pereisergio opened a new issue, #62097: URL: https://github.com/apache/airflow/issues/62097
### Apache Airflow Provider(s) apache-kafka ### Versions of Apache Airflow Providers When using AwaitMessageSensor, the timeout parameter is not respected unless I manually pass timeout=self.timeout to the defer() call in the execute() method. According to the documentation, setting timeout in the operator should be enough to enforce a timeout, but this only works if explicitly set in defer(). Steps to reproduce: 1. Use AwaitMessageSensor with the timeout parameter. 2. The task never times out unless timeout is passed to defer(). Expected behavior: The timeout parameter should be respected without manual intervention. ### Apache Airflow version 3.1.7 ### Operating System linux ### Deployment Astronomer ### Deployment details _No response_ ### What happened _No response_ ### What you think should happen instead _No response_ ### How to reproduce # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from __future__ import annotations from collections.abc import Sequence from datetime import timedelta from typing import Any from airflow.providers.apache.kafka.triggers.await_message import AwaitMessageTrigger from airflow.providers.common.compat.sdk import BaseSensorOperator VALID_COMMIT_CADENCE = {"never", "end_of_batch", "end_of_operator"} class AwaitMessageSensor(BaseSensorOperator): """ An Airflow sensor that defers until a specific message is published to Kafka. The sensor creates a consumer that reads the Kafka log until it encounters a positive event. The behavior of the consumer for this trigger is as follows: - poll the Kafka topics for a message - if no message returned, sleep - process the message with provided callable and commit the message offset - if callable returns any data, raise a TriggerEvent with the return data - else continue to next message - return event (as default xcom or specific xcom key) :param kafka_config_id: The connection object to use, defaults to "kafka_default" :param topics: Topics (or topic regex) to use for reading from :param apply_function: The function to apply to messages to determine if an event occurred. As a dot notation string. :param apply_function_args: Arguments to be applied to the processing function, defaults to None :param apply_function_kwargs: Key word arguments to be applied to the processing function, defaults to None :param poll_timeout: How long the kafka consumer should wait for a message to arrive from the kafka cluster,defaults to 1 :param poll_interval: How long the kafka consumer should sleep after reaching the end of the Kafka log, defaults to 5 :param xcom_push_key: the name of a key to push the returned message to, defaults to None :param soft_fail: Set to true to mark the task as SKIPPED on failure :param timeout: Time elapsed before the task times out and fails (in seconds) :param poke_interval: This parameter is inherited but not used in this deferrable implementation :param mode: This parameter is inherited but not used in this deferrable implementation """ BLUE = "#ffefeb" ui_color = BLUE template_fields = ( "topics", "apply_function", "apply_function_args", "apply_function_kwargs", "kafka_config_id", ) def __init__( self, topics: Sequence[str], apply_function: str, kafka_config_id: str = "kafka_default", apply_function_args: Sequence[Any] | None = None, apply_function_kwargs: dict[Any, Any] | None = None, poll_timeout: float = 1, poll_interval: float = 5, xcom_push_key=None, timeout: timedelta | int | float | None = None, **kwargs: Any, ) -> None: super().__init__(**kwargs) self.topics = topics self.apply_function = apply_function self.apply_function_args = apply_function_args self.apply_function_kwargs = apply_function_kwargs self.kafka_config_id = kafka_config_id self.poll_timeout = poll_timeout self.poll_interval = poll_interval self.xcom_push_key = xcom_push_key self.timeout = timeout def execute(self, context) -> Any: self.defer( trigger=AwaitMessageTrigger( topics=self.topics, apply_function=self.apply_function, apply_function_args=self.apply_function_args, apply_function_kwargs=self.apply_function_kwargs, kafka_config_id=self.kafka_config_id, poll_timeout=self.poll_timeout, poll_interval=self.poll_interval, ), method_name="execute_complete", timeout=self.timeout, ) def execute_complete(self, context, event=None): if self.xcom_push_key: context["task_instance"].xcom_push(key=self.xcom_push_key, value=event) return event ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [x] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) -- This is an automated message from the Apache Git Service. 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