### Description

`ShortCircuitOperator` does not return any value regardless of the result. 

Still, if `condition` evaluates to `falsey`, it can be useful to store/save the result of the condition to XCom so that downstream tasks. can use. 
Many objects evaluates to True/False, not just booleans - see  https://docs.python.org/3/library/stdtypes.html

### Use case/motivation

The change is trivial and would allow to combine a Python task and ShortCircuit into one.:

1. if callable returns None (or False) -> skip
2. if callable returns non-empty object (or True) -> continue. The proposed change is to pass on the condition to XCom.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] 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)

airflow/operators/python.py
context.update(self.op_kwargs)
        context['templates_dict'] = self.templates_dict
        self.op_kwargs = determine_kwargs(self.python_callable, self.op_args, context)
        return_value = self.execute_callable()
        if self.show_return_value_in_logs:
            self.log.info("Done. Returned value was: %s", return_value)
        else:
            self.log.info("Done. Returned value not shown")
        return return_value
    def execute_callable(self):
        """
        Calls the python callable with the given arguments.
        :return: the return value of the call.
        :rtype: any
        """
        return self.python_callable(*self.op_args, **self.op_kwargs)
class BranchPythonOperator(PythonOperator, SkipMixin):
    """
    Allows a workflow to "branch" or follow a path following the execution
    of this task.
    It derives the PythonOperator and expects a Python function that returns
    a single task_id or list of task_ids to follow. The task_id(s) returned
    should point to a task directly downstream from {self}. All other "branches"
    or directly downstream tasks are marked with a state of ``skipped`` so that
    these paths can't move forward. The ``skipped`` states are propagated
    downstream to allow for the DAG state to fill up and the DAG run's state
    to be inferred.
    """
    def execute(self, context: Dict):