**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
template='{{var.value.gcp_dataflow_base}}',
           parameters={
               'inputFile': "gs://bucket/input/my_input.txt",
               'outputFile': "gs://bucket/output/my_output.txt"
           },
           gcp_conn_id='airflow-conn-id',
           dag=my-dag)
    ``template``, ``dataflow_default_options``, ``parameters``, and ``job_name`` are
    templated so you can use variables in them.
    Note that ``dataflow_default_options`` is expected to save high-level options
    for project information, which apply to all dataflow operators in the DAG.
        .. seealso::
            https://cloud.google.com/dataflow/docs/reference/rest/v1b3
            /LaunchTemplateParameters
            https://cloud.google.com/dataflow/docs/reference/rest/v1b3/RuntimeEnvironment
            For more detail on job template execution have a look at the reference:
            https://cloud.google.com/dataflow/docs/templates/executing-templates
    """
    template_fields = [
        'template',
        'job_name',
        'options',
        'parameters',
        'project_id',
        'location',
        'gcp_conn_id'
    ]
    ui_color = '#0273d4'
    @apply_defaults
    def __init__(