graph_atlas.atlas() - Code Metrics - Inspection of "minor change" - erivlis/graphinate - Measure and Improve Code Quality continuously with Scrutinizer

Passed

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by Eran

created 2025-01-28 22:10 UTC

graph_atlas.atlas() B

↳ Parent: Project

Complexity

Conditions

Size

Total Lines	753
Code Lines	707

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	1
eloc	707
nop	0
dl	0
loc	753
rs	7
c	0
b	0
f	0

How to fix Long Method

from collections.abc import Iterable

import graphs
import networkx as nx

import graphinate
from graphinate.materializers import Materializers


def model(iterable: Iterable[nx.Graph]) -> graphinate.GraphModel:
    """
    Generate a graph model based on the provided iterable of graphs.
    The function creates a graph model named 'Graph Atlas' using the 'graphinate' library.
    It then combines all the graphs from the input iterable into a single disjoint union graph using NetworkX library.
    The function defines edges for the combined graph by iterating over all edges in the disjoint union graph and
    yielding dictionaries with 'source' and 'target' keys representing the edge connections.
    Finally, the function yields the created graph model containing the combined graph with defined edges.

    Args:
        iterable: An iterable containing graphs to be combined into a single graph model.

    Yields:
        GraphModel: A graph model containing the combined graph with defined edges.
    """

    graph_model = graphinate.model('Graph Atlas')

    @graph_model.edge()
    def edge():
        for e in nx.disjoint_union_all(g for _, g in iterable).edges:
            yield {'source': e[0], 'target': e[1]}

    return graph_model


if __name__ == '__main__':
    from gui import listbox_chooser, radiobutton_chooser

    graph_atlas = graphs.atlas()

    choices = listbox_chooser('Choose Graph', graph_atlas)

    model = model(choices)

    # or
    # model(graph_atlas.values())

    result = radiobutton_chooser('Choose Materializer',
                                 options={m.name: m.value for m in Materializers},
                                 default=(None, None))
    builder, handler = result[1]

    graphinate.materialize(model, builder=builder, builder_output_handler=handler)


1			from collections.abc import Iterable
2
3			import graphs
4			import networkx as nx
5
6			import graphinate
7			from graphinate.materializers import Materializers
8
9
10			def model(iterable: Iterable[nx.Graph]) -> graphinate.GraphModel:
11			"""
12			Generate a graph model based on the provided iterable of graphs.
13			The function creates a graph model named 'Graph Atlas' using the 'graphinate' library.
14			It then combines all the graphs from the input iterable into a single disjoint union graph using NetworkX library.
15			The function defines edges for the combined graph by iterating over all edges in the disjoint union graph and
16			yielding dictionaries with 'source' and 'target' keys representing the edge connections.
17			Finally, the function yields the created graph model containing the combined graph with defined edges.
18
19			Args:
20			iterable: An iterable containing graphs to be combined into a single graph model.
21
22			Yields:
23			GraphModel: A graph model containing the combined graph with defined edges.
24			"""
25
26			graph_model = graphinate.model('Graph Atlas')
27
28			@graph_model.edge()
29			def edge():
30			for e in nx.disjoint_union_all(g for _, g in iterable).edges:
31			yield {'source': e[0], 'target': e[1]}
32
33			return graph_model
34
35
36			if __name__ == '__main__':
37			from gui import listbox_chooser, radiobutton_chooser
38
39			graph_atlas = graphs.atlas()
40
41			choices = listbox_chooser('Choose Graph', graph_atlas)
42
43			model = model(choices)
44
45			# or
46			# model(graph_atlas.values())
47
48			result = radiobutton_chooser('Choose Materializer',
49			options={m.name: m.value for m in Materializers},
50			default=(None, None))
51			builder, handler = result[1]
52
53			graphinate.materialize(model, builder=builder, builder_output_handler=handler)
54

erivlis / graphinate

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graph_atlas.atlas() B

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How to fix Long Method

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