Function range

python/ray/data/read_api.py:258–312

Creates a :class:`~ray.data.Dataset` from a range of integers [0..n). This function allows for easy creation of synthetic datasets for testing or benchmarking :ref:`Ray Data `. The column name defaults to "id". Examples: >>> import ray >>> ds = ray.data.range(100

(
    n: int,
    *,
    parallelism: int = -1,
    concurrency: Optional[int] = None,
    override_num_blocks: Optional[int] = None,
)

@PublicAPI
def range(
    n: int,
    *,
    parallelism: int = -1,
    concurrency: Optional[int] = None,
    override_num_blocks: Optional[int] = None,
) -> Dataset:
    """Creates a :class:`~ray.data.Dataset` from a range of integers [0..n).

    This function allows for easy creation of synthetic datasets for testing or
    benchmarking :ref:`Ray Data <data>`. The column name defaults to "id".

    Examples:

        >>> import ray
        >>> ds = ray.data.range(10000)
        >>> ds  # doctest: +ELLIPSIS
        shape: (10000, 1)
        ╭───────╮
        │ id    │
        │ ---   │
        │ int64 │
        ╰───────╯
        (Dataset isn&#x27;t materialized)
        >>> ds.map(lambda row: {"id": row["id"] * 2}).take(4)
        [{'id': 0}, {'id': 2}, {'id': 4}, {'id': 6}]

    Args:
        n: The upper bound of the range of integers.
        parallelism: This argument is deprecated. Use ``override_num_blocks`` argument.
        concurrency: The maximum number of Ray tasks to run concurrently. Set this
            to control number of tasks to run concurrently. This doesn&#x27;t change the
            total number of tasks run or the total number of output blocks. By default,
            concurrency is dynamically decided based on the available resources.
        override_num_blocks: Override the number of output blocks from all read tasks.
            By default, the number of output blocks is dynamically decided based on
            input data size and available resources. You shouldn&#x27;t manually set this
            value in most cases.

    Returns:
        A :class:`~ray.data.Dataset` producing the integers from the range 0 to n.

    .. seealso::

        :meth:`~ray.data.range_tensor`
                    Call this method for creating synthetic datasets of tensor data.

    """
    datasource = RangeDatasource(n=n, block_format="arrow", column_name="id")
    return read_datasource(
        datasource,
        parallelism=parallelism,
        concurrency=concurrency,
        override_num_blocks=override_num_blocks,
    )


@PublicAPI