flask之SQLAlchemy

SQLAlchemy

1.介绍

SQLAlchemy是一个基于Python实现的ORM框架。该框架建立在 DB API之上，使用关系对象映射进行数据库操作，简言之便是：将类和对象转换成SQL，然后使用数据API执行SQL并获取执行结果。

pip3 install sqlalchemy

组成部分：

Engine，框架的引擎
Connection Pooling ，数据库连接池
Dialect，选择连接数据库的DB API种类
Schema/Types，架构和类型
SQL Exprression Language，SQL表达式语言

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

django中如何反向生成models

python manage.py inspectdb > app/models.py

2.简单使用（能创建表，删除表，不能修改表）

修改表：在数据库添加字段，类对应上

1执行原生sql（不常用）

import time
import threading
import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy.engine.base import Engine

engine = create_engine(
    "mysql+pymysql://root:123456@127.0.0.1:3306/test?charset=utf8",
    max_overflow=0,  # 超过连接池大小外最多创建的连接
    pool_size=5,  # 连接池大小
    pool_timeout=30,  # 池中没有线程最多等待的时间，否则报错
    pool_recycle=-1  # 多久之后对线程池中的线程进行一次连接的回收（重置）
)
def task(arg):
    conn = engine.raw_connection()
    cursor = conn.cursor()
    cursor.execute(
        "select * from app01_book"
    )
    result = cursor.fetchall()
    print(result)
    cursor.close()
    conn.close()

for i in range(20):
    t = threading.Thread(target=task, args=(i,))
    t.start()

2 orm使用

models.py

import datetime
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, Text, ForeignKey, DateTime, UniqueConstraint, Index
Base = declarative_base()

class Users(Base):
    __tablename__ = 'users'  # 数据库表名称
    id = Column(Integer, primary_key=True)  # id 主键
    name = Column(String(32), index=True, nullable=False)  # name列，索引，不可为空
    # email = Column(String(32), unique=True)
    #datetime.datetime.now不能加括号，加了括号，以后永远是当前时间
    # ctime = Column(DateTime, default=datetime.datetime.now)
    # extra = Column(Text, nullable=True)

    __table_args__ = (
        # UniqueConstraint('id', 'name', name='uix_id_name'), #联合唯一
        # Index('ix_id_name', 'name', 'email'), #索引
    )

def init_db():
    """
    根据类创建数据库表
    :return:
    """
    engine = create_engine(
        "mysql+pymysql://root:123456@127.0.0.1:3306/aaa?charset=utf8",
        max_overflow=0,  # 超过连接池大小外最多创建的连接
        pool_size=5,  # 连接池大小
        pool_timeout=30,  # 池中没有线程最多等待的时间，否则报错
        pool_recycle=-1  # 多久之后对线程池中的线程进行一次连接的回收（重置）
    )

    Base.metadata.create_all(engine)

def drop_db():
    """
    根据类删除数据库表
    :return:
    """
    engine = create_engine(
        "mysql+pymysql://root:123456@127.0.0.1:3306/aaa?charset=utf8",
        max_overflow=0,  # 超过连接池大小外最多创建的连接
        pool_size=5,  # 连接池大小
        pool_timeout=30,  # 池中没有线程最多等待的时间，否则报错
        pool_recycle=-1  # 多久之后对线程池中的线程进行一次连接的回收（重置）
    )

    Base.metadata.drop_all(engine)

if __name__ == '__main__':
    # drop_db()
    init_db()

app.py

from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from models import Users
#"mysql+pymysql://root@127.0.0.1:3306/aaa"
engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/aaa", max_overflow=0, pool_size=5)
Connection = sessionmaker(bind=engine)

# 每次执行数据库操作时，都需要创建一个Connection
con = Connection()

# ############# 执行ORM操作 #############
obj1 = Users(name="cxk")
con.add(obj1)
# 提交事务
con.commit()

# 关闭session，其实是将连接放回连接池
con.close()

3.一对多关系

class Hobby(Base):
    __tablename__ = 'hobby'
    id = Column(Integer, primary_key=True)
    caption = Column(String(50), default='篮球')


class Person(Base):
    __tablename__ = 'person'
    nid = Column(Integer, primary_key=True)
    name = Column(String(32), index=True, nullable=True)
    # hobby指的是tablename而不是类名，uselist=False
    hobby_id = Column(Integer, ForeignKey("hobby.id"))
    
    # 跟数据库无关，不会新增字段，只用于快速链表操作
    # 类名，backref用于反向查询
    hobby=relationship('Hobby',backref='pers')

4.多对多关系

class Boy2Girl(Base):
    __tablename__ = 'boy2girl'
    id = Column(Integer, primary_key=True, autoincrement=True)
    girl_id = Column(Integer, ForeignKey('girl.id'))
    boy_id = Column(Integer, ForeignKey('boy.id'))


class Girl(Base):
    __tablename__ = 'girl'
    id = Column(Integer, primary_key=True)
    name = Column(String(64), unique=True, nullable=False)


class Boy(Base):
    __tablename__ = 'boy'

    id = Column(Integer, primary_key=True, autoincrement=True)
    hostname = Column(String(64), unique=True, nullable=False)
    
    # 与生成表结构无关，仅用于查询方便,放在哪个单表中都可以
    servers = relationship('Girl', secondary='boy2girl', backref='boys')

5.操作数据表

from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from models import Users
  
engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/aaa", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
  
# 每次执行数据库操作时，都需要创建一个session
session = Session()
  
# ############# 执行ORM操作 #############
obj1 = Users(name="lqz")
session.add(obj1)
  
# 提交事务
session.commit()
# 关闭session
session.close()

6.基于scoped_session实现线程安全

from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session
from models import Users

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)

"""
# 线程安全，基于本地线程实现每个线程用同一个session
# 特殊的：scoped_session中有原来方法的Session中的以下方法：

public_methods = (
    '__contains__', '__iter__', 'add', 'add_all', 'begin', 'begin_nested',
    'close', 'commit', 'connection', 'delete', 'execute', 'expire',
    'expire_all', 'expunge', 'expunge_all', 'flush', 'get_bind',
    'is_modified', 'bulk_save_objects', 'bulk_insert_mappings',
    'bulk_update_mappings',
    'merge', 'query', 'refresh', 'rollback',
    'scalar'
)
"""
#scoped_session类并没有继承Session,但是却又它的所有方法
session = scoped_session(Session)
# ############# 执行ORM操作 #############
obj1 = Users(name="cxk2")
session.add(obj1)

# 提交事务
session.commit()
# 关闭session
session.close()

7.基本增删查改

import time
import threading
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
from sqlalchemy.sql import text

from _3models import Users

engine = create_engine("mysql+pymysql://tomjoy:123456@127.0.0.1:3306/aaa", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)

session = Session()

# ################ 添加 ################

# obj1 = Users(name="wupeiqi",age=10)
# session.add(obj1)

# session.add_all([
#     Users(name="kobe",age=123),
#     Users(name="james",age=45),
# ])
# session.commit()


# ################ 删除 ################

# session.query(Users).filter(Users.id == 2).delete()
# session.commit()

# ################ 修改 ################

#传字典
# session.query(Users).filter(Users.id == 3).update({"name" : "yao","age":38})
#类似于django的F查询
# session.query(Users).filter(Users.id == 3).update({Users.name: Users.name + "099"}, synchronize_session=False)
# session.query(Users).filter(Users.id == 3).update({"age": Users.age + 1}, synchronize_session="evaluate")
#session.commit()

# ################ 查询 ################

# r1 = session.query(Users).all()
# print(r1)
# #如果不加all或者first就是sql语句
#
#只取age列，把name重命名为xx
# r2 = session.query(Users.name.label('xx'), Users.age.label("age1")).all()
# print(r2[0].xx)  # name=xx
# r2 = session.query(Users.name, Users.age).all()
# print(r2[0].name)
# #filter传的是表达式，filter_by传的是参数
# r3 = session.query(Users).filter(Users.name == "kobe").first()
# print(r3)
# r4 = session.query(Users).filter_by(name='kobe').all()
# print(r4)
# r5 = session.query(Users).filter_by(name='kobe').first()
# print(r5)


#增，删，改都要commit()
session.commit()
session.close()

8.常用操作

#　条件
ret = session.query(Users).filter_by(name='lqz').all()
#表达式，and条件连接
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()
# 注意下划线
ret = session.query(Users).filter(Users.id.in_([1,3,4])).all()
#~非，除。。外
ret = session.query(Users).filter(~Users.id.in_([1,3,4])).all()
#二次筛选
ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name='eric'))).all()
from sqlalchemy import and_, or_
#or_包裹的都是or条件，and_包裹的都是and条件
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)
    )).all()


# 通配符，以e开头，不以e开头，第二个为e
ret = session.query(Users).filter(Users.name.like('e%')).all()
ret = session.query(Users).filter(~Users.name.like('e%')).all()
ret = session.query(Users).filter(~Users.name.like('_e%')).all()

# 限制，用于分页，区间
ret = session.query(Users)[1:2]

# 排序，根据name降序排列（从大到小）
ret = session.query(Users).order_by(Users.name.desc()).all()
# 第一个条件重复后，再按第二个条件升序排
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()
# 分组之后取最大id，id之和，最小id
ret = session.query(
    func.max(Users.id),
    func.sum(Users.id),
    func.min(Users.id)).group_by(Users.name).all()
# haviing筛选
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（默认用forinkey关联）

ret = session.query(Users, Favor).filter(Users.id == Favor.nid).all()
#join表，默认是inner join
ret = session.query(Person).join(Favor).all()
# isouter=True 外连，表示Person left join Favor，没有右连接，反过来即可
ret = session.query(Person).join(Favor, isouter=True).all()
#打印原生sql
aa=session.query(Person).join(Favor, isouter=True)
print(aa)
# 自己指定on条件（连表条件）,第二个参数，支持on多个条件，用and_,同上
ret = session.query(Person).join(Favor,Person.id==Favor.id, isouter=True).all()
# 组合（了解）UNION 操作符用于合并两个或多个 SELECT 语句的结果集
#union和union all的区别？
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()

9.执行原生sql

import time
import threading

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
from sqlalchemy.sql import text
from sqlalchemy.engine.result import ResultProxy
from db import Users, Hosts

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)

session = Session()

# 查询
# cursor = session.execute('select * from users')
# result = cursor.fetchall()

# 添加
cursor = session.execute('insert into users(name) values(:value)',params={"value":'lqz'})
session.commit()
print(cursor.lastrowid)

session.close()

10.一对多

import time
import threading

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
from sqlalchemy.sql import text
from sqlalchemy.engine.result import ResultProxy
from db import Users, Hosts, Hobby, Person

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
session = Session()
# 添加
"""
session.add_all([
    Hobby(caption='乒乓球'),
    Hobby(caption='羽毛球'),
    Person(name='张三', hobby_id=3),
    Person(name='李四', hobby_id=4),
])

person = Person(name='张九', hobby=Hobby(caption='姑娘'))
session.add(person)
#添加二
hb = Hobby(caption='人妖')
hb.pers = [Person(name='文飞'), Person(name='博雅')]
session.add(hb)

session.commit()
"""

# 使用relationship正向查询
"""
v = session.query(Person).first()
print(v.name)
print(v.hobby.caption)
"""

# 使用relationship反向查询
"""
v = session.query(Hobby).first()
print(v.caption)
print(v.pers)
"""
#方式一，自己链表
# person_list=session.query(models.Person.name,models.Hobby.caption).join(models.Hobby,isouter=True).all()
person_list=session.query(models.Person,models.Hobby).join(models.Hobby,isouter=True).all()
for row in person_list:
    # print(row.name,row.caption)
    print(row[0].name,row[1].caption)

#方式二：通过relationship

person_list=session.query(models.Person).all()
for row in person_list:
    print(row.name,row.hobby.caption)
#查询喜欢姑娘的所有人
obj=session.query(models.Hobby).filter(models.Hobby.id==1).first()
persons=obj.pers
print(persons)
session.close()

11.多对多

import time
import threading

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
from sqlalchemy.sql import text
from sqlalchemy.engine.result import ResultProxy
from db import Users, Hosts, Hobby, Person, Group, Server, Server2Group

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
session = Session()
# 添加
"""
session.add_all([
    Server(hostname='c1.com'),
    Server(hostname='c2.com'),
    Group(name='A组'),
    Group(name='B组'),
])
session.commit()

s2g = Server2Group(server_id=1, group_id=1)
session.add(s2g)
session.commit()


gp = Group(name='C组')
gp.servers = [Server(hostname='c3.com'),Server(hostname='c4.com')]
session.add(gp)
session.commit()


ser = Server(hostname='c6.com')
ser.groups = [Group(name='F组'),Group(name='G组')]
session.add(ser)
session.commit()
"""


# 使用relationship正向查询
"""
v = session.query(Group).first()
print(v.name)
print(v.servers)
"""

# 使用relationship反向查询
"""
v = session.query(Server).first()
print(v.hostname)
print(v.groups)
"""


session.close()

12.其它

import time
import threading

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
from sqlalchemy.sql import text, func
from sqlalchemy.engine.result import ResultProxy
from db import Users, Hosts, Hobby, Person, Group, Server, Server2Group

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
session = Session()

# 关联子查询:correlate(Group)表示跟Group表做关联，as_scalar相当于对该sql加括号，用于放在后面当子查询
subqry = session.query(func.count(Server.id).label("sid")).filter(Server.id == Group.id).correlate(Group).as_scalar()
result = session.query(Group.name, subqry)
"""
SELECT `group`.name AS group_name, (SELECT count(server.id) AS sid 
FROM server 
WHERE server.id = `group`.id) AS anon_1 
FROM `group`
"""
'''

select * from tb where id in [select id from xxx];

select id,
        name,
        #必须保证此次查询只有一个值
        (select max(id) from xxx) as mid
from tb

例如，第三个字段只能有一个值
id name  mid
1  lqz   1，2  不合理
2  egon   2


'''
'''
成绩表：
id sid    cid    score
1  1      物理      99 
2  1      化学      88
3  2      物理      95

学生表：
id   name  每个学生总分数
1     xx      88
2     yy       77

select id，name,
(select avr(score) from 成绩表 where 成绩表.sid=学生表.id) as x
from 学生表
subqry = session.query(func.count(成绩表.scort).label("sc")).filter(学生表.id == 成绩表.sid).correlate(学生表).as_scalar()
result = session.query(学生表.name, subqry)

'''

# 原生SQL
"""
# 查询
cursor = session.execute('select * from users')
result = cursor.fetchall()

# 添加
cursor = session.execute('insert into users(name) values(:value)',params={"value":'wupeiqi'})
session.commit()
print(cursor.lastrowid)
"""

session.close()

13.Flask-SQLAlchemy

flask和SQLAchemy的管理者，通过他把他们做连接

db = SQLAlchemy()
    - 包含配置
    - 包含ORM基类
    - 包含create_all
    - engine
    - 创建连接

离线脚本，创建表

详见代码

flask-migrate
python3 manage.py db init 初始化：只执行一次

python3 manage.py db migrate 等同于 makemigartions
python3 manage.py db upgrade 等同于migrate