kalluripradeep commented on issue #60443:
URL: https://github.com/apache/airflow/issues/60443#issuecomment-3831847477
Hi @DataCerealz and @potiuk ! 👋
I'd like to work on this issue. I've analyzed the code and have a clear
implementation plan.
## Problem Analysis
Currently, `TriggerDagRunOperator` has two limitations:
1. **Forces `logical_date`**: When `logical_date` is not provided, it
defaults to `timezone.utcnow()` (line 203-205)
2. **No `run_after` support**: The operator doesn't expose the `run_after`
parameter, which is crucial for parallel DAG runs in Airflow 3
This prevents users from triggering multiple parallel runs of the same DAG
with different configurations, as the unique constraint on `(dag_id,
logical_date)` causes conflicts.
## Proposed Solution
Add `run_after` parameter support to `TriggerDagRunOperator`:
### 1. **New Parameter**
```python
run_after: datetime.datetime | None | ArgNotSet = NOTSET
```
### 2. **Logic Changes**
- When `run_after` is provided and `logical_date` is `NOTSET`, set
`logical_date=None`
- Pass `run_after` to `DagRunTriggerException` for Airflow 3
- Pass `run_after` to `trigger_dag()` for Airflow 2 (if supported)
### 3. **Template Field**
Add `run_after` to `template_fields` for dynamic templating
### 4. **Updated Signature**
```python
TriggerDagRunOperator(
trigger_dag_id="my_dag",
run_after=datetime(2024, 1, 1, 12, 0, 0), # Schedule for specific time
logical_date=None, # Allow None to enable parallel runs
conf={"key": "value1"}
)
```
## Implementation Files
-
`providers/standard/src/airflow/providers/standard/operators/trigger_dagrun.py`
- `providers/standard/tests/unit/standard/operators/test_trigger_dagrun.py`
- Documentation updates
I'll submit a PR shortly with the implementation and comprehensive tests.
Let me know if this approach looks good! 🚀
Thanks!
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