**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/hooks/dataflow.py
"""
        Helper method to check the state of one job in dataflow for this task
        if job failed raise exception
        :return: True if job is done.
        :rtype: bool
        :raise: Exception
        """
        if DataflowJobStatus.JOB_STATE_DONE == job['currentState']:
            return True
        elif DataflowJobStatus.JOB_STATE_FAILED == job['currentState']:
            raise Exception("Google Cloud Dataflow job {} has failed.".format(
                job['name']))
        elif DataflowJobStatus.JOB_STATE_CANCELLED == job['currentState']:
            raise Exception("Google Cloud Dataflow job {} was cancelled.".format(
                job['name']))
        elif DataflowJobStatus.JOB_STATE_RUNNING == job['currentState'] and \
                DataflowJobType.JOB_TYPE_STREAMING == job['type']:
            return True
        elif job['currentState'] in {DataflowJobStatus.JOB_STATE_RUNNING,
                                     DataflowJobStatus.JOB_STATE_PENDING}:
            return False
        self.log.debug("Current job: %s", str(job))
        raise Exception(
            "Google Cloud Dataflow job {} was unknown state: {}".format(job['name'], job['currentState'])
        )
    def wait_for_done(self) -> None: