Function compute

dask/base.py:601–687

Compute several dask collections at once. Parameters ---------- args : object Any number of objects. If it is a dask object, it's computed and the result is returned. By default, python builtin collections are also traversed to look for dask objects (for more inf

(
    *args,
    traverse=True,
    optimize_graph=True,
    scheduler=None,
    get=None,
    **kwargs,
)

def compute(
    *args,
    traverse=True,
    optimize_graph=True,
    scheduler=None,
    get=None,
    **kwargs,
):
    """Compute several dask collections at once.

    Parameters
    ----------
    args : object
        Any number of objects. If it is a dask object, it's computed and the
        result is returned. By default, python builtin collections are also
        traversed to look for dask objects (for more information see the
        ``traverse`` keyword). Non-dask arguments are passed through unchanged.
    traverse : bool, optional
        By default dask traverses builtin python collections looking for dask
        objects passed to ``compute``. For large collections this can be
        expensive. If none of the arguments contain any dask objects, set
        ``traverse=False`` to avoid doing this traversal.
    scheduler : string, optional
        Which scheduler to use like "threads", "synchronous" or "processes".
        If not provided, the default is to check the global settings first,
        and then fall back to the collection defaults.
    optimize_graph : bool, optional
        If True [default], the optimizations for each collection are applied
        before computation. Otherwise the graph is run as is. This can be
        useful for debugging.
    get : ``None``
        Should be left to ``None`` The get= keyword has been removed.
    kwargs
        Extra keywords to forward to the scheduler function.

    Examples
    --------
    >>> import dask
    >>> import dask.array as da
    >>> a = da.arange(10, chunks=2).sum()
    >>> b = da.arange(10, chunks=2).mean()
    >>> dask.compute(a, b)
    (np.int64(45), np.float64(4.5))

    By default, dask objects inside python collections will also be computed:

    >>> dask.compute({'a': a, 'b': b, 'c': 1})
    ({'a': np.int64(45), 'b': np.float64(4.5), 'c': 1},)
    """

    collections, repack = unpack_collections(*args, traverse=traverse)
    if not collections:
        return args

    schedule = get_scheduler(
        scheduler=scheduler,
        collections=collections,
        get=get,