get(self, dsk, keys, workers=None, allow_other_workers=None, resources=None, sync=True, asynchronous=None, direct=None, retries=None, priority=0, fifo_timeout='60s', actors=None, **kwargs)

Parameters

dsk : dict

keys : object, or nested lists of objects

workers : string or iterable of strings

A set of worker addresses or hostnames on which computations may be performed. Leave empty to default to all workers (common case)

allow_other_workers : bool (defaults to False)

Used with workers . Indicates whether or not the computations may be performed on workers that are not in the :None:None:`workers` set(s).

retries : int (default to 0)

Number of allowed automatic retries if computing a result fails

priority : Number

Optional prioritization of task. Zero is default. Higher priorities take precedence

resources : dict (defaults to {})

Defines the resources each instance of this mapped task requires on the worker; e.g. {'GPU': 2} . See worker resources <resources> for details on defining resources.

sync : bool (optional)

Returns Futures if False or concrete values if True (default).

direct : bool

Whether or not to connect directly to the workers, or to ask the scheduler to serve as intermediary. This can also be set when creating the Client.

Compute dask graph

See Also

Client.compute

Compute asynchronous collections

Examples

This example is valid syntax, but we were not able to check execution

>>> from operator import add  # doctest: +SKIP
... c = Client('127.0.0.1:8787')  # doctest: +SKIP
... c.get({'x': (add, 1, 2)}, 'x')  # doctest: +SKIP
3

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

distributed.client.Client.get distributed.client.Client.compute

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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