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

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from __future__ import annotations

import abc
from collections.abc import Sequence
from typing import TYPE_CHECKING, Any

from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.comprehend import ComprehendHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.comprehend import (
    ComprehendCreateDocumentClassifierCompletedTrigger,
    ComprehendPiiEntitiesDetectionJobCompletedTrigger,
)
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class ComprehendBaseSensor(AwsBaseSensor[ComprehendHook]): """ General sensor behavior for Amazon Comprehend. Subclasses must implement following methods: - ``get_state()`` Subclasses must set the following fields: - ``INTERMEDIATE_STATES`` - ``FAILURE_STATES`` - ``SUCCESS_STATES`` - ``FAILURE_MESSAGE`` :param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore module to be installed. (default: False, but can be overridden in config file by setting default_deferrable to True) """
[docs] aws_hook_class = ComprehendHook
[docs] INTERMEDIATE_STATES: tuple[str, ...] = ()
[docs] FAILURE_STATES: tuple[str, ...] = ()
[docs] SUCCESS_STATES: tuple[str, ...] = ()
[docs] FAILURE_MESSAGE = ""
[docs] ui_color = "#66c3ff"
def __init__( self, deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False), **kwargs: Any, ): super().__init__(**kwargs) self.deferrable = deferrable
[docs] def poke(self, context: Context, **kwargs) -> bool: state = self.get_state() if state in self.FAILURE_STATES: raise AirflowException(self.FAILURE_MESSAGE) return state not in self.INTERMEDIATE_STATES
@abc.abstractmethod
[docs] def get_state(self) -> str: """Implement in subclasses."""
[docs]class ComprehendStartPiiEntitiesDetectionJobCompletedSensor(ComprehendBaseSensor): """ Poll the state of the pii entities detection job until it reaches a completed state; fails if the job fails. .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:ComprehendStartPiiEntitiesDetectionJobCompletedSensor` :param job_id: The id of the Comprehend pii entities detection job. :param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore module to be installed. (default: False, but can be overridden in config file by setting default_deferrable to True) :param poke_interval: Polling period in seconds to check for the status of the job. (default: 120) :param max_retries: Number of times before returning the current state. (default: 75) :param aws_conn_id: The Airflow connection used for AWS credentials. If this is ``None`` or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param verify: Whether to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html :param botocore_config: Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html """
[docs] INTERMEDIATE_STATES: tuple[str, ...] = ("IN_PROGRESS",)
[docs] FAILURE_STATES: tuple[str, ...] = ("FAILED", "STOP_REQUESTED", "STOPPED")
[docs] SUCCESS_STATES: tuple[str, ...] = ("COMPLETED",)
[docs] FAILURE_MESSAGE = "Comprehend start pii entities detection job sensor failed."
[docs] template_fields: Sequence[str] = aws_template_fields("job_id")
def __init__( self, *, job_id: str, max_retries: int = 75, poke_interval: int = 120, **kwargs: Any, ) -> None: super().__init__(**kwargs) self.job_id = job_id self.max_retries = max_retries self.poke_interval = poke_interval
[docs] def execute(self, context: Context) -> Any: if self.deferrable: self.defer( trigger=ComprehendPiiEntitiesDetectionJobCompletedTrigger( job_id=self.job_id, waiter_delay=int(self.poke_interval), waiter_max_attempts=self.max_retries, aws_conn_id=self.aws_conn_id, ), method_name="poke", ) else: super().execute(context=context)
[docs] def get_state(self) -> str: return self.hook.conn.describe_pii_entities_detection_job(JobId=self.job_id)[ "PiiEntitiesDetectionJobProperties" ]["JobStatus"]
[docs]class ComprehendCreateDocumentClassifierCompletedSensor(AwsBaseSensor[ComprehendHook]): """ Poll the state of the document classifier until it reaches a completed state; fails if the job fails. .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:ComprehendCreateDocumentClassifierCompletedSensor` :param document_classifier_arn: The arn of the Comprehend document classifier. :param fail_on_warnings: If set to True, the document classifier training job will throw an error when the status is TRAINED_WITH_WARNING. (default False) :param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore module to be installed. (default: False, but can be overridden in config file by setting default_deferrable to True) :param poke_interval: Polling period in seconds to check for the status of the job. (default: 120) :param max_retries: Number of times before returning the current state. (default: 75) :param aws_conn_id: The Airflow connection used for AWS credentials. If this is ``None`` or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param verify: Whether to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html :param botocore_config: Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html """
[docs] aws_hook_class = ComprehendHook
[docs] INTERMEDIATE_STATES: tuple[str, ...] = ( "SUBMITTED", "TRAINING", )
[docs] FAILURE_STATES: tuple[str, ...] = ( "DELETING", "STOP_REQUESTED", "STOPPED", "IN_ERROR", )
[docs] SUCCESS_STATES: tuple[str, ...] = ("TRAINED", "TRAINED_WITH_WARNING")
[docs] FAILURE_MESSAGE = "Comprehend document classifier failed."
[docs] template_fields: Sequence[str] = aws_template_fields("document_classifier_arn")
def __init__( self, *, document_classifier_arn: str, fail_on_warnings: bool = False, max_retries: int = 75, poke_interval: int = 120, deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False), aws_conn_id: str | None = "aws_default", **kwargs: Any, ) -> None: super().__init__(**kwargs) self.document_classifier_arn = document_classifier_arn self.fail_on_warnings = fail_on_warnings self.max_retries = max_retries self.poke_interval = poke_interval self.deferrable = deferrable self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context) -> Any: if self.deferrable: self.defer( trigger=ComprehendCreateDocumentClassifierCompletedTrigger( document_classifier_arn=self.document_classifier_arn, waiter_delay=int(self.poke_interval), waiter_max_attempts=self.max_retries, aws_conn_id=self.aws_conn_id, ), method_name="poke", ) else: super().execute(context=context)
[docs] def poke(self, context: Context, **kwargs) -> bool: status = self.hook.conn.describe_document_classifier( DocumentClassifierArn=self.document_classifier_arn )["DocumentClassifierProperties"]["Status"] self.log.info( "Poking for AWS Comprehend document classifier arn: %s status: %s", self.document_classifier_arn, status, ) if status in self.FAILURE_STATES: raise AirflowException(self.FAILURE_MESSAGE) if status in self.SUCCESS_STATES: self.hook.validate_document_classifier_training_status( document_classifier_arn=self.document_classifier_arn, fail_on_warnings=self.fail_on_warnings ) self.log.info("Comprehend document classifier `%s` complete.", self.document_classifier_arn) return True return False

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