Module dewret.backends.backend_dask

Dask backend.

Lazy-evaluation via dask.delayed.

Functions

is_lazy

def is_lazy(
    task: Any
) -> bool

Checks if a task is really a lazy-evaluated function for this backend.

Parameters:

Name	Type	Description	Default
task	None	suspected lazy-evaluated function.	None

Returns:

Type	Description
None	True if so, False otherwise.

lazy

def lazy(
    obj='__no__default__',
    name=None,
    pure=None,
    nout=None,
    traverse=True
)

Wraps a function or object to produce a Delayed.

Delayed objects act as proxies for the object they wrap, but all operations on them are done lazily by building up a dask graph internally.

Parameters:

Name	Type	Description	Default
obj	object	The function or object to wrap	None
name	Dask key	The key to use in the underlying graph for the wrapped object. Defaults to hashing content. Note that this only affects the name of the object wrapped by this call to delayed, and not the output of delayed function calls - for that use dask_key_name= as described below. .. note:: Because this name is used as the key in task graphs, you should ensure that it uniquely identifies obj. If you'd like to provide a descriptive name that is still unique, combine the descriptive name with :func:dask.base.tokenize of the array_like. See :ref:graphs for more.	s
pure	bool	Indicates whether calling the resulting Delayed object is a pure operation. If True, arguments to the call are hashed to produce deterministic keys. If not provided, the default is to check the global delayed_pure setting, and fallback to False if unset.	to
nout	int	The number of outputs returned from calling the resulting Delayed object. If provided, the Delayed output of the call can be iterated into nout objects, allowing for unpacking of results. By default iteration over Delayed objects will error. Note, that nout=1 expects obj to return a tuple of length 1, and consequently for nout=0, obj should return an empty tuple.	iteration
traverse	bool	By default dask traverses builtin python collections looking for dask objects passed to delayed. For large collections this can be expensive. If obj doesn't contain any dask objects, set traverse=False to avoid doing this traversal.	dask

run

def run(
    workflow: dewret.workflow.Workflow | None,
    task: dewret.workflow.Lazy
) -> dewret.workflow.StepReference[typing.Any]

Execute a task as the output of a workflow.

Runs a task with dask.

Parameters:

Name	Type	Description	Default
workflow	None	Workflow in which to record the execution.	None
task	None	dask.delayed function, wrapped by dewret, that we wish to compute.	None

unwrap

def unwrap(
    task: dewret.workflow.Lazy
) -> collections.abc.Callable[..., typing.Any]

Unwraps a lazy-evaluated function to get the function.

In recent dask (>=2024.3) this works with inspect.wraps, but earlier versions do not have the __wrapped__ property.

Parameters:

Name	Type	Description	Default
task	None	task to be unwrapped.	None

Returns:

Type	Description
None	Original target.

Raises:

Type	Description
RuntimeError	if the task is not a wrapped function.

Classes

Delayed

class Delayed(
    *args,
    **kwargs
)

Description of a dask delayed.

Since dask.delayed does not have a hintable type, this stands in its place, making sure that all the features of a dask.delayed are available.

More info: https://github.com/dask/dask/issues/7779

Ancestors (in MRO)

• typing.Protocol
• typing.Generic

Methods

compute

def compute(
    self,
    __workflow__: dewret.workflow.Workflow | None
) -> dewret.workflow.StepReference[typing.Any]

Evaluate this dask.delayed.

Evaluate a delayed (dask lazy-evaluated) function. dewret will have replaced it with a wrapper that expects a Workflow and all arguments will already be known to the wrapped delayed so the signature here is simple.

Parameters:

Name	Type	Description	Default
workflow	None	Workflow that this is tied to, if applicable.	None

Returns:

Type	Description
None	Reference to the final output step.