1、常用sql操作
创建一个test库:create database test;
授权一个用户:grant all privileges on *.* to 'user'@'%' identified by 'password';
创建表:create table student(id int not null);
查询:select * from tabel_name where 条件1 and 条件2
增加:insert into table_name (id, name, age, sex, grander) values (1, 'ling', 25, 'M', 99), (2, 'ajing', 45, 'F', 88);
修改:update table_name set id=10 where 条件判断
删除条件:delete from table_name where 条件判断
删除表:drop table table_name
联合查询:select a.id, b.name from A a join B b on a.id=b.tid
创建索引:create index idx_库名_表名_列名1_列名2 (列名1, 列名2)
查看sql是否走索引:explain select * from student where name='ling'
链接数据库:Python2 使用的是MySQLdb,python3 使用的pymysql 可以使用pip安装
2、python连接数据库操作
①、 创建链接和游标
注意:在mysql连接中,尽量使用一个连接,确保mysql的并发数
conn = pymysql.connect(host='', port=, user='', passwd='', db='')
cus = conn.curse()
②、执行sql
sql = "select * from Student;"
cus.execute(sql)
cus.fetchone() 获取单个 返回值 tuple
cus.fetchall() 获取多个 返回值 list(单个元素是tuple)
cus.fetchmany(size=n) 获取多个
③、关闭游标和连接
cus.close()
conn.close()
注意结合try exception finally的使用
3、SQLAlchemy操作
①、创建引擎
engine = create_engine('mysql+pymysql://username:password@hostname:port/db')
②、创建session
DBsession = sessionmaker(bind=engine)
session = DBsession()
③、创建表
a. 获得engine
b. metadata = MetaData(engine)
c. student = Table('表名', metadata, Colume('id', Integer, primary_key=True), Colume('name', String(50))
d. metadata.create_all()
④、增加
a. 先要有一个模型
Base = declarative_base()
class Student(Base):
__tablename__ = 'student'
id = Column(Integer, primary_key=True)
name = Column(String(100), primary_key=True)
b. 导入模型类,实例化该类,
sutdent1 = Student(1, 'ling')
c. session.add(单实例) session.add_all([实例1, 实例2])
⑤、查询
filter和filter_by的区别
filter:可以使用> < 等,但是列必须是: 表.列, filter的等于号是==
session.query(Student).filter(Student.id>100)
filter 不支持组合查询
session.query(Student).filter(Studnet.id>100).filter(name=='ling')
filter_by: 可以直接写列,不支持< > filter_by 等于是==
session.query(Student).filter_by(id==10)
filter_by 可以支持组合查询
session.query(Student).filter_by(name=='ling' and id=='342')
select * from student where name like '%ling%';
模糊查询含有ling的关键字
模糊查询
session.query(Student).filter(Student.name like('%ling%'))
获取数据的时候有两个方法:
one() tuple
all() list(单个元素是tuple)
如果在查询中不写one(), 或者all() 出来的就是sql语句
⑥、更新
1)、先查出来
2)、跟新一下类所对应的属性值就ok
3)、session.commit()
student1 = session.query(Student).filter(Student.id==1001)
student1.name = "test"
session.commit()
⑦、删除
1)、先查出来
2)、直接调用delete()方法就可以
3)、提交一下
⑧、统计、 分组、排序
统计:count()
只需要在查出来以后, 把one或者all替换成count()
统计有多少个
分组:group_by
查出来以后,把one或者all替换成group_by(属性)
4、示例:
from sqlalchemy import create_engine, Integer, String, Column
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
Base = declarative_base()
class Student(Base):
__tablename__ = 'student'
id = Column(Integer, primary_key=True)
name = Column(String(100))
age = Column(Integer)
address = Column(String(100))
def update(session):
student1 = session.query(Student).filter(Student.id == 1001).one()
student1.name='test123'
session.commit()
student2 = session.query(Student).filter(Student.id == 1001).one()
print(student2.name)
def delete(session):
session.query(Student).filter(Student.id == 1001).delete()
session.commit()
def insert(session):
student1 = Student(id=1004, name='ling', age=28, address='shanxi')
session.add(student1)
session.commit()
def count(session):
numnber = session.query(Student).filter().count()
print("total student is {0}".format(numnber))
def groupBy(session):
groupByAge = session.query(Student).group_by(Student.age).all()
print(groupByAge)
for i in groupByAge:
print(i.id, i.name, i.age, i.address)
def orderBy(session):
orderByAge = session.query(Student).order_by(Student.age.desc()).all()
for x in orderByAge:
print(x.id, x.name, x.age, x.address)
def main():
engine = create_engine('mysql+pymysql://xiang:xiang@192.168.48.136/sqlalchemy')
DBsession = sessionmaker(bind=engine)
session = DBsession()
# insert(session)
# update(session)
# delete(session)
# count(session)
# groupBy(session)
orderBy(session)
if __name__ == '__main__':
main()