1.介紹
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
pip3 install sqlalchemy
組成部分：python
Engine，框架的引擎 Connection Pooling ，數據庫鏈接池 Dialect，選擇鏈接數據庫的DB API種類 Schema/Types，架構和類型 SQL Exprression Language，SQL表達式語言
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
django中如何反向生成modelssql
python manage.py inspectdb > app/models.py
2.簡單使用（能建立表，刪除表，不能修改表）
修改表：在數據庫添加字段，類對應上數據庫
1執行原生sql（不經常使用）django
import time
import threading
import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy.engine.base import Engine
engine = create_engine(
"mysql+pymysql://root:123456@127.0.0.1:3306/test?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 app01_book"
)
result = cursor.fetchall()
print(result)
cursor.close()
conn.close()
for i in range(20):
t = threading.Thread(target=task, args=(i,))
t.start()
2 orm使用flask
models.py安全
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' # 數據庫表名稱
id = Column(Integer, primary_key=True) # id 主鍵
name = Column(String(32), index=True, nullable=False) # name列，索引，不可爲空
# email = Column(String(32), unique=True)
#datetime.datetime.now不能加括號，加了括號，之後永遠是當前時間
# ctime = Column(DateTime, default=datetime.datetime.now)
# extra = Column(Text, nullable=True)
__table_args__ = (
# UniqueConstraint('id', 'name', name='uix_id_name'), #聯合惟一
# Index('ix_id_name', 'name', 'email'), #索引
)
def init_db():
"""
根據類建立數據庫表
:return:
"""
engine = create_engine(
"mysql+pymysql://root:123456@127.0.0.1:3306/aaa?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:123456@127.0.0.1:3306/aaa?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()
app.pysession
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from models import Users
#"mysql+pymysql://root@127.0.0.1:3306/aaa"
engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/aaa", max_overflow=0, pool_size=5)
Connection = sessionmaker(bind=engine)
# 每次執行數據庫操做時，都須要建立一個Connection
con = Connection()
# ############# 執行ORM操做 #############
obj1 = Users(name="lqz")
con.add(obj1)
# 提交事務
con.commit()
# 關閉session，實際上是將鏈接放回鏈接池
con.close()
3.一對多關係
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指的是tablename而不是類名，uselist=False
hobby_id = Column(Integer, ForeignKey("hobby.id"))
# 跟數據庫無關，不會新增字段，只用於快速鏈表操做
# 類名，backref用於反向查詢
hobby=relationship('Hobby',backref='pers')
4.多對多關係
class Boy2Girl(Base):
__tablename__ = 'boy2girl'
id = Column(Integer, primary_key=True, autoincrement=True)
girl_id = Column(Integer, ForeignKey('girl.id'))
boy_id = Column(Integer, ForeignKey('boy.id'))
class Girl(Base):
__tablename__ = 'girl'
id = Column(Integer, primary_key=True)
name = Column(String(64), unique=True, nullable=False)
class Boy(Base):
__tablename__ = 'boy'
id = Column(Integer, primary_key=True, autoincrement=True)
name = Column(String(64), unique=True, nullable=False)
# 與生成表結構無關，僅用於查詢方便,放在哪一個單表中均可以
girl = relationship('Girl', secondary='boy2girl', backref='boys')
5.操做數據表
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from models import Users
engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/aaa", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
# 每次執行數據庫操做時，都須要建立一個session
session = Session()
# ############# 執行ORM操做 #############
obj1 = Users(name="lqz")
session.add(obj1)
# 提交事務
session.commit()
# 關閉session
session.close()
6.基於scoped_session實現線程安全
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)
"""
# 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'
)
"""
#scoped_session類並無繼承Session,可是卻又它的全部方法
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.close()
7.基本增刪查改
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")
session.add(obj1)
session.add_all([
Users(name="lqz"),
Users(name="egon"),
Hosts(name="c1.com"),
])
session.commit()
"""
# ################ 刪除 ################
"""
session.query(Users).filter(Users.id > 2).delete()
session.commit()
"""
# ################ 修改 ################
"""
#傳字典
session.query(Users).filter(Users.id > 0).update({"name" : "lqz"})
#相似於django的F查詢，這個後面必須配合synchronize_session，
#若是是字符串就用False，若是是數字就用#evaluata
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()
"""
# ################ 查詢 ################
"""
r1 = session.query(Users).all()
#只取age列，把name重命名爲xx
r2 = session.query(Users.name.label('xx'), Users.age).all()
#filter傳的是表達式，filter_by傳的是參數
r3 = session.query(Users).filter(Users.name == "lqz").all()
r4 = session.query(Users).filter_by(name='lqz').all()
r5 = session.query(Users).filter_by(name='lqz').first()
#:value 和:name 至關於佔位符，用params傳參數
r6 = session.query(Users).filter(text("id<:value and name=:name")).params(value=224, name='fred').order_by(Users.id).all()
#自定義查詢sql
r7 = session.query(Users).from_statement(text("SELECT * FROM users where name=:name")).params(name='ed').all()
"""
#增，刪，改都要commit()
session.close()
8.經常使用操做
# 條件
ret = session.query(Users).filter_by(name='lqz').all()
#表達式，and條件鏈接
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()
#注意下劃線
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()
#二次篩選
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條件，and_包裹的都是and條件
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開頭，不以e開頭
ret = session.query(Users).filter(Users.name.like('e%')).all()
ret = session.query(Users).filter(~Users.name.like('e%')).all()
# 限制，用於分頁，區間
ret = session.query(Users)[1:2]
# 排序，根據name降序排列（從大到小）
ret = session.query(Users).order_by(Users.name.desc()).all()
#第一個條件重複後，再按第二個條件升序排
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()
#分組以後取最大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篩選
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（默認用forinkey關聯）
ret = session.query(Users, Favor).filter(Users.id == Favor.nid).all()
#join表，默認是inner join
ret = session.query(Person).join(Favor).all()
#isouter=True 外連，表示Person left join Favor，沒有右鏈接，反過來便可
ret = session.query(Person).join(Favor, isouter=True).all()
#打印原生sql
aa=session.query(Person).join(Favor, isouter=True)
print(aa)
# 本身指定on條件（連表條件）,第二個參數，支持on多個條件，用and_,同上
ret = session.query(Person).join(Favor,Person.id==Favor.id, isouter=True).all()
# 組合（瞭解）UNION 操做符用於合併兩個或多個 SELECT 語句的結果集
#union和union all的區別？
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()
9.執行原生sql
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":'lqz'})
session.commit()
print(cursor.lastrowid)
session.close()
10.一對多
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)
#添加二
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)
"""
#方式一，本身鏈表
# person_list=session.query(models.Person.name,models.Hobby.caption).join(models.Hobby,isouter=True).all()
person_list=session.query(models.Person,models.Hobby).join(models.Hobby,isouter=True).all()
for row in person_list:
# print(row.name,row.caption)
print(row[0].name,row[1].caption)
#方式二：經過relationship
person_list=session.query(models.Person).all()
for row in person_list:
print(row.name,row.hobby.caption)
#查詢喜歡姑娘的全部人
obj=session.query(models.Hobby).filter(models.Hobby.id==1).first()
persons=obj.pers
print(persons)
session.close()
11.多對多
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from sql.models import Girl,Boy,Boy2Girl
engine = create_engine("mysql+pymysql://root:@127.0.0.1:3307/flask-test?charset=utf8", max_overflow=0, pool_size=5)
Session = sessionmaker(bind=engine)
session = Session()
# 添加
'''
session.add_all([
Girl(name='g_com1'),
Girl(name='g2.com1'),
Boy(name='A組1'),
Boy(name='B組2'),
])
session.commit()
s2g = Boy2Girl(girl_id=2, boy_id =2)
session.add(s2g)
session.commit()
gp = Boy(name='C組')
gp.girl = [Girl(name='c3.com'),Girl(name='c4.com')]
session.add(gp)
session.commit()
ser = Girl(name='c6.com')
ser.boys = [Boy(name='F組pp'),Boy(name='G組ll')]
session.add(ser)
session.commit()
'''
"""
# 使用relationship正向查詢
"""
'''
v = session.query(Boy).first()
print(v.name)
print(v.girl)
'''
# 使用relationship反向查詢
'''
v = session.query(Girl).first()
print(v.name)
print(v.boys)
'''
session.close()
12.其它
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:correlate(Group)表示跟Group表作關聯，as_scalar至關於對該sql加括號，用於放在後面當子查詢
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`
"""
'''
select * from tb where id in [select id from xxx];
select id,
name,
#必須保證這次查詢只有一個值
(select max(id) from xxx) as mid
from tb
例如，第三個字段只能有一個值
id name mid
1 lqz 1，2 不合理
2 egon 2
'''
'''
成績表：
id sid cid score
1 1 物理 99
2 1 化學 88
3 2 物理 95
學生表：
id name 每一個學生總分數
1 xx 88
2 yy 77
select id，name,
(select avr(score) from 成績表 where 成績表.sid=學生表.id) as x
from 學生表
subqry = session.query(func.count(成績表.scort).label("sc")).filter(學生表.id == 成績表.sid).correlate(學生表).as_scalar()
result = session.query(學生表.name, subqry)
'''
# 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()
13.Flask-SQLAlchemy
flask和SQLAchemy的管理者，經過他把他們作鏈接架構
db = SQLAlchemy() - 包含配置 - 包含ORM基類 - 包含create_all - engine - 建立鏈接
離線腳本，建立表
詳見代碼
flask-migrate
python3 manage.py db init 初始化：只執行一次
python3 manage.py db migrate 等同於 makemigartions
python3 manage.py db upgrade 等同於migrate
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