Source code for airflow.providers.google.cloud.triggers.cloud_run

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from __future__ import annotations

import asyncio
from enum import Enum
from typing import TYPE_CHECKING, Any, AsyncIterator, Sequence

from airflow.exceptions import AirflowException
from airflow.providers.google.cloud.hooks.cloud_run import CloudRunAsyncHook
from airflow.triggers.base import BaseTrigger, TriggerEvent

if TYPE_CHECKING:
    from google.longrunning import operations_pb2

[docs]DEFAULT_BATCH_LOCATION = "us-central1"
[docs]class RunJobStatus(Enum): """Enum to represent the status of a job run."""
[docs] SUCCESS = "Success"
[docs] FAIL = "Fail"
[docs] TIMEOUT = "Timeout"
[docs]class CloudRunJobFinishedTrigger(BaseTrigger): """Cloud Run trigger to check if templated job has been finished. :param operation_name: Required. Name of the operation. :param job_name: Required. Name of the job. :param project_id: Required. the Google Cloud project ID in which the job was started. :param location: Optional. the location where job is executed. If set to None then the value of DEFAULT_BATCH_LOCATION will be used. :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). :param poll_sleep: Polling period in seconds to check for the status. :timeout: The time to wait before failing the operation. """ def __init__( self, operation_name: str, job_name: str, project_id: str | None, location: str = DEFAULT_BATCH_LOCATION, gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, polling_period_seconds: float = 10, timeout: float | None = None, ): super().__init__() self.project_id = project_id self.job_name = job_name self.operation_name = operation_name self.location = location self.gcp_conn_id = gcp_conn_id self.polling_period_seconds = polling_period_seconds self.timeout = timeout self.impersonation_chain = impersonation_chain
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: """Serializes class arguments and classpath.""" return ( "airflow.providers.google.cloud.triggers.cloud_run.CloudRunJobFinishedTrigger", { "project_id": self.project_id, "operation_name": self.operation_name, "job_name": self.job_name, "location": self.location, "gcp_conn_id": self.gcp_conn_id, "polling_period_seconds": self.polling_period_seconds, "timeout": self.timeout, "impersonation_chain": self.impersonation_chain, }, )
[docs] async def run(self) -> AsyncIterator[TriggerEvent]: timeout = self.timeout hook = self._get_async_hook() while timeout is None or timeout > 0: operation: operations_pb2.Operation = await hook.get_operation(self.operation_name) if operation.done: # An operation can only have one of those two combinations: if it is succeeded, then # the response field will be populated, else, then the error field will be. if operation.response is not None: yield TriggerEvent( { "status": RunJobStatus.SUCCESS, "job_name": self.job_name, } ) else: yield TriggerEvent( { "status": RunJobStatus.FAIL, "operation_error_code": operation.error.code, "operation_error_message": operation.error.message, "job_name": self.job_name, } ) elif operation.error.message: raise AirflowException(f"Cloud Run Job error: {operation.error.message}") if timeout is not None: timeout -= self.polling_period_seconds if timeout is None or timeout > 0: await asyncio.sleep(self.polling_period_seconds) yield TriggerEvent( { "status": RunJobStatus.TIMEOUT, "job_name": self.job_name, } )
def _get_async_hook(self) -> CloudRunAsyncHook: return CloudRunAsyncHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, )

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