SQLAlchemy查询

SQLAlchemy查询


结果查询:

  •  1 from databases.wechat import User
     2 from config import session
     3 
     4 
     5 def search():
     6     result = session.query(User).all()  # 查询所有
     7     result = result[0]  # 索引取值
     8     print(result.username)  # 对象属性查询
     9     session.query(User).first()  # 查询第一条
    10 
    11     session.query(User).filter(User.username == 'bob').all()  # 按条件查询所有
    12 
    13 
    14 if __name__ == '__main__':
    15     search()
  • all() :
    • 查询所有
    • 返回一个列表对象
  • first()
    • 查询第一个符合条件的对象
    • 返回一个对象
  • 索引取值
    • 相当于列表取值
    • 返回一个列表内的值(对象)
  • 条件查询:
    • 用fillter方法来增加查询条件
  • 属性查询:
    • 直接该属性的对象对其进行普通的类属性的调用即可

条件查询

  •  1 from databases.wechat import User
     2 from config import session
     3 
     4 
     5 def search():
     6     # query接收一个查询范围,fillter增加查询条件的约束
     7     result = session.query(User.username).filter(User.username=='bob').all()  # [('bob',)]
     8     result = session.query(User.username).filter_by(username='bob').all()  # [('bob',)]
     9     """
    10     fillter和filter_by
    11     fillter可以进行比较运算(==, >, < ...)来对条件进行灵活的运用, 不同的条件用','(逗号)分割
    12     fillter_by只能指定参数传参来获取查询结果
    13     """
    14 
    15 
    16 
    17 if __name__ == '__main__':
    18     search()
    query接收一个查询范围多个范围用逗号隔开,fillter增加查询条件的约束
    fillter和filter_by
    fillter可以进行比较运算(==, >, < ...)来对条件进行灵活的运用, 不同的条件用','(逗号)分割
    fillter_by只能指定参数传参来获取查询结果

模糊查询

  •  1 from databases.wechat import User
     2 from config import session
     3 
     4 
     5 def search():
     6     # like里面传入一个字符串,不确定的位置用%代替即可
     7     result = session.query(User.username).filter(User.username.like('b%')).all()  # [('bob',)]
     8     # notlike取like的取反结果
     9     result = session.query(User.username).filter(User.username.notlike('b%')).all()
    10     # is_ 相当于 ==
    11     result = session.query(User.username).filter(User.username.is_(None)).all()
    12     result = session.query(User.username).filter(User.username == None).all()
    13     # isnot 相当于 !=
    14     result = session.query(User.username).filter(User.username.isnot(None)).all()
    15     result = session.query(User.username).filter(User.username != None).all()
    16     # in_传入一个可迭代对象,对前面的username进行约束, notin_ 和in_取反
    17     result = session.query(User.username).filter(User.username.in_(['bob', 'ivy1'])).all()
    18     result = session.query(User.username).filter(User.username.notin_(['bob', 'ivy1'])).all()
    19     # limit 限制数量查询, limit里传入一个整型来约束查看的数量, 当limit里面的参数大于实例表中的数量时,会返回所有的查询结果
    20     result = session.query(User.username).limit(6).all()
    21     # offset 偏移量查询,offset中传入一个整型,从表中的该位置开始查询,offset可以和limit混用来进行限制
    22     result = session.query(User.username).offset(1).all()
    23     result = session.query(User.username).offset(1).limit(6).all()
    24     # slice 切片查询,遵循左闭右开原则,可以和offset、limit混用
    25     result = session.query(User.username).slice(1, 3).offset(2).limit(6).all()
    26     # one 获取查询对象的一条,且查询的结果有且仅有一条,但查询结果多了的时候会报错
    27     result = session.query(User.username).filter_by(username='bob').one()
    28 
    29 
    30 
    31 
    32 if __name__ == '__main__':
    33     search()
  • like里面传入一个字符串,不确定的位置用%代替即可
  • notlike取like的取反结果
  • is_ 相当于 ==
  • isnot 相当于 !=
  • in_传入一个可迭代对象,对前面的username进行约束, notin_ 和in_取反
  • limit 限制数量查询, limit里传入一个整型来约束查看的数量, 当limit里面的参数大于实例表中的数量时,会返回所有的查询结果
  • offset 偏移量查询,offset中传入一个整型,从表中的该位置开始查询,offset可以和limit混用来进行限制
  • slice 切片查询,遵循左闭右开原则,可以和offset、limit混用
  • one 获取查询对象的一条,且查询的结果有且仅有一条,但查询结果多了的时候会报错
  •  1 from databases.wechat import User
     2 from config import session
     3 from sqlalchemy import desc
     4 
     5 def search():
     6     # 升序排列
     7     result = session.query(User.username, User.id).order_by(User.id).all()
     8     # 降序排列
     9     result = session.query(User.username, User.id).order_by(desc(User.id)).all()
    10     # 结合filter查询
    11     result = session.query(User.username, User.id).order_by(User.id).filter(User.username != 'bob').all()
    12     result = session.query(User.username, User.id).filter(User.username != 'bob').order_by(User.id).all()
    13 
    14 
    15 
    16 
    17 if __name__ == '__main__':
    18     search()

    排序查询,排序查询可结合filter、limit、slice等综合运用

 

聚合函数

  •  1 from databases.wechat import User
     2 from databases.config import session
     3 from sqlalchemy import func, extract
     4 
     5 
     6 def search():
     7     # count
     8     result = session.query(User.password, func.count(User.id)).group_by(User.password).all()
     9     # sum
    10     result = session.query(User.password, func.sum(User.id)).group_by(User.password).all()
    11     # max
    12     result = session.query(User.password, func.max(User.id)).group_by(User.password).all()
    13     # min
    14     result = session.query(User.password, func.min(User.id)).group_by(User.password).all()
    15     # having
    16     result = session.query(User.password, func.count(User.id)).group_by(User.password).having(func.count(User.id) > 1).all()
    17     # label extract
    18     result = session.query(
    19         extract('minute',User.create_time).label('minute'),
    20         func.count(User.id)
    21     ).group_by('minute')
    22     # 想当于-->SELECT EXTRACT(minute FROM user.create_time) AS minute, count(user.id) AS count_1 FROM user GROUP BY minute
    23 
    24 if __name__ == '__main__':
    25     search()

多表查询

  •  1 from databases.config import Base
     2 from sqlalchemy import Column, Integer, String, DateTime, Boolean, ForeignKey
     3 from datetime import datetime
     4 
     5 class User(Base):
     6     __tablename__ = 'user'
     7     id = Column(Integer, primary_key=True, autoincrement=True)
     8     username = Column(String(20))
     9     password = Column(String(20))
    10     create_time = Column(DateTime, default=datetime.now())
    11     is_login = Column(Boolean, default=False, nullable=False)
    12 
    13 
    14 class UserDetails(Base):
    15     __tablename__ = 'userdetails'
    16     id = Column(Integer, primary_key=True, autoincrement=True)
    17     id_card = Column(Integer, nullable=True, unique=True)
    18     last_login = Column(DateTime)
    19     login_num = Column(Integer, default=0)
    20     user_id = Column(Integer, ForeignKey('user.id'))  # user.id 表名+属性名
    21 
    22 
    23 
    24 if __name__ == '__main__':
    25     Base.metadata.create_all()

     新建表

  •  1 from databases.wechat import User, UserDetails
     2 from databases.config import session
     3 
     4 
     5 def search():
     6     # 笛卡尔连接
     7     result = session.query(User, UserDetails)
     8     # SELECT user.id AS user_id, user.username AS user_username, user.password AS user_password, user.create_time AS user_create_time, user.is_login AS user_is_login, userdetails.id AS userdetails_id, userdetails.id_card AS userdetails_id_card, userdetails.last_login AS userdetails_last_login, userdetails.login_num AS userdetails_login_num, userdetails.user_id AS userdetails_user_id FROM user, userdetails
     9     # 加filter查询
    10     result = session.query(User, UserDetails).filter(UserDetails.id==User.id).all()
    11     result = session.query(User.username, UserDetails.id_card).join(UserDetails, UserDetails.id==User.id).filter(UserDetails.id==User.id)
    12     # SELECT user.username AS user_username, userdetails.id_card AS userdetails_id_card FROM user INNER JOIN userdetails ON userdetails.id = user.id WHERE userdetails.id = user.id
    13 
    14 
    15 
    16 
    17 
    18 if __name__ == '__main__':
    19     search()

原生sql查询

  •  1 from databases.config import session
     2 
     3 
     4 def search():
     5     sql = 'select * from user '
     6     result = session.execute(sql)
     7     result.fetchone()
     8     result.fetchmany()
     9     result.fetchone()
    10 
    11 
    12 
    13 
    14 if __name__ == '__main__':
    15     search()
原文地址:https://www.cnblogs.com/ivy-blogs/p/10824606.html