code: def test_get_best_value():
      tracker = metrics_tracking.MetricsTracker()
      tracker.register("metric_min", "min")
      tracker.register("metric_max", "max")
      assert tracker.get_best_value("metric_min") is None
  
      tracker.set_history(
          "metric_min",
          [
              metrics_tracking.MetricObservation(1.0, 0),
              metrics_tracking.MetricObservation(2.0, 1),
              metrics_tracking.MetricObservation(3.0, 2),
          ],
      )
      tracker.set_history(
          "metric_max",
          [
              metrics_tracking.MetricObservation(1.0, 0),
              metrics_tracking.MetricObservation(2.0, 1),
              metrics_tracking.MetricObservation(3.0, 2),
          ],
      )
      assert tracker.get_best_value("metric_min") == 1.0
      assert tracker.get_best_value("metric_max") == 3.0
  
imports: import random
  import numpy
  import pytest
  from keras_tuner.backend.keras import losses
  from keras_tuner.backend.keras import metrics
  from keras_tuner.engine import metrics_tracking
label_desc: Use image node_id 9 for calling a global function with example usage: test_get_best_value() without return types