**What happened**:

With the new Backport providers, when calling `DataflowCreatePythonJobOperator` with an empty `py_rerquirments` Dataflow commands always launch inside a virtualenv.

**What you expected to happen**:

The Dataflow command should run locally.


airflow/providers/google/cloud/operators/dataflow.py
self.py_requirements = py_requirements or []
        self.py_system_site_packages = py_system_site_packages
        self.project_id = project_id
        self.location = location
        self.gcp_conn_id = gcp_conn_id
        self.delegate_to = delegate_to
        self.poll_sleep = poll_sleep
        self.job_id = None
        self.hook = None
    def execute(self, context):
        """Execute the python dataflow job."""
        with ExitStack() as exit_stack:
            if self.py_file.lower().startswith('gs://'):
                gcs_hook = GCSHook(self.gcp_conn_id, self.delegate_to)
                tmp_gcs_file = exit_stack.enter_context(  
                    gcs_hook.provide_file(object_url=self.py_file)
                )
                self.py_file = tmp_gcs_file.name
            self.hook = DataflowHook(
                gcp_conn_id=self.gcp_conn_id,
                delegate_to=self.delegate_to,
                poll_sleep=self.poll_sleep
            )
            dataflow_options = self.dataflow_default_options.copy()
            dataflow_options.update(self.options)
            
            camel_to_snake = lambda name: re.sub(r'[A-Z]', lambda x: '_' + x.group(0).lower(), name)
            formatted_options = {camel_to_snake(key): dataflow_options[key]
                                 for key in dataflow_options}
            def set_current_job_id(job_id):