mysql数据库----python操作mysql ------pymysql和SQLAchemy

2022-10-23 19:19:46

本篇对于Python操作MySQL主要使用两种方式：

原生模块 pymsql
ORM框架 SQLAchemy

一、pymysql

pymsql是Python中操作MySQL的模块，其使用方法和MySQLdb几乎相同。

下载安装

pip3 install pymysql

使用操作

1、执行SQL

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 import pymysql

 # 创建连接

 conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='', db='t1')

 # 创建游标

 cursor = conn.cursor()

 # 执行SQL，并返回收影响行数

 effect_row = cursor.execute("update hosts set host = '1.1.1.2'")

 # 执行SQL，并返回受影响行数

 #effect_row = cursor.execute("update hosts set host = '1.1.1.2' where nid > %s", (1,))

 # 执行SQL，并返回受影响行数

 #effect_row = cursor.executemany("insert into hosts(host,color_id)values(%s,%s)", [("1.1.1.11",1),("1.1.1.11",2)])

 # 提交，不然无法保存新建或者修改的数据

 conn.commit()

 # 关闭游标

 cursor.close()

 # 关闭连接

 conn.close()

2、获取新创建数据自增ID

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 import pymysql

 conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='', db='t1')

 cursor = conn.cursor()

 cursor.executemany("insert into hosts(host,color_id)values(%s,%s)", [("1.1.1.11",1),("1.1.1.11",2)])

 conn.commit()

 cursor.close()

 conn.close()

 # 获取最新自增ID

 new_id = cursor.lastrowid

3、获取查询数据

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 import pymysql

 conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='', db='t1')

 cursor = conn.cursor()

 cursor.execute("select * from hosts")

 # 获取第一行数据

 row_1 = cursor.fetchone()

 # 获取前n行数据

 # row_2 = cursor.fetchmany(3)

 # 获取所有数据

 # row_3 = cursor.fetchall()

 conn.commit()

 cursor.close()

 conn.close()

注：在fetch数据时按照顺序进行，可以使用cursor.scroll(num,mode)来移动游标位置，如：

cursor.scroll(1,mode='relative') # 相对当前位置移动
cursor.scroll(2,mode='absolute') # 相对绝对位置移动

4、fetch数据类型

　　关于默认获取的数据是元祖类型，如果想要或者字典类型的数据，即：

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 import pymysql

 conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='', db='t1')

 # 游标设置为字典类型

 cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)

 r = cursor.execute("call p1()")

 result = cursor.fetchone()

 conn.commit()

 cursor.close()

 conn.close()

     作业：

         参考表结构：

             用户类型

             用户信息

             权限

             用户类型&权限

         功能：

             # 登陆、注册、找回密码

             # 用户管理

             # 用户类型

             # 权限管理

             # 分配权限

         特别的：程序仅一个可执行文件

练习题

注意： (python代码操作数据库)

 import pymysql

 user = input("username:")

 pwd = input("password:")

 conn = pymysql.connect(host="localhost",user='root',password='',database="db666")

 cursor = conn.cursor()

 sql = "select * from userinfo where username='%s' and password='%s'" %(user,pwd)    #这段代码提到了注入问题，直接拼接会被他人任意登入，风险很大，所以不能这样写！

 # select * from userinfo where username='uu' or 1=1 -- ' and password='%s'    #这里就是利用了注入问题登入了数据库

 cursor.execute(sql)

 result = cursor.fetchone()

 cursor.close()

 conn.close()

 if result:

     print('登录成功')

 else:

     print('登录失败')

sql注入问题（这种写法错误）

 import pymysql

 user = input("username:")

 pwd = input("password:")

 conn = pymysql.connect(host="localhost",user='root',password='',database="db666")

 cursor = conn.cursor()

 sql = "select * from userinfo where username=%s and password=%s"

 cursor.execute(sql,user,pwd)

 # cursor.execute(sql,[user,pwd])

 # cursor.execute(sql,{'u':user,'p':pwd})

 result = cursor.fetchone()

 cursor.close()

 conn.close()

 if result:

     print('登录成功')

 else:

     print('登录失败')

正确的写法

二、SQLAchemy

SQLAlchemy是Python编程语言下的一款ORM框架，该框架建立在数据库API之上，使用关系对象映射进行数据库操作，简言之便是：将对象转换成SQL，然后使用数据API执行SQL并获取执行结果。

安装：

pip3 install SQLAlchemy

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...]

 更多详见：http://docs.sqlalchemy.org/en/latest/dialects/index.html

一、内部处理

使用 Engine/ConnectionPooling/Dialect 进行数据库操作，Engine使用ConnectionPooling连接数据库，然后再通过Dialect执行SQL语句。

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 from sqlalchemy import create_engine

 engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)

 # 执行SQL

 # cur = engine.execute(

 #     "INSERT INTO hosts (host, color_id) VALUES ('1.1.1.22', 3)"

 # )

 # 新插入行自增ID

 # cur.lastrowid

 # 执行SQL

 # cur = engine.execute(

 #     "INSERT INTO hosts (host, color_id) VALUES(%s, %s)",[('1.1.1.22', 3),('1.1.1.221', 3),]

 # )

 # 执行SQL

 # cur = engine.execute(

 #     "INSERT INTO hosts (host, color_id) VALUES (%(host)s, %(color_id)s)",

 #     host='1.1.1.99', color_id=3

 # )

 # 执行SQL

 # cur = engine.execute('select * from hosts')

 # 获取第一行数据

 # cur.fetchone()

 # 获取第n行数据

 # cur.fetchmany(3)

 # 获取所有数据

 # cur.fetchall()

二、ORM功能使用

使用 ORM/Schema Type/SQL Expression Language/Engine/ConnectionPooling/Dialect 所有组件对数据进行操作。根据类创建对象，对象转换成SQL，执行SQL。

1、创建表

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 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

 engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)

 Base = declarative_base()

 # 创建单表

 class Users(Base):

     __tablename__ = 'users'

     id = Column(Integer, primary_key=True)

     name = Column(String(32))

     extra = Column(String(16))

     __table_args__ = (

     UniqueConstraint('id', 'name', name='uix_id_name'),

         Index('ix_id_name', 'name', 'extra'),

     )

 # 一对多

 class Favor(Base):

     __tablename__ = 'favor'

     nid = Column(Integer, primary_key=True)

     caption = Column(String(50), default='red', unique=True)

 class Person(Base):

     __tablename__ = 'person'

     nid = Column(Integer, primary_key=True)

     name = Column(String(32), index=True, nullable=True)

     favor_id = Column(Integer, ForeignKey("favor.nid"))

 # 多对多

 class Group(Base):

     __tablename__ = 'group'

     id = Column(Integer, primary_key=True)

     name = Column(String(64), unique=True, nullable=False)

     port = Column(Integer, default=22)

 class Server(Base):

     __tablename__ = 'server'

     id = Column(Integer, primary_key=True, autoincrement=True)

     hostname = Column(String(64), unique=True, nullable=False)

 class ServerToGroup(Base):

     __tablename__ = 'servertogroup'

     nid = Column(Integer, primary_key=True, autoincrement=True)

     server_id = Column(Integer, ForeignKey('server.id'))

     group_id = Column(Integer, ForeignKey('group.id'))

 def init_db():

     Base.metadata.create_all(engine)

 def drop_db():

     Base.metadata.drop_all(engine)

注：设置外检的另一种方式 ForeignKeyConstraint(['other_id'], ['othertable.other_id'])

2、操作表

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 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

 engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)

 Base = declarative_base()

 # 创建单表

 class Users(Base):

     __tablename__ = 'users'

     id = Column(Integer, primary_key=True)

     name = Column(String(32))

     extra = Column(String(16))

     __table_args__ = (

     UniqueConstraint('id', 'name', name='uix_id_name'),

         Index('ix_id_name', 'name', 'extra'),

     )

     def __repr__(self):

         return "%s-%s" %(self.id, self.name)

 # 一对多

 class Favor(Base):

     __tablename__ = 'favor'

     nid = Column(Integer, primary_key=True)

     caption = Column(String(50), default='red', unique=True)

     def __repr__(self):

         return "%s-%s" %(self.nid, self.caption)

 class Person(Base):

     __tablename__ = 'person'

     nid = Column(Integer, primary_key=True)

     name = Column(String(32), index=True, nullable=True)

     favor_id = Column(Integer, ForeignKey("favor.nid"))

     # 与生成表结构无关，仅用于查询方便

     favor = relationship("Favor", backref='pers')

 # 多对多

 class ServerToGroup(Base):

     __tablename__ = 'servertogroup'

     nid = Column(Integer, primary_key=True, autoincrement=True)

     server_id = Column(Integer, ForeignKey('server.id'))

     group_id = Column(Integer, ForeignKey('group.id'))

     group = relationship("Group", backref='s2g')

     server = relationship("Server", backref='s2g')

 class Group(Base):

     __tablename__ = 'group'

     id = Column(Integer, primary_key=True)

     name = Column(String(64), unique=True, nullable=False)

     port = Column(Integer, default=22)

     # group = relationship('Group',secondary=ServerToGroup,backref='host_list')

 class Server(Base):

     __tablename__ = 'server'

     id = Column(Integer, primary_key=True, autoincrement=True)

     hostname = Column(String(64), unique=True, nullable=False)

 def init_db():

     Base.metadata.create_all(engine)

 def drop_db():

     Base.metadata.drop_all(engine)

 Session = sessionmaker(bind=engine)

 session = Session()

 表结构 + 数据库连接

表结构+数据库

增

 obj = Users(name="alex0", extra='sb')

 session.add(obj)

 session.add_all([

     Users(name="alex1", extra='sb'),

     Users(name="alex2", extra='sb'),

 ])

 session.commit()

删

session.query(Users).filter(Users.id > 2).delete()

session.commit()

改

session.query(Users).filter(Users.id > 2).update({"name" : ""})

session.query(Users).filter(Users.id > 2).update({Users.name: Users.name + ""}, synchronize_session=False)

session.query(Users).filter(Users.id > 2).update({"num": Users.num + 1}, synchronize_session="evaluate")

session.commit()

查

ret = session.query(Users).all()

ret = session.query(Users.name, Users.extra).all()

ret = session.query(Users).filter_by(name='alex').all()

ret = session.query(Users).filter_by(name='alex').first()

其他

 #　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()

更多功能参见文档，猛击这里下载PDF

｡◕‿◕｡笔记详细整理：ORM框架创建表和操作表

 #!/usr/bin/env python

 # -*- coding:utf-8 -*-

 ########################### 对象关系映射（英语：(Object Relational Mapping，简称ORM #################################

 from sqlalchemy.ext.declarative import declarative_base

 from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index,CHAR,VARCHAR

 from sqlalchemy.orm import sessionmaker, relationship

 from sqlalchemy import create_engine

 Base = declarative_base()

 engine = create_engine("mysql+pymysql://root:@127.0.0.1:3306/s4day63?charset=utf8", max_overflow=5)

 # 创建单表  (如下创建了两个类，也就是两个表；类下面的内容就是表里的列)

 class UserType(Base):

     __tablename__ = 'usertype'         #这一行是表名

     id = Column(Integer, primary_key=True, autoincrement=True)            #Colunm  列

     title = Column(VARCHAR(32), nullable=True, index=True)

 class Users(Base):

     __tablename__ = 'users'            #这一行是表名

     id = Column(Integer, primary_key=True, autoincrement=True)

     name = Column(VARCHAR(32), nullable=True, index=True)

     email = Column(VARCHAR(16), unique=True)

     user_type_id = Column(Integer,ForeignKey("usertype.id"))

 #  联合唯一索引

     # __table_args__ = (

     #     UniqueConstraint('id', 'name', name='uix_id_name'),

     #     Index('ix_n_ex','name', 'email',),

     # )

 def create_db():

     Base.metadata.create_all(engine)              #创建表

 def drop_db():

     Base.metadata.drop_all(engine)                #删除表

 # create_db()                 #调用创建表函数

 # drop_db()                   #调用删除表函数

 Session = sessionmaker(bind=engine)

 session = Session()

 # 类 -> 代指的就是表

 # 对象 -> 代指的就是行

 # ###### 增 ######

 # obj1 = UserType(title='普通用户')             #向UserType表中插入1条数据

 # session.add(obj1)

 #

 # objs =[                                      #向UserType表中插入多条数据

 #   UserType(title='超级用户'),

 #   UserType(title='白金用户'),

 #   UserType(title='黑金用户'),

 # ]

 # session.add_all(objs)

 # obj2 = Users(name='青铜')                   #向Users表中插入1条数据

 # session.add(obj2)

 #

 # objs2 = [                                    #向Users表中插入多条数据

 #     Users(name='白银'),

 #     Users(name='黄金'),

 #     Users(name='铂金'),

 #     Users(name='钻石'),

 #     Users(name='大师'),

 #     Users(name='王者'),

 # ]

 # session.add_all(objs2)

 # ###### 查 ######

 # print(session.query(UserType))               #查看表UserType，这里打印出来的是SQL语句

 # user_type_list = session.query(UserType).all()       #查看表UserType所有内容

 # for row in user_type_list:               #遍历表UserType所有内容

 #     print(row.id,row.title)               #打印遍历结果中的id和title

 # #过滤查询，相当于where，设定查询条件,filter(过滤),这里意思是查询UserType里面的id和title,并且过滤条件为id>2的

 # user_type_list = session.query(UserType.id,UserType.title).filter(UserType.id > 2)

 # for row in user_type_list:

 #     print(row.id,row.title)

 # ###### 删除 ######

 # session.query(UserType.id,UserType.title).filter(UserType.id > 2).delete()

 # ###### 修改 ######

 #**********批量修改----这里批量修改title为黑金

 # session.query(UserType.id,UserType.title).filter(UserType.id > 0).update({"title" : "黑金"})

 #**********批量字符串类型修改----这里是批量在原title基础上+'aaa',加上的内容是字符串类型,修改对象也应是字符串类型

 # session.query(UserType.id,UserType.title).filter(UserType.id > 0).update({UserType.title: UserType.title + "aaa"}, synchronize_session=False)

 #**********批量数字类型修改----这里是批量在原num基础上+'111',加上的内容是数字类型，修改对象也应是数字类型

 # session.query(UserType.id,UserType.title).filter(UserType.id > 0).update({"num": Users.num + 111}, synchronize_session="evaluate")

 session.commit()           #执行完提交

 session.close()           #关闭这次会话

ORM框架创建表和操作表

码农公寓

一、pymysql

二、SQLAchemy

相关文章