mzecov opened a new issue, #33918:
URL: https://github.com/apache/airflow/issues/33918
### Apache Airflow version
2.7.0
### What happened
Variable `{{ prev_start_date_success }}` returns unexpected results when
manually triggering DAG.
With following DAG definition file
```py
with DAG(
"demo",
schedule="*/1 * * * *",
start_date=datetime(2023, 1, 1),
max_active_runs=1,
catchup=False,
) as dag:
t1 = BashOperator(
task_id="templated",
depends_on_past=False,
bash_command="""echo "{{ prev_start_date_success }}" """,
)
t1
```
(one task only displaying `prev_start_date_success`, every minute for demo
purposes)
With following DAG runs:
- DAG run # 1: automatically triggered at 2023-08-30, 12:03:00 UTC;
data_interval_start is 2023-08-30, 12:02:00 UTC
- DAG run # 2: **manually** triggered **at 2023-08-30, 12:03:34 UTC**;
data_interval_start is 2023-08-30, 12:02:00 UTC
- DAG run # 3: automatically triggered at 2023-08-30, 12:04:00 UTC;
data_interval_start is 2023-08-30, 12:03:00 UTC
- DAG run # 4: automatically triggered at 2023-08-30, 12:05:00 UTC;
data_interval_start is 2023-08-30, 12:04:00 UTC
Logs:
- DAG run # 2: `['/bin/bash', '-c', 'echo "2023-08-30T12:03:00.378342+00:00"
']`
- DAG run # 3: `['/bin/bash', '-c', 'echo "2023-08-30T12:03:00.378342+00:00"
']`
- DAG run # 4: `['/bin/bash', '-c', 'echo "2023-08-30T12:03:34.363933+00:00"
']`
### What you think should happen instead
[Here](https://airflow.apache.org/docs/apache-airflow/stable/templates-ref.html):
`prev_start_date_success` is *"Start date from prior successful DagRun (if
available)."*. But:
- DAG run # 3 prints start date of DAG # 1, not # 2 (manually triggered). I
thought maybe runs are sorted on `data_interval_start` to get *"prior"*. And
this value is the same for DAG run # 1 and # 2. Or maybe manual triggers are
excluded.
- But why DAG # 4 prints start date of DAG # 2 ? *"prior"* DAG run should be
# 3 not # 2
- Is it a bug?
- Else, can we explain this in documentation?
Note that with `CronTriggerTimetable`, results are different and more
coherent (# 3 uses # 2 and # 4 uses # 3).
### How to reproduce
- Use upper DAG definition file
- Trigger DAG in Airflow GUI (manually), between two schedules
- Observe logs of following two DAG runs.
### Operating System
Runs in container (image 2.7.0-python3.10)
### Versions of Apache Airflow Providers
_No response_
### Deployment
Docker-Compose
### 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)
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