### Apache Airflow version

2.3.0

### What happened

When using a `PythonVirtualenvOperator` it is checked if `virtualenv` is installed by 
`if not shutil.which("virtualenv"):`
https://github.com/apache/airflow/blob/a1679be85aa49c0d6a7ba2c31acb519a5bcdf594/airflow/operators/python.py#L398
Actually, this expression checks if `virtualenv` is on PATH. If Airflow is installed in a virtual environment itself and `virtualenv` is not installed in the environment the check might pass but `virtualenv` cannot be used as it is not present in the environment.

### What you think should happen instead

It should be checked if `virtualenv` is actually available in the environment.

```python
if importlib.util.find_spec("virtualenv") is None:
    raise AirflowException('PythonVirtualenvOperator requires virtualenv, please install it.')
```
https://stackoverflow.com/a/14050282

### How to reproduce

_No response_

### Operating System

Ubuntu 20.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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)

"""Deprecated. Use :func:`airflow.decorators.task` instead.
    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):