coco_pipe.io.config =================== .. py:module:: coco_pipe.io.config .. autoapi-nested-parse:: Configuration Schemas for IO ============================ Pydantic models for verifying dataset configurations. Classes ------- TabularConfig Configuration for tabular data (CSV, Excel). BIDSConfig Configuration for BIDS-compliant datasets. EmbeddingConfig Configuration for pre-computed embeddings. DatasetConfig Union container for any dataset configuration. Author: Antigravity Date: 2026-01-16 Classes ------- .. autoapisummary:: coco_pipe.io.config.BaseDatasetConfig coco_pipe.io.config.TabularConfig coco_pipe.io.config.BIDSConfig coco_pipe.io.config.EmbeddingConfig coco_pipe.io.config.DatasetConfig Module Contents --------------- .. py:class:: BaseDatasetConfig(/, **data: Any) Bases: :py:obj:`pydantic.BaseModel` !!! abstract "Usage Documentation" [Models](../concepts/models.md) A base class for creating Pydantic models. .. attribute:: __class_vars__ The names of the class variables defined on the model. .. attribute:: __private_attributes__ Metadata about the private attributes of the model. .. attribute:: __signature__ The synthesized `__init__` [`Signature`][inspect.Signature] of the model. .. attribute:: __pydantic_complete__ Whether model building is completed, or if there are still undefined fields. .. attribute:: __pydantic_core_schema__ The core schema of the model. .. attribute:: __pydantic_custom_init__ Whether the model has a custom `__init__` function. .. attribute:: __pydantic_decorators__ Metadata containing the decorators defined on the model. This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1. .. attribute:: __pydantic_generic_metadata__ A dictionary containing metadata about generic Pydantic models. The `origin` and `args` items map to the [`__origin__`][genericalias.__origin__] and [`__args__`][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the `parameter` item maps to the `__parameter__` attribute of generic classes. .. attribute:: __pydantic_parent_namespace__ Parent namespace of the model, used for automatic rebuilding of models. .. attribute:: __pydantic_post_init__ The name of the post-init method for the model, if defined. .. attribute:: __pydantic_root_model__ Whether the model is a [`RootModel`][pydantic.root_model.RootModel]. .. attribute:: __pydantic_serializer__ The `pydantic-core` `SchemaSerializer` used to dump instances of the model. .. attribute:: __pydantic_validator__ The `pydantic-core` `SchemaValidator` used to validate instances of the model. .. attribute:: __pydantic_fields__ A dictionary of field names and their corresponding [`FieldInfo`][pydantic.fields.FieldInfo] objects. .. attribute:: __pydantic_computed_fields__ A dictionary of computed field names and their corresponding [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] objects. .. attribute:: __pydantic_extra__ A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra] is set to `'allow'`. .. attribute:: __pydantic_fields_set__ The names of fields explicitly set during instantiation. .. attribute:: __pydantic_private__ Values of private attributes set on the model instance. .. py:attribute:: path :type: pathlib.Path :value: None .. py:attribute:: subjects :type: Optional[Union[int, List[Union[str, int]]]] :value: None .. py:class:: TabularConfig(/, **data: Any) Bases: :py:obj:`BaseDatasetConfig` Configuration for TabularDataset. .. py:attribute:: mode :type: Literal['tabular'] :value: 'tabular' .. py:attribute:: target_col :type: Optional[str] :value: None .. py:attribute:: index_col :type: Optional[Union[str, int]] :value: None .. py:attribute:: sep :type: str :value: None .. py:attribute:: header :type: Optional[Union[int, List[int]]] :value: 0 .. py:attribute:: sheet_name :type: Union[str, int] :value: 0 .. py:attribute:: columns_to_dims :type: Optional[List[str]] :value: None .. py:attribute:: col_sep :type: str :value: '_' .. py:attribute:: meta_columns :type: Optional[List[str]] :value: None .. py:attribute:: clean :type: bool :value: False .. py:attribute:: clean_kwargs :type: Dict[str, Any] :value: None .. py:attribute:: select_kwargs :type: Dict[str, Any] :value: None .. py:class:: BIDSConfig(/, **data: Any) Bases: :py:obj:`BaseDatasetConfig` Configuration for BIDSDataset. .. py:attribute:: mode :type: Literal['bids'] :value: 'bids' .. py:attribute:: task :type: Optional[str] :value: None .. py:attribute:: session :type: Optional[Union[str, List[str]]] :value: None .. py:attribute:: datatype :type: str :value: 'eeg' .. py:attribute:: suffix :type: Optional[str] :value: None .. py:attribute:: loading_mode :type: str :value: None .. py:attribute:: window_length :type: Optional[float] :value: None .. py:attribute:: stride :type: Optional[float] :value: None .. py:class:: EmbeddingConfig(/, **data: Any) Bases: :py:obj:`BaseDatasetConfig` Configuration for EmbeddingDataset. .. py:attribute:: mode :type: Literal['embedding'] :value: 'embedding' .. py:attribute:: pattern :type: str :value: '*.pkl' .. py:attribute:: dims :type: Tuple[str, Ellipsis] :value: ('obs', 'feature') .. py:attribute:: coords :type: Optional[Dict[str, Union[List, Any]]] :value: None .. py:attribute:: task :type: Optional[str] :value: None .. py:attribute:: run :type: Optional[str] :value: None .. py:attribute:: processing :type: Optional[str] :value: None .. py:class:: DatasetConfig(/, **data: Any) Bases: :py:obj:`pydantic.BaseModel` Master configuration container for IO. .. py:attribute:: dataset :type: Union[TabularConfig, BIDSConfig, EmbeddingConfig] :value: None