Sqlalchemy-orm-filter-operators

SQLAlchemy ORM-フィルター演算子

次に、それぞれのコードと出力を使用してフィルター操作を学習します。

等しい

使用される通常の演算子は==であり、同等性をチェックする基準を適用します。

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は次のSQL式を送信します-

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 = ?

上記のコードの出力は次のとおりです-

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

等しくない

等しくないために使用される演算子は！=であり、等しくない基準を提供します。

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)

結果のSQL式は-

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 != ?

上記のコード行の出力は次のとおりです-

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]

Like

like（）メソッド自体は、SELECT式のWHERE句のLIKE基準を生成します。

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)

上記のSQLAlchemyコードは、次のSQL式と同等です-

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 ?

そして、上記のコードの出力は-

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

IN

この演算子は、列の値がリスト内のアイテムのコレクションに属しているかどうかを確認します。 in_（）メソッドによって提供されます。

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)

ここで、SQLiteエンジンによって評価されるSQL式は次のようになります-

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 (?, ?)

上記のコードの出力は次のとおりです-

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

AND

このコンジャンクションは、フィルターに複数のコンマ区切り基準を入れるか、以下に示すようにand_（）メソッドを使用して生成されます-

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)

上記のアプローチの両方は、同様のSQL式をもたらします-

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 ?

上記のコード行の出力は-

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

OR

この論理積は、* or_（）メソッド*によって実装されます。

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)

その結果、SQLiteエンジンは以下の同等のSQL式を取得します-

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 ?

上記のコードの出力は次のとおりです-

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]