using-python-sdk.md

copyright	lastupdated	subcollection
years 2017, 2020	2020-04-14	AnalyticsEngine

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Using the Python SDK

{: #using-python-sdk}

The {{site.data.keyword.iae_full_notm}} SDK can be installed by installing the library iaesdk from the Python Package Index.

Type the following command into a command line:

pip install iaesdk

{: codeblock}

Source code can be found at GitHub{: external}. The iaesdk library provides complete access to the {{site.data.keyword.iae_full_notm}} API.

You need to provide the service endpoints and the API key when you create a {{site.data.keyword.iae_full_notm}} service resource or a low-level client.

The service instance ID is also referred to as a instance GUID. You can retrieve the service instance ID when you create service credentials or through the CLI. See Retrieving service endpoints{: external}.

To use the iaesdk library, you need the following values:

• IAM_API_KEY: The API key generated when creating the service credentials. You can retrieve by viewing the service credentials on the IBM Cloud dashboard{: external}.
• instance_guid: The value in resource_instance_id generated when the service credentials are created. You can retrieve by viewing the service credentials on the IBM Cloud dashboard{: external}.
• IAE_ENDPOINT_URL: The service endpoint URL including the https:// protocol. See Service endpoints{: external}.

Code samples using iaesdk

{: #code-samples-python-sdk}

Getting started with the Python SDK after you have installed it, involves sourcing credentials to the {{site.data.keyword.iae_full_notm}} service, invoking the service and then issuing different cluster commands as shown in the following sample code snippets. The code examples are written for Python 3.7.

The code samples show how to:

• Authenticate to the {{site.data.keyword.iae_full_notm}} service and build a service client:

  from iaesdk import IbmAnalyticsEngineApiV2
  from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
  
  # Constants for IBM Analytics Engine values
  IAM_API_KEY = "<api-key>" # eg "W00YiRnLW4a3fTjMB-odB-2ySfTrFBIQQWanc--P3byk"
  IAE_ENDPOINT_URL = "<endpoint>" # Current list avaiable at https://cloud.ibm.com/apidocs/ibm-analytics-engine#service-endpoints
  
  # Create an IAM authenticator.
  authenticator = IAMAuthenticator(IAM_API_KEY)
  
  # Construct the service client.
  iaesdk_service = IbmAnalyticsEngineApiV2(authenticator=authenticator)
  
  # Set our custom service URL (optional)
  iaesdk_service.set_service_url(IAE_ENDPOINT_URL)
  
  # Service operations can now be invoked using the "iaesdk_service" variable.

  {: codeblock}

• Access the {{site.data.keyword.iae_full_notm}} service instance:

  def get_analytics_engine_by_id(instance_guid):
      try:
          response = iaesdk_service.get_analytics_engine_by_id(instance_guid)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Get the state of the {{site.data.keyword.iae_full_notm}} cluster:

  def get_analytics_engine_state_by_id(instance_guid):
      try:
          response = iaesdk_service.get_analytics_engine_state_by_id(instance_guid)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Create a customization request:

  def create_customization_request(instance_guid):
      try:
          # Construct a dict representation of a AnalyticsEngineCustomActionScript model
          analytics_engine_custom_action_script_model =  {
              'source_type': 'http',
              'script_path': 'testString',
              'source_props': 'unknown type: object'
          }
          # Construct a dict representation of a AnalyticsEngineCustomAction model
          analytics_engine_custom_action_model =  {
              'name': 'testString',
              'type': 'bootstrap',
              'script': analytics_engine_custom_action_script_model,
              'script_params': ['testString']
          }
  
          # Set up parameter values
          target = 'all'
          custom_actions = [analytics_engine_custom_action_model]
  
          # Invoke method
          response = iaesdk_service.create_customization_request(
              instance_guid,
              target,
              custom_actions,
          )
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Get all customization requests:

  def get_all_customization_requests(instance_guid):
      try:
          response = iaesdk_service.get_all_customization_requests(instance_guid)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Get the customization requests by ID:

  def get_customization_request_by_id(instance_guid, request_id):
      try:
          response = iaesdk_service.get_customization_request_by_id(instance_guid, request_id)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Resize the cluster:

  def resize_cluster(instance_guid, compute_nodes_count):
      try:
          response = iaesdk_service.resize_cluster(instance_guid, compute_nodes_count)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Reset the cluster password:

  def reset_cluster_password(instance_guid):
      try:
          response = iaesdk_service.reset_cluster_password(instance_guid)
          print(response.result)
      except Exception as e:
          print("Unable to reset: {0}".format(e))

  {: codeblock}

• Configure logging:

  def configure_logging(instance_guid):
      # Construct a dict representation of a AnalyticsEngineLoggingNodeSpec model
      analytics_engine_logging_node_spec_model =  {
          'node_type': 'management',
          'components': ['ambari-server']
      }
      # Construct a dict representation of a AnalyticsEngineLoggingServer model
      analytics_engine_logging_server_model =  {
          'type': 'logdna',
          'credential': 'testString',
          'api_host': 'testString',
          'log_host': 'testString',
          'owner': 'testString'
      }
  
      # Set up parameter values
      log_specs = [analytics_engine_logging_node_spec_model]
      log_server = analytics_engine_logging_server_model
      try:
          response = iaesdk_service.configure_logging(instance_guid, log_specs, log_server)
          print(response.status_code)
      except Exception as e:
          print("Unable to configure: {0}".format(e))

  {: codeblock}

• Get the log configuration:

  def get_logging_config(instance_guid):
      try:
          response = iaesdk_service.get_logging_config(instance_guid)
          print(response.result)
      except Exception as e:
          print("Unable to retrieve: {0}".format(e))

  {: codeblock}

• Delete the log configuration:

  def delete_logging_config(instance_guid):
      try:
          response = iaesdk_service.delete_logging_config(instance_guid)
          print(response.status_code)
      except Exception as e:
          print("Unable to delete: {0}".format(e))

  {: codeblock}

• Update private endpoint whitelist:

  def update_private_endpoint_whitelist(instance_guid):
      try:
          response = iaesdk_service.update_private_endpoint_whitelist(instance_guid)
               instance_guid,
               ip_ranges,
               action,
              )print(response.status_code)
      except Exception as e:
          print("Unable to update: {0}".format(e))

  {: codeblock}