EventRuleMetricDatapoint¶

pydantic model openapi_client.models.event_rule_metric_datapoint.EventRuleMetricDatapoint¶

CloudWatch datapoint after JsonSerializer stringifies Timestamp. Handler requests Statistics=[‘Average’]; SampleCount and Unit are commonly present. Sum, Minimum, and Maximum may appear if CloudWatch includes them on the datapoint.

Fields:

average (float | int | None)
maximum (float | int | None)
minimum (float | int | None)
sample_count (float | int | None)
sum (float | int | None)
timestamp (str | None)
unit (str | None)

field timestamp: Optional[StrictStr] = None (alias 'Timestamp')¶

field average: Optional[Union[StrictFloat, StrictInt]] = None (alias 'Average')¶

field unit: Optional[StrictStr] = None (alias 'Unit')¶

field sample_count: Optional[Union[StrictFloat, StrictInt]] = None (alias 'SampleCount')¶

field sum: Optional[Union[StrictFloat, StrictInt]] = None (alias 'Sum')¶

field minimum: Optional[Union[StrictFloat, StrictInt]] = None (alias 'Minimum')¶

field maximum: Optional[Union[StrictFloat, StrictInt]] = None (alias 'Maximum')¶

to_str()¶

Returns the string representation of the model using alias

Return type:: str

to_json()¶

Returns the JSON representation of the model using alias

Return type:: str

classmethod from_json(json_str)¶

Create an instance of EventRuleMetricDatapoint from a JSON string

Return type:: Optional[Self]

to_dict()¶

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:: Dict[str, Any]

classmethod from_dict(obj)¶

Create an instance of EventRuleMetricDatapoint from a dict

Return type:: Optional[Self]