@classmethod
    def from_list(
        cls,
        mapping: List[dict],
        features: Optional[Features] = None,
        info: Optional[DatasetInfo] = None,
        split: Optional[NamedSplit] = None,
    ) -> "Dataset":
        """
        Convert a list of dicts to a `pyarrow.Table` to create a [`Dataset`]`.

        Note that the keys of the first entry will be used to determine the dataset columns,
        regardless of what is passed to features.

        Important: a dataset created with from_list() lives in memory
        and therefore doesn't have an associated cache directory.
        This may change in the feature, but in the meantime if you
        want to reduce memory usage you should write it back on disk
        and reload using e.g. save_to_disk / load_from_disk.