How to Merge Lists with Shared Elements Using NetworkX?

Merging Lists with Shared Elements

This task involves merging lists that share common elements, resulting in a consolidated structure. Consider the following input:

[['a','b','c'],['b','d','e'],['k'],['o','p'],['e','f'],['p','a'],['d','g']]

Each sublist represents a component or group of elements. The objective is to merge lists based on shared elements, and continue the merging process until no more lists share elements.

Solution Using NetworkX

A suitable solution leverages the NetworkX library, which provides an efficient tool for representing and manipulating graphs. By converting the input lists into a graph, where nodes represent elements and edges represent shared elements, we can employ algorithms to identify the connected components of the graph.

Here is a Python implementation using NetworkX:

<code class="python">import networkx as nx
from networkx.algorithms.components.connected import connected_components

def to_graph(l):
    G = nx.Graph()
    for part in l:
        # each sublist is a bunch of nodes
        G.add_nodes_from(part)
        # it also imlies a number of edges:
        G.add_edges_from(to_edges(part))
    return G

def to_edges(l):
    it = iter(l)
    last = next(it)

    for current in it:
        yield last, current
        last = current    

G = to_graph(l)
print(connected_components(G))</code>

This code converts the input lists into a graph and identifies connected components, which correspond to the final merged list.

Conclusion

By utilizing NetworkX and graph theory concepts, we achieve an efficient solution to merge lists based on shared elements, resulting in the desired consolidated structure.

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