def serialize_single_metric(metric: Dict, dimension: Dict, namespace: Dict) -> Dict:
""" Helper function to build EMF object from a given metric, dimension and namespace """
my_metrics = MetricManager()
my_metrics.add_metric(**metric)
my_metrics.add_dimension(**dimension)
my_metrics.add_namespace(**namespace)
return my_metrics.serialize_metric_set()
def serialize_single_metric(metric: Dict, dimension: Dict, namespace: str, metadata: Dict = None) -> Dict:
""" Helper function to build EMF object from a given metric, dimension and namespace """
my_metrics = MetricManager(namespace=namespace)
my_metrics.add_metric(**metric)
my_metrics.add_dimension(**dimension)
if metadata is not None:
my_metrics.add_metadata(**metadata)
return my_metrics.serialize_metric_set()
def serialize_metrics(metrics: List[Dict], dimensions: List[Dict], namespace: Dict) -> Dict:
""" Helper function to build EMF object from a list of metrics, dimensions """
my_metrics = MetricManager()
for metric in metrics:
my_metrics.add_metric(**metric)
for dimension in dimensions:
my_metrics.add_dimension(**dimension)
my_metrics.add_namespace(**namespace)
return my_metrics.serialize_metric_set()
def test_metric_manage_metadata_set():
expected_dict = {"setting": "On"}
try:
metric = MetricManager(metadata_set=expected_dict)
assert metric.metadata_set == expected_dict
except AttributeError:
pytest.fail("AttributeError should not be raised")
def serialize_metrics(
metrics: List[Dict], dimensions: List[Dict], namespace: str, metadatas: List[Dict] = None
) -> Dict:
""" Helper function to build EMF object from a list of metrics, dimensions """
my_metrics = MetricManager(namespace=namespace)
for dimension in dimensions:
my_metrics.add_dimension(**dimension)
for metric in metrics:
my_metrics.add_metric(**metric)
if metadatas is not None:
for metadata in metadatas:
my_metrics.add_metadata(**metadata)
if len(metrics) != 100:
return my_metrics.serialize_metric_set()
