def METHOD_NAME():
    """
    This basic test insures that MetricsCalculator.get_metric() uses MetricsCalculator.get_metrics() correctly.
    In more detail, the purpose of this basic test is to insure that:
        1) MetricsCalculator.get_metric() calls MetricsCalculator.get_metrics() exactly once for specific "metric_name";
        2) MetricsCalculator.get_metric() correctly retrieves result from dictionary, returned by
           MetricsCalculator.get_metrics() by using the specific "metric_name", mentioned above, as the key.
    In the present test case, the role of "ExecutionEngine" is limited to providing the required constructor argument to
    the "MetricsCalculator" class (one of whose methods is under test); hence, a "DummyExecutionEngine" is employed.
    The "with mock.patch" is used judiciously, trading off the focus on the functionality under test (i.e., avoiding
    "test leakage") against going as far as mocking all non-essential methods and properties, favoring code readability.
    """
    class DummyExecutionEngine:
        pass
    execution_engine = cast(ExecutionEngine, DummyExecutionEngine)
    metrics_calculator = MetricsCalculator(execution_engine=execution_engine)
    metric_name = "my_metric_name"
    actual_metric_value = "my_metric_value"
    metric_domain_kwargs: dict = {}
    with mock.patch(
        "great_expectations.validator.metrics_calculator.MetricsCalculator.get_metrics",
        return_value={metric_name: actual_metric_value},
    ) as mock_get_metrics_method:
        metric_configuration = MetricConfiguration(
            metric_name=metric_name,
            metric_domain_kwargs=metric_domain_kwargs,
        )
        resolved_metric_value: Any = metrics_calculator.get_metric(
            metric=metric_configuration
        )
        mock_get_metrics_method.assert_called_once_with(
            metrics={metric_name: metric_configuration}
        )
        assert resolved_metric_value == actual_metric_value