python之路-----python操作 mysql

========================pymysql============================

一.pymysql 基础

  安装命令:pip3 install pymysql -i https://pypi.douban.com/simple

二.pymysql命令

 1.链接数据库

conn = pymysql.connect(host='127.0.0.1', port=3306, user='school_spt', passwd='123456', db='school_info')   #返回个链接对象

 2.创建游标

cursor = conn.cursor()

 3.sql拼接命令

1.字符串拼接(不推荐使用该方式,容易被sql注入)
user='root'
pwd='123456'
sql='select * from userinfo where password=%s and username=%s'%(pwd,user)

2.pymysql命令自带拼接
executsql命令, args)    #args可以是列表,元组或者字典

列表:

user='root'
pwd='123456'
sql='select * from userinfo where password=%s and username=%s'
cursor.execute(sql,[pwd,user]) 
元组
user='root'
pwd='123456'
sql='select * from userinfo where password=%s and username=%s'
cursor.execute(sql,(pwd,user)) 

字典
sql='select * from userinfo where password=%(password)s and username=%(username)s'
cursor.execute(sql,({'password':pwd,'username':user}))

  4.查

sql='select * from userinfo'
res=cursor.execute(sql)   #返回受影响的行数
#获取返回的数据
cursor.fetchone()      #获取返回的第一行内容
cursor.fetchmany(n)    #获取返回的前n行内容
cursor.fetchall()          #获取返回的全部内容

#返回的数据默认是元组形式,如果要以字典形式显示
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)

  5.改(改,删,增)

1.增
    sql=‘insert into userinfo(username,password) values(%s,%s)’
    cursor.execute(sql,('root','123'));   #单条插入
    也可以使用批量插入数据
    cursor.executemany(sql,[('root','123'),('root1','1234'),('root2','123')]);
2.改,删没有批量执行命令,批量一般都使用单条执行
3.增,删,改操作后,都需要使用 conn.commit()来确认提交数据

  6.execute会返回受影响的行数。一般不适用

  7.scroll 

  在fetch数据时按照顺序进行(类似生成器),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

  8.获取最后的自增id值(lastrowid)

id=cursor.lastrowid

  9.关闭游标和链接

cursor.close()  #先关闭游标
conn.close()    #再关闭连接 

 =====================================================================================================================

==============================SQLAchemy=========================================

一.ORM框架

  ORM(Object Relational Mapping)对象关系映射,用于实现面向对象编程语言里不同类型系统的数据之间的转换。从效果上说,它其实是创建了一个可在编程语言里使用的--“虚拟对象数据库”。

  简单来说,ORM的作用是:

    1.提供简单的规则

    2.自动转换为sql语句

  ORM分为两类:

    1.code first :手动创建类和数据库  ----------->orm-------->表(根据代码生成对应的数据表)

    2.db first  :手动创建数据库以及表----------->orm框架------->自动生成类(根据表来生成对应的代码)

  ORM框架只是负责将代码转换为对应的sql语句,而链接数据库执行这些语句则需要其他的模块,如pymysql。

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。

  1.安装

pip3 install SQLAlchemy

  2.SQLAchemy 结构

 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

  3.SQLAchemy使用

  3.1 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。

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()
链接数据库,执行命令

  3.2 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。

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)
创建表

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

  3.2.2 操作表

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

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
obj = Users(name="alex0", extra='sb')
session.add(obj)
session.add_all([
    Users(name="alex1", extra='sb'),
    Users(name="alex2", extra='sb'),
])
session.commit()
session.query(Users).filter(Users.id > 2).delete()
session.commit()
session.query(Users).filter(Users.id > 2).update({"name" : "099"})
session.query(Users).filter(Users.id > 2).update({Users.name: Users.name + "099"}, synchronize_session=False)
session.query(Users).filter(Users.id > 2).update({"num": Users.num + 1}, synchronize_session="evaluate")
session.commit()
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()

ret = session.query(Users).filter(text("id<:value and name=:name")).params(value=224, name='fred').order_by(User.id).all()

ret = session.query(Users).from_statement(text("SELECT * FROM users where name=:name")).params(name='ed').all()
# 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()
补充
原文地址:https://www.cnblogs.com/white-small/p/7372793.html