cloud_run.py

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from __future__ import annotations

from typing import TYPE_CHECKING, Any, 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


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).
    """

    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

    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)


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).
    """

    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

    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)


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).
    """

    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

    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)


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).
    """

    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")

    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]


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 overrides: Optional map of override values.
    :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
    """

    template_fields = ("project_id", "region", "gcp_conn_id", "impersonation_chain", "job_name")

    def __init__(
        self,
        project_id: str,
        region: str,
        job_name: str,
        overrides: dict[str, Any] | None = None,
        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.overrides = overrides
        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

    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, overrides=self.overrides
        )

        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",
            )

    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)