File size: 2,618 Bytes
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from aws_lambda_powertools.metrics.exceptions import SchemaValidationError
from aws_lambda_powertools.metrics.provider.datadog import DatadogMetrics
from aws_lambda_powertools.metrics.provider.datadog.warnings import DatadogDataValidationWarning
def test_get_namespace_property(namespace):
# GIVEN DatadogMetrics is initialized
my_metrics = DatadogMetrics(namespace=namespace)
# WHEN we try to access the namespace property
# THEN namespace property must be present
assert my_metrics.namespace == namespace
def test_set_namespace_property(namespace):
# GIVEN DatadogMetrics is initialized
my_metrics = DatadogMetrics()
# WHEN we set the namespace property after ther initialization
my_metrics.namespace = namespace
# THEN namespace property must be present
assert my_metrics.namespace == namespace
def test_default_tags_across_instances():
# GIVEN DatadogMetrics is initialized and we persist a set of default tags
my_metrics = DatadogMetrics()
my_metrics.set_default_tags(environment="test", log_group="/lambda/test")
# WHEN a new DatadogMetrics instance is created
same_metrics = DatadogMetrics()
# THEN default tags should also be present in the new instance
assert "environment" in same_metrics.default_tags
def test_invalid_datadog_metric_name():
metrics = DatadogMetrics()
# GIVEN three metrics names with different invalid names
metric_name_1 = "1_metric" # Metric name must not start with number
metric_name_2 = "metric_ç" # Metric name must not contains unicode characters
metric_name_3 = "".join(["x" for _ in range(201)]) # Metric name must have less than 200 characters
# WHEN we try to validate those metrics names
# THEN must be False
with pytest.raises(SchemaValidationError, match="Invalid metric name.*"):
metrics.add_metric(name=metric_name_1, value=1)
with pytest.raises(SchemaValidationError, match="Invalid metric name.*"):
metrics.add_metric(name=metric_name_2, value=1)
with pytest.raises(SchemaValidationError, match="Invalid metric name.*"):
metrics.add_metric(name=metric_name_3, value=1)
def test_invalid_datadog_metric_tag():
metrics = DatadogMetrics()
# GIVEN three metrics with different invalid tags
metric_tag_1 = "".join(["x" for _ in range(201)]) # Metric tags must have less than 200 characters
# WHEN we try to validate those metrics tags
# THEN must be False
with pytest.warns(DatadogDataValidationWarning):
metrics.add_metric(name="metric_2", value=1, tag1=metric_tag_1)
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