Clone dask collections, returning equivalent collections that are generated from independent calculations. Examples -------- (tokens

Collect configuration from paths and environment variables Parameters ---------- paths : list[str] A list of paths to search

Concatenate the multidimensional chunks of an array. Can be used on chunks with unknown sizes. Parameters ---------- x : dask array

Create an ipycytoscape widget for a dask graph. If `filename` is not None, write an HTML file to disk with the specified name. This use

First element in a nested list >>> deepfirst([[[1, 2], [3, 4]], [5, 6], [7, 8]]) 1

Enforce the current divisions at runtime. Injects a layer into the Task Graph that checks that the current divisions match the expect

Attempt to turn `s` into bytes. Parameters ---------- s : Any The object to be converted. Will correctly handled * str

Copy file to default location if it does not already exist This tries to move a default configuration file to a default location if if d

Ensure that a file does not exist.

Turn string or bytes to string >>> ensure_unicode('123') '123' >>> ensure_unicode(b'123') '123'

Create a function to insert value at many locations in sequence. >>> expander([0, 2])(['a', 'b', 'c'], 'z') ('z', 'a', 'z', 'b', 'c')

Reverse element order along axis. Parameters ---------- m : array_like Input array. axis : None or int or tuple of ints,

Format bytes as text >>> from dask.utils import format_bytes >>> format_bytes(1) '1 B' >>> format_bytes(1234) '1.21 kiB' >>>

Create bag from many dask Delayed objects. These objects will become the partitions of the resulting Bag. They should evaluate to a ``list``

Create a dask array from a dask delayed value This routine is useful for constructing dask arrays in an ad-hoc fashion using dask delayed, pa

Create dask array in a single block by calling a function Calling the provided function with func(*args, **kwargs) should return a NumPy arra

Get all output keys of all layers This will in most cases _not_ materialize any layers, which makes it a relative cheap operation.

Get a dict mapping funcs to colors from palette. Parameters ---------- palette : string Name of the bokeh palette to use, must be

Return a list of nodes that form a cycle if Dask is not a DAG. Returns an empty list if no cycle is found. ``keys`` may be a single key or l

Getitem function This function creates a copy of the desired selection for array-like inputs when the selection is smaller than half of the o

Return the top level node of a task

Import a module and return it; in case of failure; return None

A simple subs function that works both on tuples and strings

Return new dask with the given keys inlined with their values. Inlines all constants if ``inline_constants`` keyword is True. Note that the c

Is the input dtype a pyarrow string?

Return True if the given object is a potential dask key; False otherwise. The definition of a key in a Dask graph is any str, int, float, or tupl

Split sizes into chunks of total max_size each Parameters ---------- sizes : iterable of numbers The sizes to be chunked max_

>>> label('x') 'x' >>> label(('x', 1)) "('x', 1)" >>> from hashlib import md5 >>> x = 'x-%s-hello' % md5(b'1234').hexdiges

Map a function across all blocks of a dask array. Note that ``map_blocks`` will attempt to automatically determine the output array type by c

Return the approximate median of the values over the requested axis. Parameters ---------- method : {'default', 'tdigest', 'd

Call a function on every element within a nested container >>> def inc(x): ... return x + 1 >>> L = [[1, 2], [3, 4, 5]] >>> ndeep

Proceed to the next term in the preorder traversal.

Normalize slicing indexes 1. Replaces ellipses with many full slices 2. Adds full slices to end of index 3. Checks bounding conditions

Create a spreadsheet-style pivot table as a DataFrame. Target ``columns`` must have category dtype to infer result's ``columns``. ``index

Compute the qr factorization of a matrix. Parameters ---------- a : Array Returns ------- q: Array, orthonormal r:

Replace ... with slices, :, : ,: >>> replace_ellipsis(4, (3, Ellipsis, 2)) (3, slice(None, None, None), slice(None, None, None), 2) >>>

Standard deviation

Compute the singular value decomposition of a matrix. Parameters ---------- a : (M, N) Array coerce_signs : bool Whether

Convert chunks from Dask Array into an SVG Image Parameters ---------- chunks: tuple size: int Rough size of the image R