Fix none_failed_min_one_success trigger rule checks

[nailo2c]

Summary

none_failed_min_one_success requires all upstream tasks to avoid failed / upstream_failed and at least one upstream task to succeed.

The existing TriggerRuleDep dep-check path shared the same failure-count logic as none_failed. As a result, zero-success upstream states could be reported as dependencies met, even though the trigger rule's min-one-success contract could not be satisfied.

This showed up in two counterexamples:

• all upstream tasks skipped while flag_upstream_failed=False, where direct dependency checks such as airflow tasks failed-deps missed the trigger-rule failure reason;
• dynamically mapped upstreams where all upstream task instances were removed, where the scheduler rewrite path also did not assign a terminal failure state.

Before the fix, airflow tasks failed-deps did not report the trigger-rule violation for an all-skipped upstream case:

Reproduction Dag

import pendulum

from airflow.providers.standard.operators.empty import EmptyOperator
from airflow.providers.standard.operators.python import BranchPythonOperator
from airflow.sdk import DAG


def choose_branch():
    return "branch_b"


with DAG(
    dag_id="pattern5_repro",
    schedule=None,
    start_date=pendulum.datetime(2026, 1, 1, tz="UTC"),
    catchup=False,
    tags=["z3-counterexample"],
) as dag:
    pick = BranchPythonOperator(
        task_id="pick",
        python_callable=choose_branch,
    )

    branch_a = EmptyOperator(task_id="branch_a")
    branch_b = EmptyOperator(task_id="branch_b")

    downstream = EmptyOperator(
        task_id="downstream",
        trigger_rule="none_failed_min_one_success",
    )

    pick >> [branch_a, branch_b]
    branch_a >> downstream

[Breeze:3.10.20] root@57ce6ad76e64:/opt/airflow$ airflow tasks failed-deps pattern5_repro downstream manual__2026-05-31T23:57:32.573541+00:00
Task instance dependencies not met:
Dagrun Running: Task instance's dagrun was not in the 'running' state but in the state 'success'.
Task Instance State: Task is in the 'skipped' state.

After the fix, the missing trigger-rule dependency is reported:

[Breeze:3.10.20] root@57ce6ad76e64:/opt/airflow$ airflow tasks failed-deps pattern5_repro downstream manual__2026-05-31T23:57:32.573541+00:00
Task instance dependencies not met:
Trigger Rule: Task's trigger rule 'none_failed_min_one_success' requires at least one upstream task success, but none were found.
Dagrun Running: Task instance's dagrun was not in the 'running' state but in the state 'success'.
Task Instance State: Task is in the 'skipped' state.

Fix

Fail the none_failed_min_one_success dep check whenever no upstream task has succeeded.

Also extend the flag_upstream_failed=True rewrite path so that, once all upstreams are terminal and none succeeded, the downstream task instance is marked UPSTREAM_FAILED. This covers mapped tasks whose relevant upstream task instances were all removed.

The existing all-skipped behavior is preserved: that case is still rewritten to SKIPPED before the new all-terminal zero-success branch can run.

Test

Updated regression coverage for none_failed_min_one_success:

• all-skipped upstreams now report the missing upstream success for both flag_upstream_failed=True and False;
• all-removed mapped upstreams now report the missing upstream success, and with flag_upstream_failed=True the task instance is rewritten to UPSTREAM_FAILED.

Verified with:

uv run ruff format airflow-core/tests/unit/ti_deps/deps/test_trigger_rule_dep.py
uv run ruff check --fix airflow-core/tests/unit/ti_deps/deps/test_trigger_rule_dep.py
breeze run --backend postgres --python 3.10 --skip-image-upgrade-check --answer no pytest airflow-core/tests/unit/ti_deps/deps/test_trigger_rule_dep.py::TestTriggerRuleDep::test_none_failed_min_one_success_tr_skipped airflow-core/tests/unit/ti_deps/deps/test_trigger_rule_dep.py::TestTriggerRuleDep::test_mapped_task_upstream_all_removed_with_none_failed_min_one_success_trigger_rule -xvs

Result: 4 passed, 1 warning.

Reported by

SMT solver sweep of Airflow trigger-rule semantics using a local Z3 model.

---

Was generative AI tooling used to co-author this PR?

• Yes - Codex (GPT-5)

Generated-by: Codex (GPT-5) following the guidelines

[Pedrinhonitz]

This is fine by me, we can move on to a member review.