code: def find_secret(secret_name, keyvault):
      if running_on_synapse():
          from notebookutils.mssparkutils.credentials import getSecret
  
          return getSecret(keyvault, secret_name)
      elif running_on_synapse_internal():
          from notebookutils.mssparkutils.credentials import getSecret
  
          keyVaultURL = f"https://{keyvault}.vault.azure.net/"
          return getSecret(keyVaultURL, secret_name)
      elif running_on_databricks():
          from pyspark.sql import SparkSession
          from pyspark.dbutils import DBUtils
  
          spark = SparkSession.builder.getOrCreate()
          dbutils = DBUtils(spark)
          return dbutils.secrets.get(scope=keyvault, key=secret_name)
      else:
          raise RuntimeError(
              f"Could not find {secret_name} in keyvault {keyvault}. "
              f"If you are trying to use the mmlspark-buil-keys keyvault, you cant! "
              f"You need to make your own keyvaukt with secrets or replace this call with a string. "
              f"Make sure your notebook has access to a "
              f"keyvault named {keyvault} which contains a secret named {secret_name}. "
              f"On synapse, use a linked service keyvault, "
              f"on databricks use their secrets management sdk, "
              f"on fabric make sure your azure identity can access your azure keyvault. "
              f"If you want to avoid making a keyvault, replace this call to find secret with your secret as a string "
              f"like my_secret = 'jdiej38dnal.....'. Note that this has "
              f"security implications for publishing and sharing notebooks!"
          )
  
file_path: SynapseML/core/src/main/python/synapse/ml/core/platform/Platform.py
imports: import os
  from pyspark.sql import DataFrame
label_desc: Use image node_id 6 for calling a global function with example usage: find_secret(secret_name, keyvault) and returns: getSecret, getSecret, dbutils