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from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
from google.cloud.run_v2 import Job
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.google.cloud.hooks.cloud_run import CloudRunHook
from airflow.providers.google.cloud.operators.cloud_base import GoogleCloudBaseOperator
from airflow.providers.google.cloud.triggers.cloud_run import CloudRunJobFinishedTrigger, RunJobStatus
if TYPE_CHECKING:
from google.api_core import operation
from google.cloud.run_v2.types import Execution
from airflow.utils.context import Context
[docs]class CloudRunCreateJobOperator(GoogleCloudBaseOperator):
"""
Creates a job without executing it. Pushes the created job to xcom.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param job_name: Required. The name of the job to create.
:param job: Required. The job descriptor containing the configuration of the job to submit.
:param gcp_conn_id: The connection ID used to connect 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 = ("project_id", "region", "gcp_conn_id", "impersonation_chain", "job_name")
def __init__(
self,
project_id: str,
region: str,
job_name: str,
job: dict | Job,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.project_id = project_id
self.region = region
self.job_name = job_name
self.job = job
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook: CloudRunHook = CloudRunHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain
)
job = hook.create_job(
job_name=self.job_name, job=self.job, region=self.region, project_id=self.project_id
)
return Job.to_dict(job)
[docs]class CloudRunUpdateJobOperator(GoogleCloudBaseOperator):
"""
Updates a job and wait for the operation to be completed. Pushes the updated job to xcom.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param job_name: Required. The name of the job to update.
:param job: Required. The job descriptor containing the new configuration of the job to update.
The name field will be replaced by job_name
:param gcp_conn_id: The connection ID used to connect 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 = ("project_id", "region", "gcp_conn_id", "impersonation_chain", "job_name")
def __init__(
self,
project_id: str,
region: str,
job_name: str,
job: dict | Job,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.project_id = project_id
self.region = region
self.job_name = job_name
self.job = job
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook: CloudRunHook = CloudRunHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain
)
job = hook.update_job(
job_name=self.job_name, job=self.job, region=self.region, project_id=self.project_id
)
return Job.to_dict(job)
[docs]class CloudRunDeleteJobOperator(GoogleCloudBaseOperator):
"""
Deletes a job and wait for the the operation to be completed. Pushes the deleted job to xcom.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param job_name: Required. The name of the job to delete.
:param gcp_conn_id: The connection ID used to connect 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 = ("project_id", "region", "gcp_conn_id", "impersonation_chain", "job_name")
def __init__(
self,
project_id: str,
region: str,
job_name: str,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.project_id = project_id
self.region = region
self.job_name = job_name
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook: CloudRunHook = CloudRunHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain
)
job = hook.delete_job(job_name=self.job_name, region=self.region, project_id=self.project_id)
return Job.to_dict(job)
[docs]class CloudRunListJobsOperator(GoogleCloudBaseOperator):
"""
Lists jobs.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param show_deleted: If true, returns deleted (but unexpired)
resources along with active ones.
:param limit: The number of jobs to list. If left empty,
all the jobs will be returned.
:param gcp_conn_id: The connection ID used to connect 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 = (
"project_id",
"region",
"gcp_conn_id",
"impersonation_chain",
)
def __init__(
self,
project_id: str,
region: str,
show_deleted: bool = False,
limit: int | None = None,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.project_id = project_id
self.region = region
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.show_deleted = show_deleted
self.limit = limit
if limit is not None and limit < 0:
raise AirflowException("The limit for the list jobs request should be greater or equal to zero")
[docs] def execute(self, context: Context):
hook: CloudRunHook = CloudRunHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain
)
jobs = hook.list_jobs(
region=self.region, project_id=self.project_id, show_deleted=self.show_deleted, limit=self.limit
)
return [Job.to_dict(job) for job in jobs]
[docs]class CloudRunExecuteJobOperator(GoogleCloudBaseOperator):
"""
Executes a job and wait for the operation to be completed. Pushes the executed job to xcom.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param job_name: Required. The name of the job to update.
:param job: Required. The job descriptor containing the new configuration of the job to update.
The name field will be replaced by job_name
:param gcp_conn_id: The connection ID used to connect to Google Cloud.
:param polling_period_seconds: Optional: Control the rate of the poll for the result of deferrable run.
By default, the trigger will poll every 10 seconds.
:param timeout: The timeout for this request.
: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 deferrable: Run operator in the deferrable mode
"""
[docs] template_fields = ("project_id", "region", "gcp_conn_id", "impersonation_chain", "job_name")
def __init__(
self,
project_id: str,
region: str,
job_name: str,
polling_period_seconds: float = 10,
timeout_seconds: float | None = None,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
**kwargs,
):
super().__init__(**kwargs)
self.project_id = project_id
self.region = region
self.job_name = job_name
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.polling_period_seconds = polling_period_seconds
self.timeout_seconds = timeout_seconds
self.deferrable = deferrable
self.operation: operation.Operation | None = None
[docs] def execute(self, context: Context):
hook: CloudRunHook = CloudRunHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain
)
self.operation = hook.execute_job(
region=self.region, project_id=self.project_id, job_name=self.job_name
)
if not self.deferrable:
result: Execution = self._wait_for_operation(self.operation)
self._fail_if_execution_failed(result)
job = hook.get_job(job_name=result.job, region=self.region)
return Job.to_dict(job)
else:
self.defer(
trigger=CloudRunJobFinishedTrigger(
operation_name=self.operation.operation.name,
job_name=self.job_name,
project_id=self.project_id,
location=self.region,
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
polling_period_seconds=self.polling_period_seconds,
),
method_name="execute_complete",
)
[docs] def execute_complete(self, context: Context, event: dict):
status = event["status"]
if status == RunJobStatus.TIMEOUT:
raise AirflowException("Operation timed out")
if status == RunJobStatus.FAIL:
error_code = event["operation_error_code"]
error_message = event["operation_error_message"]
raise AirflowException(
f"Operation failed with error code [{error_code}] and error message [{error_message}]"
)
hook: CloudRunHook = CloudRunHook(self.gcp_conn_id, self.impersonation_chain)
job = hook.get_job(job_name=event["job_name"], region=self.region)
return Job.to_dict(job)
def _fail_if_execution_failed(self, execution: Execution):
task_count = execution.task_count
succeeded_count = execution.succeeded_count
failed_count = execution.failed_count
if succeeded_count + failed_count != task_count:
raise AirflowException("Not all tasks finished execution")
if failed_count > 0:
raise AirflowException("Some tasks failed execution")
def _wait_for_operation(self, operation: operation.Operation):
try:
return operation.result(timeout=self.timeout_seconds)
except Exception:
error = operation.exception(timeout=self.timeout_seconds)
raise AirflowException(error)
