jason810496 commented on code in PR #62645: URL: https://github.com/apache/airflow/pull/62645#discussion_r2882608571
########## task-sdk/src/airflow/sdk/execution_time/callback_supervisor.py: ########## @@ -0,0 +1,270 @@ +# 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. +"""Supervised execution of callback workloads.""" + +from __future__ import annotations + +import os +import time +from importlib import import_module +from typing import TYPE_CHECKING, BinaryIO, ClassVar + +import attrs +import structlog +from pydantic import TypeAdapter + +from airflow.sdk.execution_time.supervisor import WatchedSubprocess + +if TYPE_CHECKING: + from collections.abc import Callable + + from structlog.typing import FilteringBoundLogger + from typing_extensions import Self + +__all__ = ["CallbackSubprocess", "execute_callback", "supervise_callback"] + +log: FilteringBoundLogger = structlog.get_logger(logger_name="callback_supervisor") + + +def execute_callback( + callback_path: str, + callback_kwargs: dict, + log, +) -> tuple[bool, str | None]: + """ + Execute a callback function by importing and calling it, returning the success state. + + Supports two patterns: + 1. Functions - called directly with kwargs + 2. Classes that return callable instances (like BaseNotifier) - instantiated then called with context + + Example: + # Function callback + execute_callback("my_module.alert_func", {"msg": "Alert!", "context": {...}}, log) + + # Notifier callback + execute_callback("airflow.providers.slack...SlackWebhookNotifier", {"text": "Alert!"}, log) + + :param callback_path: Dot-separated import path to the callback function or class. + :param callback_kwargs: Keyword arguments to pass to the callback. + :param log: Logger instance for recording execution. + :return: Tuple of (success: bool, error_message: str | None) + """ + if not callback_path: + return False, "Callback path not found." + + try: + # Import the callback callable + # Expected format: "module.path.to.function_or_class" + module_path, function_name = callback_path.rsplit(".", 1) + module = import_module(module_path) + callback_callable = getattr(module, function_name) + + log.debug("Executing callback %s(%s)...", callback_path, callback_kwargs) + + # If the callback is a callable, call it. If it is a class, instantiate it. + result = callback_callable(**callback_kwargs) + + # If the callback is a class then it is now instantiated and callable, call it. + if callable(result): + context = callback_kwargs.get("context", {}) + log.debug("Calling result with context for %s", callback_path) + result = result(context) + + log.info("Callback %s executed successfully.", callback_path) + return True, None + + except Exception as e: + error_msg = f"Callback execution failed: {type(e).__name__}: {str(e)}" + log.exception("Callback %s(%s) execution failed: %s", callback_path, callback_kwargs, error_msg) + return False, error_msg + + +def _callback_subprocess_main(): + """ + Entry point for the callback subprocess, runs after fork. + + Reads the callback path and kwargs from environment variables, + executes the callback, and exits with an appropriate code. + """ + import json + import sys + + log = structlog.get_logger(logger_name="callback_runner") + + callback_path = os.environ.get("_AIRFLOW_CALLBACK_PATH", "") + callback_kwargs_json = os.environ.get("_AIRFLOW_CALLBACK_KWARGS", "{}") + + if not callback_path: + print("No callback path found in environment", file=sys.stderr) + sys.exit(1) + + try: + callback_kwargs = json.loads(callback_kwargs_json) + except Exception: + log.exception("Failed to deserialize callback kwargs") + sys.exit(1) + + success, error_msg = execute_callback(callback_path, callback_kwargs, log) + if not success: + log.error("Callback failed", error=error_msg) + sys.exit(1) + + +# An empty message set — callbacks don't send requests back to the supervisor (yet). +_EmptyMessage: TypeAdapter[None] = TypeAdapter(None) + + [email protected](kw_only=True) +class CallbackSubprocess(WatchedSubprocess): + """ + Supervised subprocess for executing callbacks. + + Uses the WatchedSubprocess infrastructure for fork/monitor/signal handling + while keeping a simple lifecycle: start, run callback, exit. + """ + + decoder: ClassVar[TypeAdapter] = _EmptyMessage + + @classmethod + def start( # type: ignore[override] + cls, + *, + id: str, + callback_path: str, + callback_kwargs: dict, + target: Callable[[], None] = _callback_subprocess_main, + logger: FilteringBoundLogger | None = None, + **kwargs, + ) -> Self: + """Fork and start a new subprocess to execute the given callback.""" + import json + from datetime import date, datetime + from uuid import UUID + + class _ExtendedEncoder(json.JSONEncoder): + """Handle types that stdlib json can't serialize (UUID, datetime, etc.).""" + + def default(self, o): + if isinstance(o, UUID): + return str(o) + if isinstance(o, datetime): + return o.isoformat() + if isinstance(o, date): + return o.isoformat() + if hasattr(o, "__str__"): + return str(o) + return super().default(o) + + # Pass the callback data to the child process via environment variables. + # These are set before fork so the child inherits them, and cleaned up in the parent after. + os.environ["_AIRFLOW_CALLBACK_PATH"] = callback_path + os.environ["_AIRFLOW_CALLBACK_KWARGS"] = json.dumps(callback_kwargs, cls=_ExtendedEncoder) + try: + proc: Self = super().start( + id=id, + target=target, + logger=logger, + **kwargs, + ) + finally: + # Clean up the env vars in the parent process + os.environ.pop("_AIRFLOW_CALLBACK_PATH", None) + os.environ.pop("_AIRFLOW_CALLBACK_KWARGS", None) Review Comment: I see. It is clearer with the above code snippet example. From the Copy-on-Write perspective when forking the subprocess, the closure-based approach above makes sense to me and should be the most reliable of the three approaches (JSON + env, dill + env, and the CoW mechanism with closures), but I will defer the final decision to Ash and Amogh. Thanks! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
