# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.
import os
from pyspark.sql import DataFrame
PLATFORM_SYNAPSE_INTERNAL = "synapse_internal"
PLATFORM_SYNAPSE = "synapse"
PLATFORM_BINDER = "binder"
PLATFORM_DATABRICKS = "databricks"
PLATFORM_UNKNOWN = "unknown"
SECRET_STORE = "mmlspark-build-keys"
SYNAPSE_PROJECT_NAME = "Microsoft.ProjectArcadia"
[docs]def running_on_synapse_internal():
return current_platform() is PLATFORM_SYNAPSE_INTERNAL
[docs]def running_on_synapse():
return current_platform() is PLATFORM_SYNAPSE
[docs]def running_on_binder():
return current_platform() is PLATFORM_BINDER
[docs]def running_on_databricks():
return current_platform() is PLATFORM_DATABRICKS
[docs]def find_secret(secret_name, keyvault):
try:
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("get secret is not supported on this platform.")
except:
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 keyvault 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! "
f"Please see the documentation for more information. "
f"https://microsoft.github.io/SynapseML/docs/Get%20Started/Set%20up%20Cognitive%20Services/"
)
[docs]def materializing_display(data):
if running_on_synapse() or running_on_synapse_internal():
from notebookutils.visualization import display
if isinstance(data, DataFrame):
data.collect()
display(data)
else:
print(data)