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
-- 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
)
连接数据库
执行原生SQL
# by gaoxin
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
# by gaoxin
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
# by gaoxin
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
# by gaoxin
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)
# by gaoxin
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
# by gaoxin
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": "王者毒药"})
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 分组查询在严格模式下 一般指定聚合函数
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()
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)
复制代码
标签:__,Tag,title,介绍,session,query,SQLAlchemy,id
From: https://www.cnblogs.com/mengdie1978/p/17400765.html