**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
issues check: https://issues.apache.org/jira/browse/BEAM-1251
    :type py_interpreter: str
    :param py_requirements: Additional python package(s) to install.
        If a value is passed to this parameter, a new virtual environment has been created with
        additional packages installed.
        You could also install the apache_beam package if it is not installed on your system or you want
        to use a different version.
    :type py_requirements: List[str]
    :param py_system_site_packages: Whether to include system_site_packages in your virtualenv.
        See virtualenv documentation for more information.
        This option is only relevant if the ``py_requirements`` parameter is passed.
    :param gcp_conn_id: The connection ID to use connecting to Google Cloud Platform.
    :type gcp_conn_id: str
    :param project_id: Optional, the GCP project ID in which to start a job.
        If set to None or missing, the default project_id from the GCP connection is used.
    :type project_id: str
    :param location: Job location.
    :type location: str
    :param delegate_to: The account to impersonate, if any.
        For this to work, the service account making the request must have
        domain-wide  delegation enabled.
    :type delegate_to: str
    :param poll_sleep: The time in seconds to sleep between polling Google
        Cloud Platform for the dataflow job status while the job is in the
        JOB_STATE_RUNNING state.
    :type poll_sleep: int
    """
    template_fields = ['options', 'dataflow_default_options', 'job_name', 'py_file']
    @apply_defaults
    def __init__(