Method from_directory

src/datasets/info.py:248–279

Create [`DatasetInfo`] from the JSON file in `dataset_info_dir`. This function updates all the dynamically generated fields (num_examples, hash, time of creation,...) of the [`DatasetInfo`]. This will overwrite all previous metadata. Args: dataset_info_

(cls, dataset_info_dir: str, storage_options: Optional[dict] = None)

    @classmethod
    def from_directory(cls, dataset_info_dir: str, storage_options: Optional[dict] = None) -> "DatasetInfo":
        """Create [`DatasetInfo`] from the JSON file in `dataset_info_dir`.

        This function updates all the dynamically generated fields (num_examples,
        hash, time of creation,...) of the [`DatasetInfo`].

        This will overwrite all previous metadata.

        Args:
            dataset_info_dir (`str`):
                The directory containing the metadata file. This
                should be the root directory of a specific dataset version.
            storage_options (`dict`, *optional*):
                Key/value pairs to be passed on to the file-system backend, if any.

                <Added version="2.9.0"/>

        Example:

        ```py
        >>> from datasets import DatasetInfo
        >>> ds_info = DatasetInfo.from_directory("/path/to/directory/")
        ```
        """
        fs: fsspec.AbstractFileSystem
        fs, *_ = url_to_fs(dataset_info_dir, **(storage_options or {}))
        logger.debug(f"Loading Dataset info from {dataset_info_dir}")
        if not dataset_info_dir:
            raise ValueError("Calling DatasetInfo.from_directory() with undefined dataset_info_dir.")
        with fs.open(posixpath.join(dataset_info_dir, config.DATASET_INFO_FILENAME), "r", encoding="utf-8") as f:
            dataset_info_dict = json.load(f)
        return cls.from_dict(dataset_info_dict)

    @classmethod
    def from_dict(cls, dataset_info_dict: dict) -> "DatasetInfo":