DataConfig#
- class pymc_marketing.mmm.builders.schema.DataConfig(**data)[source]#
Schema for data path configuration.
Methods
DataConfig.__init__(**data)Create a new model by parsing and validating input data from keyword arguments.
DataConfig.construct([_fields_set])DataConfig.copy(*[, include, exclude, ...])Returns a copy of the model.
DataConfig.dict(*[, include, exclude, ...])DataConfig.from_orm(obj)DataConfig.json(*[, include, exclude, ...])DataConfig.model_construct([_fields_set])Creates a new instance of the
Modelclass with validated data.DataConfig.model_copy(*[, update, deep])!!! abstract "Usage Documentation"
DataConfig.model_dump(*[, mode, include, ...])!!! abstract "Usage Documentation"
DataConfig.model_dump_json(*[, indent, ...])!!! abstract "Usage Documentation"
DataConfig.model_json_schema([by_alias, ...])Generates a JSON schema for a model class.
Compute the class name for parametrizations of generic classes.
DataConfig.model_post_init(context, /)Override this method to perform additional initialization after
__init__andmodel_construct.DataConfig.model_rebuild(*[, force, ...])Try to rebuild the pydantic-core schema for the model.
DataConfig.model_validate(obj, *[, strict, ...])Validate a pydantic model instance.
DataConfig.model_validate_json(json_data, *)!!! abstract "Usage Documentation"
DataConfig.model_validate_strings(obj, *[, ...])Validate the given object with string data against the Pydantic model.
DataConfig.parse_file(path, *[, ...])DataConfig.parse_obj(obj)DataConfig.parse_raw(b, *[, content_type, ...])DataConfig.schema([by_alias, ref_template])DataConfig.schema_json(*[, by_alias, ...])DataConfig.update_forward_refs(**localns)DataConfig.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.
X_pathy_path