SQLAlchemy介绍

SQLAlchemy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。

补充：什么是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

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　　-- SQL Expression Language SQL表达式语言

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。

# 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

不同的数据库API

from sqlalchemy import create_engine

engine = create_engine(
    "mysql+pymysql://root:[email protected]:3306/code_record?charset=utf8",
    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
)

链接数据库

执行原生SQL

from sqlalchemy import create_engine
engine = create_engine(
    "mysql+pymysql://root:[email protected]:3306/code_record?charset=utf8",
    max_overflow=0,
    pool_size=5,
)

def test():
    cur = engine.execute("select * from Course")
    result = cur.fetchall()
    print(result)
    cur.close()

if __name__ == '__main__':
    test()
# [(1, '生物', 1), (2, '体育', 2), (3, '物理', 1)]

engine.execute

ORM

一，创建表

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:[email protected]:3306/code_record?charset=utf8",)

Base = declarative_base()


class UserInfo(Base):
    __tablename__ = "user_info"

    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)

    __table_args__ = (
        UniqueConstraint("id", "name", name="uni_id_name"),
        Index("name", "email")
    )


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


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



if __name__ == '__main__':
    create_db()

单表的创建

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:[email protected]:3306/code_record?charset=utf8",)

Base = declarative_base()


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

    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)
    # FK字段的建立
    hobby_id = Column(Integer, ForeignKey("hobby.id"))
    # 不生成表结构 方便查询使用
    hobby = relationship("Hobby", backref="user")

    __table_args__ = (
        UniqueConstraint("id", "name", name="uni_id_name"),
        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()

一对多的创建

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:[email protected]:3306/code_record?charset=utf8",)

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 仅用于查询方便
    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()

多对多的创建

二，对数据库表的操作（增删改查）

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


ENGINE = create_engine("mysql+pymysql://root:[email protected]:3306/code_record?charset=utf8",)

Session = sessionmaker(bind=ENGINE)

# 每次执行数据库操作的时候，都需要创建一个session

# 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()

scoped_session

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:[email protected]:3306/code_record?charset=utf8",)

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

# ============基础查询============
# ret1 = session.query(Tag).all()
# ret2 = session.query(Tag).filter(Tag.title == "Python").all()
# 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": "王者农药"})
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()

基本的增删改查

# 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
ret15 = session.query(UserInfo, Hobby).filter(UserInfo.hobby_id == Hobby.id).all()
# print(ret15) 得到一个列表套元组 元组里是两个对象
ret16 = session.query(UserInfo).join(Hobby).all()
# print(ret16) 得到列表里面是前一个对象
# 相当于inner join
# for i in ret16:
#     # print(i[0].name, i[1].title)
#     print(i.hobby.title)
ret17 = session.query(Hobby).join(UserInfo, isouter=True).all()
ret17_1 = session.query(UserInfo).join(Hobby, isouter=True).all()
ret18 = session.query(Hobby).outerjoin(UserInfo).all()
ret18_1 = session.query(UserInfo).outerjoin(Hobby).all()
# 相当于left join
print(ret17)
print(ret17_1)
print(ret18)
print(ret18_1)

常用操作

# 基于relationship的FK
# 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")]
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FK

# 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()

#  上面有坑哦~~~~
book = Book(title="测试")
book.tags = [Tag(title="测试标签1"), Tag(title="测试标签2")]
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relationship的M2M

Python SQLAlchemy

SQLAlchemy介绍

连接数据库

执行原生SQL

ORM

一，创建表

二，对数据库表的操作（增删改查）

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