DiagnosticValidationConfig#
- class rojak.orchestrator.configuration.DiagnosticValidationConfig(*, validation_conditions: list[DiagnosticValidationCondition], min_group_size: Annotated[int, Gt(gt=0), Strict(strict=True)] = 20, spatial_group_by_strategy: SpatialGroupByStrategy | None = None, aggregation_metric: AggregationMetricOption | None = None)[source]#
Bases:
BaseConfigModelCreate a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- Parameters:
validation_conditions (list[DiagnosticValidationCondition])
min_group_size (Annotated[int, Gt(gt=0), Strict(strict=True)])
spatial_group_by_strategy (SpatialGroupByStrategy | None)
aggregation_metric (AggregationMetricOption | None)
- __init__(**data: Any) None[source]#
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- Parameters:
data (Any)
- Return type:
None
Methods
__init__(**data)Create a new model by parsing and validating input data from keyword arguments.
check_all_groupby_settings_are_specified()check_conditions_are_unique()construct([_fields_set])copy(*[, include, exclude, update, deep])Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])from_orm(obj)from_yaml(path)json(*[, include, exclude, by_alias, ...])model_construct([_fields_set])Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])Generates a JSON schema for a model class.
model_parametrized_name(params)Compute the class name for parametrizations of generic classes.
model_post_init(context, /)Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])parse_obj(obj)parse_raw(b, *[, content_type, encoding, ...])schema([by_alias, ref_template])schema_json(*[, by_alias, ref_template])update_forward_refs(**localns)validate(value)Attributes
model_computed_fieldsmodel_configConfiguration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extraGet extra fields set during validation.
model_fieldsmodel_fields_setReturns the set of fields that have been explicitly set on this model instance.
validation_conditionsmin_group_sizespatial_group_by_strategyaggregation_metric