Query SQL Server JSON columns using SQLAlchemy

Question

I'm looking for a way to replicate the functionality of SQL Server's JSON_VALUE function using a SQLAlchemy query. I'm using metadata.reflect to define my existing db tables in SQLAlchemy.

SQL:

SELECT Id,
JSON_VALUE(BankDataJSON,'$.AccountName')
FROM BankData

SQLAlchemy Model:

db = SQLAlchemy()
db.Model.metadata.reflect(db.engine)

class BankData(db.Model):
    __table__ = db.Model.metadata.tables['BankData'] 

Endpoint / Query:

@cust_accts_bp.route('/api/CustomerAccts')
def get_cust_accts():
    custId = request.args.get('custId')

    db = SQLAlchemy(app)
    BankData = models.bank_data.BankData
    BankAccounts = models.bank_accounts.BankAccounts

    qry = db.session.query(BankAccounts.Id, BankAccounts.AccountNumber, BankAccounts.BankName,
                           BankData.AppId, BankData.CustomerId, BankAccounts.Filename, BankData.BankDataJSON) \
                           .filter(
                               and_(BankData.Id == BankAccounts.BankDataId, BankData.CustomerId == custId)
                            )

    engine = app.config['SQLALCHEMY_DATABASE_URI']
    df = pd.read_sql(qry.statement, engine)

    df['BankDataJSON'] = df['BankDataJSON'].apply(json.loads) # convert string representation of JSON
    df['BankDataJSON'] = df['BankDataJSON'].map(lambda x:[x[i] for i in x if i=='AccountName'][0])
    df = df.rename(columns={'BankDataJSON':'BusinessName'})

    response = json.loads(df.to_json(orient="records"))

    return(json.dumps(response))

Using this method, I have to manually serialize the JSON object (BankDataJSON) to a Python dict, and parse it to get the value I want ('AccountName'). If I were to use SQL Server's JSON_VALUE function, this is all done for you.

JSON response:

[
  {
    "Id": 3003,
    "AccountNumber": "111111111",
    "BankName": "Wells Fargo",
    "AppId": 111111,
    "CustomerId": "555555",
    "Filename": "some filename.pdf",
    "BusinessName": "Some BusinessName"
  },
  {
    "Id": 3004,
    "AccountNumber": "22222222",
    "BankName": "Wells Fargo",
    "AppId": 111111,
    "CustomerId": "555555",
    "Filename": "Some filename",
    "BusinessName": "Some Businessname"
  },
]

How can I go about doing this? I walso want to be able to replicated SQL Server's CROSS APPLY OPENJSON functionality for working with array of JSON objects in the future. Do I need to define the BankDataJSON column as a JSON type in my model? When I do this, I get an error regarding pyodbcs inability to deserialize JSON in the MSSQL dialect

Answer 1

may be you can try to implement the server's function in your query, something like this

from sqlalchemy.sql import func


db = SQLAlchemy(app)
BankData = models.bank_data.BankData

qry = db.session.query(BankData.Id, 
     func.JSON_VALUE(BankData.BankDataJSON,'$.AccountName'))