EventRulePutRequest

pydantic model openapi_client.models.event_rule_put_request.EventRulePutRequest

Body is unused for enable-rule/disable-rule and for run-job types that only need the rule name. Fields below are action- and rule-specific.

Fields:

• auto_ml_request (bool | None)

• dataset_ids (List[str] | None)

• document_output_format (List[str] | None)

• end_date (str | None)

• file_ids (List[str] | None)

• file_processing_mode (str | None)

• from_time (str | None)

• max_capacity (float | int | None)

• modalities (List[str] | None)

• modality_configs (Dict[str, Any] | None)

• number_of_workers (int | None)

• start_date (str | None)

• target_dataset_id (str | None)

• target_dataset_provided (bool | None)

• timeout (int | None)

• to_time (str | None)

field number_of_workers: Optional[StrictInt] = None (alias 'NumberOfWorkers')

DataProfiling run-job or update-config. Integer 2-10. update-config defaults to 5 when omitted.

field timeout: Optional[StrictInt] = None (alias 'Timeout')

Minutes. DataProfiling run-job 1-480. update-config defaults to 240 (max 480).

field auto_ml_request: Optional[StrictBool] = None (alias 'autoMLRequest')

Optional DataProfiling run-job flag. Defaults to false.

field file_processing_mode: Optional[StrictStr] = None (alias 'FileProcessingMode')

BDAExtractor run-job. Extra keys on that body return IPV-1008.

field dataset_ids: Optional[List[StrictStr]] = None (alias 'DatasetIds')

Dataset IDs for BDAExtractor run-job, and required for DataProfiling run-job where the list is capped at 10 and every dataset must have data profiling enabled. Do not add a lowercase datasetIds property — openapi-generator maps both to the same dataset_ids attribute and the later declaration overwrites the earlier, so typed clients could not send this body at all. The handler still accepts datasetIds for backwards compatibility.

field file_ids: Optional[List[StrictStr]] = None (alias 'FileIds')

BDAExtractor run-job file IDs.

field from_time: Optional[StrictStr] = None (alias 'FromTime')

BDAExtractor run-job start bound; N/A when omitted.

field to_time: Optional[StrictStr] = None (alias 'ToTime')

BDAExtractor run-job end bound; N/A when omitted.

field target_dataset_provided: Optional[StrictBool] = None (alias 'TargetDatasetProvided')

BDAExtractor run-job. When true, TargetDatasetId is required (IPV-1008 if missing or N/A).

field target_dataset_id: Optional[StrictStr] = None (alias 'TargetDatasetId')

field start_date: Optional[StrictStr] = None (alias 'startDate')

Required with endDate for Observability and CloudwatchLogsToS3 run-job. Format YYYY-MM-DD.

field end_date: Optional[StrictStr] = None (alias 'endDate')

Required with startDate for those log backfill jobs. YYYY-MM-DD.

field max_capacity: Optional[Union[StrictFloat, StrictInt]] = None (alias 'MaxCapacity')

BDAExtractor update-config. 0.0625 or 1. Defaults to 1.

field modalities: Optional[List[StrictStr]] = None (alias 'Modalities')

BDAExtractor update-config list of modality names.

field document_output_format: Optional[List[StrictStr]] = None (alias 'DocumentOutputFormat')

BDAExtractor update-config. Allowed PLAIN_TEXT, HTML, MARKDOWN, CSV.

field modality_configs: Optional[Dict[str, Any]] = None (alias 'ModalityConfigs')

BDAExtractor update-config map keyed by modality. Must include an entry for every selected modality.

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 EventRulePutRequest 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 EventRulePutRequest from a dict

Return type:

Optional[Self]