plaid.storage.common.reader
===========================

.. py:module:: plaid.storage.common.reader

.. autoapi-nested-parse::

   Common storage reader utilities.

   This module provides common utilities for reading dataset metadata, problem definitions,
   and other auxiliary files from disk or downloading them from Hugging Face Hub.



Functions
---------

.. autoapisummary::

   plaid.storage.common.reader.load_infos_from_disk
   plaid.storage.common.reader.load_problem_definitions_from_disk
   plaid.storage.common.reader.load_metadata_from_disk
   plaid.storage.common.reader.load_infos_from_hub
   plaid.storage.common.reader.load_problem_definitions_from_hub
   plaid.storage.common.reader.load_metadata_from_hub


Module Contents
---------------

.. py:function:: load_infos_from_disk(path: Union[str, pathlib.Path]) -> dict[str, Any]

   Load dataset information from a YAML file stored on disk.

   :param path: Directory path containing the `infos.yaml` file.
   :type path: Union[str, Path]

   :returns: Dictionary containing dataset infos.
   :rtype: dict[str, dict[str, str]]


.. py:function:: load_problem_definitions_from_disk(path: Union[str, pathlib.Path]) -> Optional[list[plaid.ProblemDefinition]]

   Load ProblemDefinitions from disk.

   :param path: The directory path for loading.
   :type path: Union[str, Path]

   :returns: List of loaded problem definitions, or None if not found.
   :rtype: Optional[list[ProblemDefinition]]


.. py:function:: load_metadata_from_disk(path: Union[str, pathlib.Path]) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]

   Load dataset metadata from disk.

   :param path: Directory path containing the metadata files.
   :type path: Union[str, Path]

   :returns:     - flat_cst: constant features dictionary
                 - variable_schema: variable schema dictionary
                 - constant_schema: constant schema dictionary
                 - cgns_types: CGNS types dictionary
   :rtype: tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]


.. py:function:: load_infos_from_hub(repo_id: str) -> dict[str, Any]

   Load dataset infos from the Hugging Face Hub.

   Downloads the infos.yaml file from the specified repository and parses it as a dictionary.

   :param repo_id: The repository ID on the Hugging Face Hub.
   :type repo_id: str

   :returns: Dictionary containing dataset infos.
   :rtype: dict[str, dict[str, str]]


.. py:function:: load_problem_definitions_from_hub(repo_id: str) -> Optional[list[plaid.ProblemDefinition]]

   Load ProblemDefinitions from Hugging Face Hub.

   :param repo_id: The repository ID on the Hugging Face Hub.
   :type repo_id: str

   :returns: List of loaded problem definitions, or None if not found.
   :rtype: Optional[list[ProblemDefinition]]


.. py:function:: load_metadata_from_hub(repo_id: str) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]

   Load dataset metadata from Hugging Face Hub.

   :param repo_id: The repository ID on the Hugging Face Hub.
   :type repo_id: str

   :returns:     - flat_cst: constant features dictionary
                 - variable_schema: variable schema dictionary
                 - constant_schema: constant schema dictionary
                 - cgns_types: CGNS types dictionary
   :rtype: tuple[dict[str, Any], dict[str, Any], dict[str, Any], dict[str, Any]]