Source code for airflow.providers.microsoft.azure.operators.powerbi

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from __future__ import annotations

from typing import TYPE_CHECKING, Any, Sequence

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator, BaseOperatorLink
from airflow.providers.microsoft.azure.hooks.powerbi import (
    PowerBIHook,
)
from airflow.providers.microsoft.azure.triggers.powerbi import PowerBITrigger

if TYPE_CHECKING:
    from msgraph_core import APIVersion

    from airflow.models.taskinstancekey import TaskInstanceKey
    from airflow.utils.context import Context





[docs]class PowerBIDatasetRefreshOperator(BaseOperator): """ Refreshes a Power BI dataset. :param dataset_id: The dataset id. :param group_id: The workspace id. :param conn_id: Airflow Connection ID that contains the connection information for the Power BI account used for authentication. :param timeout: Time in seconds to wait for a dataset to reach a terminal status for asynchronous waits. Used only if ``wait_for_termination`` is True. :param check_interval: Number of seconds to wait before rechecking the refresh status. """
[docs] template_fields: Sequence[str] = ( "dataset_id", "group_id", )
[docs] template_fields_renderers = {"parameters": "json"}
def __init__( self, *, dataset_id: str, group_id: str, conn_id: str = PowerBIHook.default_conn_name, timeout: float = 60 * 60 * 24 * 7, proxies: dict | None = None, api_version: APIVersion | None = None, check_interval: int = 60, **kwargs, ) -> None: super().__init__(**kwargs) self.hook = PowerBIHook(conn_id=conn_id, proxies=proxies, api_version=api_version, timeout=timeout) self.dataset_id = dataset_id self.group_id = group_id self.wait_for_termination = True self.conn_id = conn_id self.timeout = timeout self.check_interval = check_interval
[docs] def execute(self, context: Context): """Refresh the Power BI Dataset.""" if self.wait_for_termination: self.defer( trigger=PowerBITrigger( conn_id=self.conn_id, group_id=self.group_id, dataset_id=self.dataset_id, timeout=self.timeout, check_interval=self.check_interval, wait_for_termination=self.wait_for_termination, ), method_name=self.execute_complete.__name__, )
[docs] def execute_complete(self, context: Context, event: dict[str, str]) -> Any: """ Return immediately - callback for when the trigger fires. Relies on trigger to throw an exception, otherwise it assumes execution was successful. """ if event: if event["status"] == "error": raise AirflowException(event["message"]) self.xcom_push( context=context, key="powerbi_dataset_refresh_Id", value=event["dataset_refresh_id"] ) self.xcom_push(context=context, key="powerbi_dataset_refresh_status", value=event["status"])

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