Users.id == 3).update({"name":"alexDSB"}) # 更新id=3的数据 # db_session.commit() # 关闭连接 db_session.close()
高级版查询操作
from CreateDB import Users, School # 1. 创建一个用户添加到数据库 # 创建连接 from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker engine = create_engine("mysql+pymysql://root:[email protected]:3306/dragon?charset=utf8", ) # 创建数据表操作对象 sessionmaker DB_session = sessionmaker(engine) db_session = DB_session() # 查询数据表操作 """ 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() """ # 筛选查询列 # user_list = db_session.query(Users.name).all() # print(user_list) # [(‘alexDSB‘,), (‘zhangsan‘,)] 虽然看到的是元祖,但是依然可以通过对象打点儿调用属性 # for row in user_list: # print(row.name) # 别名映射 name as nick # user_list = db_session.query(Users.name.label("nick")).all() # print(user_list) # [(‘alexDSB‘,), (‘zhangsan‘,)] 虽然看到的是元祖,但是依然可以通过对象打点儿调用属性 # for row in user_list: # print(row.nick) # 这里要写别名了 # 筛选条件格式 # user_list = db_session.query(Users).filter(Users.name == "alexDSB").all() # user_list = db_session.query(Users).filter(Users.name == "alexDSB").first() # user_list = db_session.query(Users).filter_by(name="alexDSB").first() # for row in user_list: # print(row.nick) # 复杂查询 # from sqlalchemy.sql import text # user_list = db_session.query(Users).filter(text("id<:value and name=:name")).params(value=3,name="alexDSB") # 查询语句 # from sqlalchemy.sql import text # user_list = db_session.query(Users).filter(text("select * from users id<:value and name=:name")).params(value=3,name="alexDSB") # 排序 : # user_list = db_session.query(Users).order_by(Users.id).all() # user_list = db_session.query(Users).order_by(Users.id.desc()).all() # for row in user_list: # print(row.name,row.id) #其他查询条件 """ 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() # between 大于1小于3的 ret = session.query(Users).filter(Users.id.in_([1,3,4])).all() # in_([1,3,4]) 只查询id等于1,3,4的 ret = session.query(Users).filter(~Users.id.in_([1,3,4])).all() # ~xxxx.in_([1,3,4]) 查询不等于1,3,4的 ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name=‘eric‘))).all() 子查询 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() # select * from users where id<2 or (name="eric" and id>3) or extra != "" """ # 关闭连接 db_session.close()
高级版更新操作
""" db_session.query(Users).filter(Users.id > 0).update({"name" : "099"}) db_session.query(Users).filter(Users.id > 0).update({Users.name: Users.name + "099"}, synchronize_session=False) db_session.query(Users).filter(Users.id > 0).update({"age": Users.age + 1}, synchronize_session="evaluate") db_session.commit() """
扩展内容
- 一对多：
- 创建表：
from sqlalchemy import create_engine from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey from sqlalchemy.orm import relationship #创建基类,相当于Django中的 models.Model,被各个数据表类所继承 Base = declarative_base() # ##################### 多表示例 ######################### # 创建一张数据表 class Author(Base): __tablename__ = ‘author‘ id = Column(Integer, primary_key=True) name = Column(String(32), index=True) # 创建另一张数据表 class Book(Base): __tablename__ = ‘book‘ id = Column(Integer, primary_key=True) name = Column(String(32), index=True) author_id = Column(Integer,ForeignKey("author.id")) # relationshi 不会单独生成字段 ,只用于增加查询操作 user = relationship("Author",backref="author2book") # backref 反向查找的名字 # 创建数据库链接 engine = create_engine( "mysql+pymysql://root:[email protected]:3306/dragon?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） ) # 通过Base.metadata找到所有继承 Base 的数据表class Base.metadata.create_all(engine)
- 增删改查：
from SQLAlchemy_ready.ss2_ForeignKey_relationship import Author, Book # 1. 创建一个用户添加到数据库 # 创建连接 from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker engine = create_engine("mysql+pymysql://root:[email protected]:3306/dragon?charset=utf8", ) # 创建数据表操作对象 sessionmaker DB_session = sessionmaker(engine) db_session = DB_session() # 1.增加 操作数据表 # 添加两个作者: # db_session.add_all([ # Author(name="alex"), # Author(name="yinwangba") # ]) # db_session.commit() # 添加一本书 jinpingmei 作者是 yinwangba # author = db_session.query(Author).filter(Author.name == "yinwangba").first() # db_session.add(Book(name="jinpingmei",author_id=author.id)) # db_session.commit() # 2.查询所有数据,并显示作者名称,连表查询 # book_list = db_session.query(Book).all() # for row in book_list: # print(row.name,row.author_id) # book_list = db_session.query(Book.name.label("bname"),Author.name.label ("aname")).join(Author,Book.author_id == Author.id,isouter=True).all() # print(book_list) # for row in book_list: # print(row.aname,row.bname) # 查询之relationship 快速连表 # 创建表的时候加入 relationship #普通版添加 # obj = Author(name="yinwangba") # db_session.add(obj) # db_session.commit() # print(obj.id,obj.name) # # obj_book = Book(name="jinpingmei",author_id=obj.id) # db_session.add(obj_book) # db_session.commit() # obj = Author(name="yinwangba") # relationship版 添加 # bobj = Book(name="jinpingmei",user=Author(name="yinwangba")) # db_session.add(bobj) # db_session.commit() # 查询之relationship 快速连表 # book_list = db_session.query(Book).all() # for row in book_list: # print(row.name,row.user.name) # 查询作者的所有书籍 # obj = db_session.query(Author).filter(Author.name=="yinwangba").first() # print(obj.author2book) # 反向字段添加 # author_obj = Author(name="alex") # author_obj.author2book = [Book(name="儒林外史之银林大战"),Book(name="邻家小妹妹")] # db_session.add(author_obj) # db_session.commit() # 关闭连接 db_session.close()
- 多对多 ManyToMany：
- 创建表：
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 from sqlalchemy.orm import relationship #创建基类,相当于Django中的 models.Model,被各个数据表类所继承 Base = declarative_base() # 创建第三张表 Boys and Girls class Hotel(Base): __tablename__ = "hotel" id = Column(Integer,primary_key=True) boy_id = Column(Integer,ForeignKey("boys.id")) girl_id = Column(Integer,ForeignKey("girls.id")) # 创建一张数据表 class Boys(Base): __tablename__ = ‘boys‘ id = Column(Integer, primary_key=True) name = Column(String(32), index=True) # 创建于酒店的关系 girls = relationship("Girls",secondary="hotel",backref="boys") # 创建另一张数据表 class Girls(Base): __tablename__ = "girls" id = Column(Integer,primary_key=True,autoincrement=True) name = Column(String(32),index =True) # 创建于酒店的关系 # boy = relationship("Boys",secondary="hotel",backref="toHotel") # 创建数据库链接 engine = create_engine( "mysql+pymysql://root:[email protected]:3306/dragon?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） ) # 通过Base.metadata找到所有继承 Base 的数据表class Base.metadata.create_all(engine) # SQLAlchemy数据表进行修改后,无法直接进行更新,只能删除表后进行操作,重新进行操作, # 但Flask-SQLAlchemy + Flask-migrate + Flask-script 就可以实现 Django 的数据迁移 MakeMigration migrate # 多对多关系建立
- 操作：
from SQLAlchemy_ready.ss4_M2M import Girls, Boys,Hotel # 1. 创建一个用户添加到数据库 # 创建连接 from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker engine = create_engine("mysql+pymysql://root:[email protected]:3306/dragon?charset=utf8") # 创建数据表操作对象 sessionmaker DB_session = sessionmaker(engine) db_session = DB_session() # 1.增加 操作数据表 # boy = Boys(name="jinwangba") # boy.girls = [Girls(name="fengjie"),Girls(name="juaner")] # db_session.add(boy) # db_session.commit() # 2.查询 # 使用relationship正向查询 # boy = db_session.query(Boys).first() # print(boy.name,boy.girls[0].name) # 使用relationship反向查询 # girls = db_session.query(Girls).first() # print(girls.boys[0].name , girls.name) # 关闭连接 db_session.close()