shivaam commented on code in PR #62645:
URL: https://github.com/apache/airflow/pull/62645#discussion_r2937212212
##########
airflow-core/src/airflow/executors/workloads/base.py:
##########
@@ -83,3 +83,59 @@ class BaseDagBundleWorkload(BaseWorkloadSchema, ABC):
dag_rel_path: os.PathLike[str] # Filepath where the DAG can be found
(likely prefixed with `DAG_FOLDER/`)
bundle_info: BundleInfo
log_path: str | None # Rendered relative log filename template the task
logs should be written to.
+
+ @property
+ @abstractmethod
+ def key(self) -> Any:
Review Comment:
nit; can this be of type `Hashable` to enforce the constraint that key must
be hashable?
```
from collections.abc import Hashable
def key(self) -> Hashable:
```
##########
task-sdk/src/airflow/sdk/execution_time/callback_supervisor.py:
##########
@@ -0,0 +1,280 @@
+# 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", "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)
Review Comment:
[Potential Bug]: The callback execution path needs to set up the DAG bundle
on `sys.path` before calling `import_module()`, the same way tasks do via
[`BundleDagBag.__init__()`](https://github.com/apache/airflow/blob/main/airflow-core/src/airflow/dag_processing/dagbag.py#L554-L555).
Without this, user-defined callbacks in DAG bundles aren't importable on
container-based executors (ECS, Batch, K8s).
I tested this end-to-end on ECS and confirmed the fix works:
```python
bundle = DagBundlesManager().get_bundle(
name=workload.bundle_info.name,
version=workload.bundle_info.version,
)
bundle.initialize()
if str(bundle.path) not in sys.path:
sys.path.append(str(bundle.path))
```
##########
task-sdk/src/airflow/sdk/execution_time/callback_supervisor.py:
##########
@@ -0,0 +1,280 @@
+# 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", "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; the callback subprocess doesn't currently communicate
back to the
+# supervisor. This means callback code cannot access runtime services like
Connection.get()
+# or Variable.get() which require the supervisor to pass requests to the API
server.
+# To enable this, add the needed message types here and implement
_handle_request accordingly.
+# See ActivitySubprocess.decoder in supervisor.py for the full task message
set and examples.
+_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:
Review Comment:
Minor note: `CallbackSubprocess.wait()` doesn't have the
`SOCKET_CLEANUP_TIMEOUT` + `_cleanup_open_sockets()` safety net that
`ActivitySubprocess._monitor_subprocess()` has. Could this potentially hang if
a socket doesn't close itself after the child exits?
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