EventRuleMetrics

pydantic model openapi_client.models.event_rule_metrics.EventRuleMetrics

EventRuleMetrics

Fields:

• end_time (str | None)

• execution_history (List[openapi_client.models.event_rule_bda_execution_record.EventRuleBdaExecutionRecord] | None)

• invocations (openapi_client.models.event_rule_cloud_watch_metric.EventRuleCloudWatchMetric | None)

• rule_name (str | None)

• start_time (str | None)

• triggered_rules (openapi_client.models.event_rule_cloud_watch_metric.EventRuleCloudWatchMetric | None)

field rule_name: Optional[StrictStr] = None (alias 'RuleName')

field start_time: Optional[StrictStr] = None (alias 'StartTime')

Window start as YYYY-MM-DD HH:MM:SS (UTC).

field end_time: Optional[StrictStr] = None (alias 'EndTime')

Window end as YYYY-MM-DD HH:MM:SS (UTC).

field invocations: Optional[EventRuleCloudWatchMetric] = None (alias 'Invocations')

field triggered_rules: Optional[EventRuleCloudWatchMetric] = None (alias 'TriggeredRules')

field execution_history: Optional[List[EventRuleBdaExecutionRecord]] = None (alias 'ExecutionHistory')

Present only when the rule name contains BDAExtractor. Glue fetch failures return an empty list, not an error.

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 EventRuleMetrics 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 EventRuleMetrics from a dict

Return type:

Optional[Self]