### group_by：
根據某個字段進行分組。比如想要根據性別進行分組，來統計每個分組分別有多少人

### having：

having是對查找結果進一步過濾。比如只想要看未成年人的數量，那麽可以首先對年齡進行分組統計人數，然後再對分組進行having過濾。示例代碼如下：

 1 # coding:utf-8
 2 # Author: liangjun.chen
 3 
 4 from datetime import datetime
 5 from sqlalchemy import create_engine, Column, Integer, String, Enum, func
 6
 
 
 7 from sqlalchemy.ext.declarative import declarative_base
 8 from sqlalchemy.orm import sessionmaker, relationship, backref
 9 
10 HOSTNAME = ‘127.0.0.1‘
11 PORT = 3306
12 DATABASE = ‘sqlalchemy_first‘
13 USERNAME = ‘root‘
14 PASSWORD = ‘123456‘
15 
16 DB_URI = ‘mysql+pymysql://{username}:{password}@{host}:{port}/{dbname}?charset=utf8
 
‘.format(
17         username=USERNAME, password=PASSWORD, host=HOSTNAME, port=PORT, dbname=DATABASE
18 )
19 engine = create_engine(DB_URI)
20 Base = declarative_base(engine)
21 Session = sessionmaker(engine)
22 session = Session()
23 
24 
25 
26 class User(Base):
27     __tablename__ = ‘user‘
28     id = Column(Integer, primary_key=True, autoincrement=True)
 
29     username = Column(String(50), nullable=False)
30     age = Column(Integer, default=0)
31     gender = Column(Enum(‘male‘, ‘female‘, "secret"), default=‘male‘)
32 
33     def __repr__(self):
34         return "User<{}>".format(self.username)
35 # Base.metadata.drop_all()
36 # Base.metadata.create_all()
37 #
38 # user = User(username=‘saber‘, age=17, gender=‘male‘)
39 # user2 = User(username=‘saber2‘, age=18, gender=‘male‘)
40 # user3 = User(username=‘saber3‘, age=18, gender=‘female‘)
41 # user4 = User(username=‘saber4‘, age=19, gender=‘female‘)
42 # user5 = User(username=‘saber5‘, age=19, gender=‘female‘)
43 #
44 # session.add_all([user, user2, user3, user4, user5])
45 # session.commit()
46 
47 # group_by
48 
49 users = session.query(User.age, func.count(User.id)).group_by(User.age)
50 print users.all()
51 
52 # having
53 users = session.query(User.age, func.count(User.id)).group_by(User.age).having(User.age>18).all()
54 print users

【Flask】Sqlalchemy group_by having