ArqQueueStatsEvent#

pydantic model safir.metrics.arq.ArqQueueStatsEvent#

Statistics for an Arq queue.

Parameters:

data (Any)

Fields:

num_queued (int)
queue (str)

field num_queued: int [Required]#: The number of jobs that are currently in the queue.

field queue: str [Required]#: The queue that these stats apply to.

classmethod avro_schema(case_type=None, **kwargs)#

Parameters:: case_type (str | None, default: None)
Return type:: str

classmethod avro_schema_to_python(parent=None, case_type=None)#

Parameters:

parent (Type[AvroModel] | None, default: None)
case_type (str | None, default: None)

Return type:

Dict[str, Any]

classmethod deserialize(data, serialization_type='avro', create_instance=True, writer_schema=None)#

Overloads:

cls (Type[TSelf]), data (bytes), serialization_type (serialization.SerializationType), create_instance (Literal[True]), writer_schema (Optional[Union[JsonDict, Type[‘AvroModel’]]]) → TSelf
cls (Type[TSelf]), data (bytes), serialization_type (serialization.SerializationType), create_instance (Literal[False]), writer_schema (Optional[Union[JsonDict, Type[‘AvroModel’]]]) → JsonDict
cls (Type[TSelf]), data (bytes), serialization_type (serialization.SerializationType), create_instance (bool), writer_schema (Optional[Union[JsonDict, Type[‘AvroModel’]]]) → Union[TSelf, JsonDict]

classmethod deserialize_to_python(data, serialization_type='avro', writer_schema=None)#

Parameters:

data (bytes)
serialization_type (Literal['avro', 'avro-json'], default: 'avro')
writer_schema (Dict[str, Any] | Type[AvroModel] | None, default: None)

Return type:

dict

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

classmethod generate_schema(schema_type='avro')#

Parameters:: schema_type (Literal['avro', 'avro-json'], default: 'avro')
Return type:: OrderedDict | None

classmethod get_fields()#

Return type:: List[FieldProtocol]

classmethod get_fullname()#

Fullname is composed of two parts: a name and a namespace separated by a dot. A namespace is a dot-separated sequence of such names. The empty string may also be used as a namespace to indicate the null namespace. Equality of names (including field names and enum symbols) as well as fullnames is case-sensitive.

Return type:: str

classmethod json_schema(*args, **kwargs)#

Parameters:

args (Any)
kwargs (Any)

Return type:

str

classmethod validate_structure()#

Do runtime validation of fields.

Make sure all of the fields are compatible with the backing datastore (InfluxDB at the moment).

Return type:: None

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.

Return type:: Dict[str, Any]

serialize(serialization_type='avro')#

Overrides the base AvroModel’s serialize method to inject this class’s standardization factory method

Parameters:: serialization_type (Literal['avro', 'avro-json'], default: 'avro')
Return type:: bytes

to_dict()#

Return type:: Dict[str, Any]

to_json(**kwargs)#

Parameters:: kwargs (Any)
Return type:: str

validate_avro()#

Validate that instance matches the avro schema

Return type:: bool