SQLAlchemy

一、SQLAlchemy介绍

QLAlchemy是一个基于Python的ORM框架。该框架是建立在DB-API之上,使用关系对象映射进行数据库操作。
简而言之就是,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。

什么是DB-API?
DB-API是Python的数据库接口规范。

在没有DB-API之前,各数据库之间的应用接口非常混乱,实现各不相同,
项目需要更换数据库的时候,需要做大量的修改,非常不方便,DB-API就是为了解决这样的问题。



pip install sqlalchemy

组成部分:
  -- engine,框架的引擎
  -- connection pooling 数据库连接池
  -- Dialect 选择链接数据库的DB-API种类(实际选择哪个模块链接数据库)
  -- Schema/Types 架构和类型
  -- SQL Expression Language SQL表达式语言

 

二、连接数据库

SQLAlchemy 本身无法操作数据库,其必须依赖遵循DB-API规范的三方模块,
Dialect 用于和数据API进行交互,根据配置的不同调用不同数据库API,从而实现数据库的操作。

下面是不同数据库的API:

# 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...]

 

连接数据库

from sqlalchemy import create_engine


# create_engine就是去建立连接,相当于我们pymsql建立连接的时候 conn= pymysql.connect(...)
conn = create_engine(
    "mysql+pymysql://root:123abc@127.0.0.1:3306/数据库名?charset=utf8mb4",
    max_overflow=0,   # 超过连接池大小外最多创建的连接数
    pool_size=5,      # 连接池大小
    pool_timeout=30,  # 连接池中没有线程最多等待时间,否则报错
    pool_recycle=-1,  # 多久之后对连接池中的连接进行回收(重置)-1不回收
)

 

三、执行原生SQL

from sqlalchemy import create_engine
conn = create_engine(
    "mysql+pymysql://root:123abc@127.0.0.1:3306/test?charset=utf8mb4",
    max_overflow=0,
    pool_size=5,
)

def test():
    ret = conn.execute("select * from MyTest")
    result = ret.fetchall()
    print(result)
    ret.close()

if __name__ == '__main__':
    test()

 

四、ORM

1、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()
1. 创建单表
# 2. 创建一对多的表
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()
2. 创建一对多的表
# 3. 创建多对多的表
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()
3. 创建多对多的表
from sqlalchemy import create_engine, ForeignKey, UniqueConstraint, Index
from sqlalchemy import Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, scoped_session
from sqlalchemy.orm import relationship
from sqlalchemy import Index, UniqueConstraint

conn = create_engine(
    "mysql+pymysql://root:123abc@127.0.0.1:3306/mytest?charset=utf8mb4",
    max_overflow=0,  # 超过连接池大小外最多创建的连接数
    pool_size=5,  # 连接池大小
    pool_timeout=30,  # 连接池中没有线程最多等待时间,否则报错
    pool_recycle=-1,  # 多久之后对连接池中的连接进行回收(重置)-1不回收
)

Base = declarative_base()


class Book(Base):
    __tablename__ = 'book'

    id = Column(Integer, primary_key=True)
    title = Column(String(64), nullable=False)
    publisher_id = Column(Integer, ForeignKey('publisher.id'))
    publisher = relationship('Publisher', backref='books')
    tags = relationship('Tag', backref='books', secondary='book2tag')

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

    def __repr__(self):
        return self.title


class Publisher(Base):
    __tablename__ = 'publisher'

    id = Column(Integer, primary_key=True)
    title = Column(String(64), nullable=False)

    def __repr__(self):
        return self.title


class Tag(Base):
    __tablename__ = 'tag'

    id = Column(Integer, primary_key=True)
    title = Column(String(64), nullable=False)

    def __repr__(self):
        return self.title


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():
    # metadata.create_all创建所有表
    Base.metadata.create_all(conn)


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


# 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_factory = sessionmaker(bind=conn)
# 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_factory)
# 实例化(相当于实现了一个单例模式)
session = Session()
# session2 = Session() --> session is session2


# 下面这种情况
# session_factory = sessionmaker(bind=conn)
# session3 = session_factory()
# session4 = session_factory()
# session3 is not session4


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

    # publisher_obj = Publisher(title='xxx出版社')
    # book_obj = Book(title='时间简史', publisher=publisher_obj)
    # tag_obj1 = Tag(title='python')
    # tag_obj2 = Tag(title='go')
    # tag_obj3 = Tag(title='linux')
    # session.add(publisher_obj)
    # session.add(book_obj)
    # session.add_all([tag_obj1, tag_obj2, tag_obj3])
    # session.commit()
    # session.close()

    # ret1 = session.query(Tag).filter(Tag.id==1).first()
    # ret2 = session.query(Tag).filter_by(id=2).first()
    # print(ret1)
    # print(ret2)

    # session.query(Tag).filter_by(id=2).update({"title": 'golang'})
    # tag_obj = Tag(title='heihei2')
    # tag_obj.books = [session.query(Book).filter_by(id=1).first()]
    # session.add(tag_obj)
    # session.commit()

    # book_obj = Book(title='狗屎仔',
    #                 publisher_id=1,
    #                 tags=[session.query(Tag).filter_by(id=1).first(), session.query(Tag).filter_by(id=2).first()])
    # session.add(book_obj)
    # session.commit()

    # ret = session.query(Book, Publisher).filter(Book.publisher_id==Publisher.id).all()
    # ret = session.query(Book).join(Publisher).all()
    # ret = session.query(Book).join(Publisher, isouter=True).all()
    ret = session.query(Book).outerjoin(Publisher).all()
    print(ret)
4. 完整的Demo

 

2、对数据库表的操作(增删改查)

# 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()
1. scoped_session

 

# 2. 基本增删改查
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()
2. 基本增删改查

 

# 3. 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)
3. 常用操作

 

# 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()
4. 基于relationship的ForeignKey

 

# 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)
5. 基于relationship的M2M

 

posted @ 2019-01-03 08:43  我用python写Bug  阅读(4963)  评论(2编辑  收藏  举报