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import sys
import time

from botocore.exceptions import ClientError

from airflow import AirflowException
from import AwsBaseHook
from import StsHook

if sys.version_info >= (3, 8):
    from functools import cached_property
    from cached_property import cached_property

[docs]class QuickSightHook(AwsBaseHook): """ Interact with Amazon QuickSight. Additional arguments (such as ``aws_conn_id``) may be specified and are passed down to the underlying AwsBaseHook. .. seealso:: :class:`` """
def __init__(self, *args, **kwargs): super().__init__(client_type="quicksight", *args, **kwargs) @cached_property
[docs] def sts_hook(self): return StsHook(aws_conn_id=self.aws_conn_id)
[docs] def create_ingestion( self, data_set_id: str, ingestion_id: str, ingestion_type: str, wait_for_completion: bool = True, check_interval: int = 30, ): """ Creates and starts a new SPICE ingestion for a dataset. Refreshes the SPICE datasets :param data_set_id: ID of the dataset used in the ingestion. :param ingestion_id: ID for the ingestion. :param ingestion_type: Type of ingestion . "INCREMENTAL_REFRESH"|"FULL_REFRESH" :param wait_for_completion: if the program should keep running until job finishes :param check_interval: the time interval in seconds which the operator will check the status of QuickSight Ingestion :return: Returns descriptive information about the created data ingestion having Ingestion ARN, HTTP status, ingestion ID and ingestion status. :rtype: Dict """"Creating QuickSight Ingestion for data set id %s.", data_set_id) quicksight_client = self.get_conn() try: aws_account_id = self.sts_hook.get_account_number() create_ingestion_response = quicksight_client.create_ingestion( DataSetId=data_set_id, IngestionId=ingestion_id, IngestionType=ingestion_type, AwsAccountId=aws_account_id, ) if wait_for_completion: self.wait_for_state( aws_account_id=aws_account_id, data_set_id=data_set_id, ingestion_id=ingestion_id, target_state={"COMPLETED"}, check_interval=check_interval, ) return create_ingestion_response except Exception as general_error: self.log.error("Failed to run Amazon QuickSight create_ingestion API, error: %s", general_error) raise
[docs] def get_status(self, aws_account_id: str, data_set_id: str, ingestion_id: str): """ Get the current status of QuickSight Create Ingestion API. :param aws_account_id: An AWS Account ID :param data_set_id: QuickSight Data Set ID :param ingestion_id: QuickSight Ingestion ID :return: An QuickSight Ingestion Status :rtype: str """ try: describe_ingestion_response = self.get_conn().describe_ingestion( AwsAccountId=aws_account_id, DataSetId=data_set_id, IngestionId=ingestion_id ) return describe_ingestion_response["Ingestion"]["IngestionStatus"] except KeyError: raise AirflowException("Could not get status of the Amazon QuickSight Ingestion") except ClientError: raise AirflowException("AWS request failed, check logs for more info")
[docs] def wait_for_state( self, aws_account_id: str, data_set_id: str, ingestion_id: str, target_state: set, check_interval: int, ): """ Check status of a QuickSight Create Ingestion API :param aws_account_id: An AWS Account ID :param data_set_id: QuickSight Data Set ID :param ingestion_id: QuickSight Ingestion ID :param target_state: Describes the QuickSight Job's Target State :param check_interval: the time interval in seconds which the operator will check the status of QuickSight Ingestion :return: response of describe_ingestion call after Ingestion is is done """ sec = 0 status = self.get_status(aws_account_id, data_set_id, ingestion_id) while status in self.NON_TERMINAL_STATES and status != target_state:"Current status is %s", status) time.sleep(check_interval) sec += check_interval if status in self.FAILED_STATES: raise AirflowException("The Amazon QuickSight Ingestion failed!") if status == "CANCELLED": raise AirflowException("The Amazon QuickSight SPICE ingestion cancelled!") status = self.get_status(aws_account_id, data_set_id, ingestion_id)"QuickSight Ingestion completed") return status

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