ActiveLabsEvent¶
- pydantic model controller.events.ActiveLabsEvent¶
Current count of the number of active labs.
Notes
This is really a gauge metric that is measured periodically, not an event. For now, the Nublado controller uses the event system to log this metric, since that’s the system we have in place. If we later have a proper metrics system for storing measurements, this event should move to that system.
- Parameters:
data (
Any
)
Show JSON schema
{ "title": "ActiveLabsEvent", "description": "Current count of the number of active labs.\n\nNotes\n-----\nThis is really a gauge metric that is measured periodically, not an event.\nFor now, the Nublado controller uses the event system to log this metric,\nsince that's the system we have in place. If we later have a proper\nmetrics system for storing measurements, this event should move to that\nsystem.", "type": "object", "properties": { "count": { "description": "Number of currently-running labs", "title": "Active labs", "type": "integer" } }, "required": [ "count" ] }
- Fields:
- field count: int [Required]¶
Number of currently-running labs
- asdict()¶
Returns this model in dictionary form. This method differs from pydantic’s dict by converting all values to their Avro representation. It also doesn’t provide the exclude, include, by_alias, etc. parameters that dict provides.
- classmethod fake(**data)¶
Creates a fake instance of the model.
- Attributes:
data: Dict[str, Any] represent the user values to use in the instance
- Parameters:
data (
Any
)- Return type:
AvroBaseModel
- serialize(serialization_type='avro')¶
Overrides the base AvroModel’s serialize method to inject this class’s standardization factory method