SQLAlchemy是一個基於Python實現的ORM框架。該框架創建在 DB API之上,使用關係對象映射進行數據庫操做,簡言之即是:將類和對象轉換成SQL,而後使用數據API執行SQL並獲取執行結果。html
安裝python
pip3 install sqlalchemy
SQLAlchemy自己沒法操做數據庫,其必須以來pymsql等第三方插件,Dialect用於和數據API進行交流,根據配置文件的不一樣調用不一樣的數據庫API,從而實現對數據庫的操做,如:mysql
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
1、利用原生SQL語句進行操做sql
利用原生SQL語句進行是一種操做方式,但其實日常咱們並不適用這種方式。數據庫
import time import threading import sqlalchemy from sqlalchemy import create_engine from sqlalchemy.engine.base import Engine engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/t1?charset=utf8", max_overflow=0, # 超過鏈接池大小外最多建立的鏈接 pool_size=5, # 鏈接池大小 pool_timeout=30, # 池中沒有線程最多等待的時間,不然報錯 pool_recycle=-1 # 多久以後對線程池中的線程進行一次鏈接的回收(重置) ) def task(arg): conn = engine.raw_connection() cursor = conn.cursor() cursor.execute( "select * from t1" ) result = cursor.fetchall() cursor.close() conn.close() for i in range(20): t = threading.Thread(target=task, args=(i,)) t.start()
#!/usr/bin/env python # -*- coding:utf-8 -*- import time import threading import sqlalchemy from sqlalchemy import create_engine from sqlalchemy.engine.base import Engine engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=0, pool_size=5) def task(arg): conn = engine.contextual_connect() with conn: cur = conn.execute( "select * from t1" ) result = cur.fetchall() print(result) for i in range(20): t = threading.Thread(target=task, args=(i,)) t.start()
#!/usr/bin/env python # -*- coding:utf-8 -*- import time import threading import sqlalchemy from sqlalchemy import create_engine from sqlalchemy.engine.base import Engine from sqlalchemy.engine.result import ResultProxy engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=0, pool_size=5) def task(arg): cur = engine.execute("select * from t1") result = cur.fetchall() cur.close() print(result) for i in range(20): t = threading.Thread(target=task, args=(i,)) t.start()
#!/usr/bin/env python # -*- coding:utf-8 -*- 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() # 查詢 # 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()
2、ORMflask
flask是輕量級框架,因此自己並不具有ORM。想要操做數據庫就必須配合着SQLAlchemy來使用。安全
注:SQLAlchemy建立的表默認引擎不是InnoDB,若想改爲InnoDB只要加一條參數便可session
class User(BaseModel): __table_args__ = { 'mysql_engine': 'InnoDB', 'mysql_charset': 'utf8' }
建立單表:多線程
#!/usr/bin/env python # -*- coding:utf-8 -*- 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'#表名,與Django不一樣的是,flask必須寫 id = Column(Integer, primary_key=True) name = Column(String(32), index=True, nullable=False) # email = Column(String(32), unique=True) # ctime = Column(DateTime, default=datetime.datetime.now) # extra = Column(Text, nullable=True) __table_args__ = ( # UniqueConstraint('id', 'name', name='uix_id_name'), # Index('ix_id_name', 'name', 'email'), ) def init_db(): """ 根據類建立數據庫表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超過鏈接池大小外最多建立的鏈接 pool_size=5, # 鏈接池大小 pool_timeout=30, # 池中沒有線程最多等待的時間,不然報錯 pool_recycle=-1 # 多久以後對線程池中的線程進行一次鏈接的回收(重置) ) Base.metadata.create_all(engine) def drop_db(): """ 根據類刪除數據庫表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超過鏈接池大小外最多建立的鏈接 pool_size=5, # 鏈接池大小 pool_timeout=30, # 池中沒有線程最多等待的時間,不然報錯 pool_recycle=-1 # 多久以後對線程池中的線程進行一次鏈接的回收(重置) ) Base.metadata.drop_all(engine) if __name__ == '__main__': drop_db() init_db()
建立多表(包含FK和M2M兩種可能):oracle
#!/usr/bin/env python # -*- coding:utf-8 -*- 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 from sqlalchemy.orm import relationship Base = declarative_base() # ##################### 單表示例 ######################### class Users(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String(32), index=True) age = Column(Integer, default=18) email = Column(String(32), unique=True) ctime = Column(DateTime, default=datetime.datetime.now) extra = Column(Text, nullable=True) __table_args__ = ( # UniqueConstraint('id', 'name', name='uix_id_name'), # Index('ix_id_name', 'name', 'extra'), ) class Hosts(Base): __tablename__ = 'hosts' id = Column(Integer, primary_key=True) name = Column(String(32), index=True) ctime = Column(DateTime, default=datetime.datetime.now) # ##################### 一對多示例 ######################### class Hobby(Base): __tablename__ = 'hobby' id = Column(Integer, primary_key=True) caption = Column(String(50), default='籃球') class Person(Base): __tablename__ = 'person' nid = Column(Integer, primary_key=True) name = Column(String(32), index=True, nullable=True) hobby_id = Column(Integer, ForeignKey("hobby.id"))#外鍵 # 與生成表結構無關,僅用於查詢方便,backref至關於Django的related_name hobby = relationship("Hobby", backref='pers') # ##################### 多對多示例 ######################### #與Django不一樣,flask中多對多的第三張表必須本身手動建立 class Server2Group(Base): __tablename__ = 'server2group' id = Column(Integer, primary_key=True, autoincrement=True) server_id = Column(Integer, ForeignKey('server.id')) group_id = Column(Integer, ForeignKey('group.id')) class Group(Base): __tablename__ = 'group' id = Column(Integer, primary_key=True) name = Column(String(64), unique=True, nullable=False) # 與生成表結構無關,僅用於查詢方便,secondary指的是第三張表的表名 servers = relationship('Server', secondary='server2group', backref='groups') class Server(Base): __tablename__ = 'server' id = Column(Integer, primary_key=True, autoincrement=True) hostname = Column(String(64), unique=True, nullable=False) def init_db(): """ 根據類建立數據庫表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超過鏈接池大小外最多建立的鏈接 pool_size=5, # 鏈接池大小 pool_timeout=30, # 池中沒有線程最多等待的時間,不然報錯 pool_recycle=-1 # 多久以後對線程池中的線程進行一次鏈接的回收(重置) ) Base.metadata.create_all(engine) def drop_db(): """ 根據類刪除數據庫表 :return: """ engine = create_engine( "mysql+pymysql://root:123@127.0.0.1:3306/s6?charset=utf8", max_overflow=0, # 超過鏈接池大小外最多建立的鏈接 pool_size=5, # 鏈接池大小 pool_timeout=30, # 池中沒有線程最多等待的時間,不然報錯 pool_recycle=-1 # 多久以後對線程池中的線程進行一次鏈接的回收(重置) ) Base.metadata.drop_all(engine) if __name__ == '__main__': drop_db() init_db()
基本增刪改查示例:
#!/usr/bin/env python # -*- coding:utf-8 -*- 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 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() # ################ 添加 ################ """ obj1 = Users(name="wupeiqi")#建立對象 session.add(obj1)#加入內存 #批量建立 session.add_all([ Users(name="wupeiqi"), Users(name="alex"), Hosts(name="c1.com"), ]) session.commit()#提交(不執行這步,上述操做都無效) """ # ################ 刪除 ################ """ session.query(Users).filter(Users.id > 2).delete()#刪除操做 session.commit()#提交 """ # ################ 修改 ################ """ #synchronize_session是用來講明相加時時數字類型的相加仍是字符串類型的相加 session.query(Users).filter(Users.id > 0).update({"name" : "099"}) session.query(Users).filter(Users.id > 0).update({Users.name: Users.name + "099"}, synchronize_session=False) session.query(Users).filter(Users.id > 0).update({"age": Users.age + 1}, synchronize_session="evaluate") session.commit()#提交 """ # ################ 查詢 ################ """ #filter_by的後面的括號直接寫字段=條件,相似Django。filter則需寫表名.字段==條件 r1 = session.query(Users).all() r2 = session.query(Users.name.label('xx'), Users.age).all() r3 = session.query(Users).filter(Users.name == "alex").all() r4 = session.query(Users).filter_by(name='alex').all() r5 = session.query(Users).filter_by(name='alex').first() #佔位符操做示例 r6 = session.query(Users).filter(text("id<:value and name=:name")).params(value=224, name='fred').order_by(Users.id).all() r7 = session.query(Users).from_statement(text("SELECT * FROM users where name=:name")).params(name='ed').all() """ session.close()#操做commit後,需將連接關閉
其餘經常使用的查詢操做(條件查詢、模糊查詢、排序、分組、連表、組合)
# 條件 ret = session.query(Users).filter_by(name='alex').all() 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() ret = session.query(Users).filter(Users.id.in_([1,3,4])).all() ret = session.query(Users).filter(~Users.id.in_([1,3,4])).all() ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name='eric'))).all() from sqlalchemy import and_, or_ 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 ret = session.query(Users).filter(Users.name.like('e%')).all() ret = session.query(Users).filter(~Users.name.like('e%')).all() # 限制 ret = session.query(Users)[1:2] # 排序 ret = session.query(Users).order_by(Users.name.desc()).all() ret = session.query(Users).order_by(Users.name.desc(), Users.id.asc()).all() # 分組 from sqlalchemy.sql import func ret = session.query(Users).group_by(Users.extra).all() ret = session.query( func.max(Users.id), func.sum(Users.id), func.min(Users.id)).group_by(Users.name).all() 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() # 連表 ret = session.query(Users, Favor).filter(Users.id == Favor.nid).all() ret = session.query(Person).join(Favor).all() ret = session.query(Person).join(Favor, isouter=True).all() # 組合 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()
基於scop-session建立鏈接能夠增長多線程操做的安全
#!/usr/bin/env python # -*- coding:utf-8 -*- 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) """ # 方式一:因爲沒法提供線程共享功能,全部在開發時要注意,在每一個線程中本身建立 session。 # from sqlalchemy.orm.session import Session # 本身具備操做數據庫的:'close', 'commit', 'connection', 'delete', 'execute', 'expire',..... session = SessionFactory() # print('原生session',session) # 操做 session.close() """ """ # 線程安全,基於本地線程實現每一個線程用同一個session # 特殊的:scoped_session中有原來方法的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' ) """ session = scoped_session(Session) # ############# 執行ORM操做 ############# obj1 = Users(name="alex1") session.add(obj1) # 提交事務 session.commit() # 關閉session session.remove()#咱們不同
連表查詢FK
#!/usr/bin/env python # -*- coding:utf-8 -*- 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='張三', hobby_id=3), Person(name='李四', hobby_id=4), ]) person = Person(name='張九', hobby=Hobby(caption='姑娘')) session.add(person) hb = Hobby(caption='人妖') hb.pers = [Person(name='文飛'), Person(name='博雅')] session.add(hb) session.commit() """ # 使用relationship正向查詢 """ v = session.query(Person).first() print(v.name) print(v.hobby.caption) """ # 使用relationship反向查詢 """ v = session.query(Hobby).first() print(v.caption) print(v.pers) """ session.close() 基於relationship操做ForeignKey
連表查詢M2M
#!/usr/bin/env python # -*- coding:utf-8 -*- 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組'), Group(name='B組'), ]) session.commit() s2g = Server2Group(server_id=1, group_id=1) session.add(s2g) session.commit() gp = Group(name='C組') 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組'),Group(name='G組')] session.add(ser) session.commit() """ # 使用relationship正向查詢 """ v = session.query(Group).first() print(v.name) print(v.servers) """ # 使用relationship反向查詢 """ v = session.query(Server).first() print(v.hostname) print(v.groups) """ session.close() 基於relationship操做m2m
關聯子查詢
#!/usr/bin/env python # -*- coding:utf-8 -*- 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() # 關聯子查詢 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` """ # 原生SQL """ # 查詢 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() 其餘
flask-sqlalchemy 是在 sqlalchemy 的基礎上,提供了一些經常使用的工具,並預設了一些默認值,幫助你=咱們更輕鬆地完成常見任務。
flask-sqlalchemy 用起來比直接用 sqlalchemy 方便、省事,不過有些高級一點的功能若是不瞭解 sqlalchemy 的話會用很差。
下面咱們來詳述flask-sqlalchemy的操做方法
# 1. 引入Flask-SQLAlchemy from flask_sqlalchemy import SQLAlchemy # 2.實例化一個SQLAlchemy對象 """ 實例化方式一: 在函數裏面,SQLAlchemy(app) #若是想在其餘地方使用這種方式就很差使了,因此推薦使用方式二 """ #方式二 db = SQLAlchemy()#在全局中建立實例化 db.init_app(app) #在函數中調用init_app方法吧app放進去了 # 3. 導入models中的表 from .models import * #4. 在須要建立表的文件中導入db.model,全部的表再建立時繼承db.model #5. 藉助Flask-Migrate組件來完成表的生成 """ 安裝 pip3 install Flask-Migrate # 5.1 導入 from flask_migrate import Migrate, MigrateCommand from app import create_app, db app = create_app() manager = Manager(app) # 5.2 建立migrate示例 migrate = Migrate(app, db) # 5.3 建立db命令 manager.add_command('db', MigrateCommand) """ #上述代碼完畢後,咱們就能夠在命令終端敲入相似Django的終端代碼在數據庫生成表了 python manage.py db init#只需初次建立庫時敲 #如下兩行代碼在每次對數據庫中的表進行修改時都需執行(數據庫遷移) python manage.py db migrate#功能與Django的python manage.py db makemigrations相同 python manage.py db upgrade#功能與Django的python manage.py db migrate相同 #之後執行SQL時,咱們就能夠實現與Django相似的ORM操做了: #方式一: result = db.session.query(models.User.id,models.User.name).all() db.session.remove() #方式二: result = models.Users.query.all()