def serialize(context: MetricsContext) -> List[str]:
config = get_config()
dimension_keys = []
dimensions_properties: Dict[str, str] = {}
for dimension_set in context.get_dimensions():
keys = list(dimension_set.keys())
dimension_keys.append(keys[0:MAX_DIMENSIONS])
dimensions_properties = {**dimensions_properties, **dimension_set}
def create_body() -> Dict[str, Any]:
body: Dict[str, Any] = {
**dimensions_properties,
**context.properties,
}
if not config.disable_metric_extraction:
body["_aws"] = {
**context.meta,
"CloudWatchMetrics": [
{
"Dimensions": dimension_keys,
"Metrics": [],
"Namespace": context.namespace,
},
],
}
return body
current_body: Dict[str, Any] = create_body()
event_batches: List[str] = []
num_metrics_in_current_body = 0
for metric_name, metric in context.metrics.items():
if len(metric.values) == 1:
current_body[metric_name] = metric.values[0]
else:
current_body[metric_name] = metric.values
if not config.disable_metric_extraction:
current_body["_aws"]["CloudWatchMetrics"][0]["Metrics"].append(
{
"Name": metric_name,
"Unit": metric.unit
})
num_metrics_in_current_body += 1
should_serialize: bool = num_metrics_in_current_body == MAX_METRICS_PER_EVENT
if should_serialize:
event_batches.append(json.dumps(current_body))
current_body = create_body()
num_metrics_in_current_body = 0
if not event_batches or num_metrics_in_current_body > 0:
event_batches.append(json.dumps(current_body))
return event_batches
def serialize(context: MetricsContext) -> List[str]:
dimension_keys = []
dimensions_properties: Dict[str, str] = {}
for dimension_set in context.get_dimensions():
keys = list(dimension_set.keys())
dimension_keys.append(keys[0:MAX_DIMENSIONS])
dimensions_properties = {**dimensions_properties, **dimension_set}
def create_body() -> Dict[str, Any]:
return {
**dimensions_properties,
**context.properties,
"_aws": {
**context.meta,
"CloudWatchMetrics": [
{
"Dimensions": dimension_keys,
"Metrics": [],
"Namespace": context.namespace,
},
],
},
}
current_body: Dict[str, Any] = create_body()
event_batches: List[str] = []
for metric_name, metric in context.metrics.items():
if len(metric.values) == 1:
current_body[metric_name] = metric.values[0]
else:
current_body[metric_name] = metric.values
current_body["_aws"]["CloudWatchMetrics"][0]["Metrics"].append({
"Name":
metric_name,
"Unit":
metric.unit
})
should_serialize: bool = len(
current_body["_aws"]["CloudWatchMetrics"][0]
["Metrics"]) == MAX_METRICS_PER_EVENT
if should_serialize:
event_batches.append(json.dumps(current_body))
current_body = create_body()
if not event_batches or current_body["_aws"]["CloudWatchMetrics"][0][
"Metrics"]:
event_batches.append(json.dumps(current_body))
return event_batches
def test_get_dimensions_returns_default_dimensions_if_custom_dimensions_not_set(
):
# arrange
context = MetricsContext()
dimension_key = fake.word()
dimension_value = fake.word()
expected_dimensions = {dimension_key: dimension_value}
context.set_default_dimensions(expected_dimensions)
# act
actual_dimensions = context.get_dimensions()
# assert
assert [expected_dimensions] == actual_dimensions
def serialize(context: MetricsContext) -> List[str]:
dimension_keys = []
dimensions_properties: Dict[str, str] = {}
for dimension_set in context.get_dimensions():
keys = list(dimension_set.keys())
dimension_keys.append(keys[0:MAX_DIMENSIONS])
dimensions_properties = {**dimensions_properties, **dimension_set}
metric_pointers: List[Dict[str, str]] = []
metric_definitions = {
"Dimensions": dimension_keys,
"Metrics": metric_pointers,
"Namespace": context.namespace,
}
cloud_watch_metrics = [metric_definitions]
event_batches: List[str] = []
body: Dict[str, Any] = {
**dimensions_properties,
**context.properties,
"_aws": {
**context.meta, "CloudWatchMetrics": cloud_watch_metrics
},
}
for metric_name, metric in context.metrics.items():
if len(metric.values) == 1:
body[metric_name] = metric.values[0]
else:
body[metric_name] = metric.values
metric_pointers.append({"Name": metric_name, "Unit": metric.unit})
should_serialize: bool = len(
metric_pointers) == MAX_METRICS_PER_EVENT
if should_serialize:
event_batches.append(json.dumps(body))
metric_pointers = []
body["_aws"]["CloudWatchMetrics"][0][
"Metrics"] = metric_pointers
if not event_batches or metric_pointers:
event_batches.append(json.dumps(body))
return event_batches
def test_get_dimensions_returns_merged_custom_and_default_dimensions():
# arrange
context = MetricsContext()
custom_dimension_key = fake.word()
custom_dimension_value = fake.word()
default_dimension_key = fake.word()
default_dimension_value = fake.word()
expected_dimensions = {
default_dimension_key: default_dimension_value,
custom_dimension_key: custom_dimension_value,
}
context.set_default_dimensions(
{default_dimension_key: default_dimension_value})
context.put_dimensions({custom_dimension_key: custom_dimension_value})
# act
actual_dimensions = context.get_dimensions()
# assert
assert [expected_dimensions] == actual_dimensions
def serialize(context: MetricsContext) -> str:
dimension_keys = []
dimensions_properties: Dict[str, str] = {}
for dimension_set in context.get_dimensions():
keys = list(dimension_set.keys())
dimension_keys.append(keys[0:MAX_DIMENSIONS])
dimensions_properties = {**dimensions_properties, **dimension_set}
metric_pointers: List[Dict[str, str]] = []
metric_definitions = {
"Dimensions": dimension_keys,
"Metrics": metric_pointers,
"Namespace": context.namespace,
}
cloud_watch_metrics = [metric_definitions]
body: Dict[str, Any] = {
**dimensions_properties,
**context.properties,
"_aws": {
**context.meta, "CloudWatchMetrics": cloud_watch_metrics
},
}
for metric_name, metric in context.metrics.items():
if len(metric.values) == 1:
body[metric_name] = metric.values[0]
else:
body[metric_name] = metric.values
metric_pointers.append({"Name": metric_name, "Unit": metric.unit})
return json.dumps(body)
def serialize(context: MetricsContext) -> List[str]:
config = get_config()
dimension_keys = []
dimensions_properties: Dict[str, str] = {}
for dimension_set in context.get_dimensions():
keys = list(dimension_set.keys())
dimension_keys.append(keys[0:MAX_DIMENSIONS])
dimensions_properties = {**dimensions_properties, **dimension_set}
def create_body() -> Dict[str, Any]:
body: Dict[str, Any] = {
**dimensions_properties,
**context.properties,
}
if not config.disable_metric_extraction:
body["_aws"] = {
**context.meta,
"CloudWatchMetrics": [
{
"Dimensions": dimension_keys,
"Metrics": [],
"Namespace": context.namespace,
},
],
}
return body
current_body: Dict[str, Any] = {}
event_batches: List[str] = []
num_metrics_in_current_body = 0
# Track if any given metric has data remaining to be serialized
remaining_data = True
# Track batch number to know where to slice metric data
i = 0
while remaining_data:
remaining_data = False
current_body = create_body()
for metric_name, metric in context.metrics.items():
if len(metric.values) == 1:
current_body[metric_name] = metric.values[0]
else:
# Slice metric data as each batch cannot contain more than
# MAX_DATAPOINTS_PER_METRIC entries for a given metric
start_index = i * MAX_DATAPOINTS_PER_METRIC
end_index = (i + 1) * MAX_DATAPOINTS_PER_METRIC
current_body[metric_name] = metric.values[
start_index:end_index]
# Make sure to consume remaining values if we sliced before the end
# of the metric value list
if len(metric.values) > end_index:
remaining_data = True
if not config.disable_metric_extraction:
current_body["_aws"]["CloudWatchMetrics"][0][
"Metrics"].append({
"Name": metric_name,
"Unit": metric.unit
})
num_metrics_in_current_body += 1
if (num_metrics_in_current_body == MAX_METRICS_PER_EVENT):
event_batches.append(json.dumps(current_body))
current_body = create_body()
num_metrics_in_current_body = 0
# iter over missing datapoints
i += 1
if not event_batches or num_metrics_in_current_body > 0:
event_batches.append(json.dumps(current_body))
return event_batches