回顾:使用PyMySQLl操作MySQL
使用PyMySQL的前提:
1. 先建好表
2. 自己动手需要手动去写多条SQL语句
改进:
类 ------> 表
实例化 -> 数据
这种思想叫:ORM(Object Relationship Mapping)对象关系映射
SQLAlchemy是Python编程语言下的一款ORM框架
SQLAlchemy的操作:
基本原理:将代码转换成SQL语句执行
1. 创建表
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 # 链接MySQL engine = create_engine("mysql+pymysql://[email protected]:3306/day45?charset=utf8", max_overflow = 5) # max_overflow = 5代表最大连接池为5 # 声明Base类,后续的类都要继承Base类 Base = declarative_base() # 创建单表 """ create table user( id int auto_increment primary key, name varchar(32) not null default ‘‘, extra varchar(32) not null default ‘‘ )engine=Innodb charset=utf8 """ # 创建usertype, 并设置id,title class UserType(Base): __tablename__ = "usertype" # 表名 id = Column(Integer, autoincrement=True, primary_key=True) title = Column(String(32), nullable=False,server_default="") # 创建user表,并设置表的id, name, extra class Users(Base): __tablename__ = ‘user‘ # 表名 id = Column(Integer, autoincrement=True, primary_key=True) # Column:字段,列 name = Column(String(32), nullable=False, server_default="") # name = Column(String(32), nullable=False, server_default="", unique=True) # 给name这一列添加唯一索引 extra = Column(String(32), nullable=False, server_default="") # extra:特点 # 外键(让User中的id与UserType中的id发生了外键的关系) type_id = Column(Integer, ForeignKey(UserType.id)) # type_id = Column(Integer, ForeignKey("usertype".id)) # # 添加索引 # __table_args__ = ( # UniqueConstraint("id", "name", name="uix_id_name"), # 给id,name添加联合唯一索引 # Index("ix_id_name","name", "extra") # 给name,extra添加普通索引 # ) # 删除表 def drop_db(): Base.metadata.drop_all(engine) # 会将当前文件中所有继承自Base类的类,生成表 def create_db(): Base.metadata.create_all(engine)
2. 操作表
# 操作表中的数据 Session = sessionmaker(bind=engine) session = Session() # session:窗口, 实例化Session,相当于从连接池中拿一个连接过来进行操作
2.1 添加数据
# 往UserType中添加数据, 因为UserType与User存在外键联系,所以给UserType添加数据,则再往User中添加数据时,type_id就会有数据产生 # 添加一条数据 obj = UserType(title = "普通用户") session.add(obj) # 把对象数据添加到数据库中 # 添加多条数据 session.add_all([ UserType(title = "VIP用户"), UserType(title = "VIP中P用户"), UserType(title = "SVIP用户"), UserType(title = "黑金用户") ]) session.commit() session.close()
2.2 查询数据
2.2.1 普通查询(.all(), .first())
res = session.query(UserType) # 这一步就是将代码转换成SQL语句 print(res) # SELECT usertype.id AS usertype_id, usertype.title AS usertype_title FROM usertype # 查询全部,返回的是列表,列表中是对象 res = session.query(UserType).all() # .all()就是讲SQL语句发送给服务端执行SQL指令,得到一个列表对象 print(res) # [<__main__.UserType object at 0x00000164C846BEF0>, <__main__.UserType object at 0x00000164C846BF60>, <__main__.UserType object at 0x00000164C846BDA0>, <__main__.UserType object at 0x00000164C846BDD8>, <__main__.UserType object at 0x00000164C846BC88>] for k in res: print(k.id, k.title) # 1 普通用户 # 2 VIP用户 # 3 VIP中P用户 # 4 SVIP用户 # 5 黑金用户 # 查询一条,获得一条对象 res = session.query(UserType).first() print(res) # <__main__.UserType object at 0x000001640E9EBDD8> print(res.id, res.title) # 1 普通用户
2.2.2 类似sql中的where查询(filter(), filter_by())
# filter res = session.query(UserType).filter(UserType.title=="VIP用户") # filter 将查找(过滤)的条件转换成SQL语句 print(res) # SELECT usertype.id AS usertype_id, usertype.title AS usertype_title FROM usertype WHERE usertype.title = %(title_1)s res = session.query(UserType).filter(UserType.title=="VIP用户", UserType.id==2).all() # .first()与上一样 print(res) # [<__main__.UserType object at 0x000002C1ADFD73C8>] for row in res: print(row.id, row.title) # 2 VIP用户 print(res[0].id, res[0].title) # 2 VIP用户 # filter_by 传入的是一个类似key=value的数据, filter中传入的是一个表达式 res = session.query(UserType).filter_by(title="VIP用户").all() print(res) # [<__main__.UserType object at 0x000001FCDB07FDA0>]
2.3 删除数据(delete)
# 删除数据之前先查找数据 session.query(UserType).filter(UserType.id>3).delete() session.query(UserType).delete() # 相当于删除整个表
2.4 修改数据(update)
session.query(UserType).filter(UserType.id == 3).update({"title":"SVIP用户"}) # 将id=3数据的title的值改为SVIP用户
2.5 高级查询
""" 高级查询: 通配符、分组、排序、between and、in、not in、or """ """ 此时数据恢复成如下所示 +----+------------+ | id | title | +----+------------+ | 1 | 普通用户 | | 2 | VIP用户 | | 3 | VIP中P用户 | | 4 | SVIP用户 | | 5 | 黑金用户 | +----+------------+ """ # 逗号默认为 and res = session.query(UserType).filter(UserType.id==2, UserType.title=="VIP用户").all() for row in res: print(row.id, row.title) # row # between(1,3) 在1到3的范围内,包括1和3 res = session.query(UserType).filter(UserType.id.between(1,3 )).all() for row in res: print(row.id, row.title) # 1 普通用户 # 2 VIP用户 # 3 VIP中P用户 # in not in res = session.query(UserType).filter(UserType.id.in_([1,3,4])).all() ret = session.query(UserType).filter(~UserType.id.in_([1,3,4])).all() print(res) # [<__main__.UserType object at 0x000002839AD46048>, <__main__.UserType object at 0x000002839AD46198>, <__main__.UserType object at 0x000002839AD46278>] print(ret) # [<__main__.UserType object at 0x000002839AD467B8>, <__main__.UserType object at 0x000002839AD46828>] rer = session.query(UserType).filter(UserType.id.in_(session.query(UserType.id).filter_by(title=‘VIP用户‘))).all() print(rer) # [<__main__.UserType object at 0x0000023CBD0D57B8>] from sqlalchemy import and_,or_ ret = session.query(UserType).filter(and_(UserType.id > 3, UserType.title == ‘VIP用户‘)).all() res = session.query(UserType).filter(or_(UserType.id < 2, UserType.title == ‘VIP用户‘)).all() print(ret) print(res) # 通配符 ret = session.query(UserType).filter(UserType.title.like(‘S%‘)).all() res = session.query(UserType).filter(~UserType.title.like(‘S%‘)).all() print(ret) print(res) # 排序 ret = session.query(UserType).order_by(UserType.title.desc()).all() res = session.query(UserType).order_by(UserType.title.desc(), UserType.id.asc()).all() # 分组 group_by """ +----+----------+-------+---------+ | id | name | extra | type_id | +----+----------+-------+---------+ | 1 | wangyong | nb | 5 | | 2 | liguo | cb | 3 | | 3 | jiyuzhi | sb | 1 | | 4 | kelinwei | zb | 3 | | 5 | gouyang | bb | 2 | +----+----------+-------+---------+ """ from sqlalchemy.sql import func res = session.query( Users.type_id, func.max(Users.id), func.min(Users.id)).group_by(Users.type_id).all() print(res) # [(1, 3, 3), (2, 5, 5), (3, 4, 2), (5, 1, 1)] res = session.query( Users.type_id, func.max(Users.id), func.min(Users.id)).group_by(Users.type_id).having(func.min(Users.id)>2).all() print(res) # [(1, 3, 3), (2, 5, 5)] """ 连表 """ res = session.query(Users).join(UserType) print(res) # SELECT user.id AS user_id, user.name AS user_name, user.extra AS user_extra, user.type_id AS user_type_id # FROM user INNER JOIN usertype ON usertype.id = user.type_id res = session.query(Users).join(UserType,isouter=True) # 会自动检测是否含有外键,如果存在,会自动进行关联 print(res) # SELECT user.id AS user_id, user.name AS user_name, user.extra AS user_extra, user.type_id AS user_type_id # FROM user LEFT OUTER JOIN usertype ON usertype.id = user.type_id res = session.query(Users).join(UserType,isouter=True).all() # 存在问题:只能查询到Users表的值,UserType表中的值无法查询 print(res) # [<__main__.Users object at 0x0000026AD9D74898>, <__main__.Users object at 0x0000026AD9D74908>, <__main__.Users object at 0x0000026AD9D74978>, <__main__.Users object at 0x0000026AD9D749E8>, <__main__.Users object at 0x0000026AD9D74A58>] for row in res: print(row.id, row.name) # 1. 想要既能查询到Users表中数据,又能查询到UserType中的数据 # 方法一: res = session.query(Users, UserType).join(UserType,isouter=True).all() # 存在问题:只能查询到Users表的值,UserType表中的值无法查询 for row in res: print(row[0].id, row[0].name, row[1].title) # 方法二:使用relationship 在Users类中加入 usertype = relationship(‘UserType‘) # 关联到UserType,在创建User表时,会将UserType的数据添加到Users中,但是不会显示出来,就相当于一个隐藏属性 res = session.query(Users).all() for row in res: print(row.id, row.name, row.extra, row.usertype.title) # 2.想要知道某一个类型下面的用户 # 第一种 res = session.query(UserType).all() for row in res: print(row.id, row.title, session.query(Users.id).filter(Users.type_id==row.id).all()) # 第二种 在定义Users类时,继续添加 usertype = relationship(‘UserType‘, backref = "xxoo") backref:反向查询 res = session.query(UserType).all() for row in res: print(row.id, row.title, row.xxoo) # row.xxoo 多条记录查询 # relationship 哪张表中有外键,就把relationship 放在哪张表中
原文地址:https://www.cnblogs.com/liguodeboke/p/11047855.html
时间: 2024-10-09 04:35:17