### 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>
"""Use :func:`airflow.decorators.task` instead, this is deprecated.
    Calls ``@task.python`` and allows users to turn a Python function into
    an Airflow task.
    :param python_callable: A reference to an object that is callable
    :param op_kwargs: a dictionary of keyword arguments that will get unpacked
        in your function (templated)
    :param op_args: a list of positional arguments that will get unpacked when
        calling your callable (templated)
    :param multiple_outputs: if set, function return value will be
        unrolled to multiple XCom values. Dict will unroll to xcom values with keys as keys.
        Defaults to False.
    """
    
    
    from airflow.decorators.python import python_task
    warnings.warn(
        """airflow.operators.python.task is deprecated. Please use the following instead
        from airflow.decorators import task
        @task
        def my_task()""",
        RemovedInAirflow3Warning,
        stacklevel=2,
    )
    return python_task(python_callable=python_callable, multiple_outputs=multiple_outputs, **kwargs)
class PythonOperator(BaseOperator):