8.2.8.18. SubDispatch

class SubDispatch(dsp, outputs=None, cutoff=None, inputs_dist=None, wildcard=False, no_call=False, shrink=False, rm_unused_nds=False, output_type='all')

It dispatches a given Dispatcher like a function.

This function takes a sequence of dictionaries as input that will be combined before the dispatching.

Returns:A function that executes the dispatch of the given Dispatcher. Return type:callable

See also

dispatch(), combine_dicts()

Example:

>>> from schedula import Dispatcher
>>> sub_dsp = Dispatcher(name='Sub-dispatcher')
...
>>> def fun(a):
...     return a + 1, a - 1
...
>>> sub_dsp.add_function('fun', fun, ['a'], ['b', 'c'])
'fun'
>>> dispatch = SubDispatch(sub_dsp, ['a', 'b', 'c'], output_type='dict')
>>> dsp = Dispatcher(name='Dispatcher')
>>> dsp.add_function('Sub-dispatch', dispatch, ['d'], ['e'])
'Sub-dispatch'

The Dispatcher output is:

>>> o = dsp.dispatch(inputs={'d': {'a': 3}})

while, the Sub-dispatch is:

>>> sol = o.workflow.nodes['Sub-dispatch']['solution']
>>> sol
Solution([('a', 3), ('b', 4), ('c', 2)])
>>> sol == o['e']
True

Methods

__init__	Initializes the Sub-dispatch.
blue	Constructs a Blueprint out of the current object.
copy
get_node	Returns a sub node of a dispatcher.
plot	Plots the Dispatcher with a graph in the DOT language with Graphviz.
search_node_description
web	Creates a dispatcher Flask app.

__init__(dsp, outputs=None, cutoff=None, inputs_dist=None, wildcard=False, no_call=False, shrink=False, rm_unused_nds=False, output_type='all')

Initializes the Sub-dispatch.

Parameters:

• dsp (schedula.Dispatcher) – A dispatcher that identifies the model adopted.
• outputs (list[str], iterable) – Ending data nodes.
• cutoff (float, int, optional) – Depth to stop the search.
• inputs_dist (dict[str, int | float], optional) – Initial distances of input data nodes.
• wildcard (bool, optional) – If True, when the data node is used as input and target in the ArciDispatch algorithm, the input value will be used as input for the connected functions, but not as output.
• no_call (bool, optional) – If True data node estimation function is not used.
• shrink (bool, optional) – If True the dispatcher is shrink before the dispatch.
• rm_unused_nds (bool, optional) – If True unused function and sub-dispatcher nodes are removed from workflow.
• output_type (str, optional) –

  Type of function output:

  • ’all’: a dictionary with all dispatch outputs.
  • ’list’: a list with all outputs listed in outputs.
  • ’dict’: a dictionary with any outputs listed in outputs.

blue(memo=None)

Constructs a Blueprint out of the current object.

Parameters:memo (dict[T,schedula.utils.blue.Blueprint]) – A dictionary to cache Blueprints. Returns:A Blueprint of the current object. Return type:schedula.utils.blue.Blueprint