考虑使用

Consider using SQL server authentication as a workaround/alternative solution to connect to that db (the same dataflow syntax will work):

import azureml.dataprep as dprep
secret = dprep.register_secret(value="[SECRET-PASSWORD]", id="[SECRET-ID]")

ds = dprep.MSSQLDataSource(server_name="[SERVER-NAME],[PORT]",
               database_name="[DATABASE-NAME]",
               user_name="[DATABASE-USERNAME]",
               password=secret)

请注意，不赞成使用 dataprep ，可以替代使用 sqlalchemy

note that usage of dataprep is deprecated, sqlalchemy can be used an alternative

import pandas as pd
from sqlalchemy import create_engine

def mssql_engine(user = "[DATABASE-USERNAME]", 
                 password = "[SECRET-PASSWORD]", 
                 host = "[SERVER-NAME],[PORT]",
                 db = "[DATABASE-NAME]"):
    engine = create_engine(f'mssql+pyodbc://{user}:{password}@{host}/{db}?driver=SQL+Server')
    return engine

query = "SELECT ..."

df = pd.read_sql(query, mssql_engine())