Tegh25 opened a new pull request, #68359:
URL: https://github.com/apache/airflow/pull/68359
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closes: #66791
When a Dag is configured with `catchup=False` and the scheduler advances
past missed intervals (for example after a restart or re-enable), the skip
happens silently: no DagRun rows are created and no hook fires. Operators
who need observability for skipped partitions (SLA accounting, compliance
audit trails, dashboard counters) had to compare
`last_automated_data_interval`
against wall clock externally.
This PR adds two symmetric extension points:
1. **`on_skipped_intervals_callback`** — a Dag-level callback on the SDK
`DAG` constructor, using the same context-based signature as
`on_success_callback` / `on_failure_callback`. The context includes
`dag`, `reason` (`"skipped_intervals"`), and `skipped_intervals` (a
list of `DataInterval` objects).
2. **`on_intervals_skipped`** — an AIP-61 listener hookspec for plugins
that need in-process observability without reloading the Dag file.
### How it works
Skipped intervals are detected by **reconstruction** at scheduled DagRun
creation time (timetable-agnostic):
- When the scheduler creates a new `SCHEDULED` run for a `catchup=False`
Dag, it compares the new run's `data_interval_start` against the
`data_interval_end` of the most recent prior scheduled run.
- It enumerates the gap using `SerializedDAG.iter_dagrun_infos_between`
(which uses `catchup=True` internally) and collects intervals strictly
between the two endpoints.
- Detection is gated: reconstruction runs only when `not dag.catchup` AND
(`has_on_skipped_intervals_callback` is set OR an `on_intervals_skipped`
listener implementation is registered).
**Listener** fires synchronously in the scheduler (same pattern as
`on_dag_run_running` for Dag start events).
**Callback** follows the existing Dag callback pipeline:
`DagSkippedIntervalsCallbackRequest` → `DatabaseCallbackSink` → Dag File
Processor reloads the Dag file and invokes the callable. Skipped intervals
are serialized as `(start, end)` datetime pairs in the request because no
DagRun row exists for skipped intervals and the processor cannot reliably
reconstruct the gap later.
### Files changed
| Area | Files |
|------|-------|
| SDK Dag definition | `task-sdk/src/airflow/sdk/definitions/dag.py` |
| Serialization | `serialization/definitions/dag.py`,
`serialized_objects.py`, `schema.json` |
| Callback transport | `callbacks/callback_requests.py`,
`dag_processing/processor.py` |
| Listener | `listeners/spec/dag.py` (new), `listeners/listener.py` |
| Scheduler | `jobs/scheduler_job_runner.py` |
### Usage (preview)
```python
from airflow.sdk import DAG
from airflow.timetables.base import DataInterval
def notify_skipped(context):
for interval in context["skipped_intervals"]:
print(f"Skipped: {interval.start} → {interval.end}")
with DAG("my_dag", schedule="@daily", catchup=False,
on_skipped_intervals_callback=notify_skipped) as dag:
...
```
## Follow-up (Will be added to this PR)
- [ ] Unit and integration tests (scheduler skip detection, callback
execution, listener hook, serialization roundtrip)
- [ ] User documentation (on_skipped_intervals_callback in Dag reference,
on_intervals_skipped in listeners docs)
- [ ] Newsfragment in airflow-core/newsfragments/ (user-facing feature)
### Test plan
*To be completed before marking Ready for review:*
- [ ] Scheduler creates skip callback request when catchup=False Dag jumps
past intervals and callback is configured
- [ ] Listener on_intervals_skipped fires with correct intervals
- [ ] Dag File Processor executes callback with skipped_intervals in context
- [ ] No overhead when callback and listener are both unset
- [ ] Serialization roundtrip preserves has_on_skipped_intervals_callback
- [ ] prek run --from-ref main --stage pre-commit passes
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