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"""This module contains a Google Cloud Dataform sensor."""
from __future__ import annotations

from typing import TYPE_CHECKING, Iterable, Sequence

from airflow.exceptions import AirflowException, AirflowSkipException
from import DataformHook
from airflow.sensors.base import BaseSensorOperator

    from airflow.utils.context import Context

[docs]class DataformWorkflowInvocationStateSensor(BaseSensorOperator): """ Checks for the status of a Workflow Invocation in Google Cloud Dataform. :param project_id: Required, the Google Cloud project ID in which to start a job. If set to None or missing, the default project_id from the Google Cloud connection is used. :param region: Required, The location of the Dataform workflow invocation (for example europe-west1). :param repository_id: Required. The ID of the Dataform repository that the task belongs to. :param workflow_invocation_id: Required, ID of the workflow invocation to be checked. :param expected_statuses: The expected state of the operation. See: :param failure_statuses: State that will terminate the sensor with an exception :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ("workflow_invocation_id",)
def __init__( self, *, project_id: str, region: str, repository_id: str, workflow_invocation_id: str, expected_statuses: set[int] | int, failure_statuses: Iterable[int] | None = None, gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, **kwargs, ) -> None: super().__init__(**kwargs) self.repository_id = repository_id self.workflow_invocation_id = workflow_invocation_id self.expected_statuses = ( {expected_statuses} if isinstance(expected_statuses, int) else expected_statuses ) self.failure_statuses = failure_statuses self.project_id = project_id self.region = region self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain self.hook: DataformHook | None = None
[docs] def poke(self, context: Context) -> bool: self.hook = DataformHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) workflow_invocation = self.hook.get_workflow_invocation( project_id=self.project_id, region=self.region, repository_id=self.repository_id, workflow_invocation_id=self.workflow_invocation_id, ) workflow_status = workflow_invocation.state if workflow_status is not None: if self.failure_statuses and workflow_status in self.failure_statuses: # TODO: remove this if check when min_airflow_version is set to higher than 2.7.1 message = ( f"Workflow Invocation with id '{self.workflow_invocation_id}' " f"state is: {workflow_status}. Terminating sensor..." ) if self.soft_fail: raise AirflowSkipException(message) raise AirflowException(message) return workflow_status in self.expected_statuses

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