[I] dag.test "mark_success_pattern" could work nicer with dynamically mapped tasks [airflow]

["jablecherman (via GitHub)" <gi...@apache.org>]

jablecherman opened a new issue, #61558:
URL: https://github.com/apache/airflow/issues/61558

   ### Apache Airflow version
   
   Other Airflow 3 version (please specify below)
   
   ### If "Other Airflow 3 version" selected, which one?
   
   3.1.2
   
   ### What happened?
   
   `Cannot expand <SerializedMappedTask(PythonOperator): process_item> for run manual__2026-02-06T19:06:43.772890+00:00; missing upstream values: ['op_args']`
   
   This occurs whenever you run `dag.test()` and provide a `mark_success_pattern` for the upstream task to the dynamic operator. The dynamic task has no input values to map over, and predictably fails.
   
   What could be considered a bug, is the same error still occurs when you ALSO provide a `mark_success_pattern` for the dynamic task itself. 
   
   ### What you think should happen instead?
   
   I would prefer if the test function were smart enough to check for tasks it should auto-succeed, **including dynamic tasks**, before checking for "missing upstream values."
   
   One difficulty is a task still needs to be generated, but it should be simple enough to generate a single successful mapped task.
   
   (The more I think about this, the more I think it is a feature request and not a bug, but hey 🤷 ).
   
   
   ### How to reproduce
   
   ```
   from airflow import DAG
   from airflow.providers.standard.operators.python import PythonOperator
   
   def generate_list():
       return [["item1"], ["item2"], ["item3"]]
   
   def process_item(item):
       print(f"Processing {item}")
   
   with DAG(
       dag_id="test_dynamic_mapping_dag",
       default_args={"owner": "airflow"},
       schedule=None,
   ) as dag:
   
       generate_task = PythonOperator(
           task_id="generate_list",
           python_callable=generate_list,
       )
   
       process_task = PythonOperator.partial(
           task_id="process_item",
           python_callable=process_item,
       ).expand(op_args=generate_task.output)
   
   if __name__ == "__main__":
       # running the below will understandably fail
       # dag.test(mark_success_pattern="generate_list")
   
       # running the below will fail, but arguably should succeed
       dag.test(mark_success_pattern="generate_list|process_item")
   
   ```
   
   ### Operating System
   
   Debian GNU/Linux
   
   ### Versions of Apache Airflow Providers
   
   _No response_
   
   ### Deployment
   
   Official Apache Airflow Helm Chart
   
   ### Deployment details
   
   _No response_
   
   ### Anything else?
   
   _No response_
   
   ### Are you willing to submit PR?
   
   - [ ] Yes I am willing to submit a PR!
   
   ### Code of Conduct
   
   - [x] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
   


-- 
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: commits-unsubscribe@airflow.apache.org.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

Re: [I] dag.test "mark_success_pattern" could work nicer with dynamically mapped tasks [airflow]

["abhijeets25012-tech (via GitHub)" <gi...@apache.org>]

abhijeets25012-tech commented on issue #61558:
URL: https://github.com/apache/airflow/issues/61558#issuecomment-3863473240

   i would like to take it 


-- 
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: commits-unsubscribe@airflow.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

Re: [I] dag.test "mark_success_pattern" could work nicer with dynamically mapped tasks [airflow]

["potiuk (via GitHub)" <gi...@apache.org>]

potiuk commented on issue #61558:
URL: https://github.com/apache/airflow/issues/61558#issuecomment-3986403264

   @abhijeets25012-tech We are unassigning you from this issue as part of our updated [assignment policy](https://github.com/apache/airflow/blob/main/contributing-docs/04_how_to_contribute.rst#contribute-code-changes).
   
   This is not meant to discourage your contribution — quite the opposite! You are still very welcome to work on this issue and submit a PR for it. Simply comment that you are working on it and open a PR when ready.
   
   We found that formal assignments were not working well, as they often prevented others from contributing when the assignee was not actively working on the issue.


-- 
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: commits-unsubscribe@airflow.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org