o-nikolas commented on code in PR #62645:
URL: https://github.com/apache/airflow/pull/62645#discussion_r2874571391
##########
airflow-core/src/airflow/executors/base_executor.py:
##########
@@ -228,7 +229,7 @@ def log_task_event(self, *, event: str, extra: str, ti_key:
TaskInstanceKey):
"""Add an event to the log table."""
self._task_event_logs.append(Log(event=event, task_instance=ti_key,
extra=extra))
- def queue_workload(self, workload: workloads.All, session: Session) ->
None:
Review Comment:
Nice, I love that this is actually a helpful/concrete type now
##########
airflow-core/src/airflow/executors/workloads/callback.py:
##########
@@ -75,6 +75,24 @@ class ExecuteCallback(BaseDagBundleWorkload):
type: Literal["ExecuteCallback"] = Field(init=False,
default="ExecuteCallback")
+ @property
+ def key(self) -> CallbackKey:
+ """Return the callback key for this workload."""
+ return self.callback.key
+
+ @property
+ def display_name(self) -> str:
+ """Return the callback ID as a display name."""
+ return str(self.callback.id)
Review Comment:
Nit/curiosity: Would the command/callable being run be a more suitable title?
##########
providers/celery/src/airflow/providers/celery/executors/celery_executor_utils.py:
##########
@@ -209,9 +209,14 @@ def execute_workload(input: str) -> None:
log_path=workload.log_path,
)
elif isinstance(workload, workloads.ExecuteCallback):
- success, error_msg = execute_callback_workload(workload.callback, log)
- if not success:
- raise RuntimeError(error_msg or "Callback execution failed")
+ exit_code = supervise_callback(
+ id=workload.callback.id,
+ callback_path=workload.callback.data.get("path", ""),
+ callback_kwargs=workload.callback.data.get("kwargs", {}),
+ log_path=workload.log_path,
+ )
+ if exit_code != 0:
+ raise RuntimeError(f"Callback subprocess exited with code
{exit_code}")
Review Comment:
It feels odd that we're handling the result here in the Callback case but
not the task case. Is there logging in the supervisor code that's handling this
communication of the result for the task case?
##########
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).
Review Comment:
What are the implications of this? Can you add a bit more context to this
comment?
##########
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)
+ return proc
+
+ def wait(self) -> int:
+ """
+ Wait for the callback subprocess to complete.
+
+ A simplified monitor loop compared to ActivitySubprocess — no
heartbeating,
+ no task API state management. Just monitors process output and waits
for exit.
+ """
+ if self._exit_code is not None:
+ return self._exit_code
+
+ try:
+ while self._exit_code is None or self._open_sockets:
+ self._service_subprocess(max_wait_time=5.0)
+ finally:
+ self.selector.close()
+
+ self._exit_code = self._exit_code if self._exit_code is not None else 1
+ return self._exit_code
+
+ def _handle_request(self, msg, log: FilteringBoundLogger, req_id: int) ->
None:
+ """Handle incoming requests from the callback subprocess (currently
none expected)."""
+ log.warning("Unexpected request from callback subprocess", msg=msg)
+
+
+def _configure_logging(log_path: str) -> tuple[FilteringBoundLogger, BinaryIO]:
+ """Configure file-based logging for the callback subprocess."""
+ from airflow.sdk.log import init_log_file, logging_processors
+
+ log_file = init_log_file(log_path)
+ log_file_descriptor: BinaryIO = log_file.open("ab")
+ underlying_logger = structlog.BytesLogger(log_file_descriptor)
+ processors = logging_processors(json_output=True)
+ logger = structlog.wrap_logger(underlying_logger, processors=processors,
logger_name="callback").bind()
+
+ return logger, log_file_descriptor
+
+
+def supervise_callback(
+ *,
+ id: str,
+ callback_path: str,
+ callback_kwargs: dict,
+ log_path: str | None = None,
+) -> int:
+ """
+ Run a single callback execution to completion in a supervised subprocess.
+
+ :param id: Unique identifier for this callback execution.
+ :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_path: Path to write logs, if required.
+ :return: Exit code of the subprocess (0 = success).
+ """
+ start = time.monotonic()
+
+ logger: FilteringBoundLogger | None = None
+ log_file_descriptor: BinaryIO | None = None
+ if log_path:
+ logger, log_file_descriptor = _configure_logging(log_path)
+
+ try:
+ process = CallbackSubprocess.start(
+ id=id,
+ callback_path=callback_path,
+ callback_kwargs=callback_kwargs,
+ logger=logger,
+ )
+
+ exit_code = process.wait()
+ end = time.monotonic()
+ log.info(
+ "Workload finished",
Review Comment:
Here is the spot I would maybe put the completion logging (either another
line or updating this one)? Rather than putting it in each executor.
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