Source code for airflow.providers.amazon.aws.sensors.sagemaker_unified_studio

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#
#   http://www.apache.org/licenses/LICENSE-2.0
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"""This module contains the Amazon SageMaker Unified Studio Notebook sensor."""

from __future__ import annotations

from typing import TYPE_CHECKING

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.sagemaker_unified_studio import (
    SageMakerNotebookHook,
)
from airflow.sensors.base import BaseSensorOperator

if TYPE_CHECKING:
    from airflow.utils.context import Context



[docs]
class SageMakerNotebookSensor(BaseSensorOperator):
    """
    Waits for a Sagemaker Workflows Notebook execution to reach any of the status below.

    'FAILED', 'STOPPED', 'COMPLETED'

    :param execution_id: The Sagemaker Workflows Notebook running execution identifier
    :param execution_name: The Sagemaker Workflows Notebook unique execution name
    """

    def __init__(self, *, execution_id: str, execution_name: str, **kwargs):
        super().__init__(**kwargs)

[docs]
        self.execution_id = execution_id


[docs]
        self.execution_name = execution_name


[docs]
        self.success_state = ["COMPLETED"]


[docs]
        self.in_progress_states = ["PENDING", "RUNNING"]



[docs]
    def hook(self):
        return SageMakerNotebookHook(execution_name=self.execution_name)


    # override from base sensor

[docs]
    def poke(self, context=None):
        status = self.hook().get_execution_status(execution_id=self.execution_id)

        if status in self.success_state:
            log_info_message = f"Exiting Execution {self.execution_id} State: {status}"
            self.log.info(log_info_message)
            return True
        elif status in self.in_progress_states:
            return False
        else:
            error_message = f"Exiting Execution {self.execution_id} State: {status}"
            self.log.info(error_message)
            raise AirflowException(error_message)



[docs]
    def execute(self, context: Context):
        # This will invoke poke method in the base sensor
        log_info_message = f"Polling Sagemaker Workflows Artifact execution: {self.execution_name} and execution id: {self.execution_id}"
        self.log.info(log_info_message)
        super().execute(context=context)