DeferredFactory

class pymc_marketing.serialization.DeferredFactory(**data)

Serializable recipe for creating objects with non-serializable state.

Instead of storing a live object (e.g., a Prior with PyTensor tensor parameters), store the factory function path and its scalar arguments. Call resolve() at build_model() time to create the actual object.

Methods

DeferredFactory.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
DeferredFactory.construct([_fields_set])
DeferredFactory.copy(*[, include, exclude, ...])	Returns a copy of the model.
DeferredFactory.dict(*[, include, exclude, ...])
DeferredFactory.from_dict(data)	Reconstruct a DeferredFactory from a dict.
DeferredFactory.from_orm(obj)
DeferredFactory.json(*[, include, exclude, ...])
DeferredFactory.model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
DeferredFactory.parse_file(path, *[, ...])
DeferredFactory.parse_obj(obj)
DeferredFactory.parse_raw(b, *[, ...])
DeferredFactory.resolve()	Import the factory function and call it with kwargs.
DeferredFactory.schema([by_alias, ref_template])
DeferredFactory.schema_json(*[, by_alias, ...])
DeferredFactory.to_dict()	Serialize the deferred factory to a dict.
DeferredFactory.update_forward_refs(**localns)
DeferredFactory.validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
factory
kwargs