### 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)

file.write_text("\n".join(map(str, self.string_args)))
    def _read_result(self, path: Path):
        if path.stat().st_size == 0:
            return None
        try:
            return self.pickling_library.loads(path.read_bytes())
        except ValueError as value_error:
            raise DeserializingResultError() from value_error
    def __deepcopy__(self, memo):
        
        memo[id(self.pickling_library)] = self.pickling_library
        return super().__deepcopy__(memo)
    def _execute_python_callable_in_subprocess(self, python_path: Path, tmp_dir: Path):
        op_kwargs: dict[str, Any] = {k: v for k, v in self.op_kwargs.items()}
        if self.templates_dict:
            op_kwargs["templates_dict"] = self.templates_dict
        input_path = tmp_dir / "script.in"
        output_path = tmp_dir / "script.out"
        string_args_path = tmp_dir / "string_args.txt"
        script_path = tmp_dir / "script.py"
        termination_log_path = tmp_dir / "termination.log"
        self._write_args(input_path)
        self._write_string_args(string_args_path)
        write_python_script(
            jinja_context=dict(
                op_args=self.op_args,
                op_kwargs=op_kwargs,
                expect_airflow=self.expect_airflow,
                pickling_library=self.pickling_library.__name__,
                python_callable=self.python_callable.__name__,