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

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from __future__ import annotations

from typing import TYPE_CHECKING, Any, Sequence

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.lambda_function import LambdaHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.utils import trim_none_values
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class LambdaFunctionStateSensor(AwsBaseSensor[LambdaHook]):
    """
    Poll the deployment state of the AWS Lambda function until it reaches a target state.

    Fails if the query fails.

    .. 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'
        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).
    """

[docs]    FAILURE_STATES = ("Failed",)

[docs]    aws_hook_class = LambdaHook
[docs]    template_fields: Sequence[str] = aws_template_fields(
        "function_name",
        "qualifier",
    )

    def __init__(
        self,
        *,
        function_name: str,
        qualifier: str | None = None,
        target_states: list | None = None,
        **kwargs: Any,
    ) -> None:
        super().__init__(**kwargs)
        self.function_name = function_name
        self.qualifier = qualifier
        self.target_states = target_states or ["Active"]

[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