def _populate_fields(self, metric, fields):
"""Fill in the fields attribute of a metric protocol buffer.
Args:
metric (metrics_pb2.MetricsData): a metrics protobuf to populate
fields (list of (key, value) tuples): normalized metric fields
Raises:
MonitoringInvalidFieldTypeError: if a field has a value of unknown type
"""
for key, value in fields:
field = metric.fields.add()
field.name = key
if isinstance(value, basestring):
field.type = metrics_pb2.MetricsField.STRING
field.string_value = value
elif isinstance(value, bool):
field.type = metrics_pb2.MetricsField.BOOL
field.bool_value = value
elif isinstance(value, int):
field.type = metrics_pb2.MetricsField.INT
field.int_value = value
else:
raise errors.MonitoringInvalidFieldTypeError(
self._name, key, value)
def _populate_field_descriptors(self, data_set, fields):
"""Populate `field_descriptor` in MetricsDataSet.
Args:
data_set (new_metrics_pb2.MetricsDataSet): a data set protobuf to
populate
fields (list of (key, value) tuples): normalized metric fields
Raises:
MonitoringInvalidFieldTypeError: if a field has a value of unknown type
"""
field_type = new_metrics_pb2.MetricsDataSet.MetricFieldDescriptor
for key, value in fields:
descriptor = data_set.field_descriptor.add()
descriptor.name = key
if isinstance(value, basestring):
descriptor.field_type = field_type.STRING
elif isinstance(value, bool):
descriptor.field_type = field_type.BOOL
elif isinstance(value, int):
descriptor.field_type = field_type.INT64
else:
raise errors.MonitoringInvalidFieldTypeError(
self._name, key, value)
def validate_value(self, metric_name, value):
if not isinstance(value, self.allowed_python_types):
raise errors.MonitoringInvalidFieldTypeError(
metric_name, self.name, value)
