SQLAlchemy ORM-过滤运算符

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📜 SQLAlchemy ORM-过滤运算符

📅 最后修改于: 2020-11-27 07:47:27 🧑 作者: Mango

现在，我们将学习过滤器操作及其相应的代码和输出。

等于

常用的运算符是==，它应用条件检查相等性。

result = session.query(Customers).filter(Customers.id == 2)

for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

SQLAlchemy将发送以下SQL表达式-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.id = ?

上面代码的输出如下-

ID: 2 Name: Komal Pande Address: Banjara Hills Secunderabad Email: komal@gmail.com

不等于

用于不等于的运算符是！=，它提供了不等于条件。

result = session.query(Customers).filter(Customers.id! = 2)

for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

最终的SQL表达式为-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.id != ?

以上代码行的输出如下-

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: ravi@gmail.com
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: nath@gmail.com
ID: 4 Name: S.M.Krishna Address: Budhwar Peth, Pune Email: smk@gmail.com

喜欢

like()方法本身为SELECT表达式中的WHERE子句生成LIKE标准。

result = session.query(Customers).filter(Customers.name.like('Ra%'))
for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

上面的SQLAlchemy代码等效于以下SQL表达式-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.name LIKE ?

上面代码的输出是-

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: ravi@gmail.com
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: nath@gmail.com

在

此运算符检查列值是否属于列表中的项目集合。它由in_()方法提供。

result = session.query(Customers).filter(Customers.id.in_([1,3]))
for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

在这里，由SQLite引擎评估的SQL表达式如下-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.id IN (?, ?)

上面代码的输出如下-

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: ravi@gmail.com
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: nath@gmail.com

和

通过将多个逗号分隔的条件放入过滤器中或使用如下所示的and_()方法，可以生成此连接-

result = session.query(Customers).filter(Customers.id>2, Customers.name.like('Ra%'))
for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

from sqlalchemy import and_
result = session.query(Customers).filter(and_(Customers.id>2, Customers.name.like('Ra%')))

for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

以上两种方法都导致类似的SQL表达式-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.id > ? AND customers.name LIKE ?

以上代码行的输出是-

ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: nath@gmail.com

要么

此连接通过or_()方法实现。

from sqlalchemy import or_
result = session.query(Customers).filter(or_(Customers.id>2, Customers.name.like('Ra%')))

for row in result:
   print ("ID:", row.id, "Name: ",row.name, "Address:",row.address, "Email:",row.email)

结果，SQLite引擎得到以下等效的SQL表达式-

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers
WHERE customers.id > ? OR customers.name LIKE ?

上面代码的输出如下-

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: ravi@gmail.com
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: nath@gmail.com
ID: 4 Name: S.M.Krishna Address: Budhwar Peth, Pune Email: smk@gmail.com