(
        self,
        *,
        opinion_author: Optional[int | Set[int]] = None,
        decision_direction: Optional[str | Set[str]] = None,
        issue_area: Optional[int | Set[int]] = None,
        date_range: Optional[Tuple[Optional[str], Optional[str]]] = None,
        min_len: Optional[int] = None,
        limit: Optional[int] = None,
    )
Iterate over decisions in this dataset, optionally filtering by a variety
        of metadata and/or text length, and yield text + metadata pairs,
        in chronological order by decision date.

        Args:
            opinion_author: Filter decisions by the name(s) of the majority opinion's author,
                coded as an integer whose mapping is given in
                :attr:`SupremeCourt.opinion_author_codes`.
            decision_direction: Filter decisions by the ideological direction
                of the majority's decision; see
                :attr:`SupremeCourt.decision_directions`.
            issue_area: Filter decisions by the issue area of the case's subject matter,
                coded as an integer whose mapping is given in
                :attr:`SupremeCourt.issue_area_codes`.
            date_range: Filter decisions by the date on which they were decided;
                both start and end date must be specified, but a null value for either
                will be replaced by the min/max date available for the dataset.
            min_len: Filter decisions by the length (# characters) of their text content.
            limit: Yield no more than ``limit`` decisions that match all specified filters.

        Yields:
            Text of the next decision in dataset passing all filters,
            and its corresponding metadata.

        Raises:
            ValueError: If any filtering options are invalid.
Iterate over decisions in this dataset, optionally filtering by a variety
        of metadata and/or text length, and yield text + metadata pairs,
        in chronological order by decision date.
Iterate over decisions in this dataset optionally filtering by a variety of metadata and / or text length and yield text + metadata pairs in chronological order by decision date .
def records(
        self,
        *,
        opinion_author: Optional[int | Set[int]] = None,
        decision_direction: Optional[str | Set[str]] = None,
        issue_area: Optional[int | Set[int]] = None,
        date_range: Optional[Tuple[Optional[str], Optional[str]]] = None,
        min_len: Optional[int] = None,
        limit: Optional[int] = None,
    ) -> Iterable[types.Record]:
        """
        Iterate over decisions in this dataset, optionally filtering by a variety
        of metadata and/or text length, and yield text + metadata pairs,
        in chronological order by decision date.

        Args:
            opinion_author: Filter decisions by the name(s) of the majority opinion's author,
                coded as an integer whose mapping is given in
                :attr:`SupremeCourt.opinion_author_codes`.
            decision_direction: Filter decisions by the ideological direction
                of the majority's decision; see
                :attr:`SupremeCourt.decision_directions`.
            issue_area: Filter decisions by the issue area of the case's subject matter,
                coded as an integer whose mapping is given in
                :attr:`SupremeCourt.issue_area_codes`.
            date_range: Filter decisions by the date on which they were decided;
                both start and end date must be specified, but a null value for either
                will be replaced by the min/max date available for the dataset.
            min_len: Filter decisions by the length (# characters) of their text content.
            limit: Yield no more than ``limit`` decisions that match all specified filters.

        Yields:
            Text of the next decision in dataset passing all filters,
            and its corresponding metadata.

        Raises:
            ValueError: If any filtering options are invalid.
        """
        filters = self._get_filters(
            opinion_author, decision_direction, issue_area, date_range, min_len
        )
        for record in itertools.islice(self._filtered_iter(filters), limit):
            yield types.Record(text=record.pop("text"), meta=record)
def records ( self , * , opinion_author : Optional [ int | Set [ int ] ] = None , decision_direction : Optional [ str | Set [ str ] ] = None , issue_area : Optional [ int | Set [ int ] ] = None , date_range : Optional [ Tuple [ Optional [ str ] , Optional [ str ] ] ] = None , min_len : Optional [ int ] = None , limit : Optional [ int ] = None , ) -> Iterable [ types . Record ] : filters = self . _get_filters ( opinion_author , decision_direction , issue_area , date_range , min_len ) for record in itertools . islice ( self . _filtered_iter ( filters ) , limit ) : yield types . Record ( text = record . pop ( "text" ) , meta = record )