SQLAlchemy ORM – 过滤操作符

现在，我们将学习过滤器操作及其各自的代码和输出。

等于

通常使用的运算符是 ==，它应用标准来检查相等性。

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 = ?

上述代码的输出如下 –

ID: 2 Name: Komal Pande Address: Banjara Hills Secunderabad Email: [email protected]

不等于

用于不等于的运算符是 != 并且它提供不等于条件。

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)

生成的 SQL 表达式是 –

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 != ?

上述代码行的输出如下 –

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: [email protected]
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: [email protected]
ID: 4 Name: S.M.Krishna Address: Budhwar Peth, Pune Email: [email protected]

喜欢

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

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)

以上 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: [email protected]
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: [email protected]

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 (?, ?)

上述代码的输出如下 –

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: [email protected]
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: [email protected]

和

这种连接是通过在过滤器中放置多个逗号分隔的条件或使用 and_() 方法生成的，如下所示 –

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)

上述两种方法都会产生类似的 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: [email protected]

或者

这个连接是由or_() 方法实现的。

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)

因此，SQLite 引擎遵循等效的 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 ?

上述代码的输出如下 –

ID: 1 Name: Ravi Kumar Address: Station Road Nanded Email: [email protected]
ID: 3 Name: Rajender Nath Address: Sector 40, Gurgaon Email: [email protected]
ID: 4 Name: S.M.Krishna Address: Budhwar Peth, Pune Email: [email protected]