0221 SQLAlchemy

目录

SQlAlchemy

介绍

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。

补充

MySQL数据库连接不上的原因

# 1 用户名密码错误，用户权限不够，
# 2 ip和端口不对。远程ip,该服务器的防火墙有没有关闭，端口不一定是3306，3307，3308，3309，3310

ORM

创建表

# 1. 创建单表
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, DateTime
from sqlalchemy import Index, UniqueConstraint
import datetime

ENGINE = create_engine("mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",)

# Base是declarative_base的实例化对象
Base = declarative_base()


# 每个类都要继承Base
class UserInfo(Base):
    # __tablename__是必须要的，它是设置实际存在数据库中的表名
    __tablename__ = "user_info"

    # Column是列的意思，固定写法 Column(字段类型, 参数)
    # primary_key主键、index索引、nullable是否可以为空
    id = Column(Integer, primary_key=True)
    name = Column(String(32), index=True, nullable=False)
    email = Column(String(32), unique=True)
    create_time = Column(DateTime, default=datetime.datetime.now)

    # 相当于Django的ORM的class Meta，是一些元信息
    __table_args__ = (
        UniqueConstraint("id", "name", name="uni_id_name"),
        Index("name", "email")
    )


def create_db():
    # metadata.create_all创建所有表
    Base.metadata.create_all(ENGINE)


def drop_db():
    # metadata.drop_all删除所有表
    Base.metadata.drop_all(ENGINE)


if __name__ == '__main__':
    create_db()

一对一表

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, DateTime
from sqlalchemy import Index, UniqueConstraint, ForeignKey
from sqlalchemy.orm import relationship
import datetime


ENGINE = create_engine("mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",)

Base = declarative_base()


# ======一对多示例=======
class UserInfo(Base):
    __tablename__ = "user_info"

    id = Column(Integer, primary_key=True)
    # index=True,设置索引
    name = Column(String(32), index=True, nullable=False)
    email = Column(String(32), unique=True)
    create_time = Column(DateTime, default=datetime.datetime.now)
    # ForeignKey字段的建立,需要指定外键绑定哪个表的哪个字段
    hobby_id = Column(Integer, ForeignKey("hobby.id"))
    # 不生成表结构 方便查询和增加的操作
    # 第一个参数是关联到哪个类(表), backref是给关联的那个类反向查询用的
    hobby = relationship("Hobby", backref="user")

    __table_args__ = (
        # UniqueConstraint联合唯一，这个联合唯一的字段名为：uni_id_name
        UniqueConstraint("id", "name", name="uni_id_name"),
        # 联合索引
        Index("name", "email")
    )


class Hobby(Base):
    __tablename__ = "hobby"

    id = Column(Integer, primary_key=True)
    title = Column(String(32), default="码代码")




def create_db():
    Base.metadata.create_all(ENGINE)


def drop_db():
    Base.metadata.drop_all(ENGINE)



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

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')

多对多表

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, DateTime
from sqlalchemy import Index, UniqueConstraint, ForeignKey
from sqlalchemy.orm import relationship
import datetime


ENGINE = create_engine("mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",)

Base = declarative_base()


# ======多对多示例=======
class Book(Base):
    __tablename__ = "book"

    id = Column(Integer, primary_key=True)
    title = Column(String(32))
    # 不生成表字段 仅用于查询和增加方便
    # 多对多的relationship还需要设置额外的参数secondary：绑定多对多的中间表
    tags = relationship("Tag", secondary="book2tag", backref="books")


class Tag(Base):
    __tablename__ = "tag"

    id = Column(Integer, primary_key=True)
    title = Column(String(32))


class Book2Tag(Base):
    __tablename__ = "book2tag"

    id = Column(Integer, primary_key=True)
    book_id = Column(Integer, ForeignKey("book.id"))
    tag_id = Column(Integer, ForeignKey("tag.id"))


def create_db():
    Base.metadata.create_all(ENGINE)

def drop_db():
    Base.metadata.drop_all(ENGINE)

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

数据库操作

scoped_session

# 1. scoped_session
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, scoped_session
from models_demo import Tag


ENGINE = create_engine("mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",)

# 每次执行数据库操作的时候，都需要创建一个session,相当于管理器(相当于Django的ORM的objects)
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
session = scoped_session(Session)


# =======执行ORM操作==========
tag_obj = Tag(title="SQLAlchemy")
# 添加
session.add(tag_obj)
# 提交
session.commit()
# 关闭session
session.close()

增删改查

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, scoped_session
from models_demo import Tag, UserInfo
import threading


ENGINE = create_engine("mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",)

Session = sessionmaker(bind=ENGINE)

# 每次执行数据库操作的时候，都需要创建一个session
session = Session()
session = scoped_session(Session)


# ============添加================
tag_obj = Tag(title="SQLAlchemy")
session.add(tag_obj)

# 批量添加
session.add_all([
    Tag(title="Python"),
    Tag(title="Django"),
])
# 提交
session.commit()
# 关闭session
session.close()


# ============基础查询============
ret = session.query(Tag).all()
# get(id)
ret1 = session.query(Tag).get(1)  # 查询Tag表 id=1的记录
# filter(表达式)
ret2 = session.query(Tag).filter(Tag.title == "Python").all()
# filter_by(字段=xx)
ret3 = session.query(Tag).filter_by(title="Python").all()
ret4 = session.query(Tag).filter_by(title="Python").first()
print(ret1, ret2, ret3, ret4)


# ============删除===========
session.query(Tag).filter_by(id=1).delete()
session.commit()


# ===========修改===========
session.query(Tag).filter_by(id=22).update({Tag.title: "LOL"})
session.query(Tag).filter_by(id=23).update({"title": "吃鸡"})
session.query(Tag).filter_by(id=24).update({"title": Tag.title + "~"}, synchronize_session=False)
# synchronize_session="evaluate" 默认值进行数字加减
session.commit()

常用操作

# 条件查询
ret1 = session.query(Tag).filter_by(id=22).first()
ret2 = session.query(Tag).filter(Tag.id > 1, Tag.title == "LOL").all()
ret3 = session.query(Tag).filter(Tag.id.between(22, 24)).all()
ret4 = session.query(Tag).filter(~Tag.id.in_([22, 24])).first()
from sqlalchemy import and_, or_
ret5 = session.query(Tag).filter(and_(Tag.id > 1, Tag.title == "LOL")).first()
ret6 = session.query(Tag).filter(or_(Tag.id > 1, Tag.title == "LOL")).first()
ret7 = session.query(Tag).filter(or_(
    Tag.id>1,
    and_(Tag.id>3, Tag.title=="LOL")
)).all()

# 通配符
ret8 = session.query(Tag).filter(Tag.title.like("L%")).all()
ret9 = session.query(Tag).filter(~Tag.title.like("L%")).all()

# 限制
ret10 = session.query(Tag).filter(~Tag.title.like("L%")).all()[1:2]

# 排序
ret11 = session.query(Tag).order_by(Tag.id.desc()).all()  # 倒序
ret12 = session.query(Tag).order_by(Tag.id.asc()).all()  # 正序

# 分组
ret13 = session.query(Tag.test).group_by(Tag.test).all()

# 聚合函数
from sqlalchemy.sql import func
ret14 = session.query(
    func.max(Tag.id),
    func.sum(Tag.test),
    func.min(Tag.id)
).group_by(Tag.title).having(func.max(Tag.id > 22)).all()

# 连表
# print(ret15) 得到一个列表套元组 元组里是两个对象
# [(user_obj1, hobby_obj1), (user_obj2, hobby_obj2), ]
ret15 = session.query(UserInfo, Hobby).filter(UserInfo.hobby_id == Hobby.id).all()

# print(ret16) 得到列表里面是前一个对象，join相当于inner join
# [user_obj1, user_obj2, ]
ret16 = session.query(UserInfo).join(Hobby).all()

# 相当于inner join
# for i in ret16:
#     # print(i[0].name, i[1].title)
#     print(i.hobby.title)

# 指定isouter=True相当于left join
ret17 = session.query(Hobby).join(UserInfo, isouter=True).all()
ret17_1 = session.query(UserInfo).join(Hobby, isouter=True).all()

# 或者直接用outerjoin也是相当于left join
ret18 = session.query(Hobby).outerjoin(UserInfo).all()
ret18_1 = session.query(UserInfo).outerjoin(Hobby).all()
print(ret17)
print(ret17_1)
print(ret18)
print(ret18_1)




------------------------------------------------------------



#　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),
        Users.extra != ""
    )).all()


# 通配符，以e开头，不以e开头
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()

基于relationship的ForeignKey

# 4. 基于relationship的ForeignKey
# 添加
user_obj = UserInfo(name="提莫", hobby=Hobby(title="种蘑菇"))
session.add(user_obj)

hobby = Hobby(title="弹奏一曲")
hobby.user = [UserInfo(name="琴女"), UserInfo(name="妹纸")]
# hobby.user = [session.query(UserInfo).filter_by(id=1).first(), ]
session.add(hobby)
session.commit()

# 基于relationship的正向查询
user_obj_1 = session.query(UserInfo).first()
print(user_obj_1.name)
print(user_obj_1.hobby.title)

# 基于relationship的反向查询
hb = session.query(Hobby).first()
print(hb.title)
for i in hb.user:
    print(i.name)

session.close()

基于relationship的M2M

# 5. 基于relationship的M2M
# 添加
# 直接给中间表添加
book_obj = Book(title="Python源码剖析")
tag_obj = Tag(title="Python")
b2t = Book2Tag(book_id=book_obj.id, tag_id=tag_obj.id)
session.add_all([
    book_obj,
    tag_obj,
    b2t,
])
session.commit()

# 通过反向字段添加
book = Book(title="测试")
book.tags = [Tag(title="测试标签1"), Tag(title="测试标签2")]
# book.tags = [session.query(Tag).filter_by(id=1).first(), ]
session.add(book)
session.commit()

tag = Tag(title="LOL")
tag.books = [Book(title="大龙刷新时间"), Book(title="小龙刷新时间")]
session.add(tag)
session.commit()

# 基于relationship的正向查询
book_obj = session.query(Book).filter_by(id=4).first()
print(book_obj.title)
print(book_obj.tags)
# 基于relationship的反向查询
tag_obj = session.query(Tag).first()
print(tag_obj.title)
print(tag_obj.books)

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中的一下方法：

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="alex1")
session.add(obj1)

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

其他

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()

Flask-SQLAlchemy

flask和SQLAlchemy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

flask-migrate
python3 manage.py db init 初始化: 只执行一次
python3 manage.py db migrate 等同于makemigrations
python3 manage.py db upgrade 等同于 migrate
posted @ 2020-03-10 21:57  fwzzz  阅读(138)  评论(0)  编辑  收藏  举报