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from __future__ import annotations

from typing import TYPE_CHECKING, Any, Sequence

from import LambdaHook
from import trim_none_values

    from airflow.utils.context import Context

from airflow.compat.functools import cached_property
from airflow.exceptions import AirflowException
from airflow.sensors.base import BaseSensorOperator

[docs]class LambdaFunctionStateSensor(BaseSensorOperator): """ Asks for the state of the Lambda until it reaches a target state. If the query fails, the task will fail. .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:LambdaFunctionStateSensor` :param function_name: The name of the AWS Lambda function, version, or alias. :param qualifier: Specify a version or alias to get details about a published version of the function. :param target_states: The Lambda states desired. :param aws_conn_id: aws connection to use, defaults to 'aws_default' """
[docs] FAILURE_STATES = ("Failed",)
[docs] template_fields: Sequence[str] = ( "function_name", "qualifier",
) def __init__( self, *, function_name: str, qualifier: str | None = None, target_states: list = ["Active"], aws_conn_id: str = "aws_default", **kwargs: Any, ) -> None: super().__init__(**kwargs) self.aws_conn_id = aws_conn_id self.function_name = function_name self.qualifier = qualifier self.target_states = target_states
[docs] def poke(self, context: Context) -> bool: get_function_args = { "FunctionName": self.function_name, "Qualifier": self.qualifier, } state = self.hook.conn.get_function(**trim_none_values(get_function_args))["Configuration"]["State"] if state in self.FAILURE_STATES: raise AirflowException( "Lambda function state sensor failed because the Lambda is in a failed state" ) return state in self.target_states
[docs] def hook(self) -> LambdaHook: return LambdaHook(aws_conn_id=self.aws_conn_id)

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