7.2.8.16. DispatchPipe

class DispatchPipe(dsp, function_id=None, inputs=None, outputs=None, cutoff=None, inputs_dist=None, no_domain=True, wildcard=True)[source]

It converts a Dispatcher into a function.

This function takes a sequence of arguments as input of the dispatch.

Returns:A function that executes the pipe of the given dsp, updating its workflow.
Return type:callable

Note

This wrapper is not thread safe, because it overwrite the solution.

See also

dispatch(), shrink_dsp()

Example:

A dispatcher with two functions max and min and an unresolved cycle (i.e., a –> max –> c –> min –> a):

Extract a static function node, i.e. the inputs a and b and the output a are fixed:

>>> fun = DispatchPipe(dsp, 'myF', ['a', 'b'], ['a'])
>>> fun.__name__
'myF'
>>> fun(2, 1)
1

The created function raises a ValueError if un-valid inputs are provided:

>>> fun(1, 0)
0

Methods

__init__ Initializes the Sub-dispatch Function.
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.
web Creates a dispatcher Flask app.
__init__(dsp, function_id=None, inputs=None, outputs=None, cutoff=None, inputs_dist=None, no_domain=True, wildcard=True)

Initializes the Sub-dispatch Function.

Parameters:
  • dsp (schedula.Dispatcher) – A dispatcher that identifies the model adopted.
  • function_id (str) – Function name.
  • inputs (list[str], iterable) – Input data nodes.
  • outputs (list[str], iterable, optional) – 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.

Attributes

var_keyword
plot(workflow=None, *args, **kwargs)[source]

Plots the Dispatcher with a graph in the DOT language with Graphviz.

Parameters:
  • workflow (bool, optional) – If True the latest solution will be plotted, otherwise the dmap.
  • view (bool, optional) – Open the rendered directed graph in the DOT language with the sys default opener.
  • edge_data (tuple[str], optional) – Edge attributes to view.
  • node_data (tuple[str], optional) – Data node attributes to view.
  • node_function (tuple[str], optional) – Function node attributes to view.
  • node_styles (dict[str|Token, dict[str, str]]) – Default node styles according to graphviz node attributes.
  • depth (int, optional) – Depth of sub-dispatch plots. If negative all levels are plotted.
  • name (str) – Graph name used in the source code.
  • comment (str) – Comment added to the first line of the source.
  • directory (str, optional) – (Sub)directory for source saving and rendering.
  • format (str, optional) – Rendering output format (‘pdf’, ‘png’, …).
  • engine (str, optional) – Layout command used (‘dot’, ‘neato’, …).
  • encoding (str, optional) – Encoding for saving the source.
  • graph_attr (dict, optional) – Dict of (attribute, value) pairs for the graph.
  • node_attr (dict, optional) – Dict of (attribute, value) pairs set for all nodes.
  • edge_attr (dict, optional) – Dict of (attribute, value) pairs set for all edges.
  • body (dict, optional) – Dict of (attribute, value) pairs to add to the graph body.
  • directory – Where is the generated Flask app root located?
  • sites (set[Site], optional) – A set of Site to maintain alive the backend server.
  • index (bool, optional) – Add the site index as first page?
  • max_lines (int, optional) – Maximum number of lines for rendering node attributes.
  • max_width (int, optional) – Maximum number of characters in a line to render node attributes.
  • view – Open the main page of the site?
Returns:

A SiteMap.
Return type:

schedula.utils.drw.SiteMap

Example:

>>> from schedula import Dispatcher
>>> dsp = Dispatcher(name='Dispatcher')
>>> def fun(a):
...     return a + 1, a - 1
>>> dsp.add_function('fun', fun, ['a'], ['b', 'c'])
'fun'
>>> dsp.plot(view=False, graph_attr={'ratio': '1'})
SiteMap([(Dispatcher, SiteMap())])