PopularInCategoryModelConfig

class rectools.models.popular_in_category.PopularInCategoryModelConfig(*, cls: Optional[Type[ModelBase]] = None, verbose: int = 0, popularity: Popularity = Popularity.N_USERS, period: Optional[timedelta] = None, begin_from: Optional[datetime] = None, add_cold: bool = False, inverse: bool = False, category_feature: str, n_categories: Optional[int] = None, mixing_strategy: MixingStrategy = MixingStrategy.ROTATE, ratio_strategy: RatioStrategy = RatioStrategy.PROPORTIONAL)

Bases: PopularModelConfig

Config for PopularInCategoryModel.

Inherited-members

Parameters

• cls (Optional[Type[ModelBase]]) –

• verbose (int) –

• popularity (Popularity) –

• period (Optional[timedelta]) –

• begin_from (Optional[datetime]) –

• add_cold (bool) –

• inverse (bool) –

• category_feature (str) –

• n_categories (Optional[int]) –

• mixing_strategy (MixingStrategy) –

• ratio_strategy (RatioStrategy) –

Methods

construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
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(_BaseModel__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, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])	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_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.
category_feature
n_categories
mixing_strategy
ratio_strategy

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].