### Discussed in https://github.com/apache/airflow/discussions/33345

<div type='discussions-op-text'>

<sup>Originally posted by **vuphamcs** August 11, 2023</sup>
### Description

Is there a variable similar to `prev_start_date_success` but for the previous DAG run’s completion date? The value I’m hoping to retrieve to use within the next DAG run is `2023-08-10 16:04:30`

![image](https://github.com/apache/airflow/assets/1600760/9e2af349-4c3e-47e1-8a1a-9d8827b56f57)


### Use case/motivation

One particular use case is to help guarantee that the next DAG run only queries data that was inserted during the existing DAG run, and not the past DAG run.

```python
prev_ts = context['prev_end_date_success']

sql = f"SELECT * FROM results WHERE created_at > {context['prev_end_date_success']}"
```

### Related issues

_No response_

### Are you willing to submit a 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)
</div>
from airflow import __version__ as airflow_version
        try:
            result = subprocess.check_output(
                [self.python, "-c", "from airflow import __version__; print(__version__)"],
                text=True,
                
                env={**os.environ, "_AIRFLOW__AS_LIBRARY": "true"},
            )
            target_airflow_version = result.strip()
            if target_airflow_version != airflow_version:
                raise AirflowConfigException(
                    f"The version of Airflow installed for the {self.python}("
                    f"{target_airflow_version}) is different than the runtime Airflow version: "
                    f"{airflow_version}. Make sure your environment has the same Airflow version "
                    f"installed as the Airflow runtime."
                )
            return target_airflow_version
        except Exception as e:
            if self.expect_airflow:
                self.log.warning("When checking for Airflow installed in virtual environment got %s", e)
                self.log.warning(
                    f"This means that Airflow is not properly installed by  "
                    f"{self.python}. Airflow context keys will not be available. "
                    f"Please Install Airflow {airflow_version} in your environment to access them."
                )
            return None
class BranchExternalPythonOperator(ExternalPythonOperator, BranchMixIn):