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
pymsql
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
# 创建连接
conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123456', db='db1',charset='utf8')
# 创建游标
cursor = conn.cursor() # 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()
增,删,改需要执行 conn.commit()
2、获取新创建数据自增ID
import pymysql conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123', 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 => 如果插入多条,只能拿到最后一条id
new_id = cursor.lastrowid
3、获取查询数据
import pymysql conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123', db='t1')
cursor = conn.cursor()
cursor.execute("select * from hosts") # 获取第一行数据
row_1 = cursor.fetchone()
# => 再次执行:cursor.fetchone() 获得下一条数据,没有时为None # 获取前n行数据
# row_2 = cursor.fetchmany(n)
# ==> 执行了n次fetchone() # 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:
import pymysql conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='123456', db='t1') # 游标设置为字典类型
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor) row = cursor.execute("select * from user") result = cursor.fetchone()
print(result) conn.commit()
cursor.close()
conn.close()
补充:
1.SQL注入
"select name from user where name='%s' and password ='%s' " %(username,password)
"select name from user where name=%s and password =%s ",( username,password )
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。
ORM:
ORM框架的作用就是把数据库表的一行记录与一个对象互相做自动转换。 正确使用ORM的前提是了解关系数据库的原理。
ORM就是把数据库表的行与相应的对象建立关联,互相转换。 由于关系数据库的多个表还可以用外键实现一对多、多对多等关联,
相应地, ORM框架也可以提供两个对象之间的一对多、多对多等功能。
SQLAlchemy:
本身无法操作数据库,其必须以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
#!/usr/bin/env python
# -*-coding:utf-8 -*- from sqlalchemy import create_engine,and_,or_,func,Table
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String,ForeignKey
from sqlalchemy.orm import sessionmaker,relationship engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/t1?charset=utf8", max_overflow=5) Base = declarative_base() def init_db():
Base.metadata.create_all(engine) def drop_db():
Base.metadata.drop_all(engine)
一、底层处理
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。处理中文数据时,在连接数据库时要加上 ?charset=utf8
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)) # 设置索引:
__table_args__ = (
UniqueConstraint('id', 'name', name='uix_id_name'),
Index('ix_id_name', 'name', 'extra'),
) # 输出Users对象时,调用:
def __repr__(self):
return "%s-%s-%s" % (self.id, self.name , self.extra) def init_db():
Base.metadata.create_all(engine) #创建表 def drop_db():
Base.metadata.drop_all(engine) #删除表
一对多
# 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")) # 外键
多对多
# 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'))
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) #生成一个SQLORM基类
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) # 这两行触发sessionmaker类下的__call__方法,return得到 Session实例,赋给变量session,
# 所以session可以调用Session类下的add,add_all等方法 Session = sessionmaker(bind=engine)
session = Session()
.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()
3.更多查询方法:
#!/usr/bin/env python
# -*-coding:utf-8 -*- from sqlalchemy import create_engine,and_,or_,func,Table
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String,ForeignKey
from sqlalchemy.orm import sessionmaker,relationship engine = create_engine('mysql+pymysql://root@127.0.0.1:3307/day40?charset=utf8') Base = declarative_base() class Man_To_Woman(Base): __tablename__ = 'man_to_woman'
nid = Column(Integer,primary_key=True)
man_id = Column(Integer,ForeignKey('man.nid'))
woman_id = Column(Integer,ForeignKey('woman.nid')) class Man(Base): __tablename__ = 'man'
nid = Column(Integer,primary_key=True)
name = Column(String(20),nullable=False)
woman = relationship("Woman", secondary=Man_To_Woman.__table__) class Woman(Base): __tablename__ = 'woman'
nid = Column(Integer,primary_key=True)
name = Column(String(20),nullable=False)
man = relationship("Man",secondary=Man_To_Woman.__table__) Base.metadata.create_all(engine) MySession = sessionmaker(engine)
session = MySession()
事例: 表结构
1.filter_by( ... ) 填写键值对方式
ret = session.query(Man).filter_by(name='alex').first()
print(ret.nid,ret.name)
2.filter 填写条件判断
ret = session.query(Man).filter(Man.name=='eric').first() ret = session.query(Man).filter(Man.name=='eric' , Man.nid > 0).first() row = session.query(Man).filter(Man.nid.between(1,4)).all() ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name='eric'))).all()
3.and_ or_ 条件判断
from sqlalchemy import and_, or_ ret = session.query(Man).filter(and_(Man.name == 'eric',Man.nid == 2)).first()
ret = session.query(Man).filter(or_(Man.name == 'eric',Man.nid == 2)).first()
4.~ 取反
ret = session.query(Man).filter(Man.nid.in_([2,3])).first()
ret = session.query(Man).filter(~Man.nid.in_([2,3])).first()
5.like + % 通配符
ret = session.query(Man).filter(Man.name.like('%x')).first()
ret = session.query(Man).filter(~Man.name.like('%x')).first()
6.切片 限制 ( 序号,前闭后开 )
row = session.query(Man)[1:3]
for ret in row:
print(ret.nid, ret.name) row = session.query(Man).limit(3).offset(1)
7.order_by 排序
row = session.query(Man).order_by(Man.nid.desc()).all()
row = session.query(Man).order_by(Man.nid.asc()).all()
8.group_by 分组
row = session.query(func.count('*')).select_from(Man).all()
row = session.query(func.count('*')).filter(Man_To_Woman.nid > 1).all()
row = session.query(func.count('*')).select_from(Man_To_Woman).group_by(Man_To_Woman.man_id).all()
row = session.query(func.count('*')).select_from(Man_To_Woman).group_by(Man_To_Woman.man_id).limit(1).all() row = session.query(Man_To_Woman).group_by(Man_To_Woman.man_id).all() 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()
9.join 连表
row = session.query(Users, Favor).filter(Users.id == Favor.nid).all() ret = session.query(Son).join(Father).all() ret = session.query(Son).join(Father, isouter=True).all()
10.union 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
补充 Relationship:
改变数据输出的方式:可以在表的类中定义一个特殊成员:__repr__, return一个自定义的由字符串拼接的数据连接方式.
数据库中表关系之间除了MySQL中标准的外键(ForeignKey)之外,还可以创建一个虚拟的关系,比如
group = relationship("Group",backref='uuu')
,一般此虚拟关系与foreignkey一起使用.
relationship : 通过relatioinship 找到绑定关系的数据 !!!
一对多,连表操作:
class Father(Base): __tablename__ ='father'
nid = Column(Integer,primary_key=True)
name = Column(String(32))
son = relationship('Son') class Son(Base): __tablename__ = 'son'
nid = Column(Integer, primary_key=True)
name = Column(String(32))
father_id = Column(Integer,ForeignKey('father.nid'))
father = relationship('Father')
表结构
正向查询:
需求:查询Son表中所有数据,并且显示对应的Father表中的数据.
ret = session.query(Son).all()
for obj in ret:
print(obj.nid,obj.name,obj.father_id,obj.father.name)
反向查询:
需求:查询Father表中, 属于 alvin 的所有儿子Son.
obj = session.query(Father).filter(Father.name=='alvin').first() row = obj.son
for ret in row:
print(ret.nid,ret.name,ret.father.name)
多对多,连表操作:
#!/usr/bin/env python
# -*-coding:utf-8 -*- from sqlalchemy import create_engine,and_,or_,func,Table
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String,ForeignKey
from sqlalchemy.orm import sessionmaker,relationship engine = create_engine('mysql+pymysql://root@127.0.0.1:3307/day40?charset=utf8') Base = declarative_base() class Man_To_Woman(Base): __tablename__ = 'man_to_woman'
nid = Column(Integer,primary_key=True)
man_id = Column(Integer,ForeignKey('man.nid'))
woman_id = Column(Integer,ForeignKey('woman.nid')) class Man(Base): __tablename__ = 'man'
nid = Column(Integer,primary_key=True)
name = Column(String(20),nullable=False)
woman = relationship("Woman", secondary=Man_To_Woman.__table__) class Woman(Base): __tablename__ = 'woman'
nid = Column(Integer,primary_key=True)
name = Column(String(20),nullable=False)
man = relationship("Man",secondary=Man_To_Woman.__table__) Base.metadata.create_all(engine) MySession = sessionmaker(engine)
session = MySession()
表结构
正,反向操作:
1.alex的所有女人
2.凤姐的所有男人
man1 = session.query(Man).filter(Man.name=='alex').first()
print(man1)
for ret in man1.woman:
print(ret.nid,ret.name) woman1 = session.query(Woman).filter(Woman.name=='fengjie').first()
print(woman1)
for ret in woman1.man:
print(ret.nid,ret.name)
relatioinship 语句的简写: ,我添加到Man表中
woman = relationship("Woman", secondary=Man_To_Woman.__table__,backref='man')
1 关于 session.add session.query session.commit的顺序问题?
在同一个会话中, insert into table (xxxx)后,可以接着 select * from xxx; 查询到刚刚插入的数据;
只是不能在其他会话,比如我另开一个客户端去连接数据库不能查询到刚刚插入的数据。
这个数据已经到数据库。值是数据库吧这个数据给锁了。只有插入数据的那个session可以查看到,其他的session不能查看到,可以理解提交并解锁吧。