将Python列表转换为NetworkX图的实现方案求助

Let's walk through how to turn your nested list into the exact NetworkX edges you need. The key idea is to extract unique node-weight-node pairs from each sublist and avoid adding duplicate edges to the graph.

Approach #

1. Iterate through each sublist: Each entry is a chain of nodes connected by weights, so we'll process them in groups of three (node → weight → node).
2. Track unique edges: Since multiple sublists share the same edges, we'll use a set to keep track of edges we've already added (to avoid duplicates in the undirected graph).
3. Add edges to the graph: For each unique node-weight-node triplet, add the edge to the NetworkX graph with its corresponding weight.

Complete Code #

import networkx as nx

# Your input data
input_list = [
    ['Мама мыть', 10, 'рама'],
    ['Мама мыть', 10, 'рама', 5, 'долго'],
    ['Мама мыть', 10, 'рама', 3, 'вчера'],
    ['Мама мыть', 10, 'рама', 3, 'вчера', 1, 'поздно']
]

# Initialize graph and edge tracker
G = nx.Graph()
added_edges = set()

for sublist in input_list:
    # Step through the sublist in pairs of node-weight-node
    for i in range(0, len(sublist) - 1, 2):
        source = sublist[i]
        weight = sublist[i + 1]
        target = sublist[i + 2]
        
        # Use a sorted tuple to represent undirected edges (avoids duplicate (a,b) and (b,a))
        edge_key = tuple(sorted((source, target)))
        
        if edge_key not in added_edges:
            G.add_edge(source, target, weight=weight)
            added_edges.add(edge_key)

# Verify the result (optional)
for u, v, data in G.edges(data=True):
    print(f"G.add_edge('{u}', '{v}', weight={data['weight']})")

Explanation #

• Edge tracking: The added_edges set uses sorted tuples to ensure we don't add the same undirected edge twice (since ('рама', 'вчера') is identical to ('вчера', 'рама') in an undirected graph).
• Loop logic: The range(0, len(sublist)-1, 2) loop steps through each sublist in increments of 2, so we always grab a node, its connecting weight, and the next node in the chain.

When you run this code, it will output exactly the edges you're targeting:

G.add_edge('Мама мыть', 'рама', weight=10)
G.add_edge('рама', 'долго', weight=5)
G.add_edge('рама', 'вчера', weight=3)
G.add_edge('вчера', 'поздно', weight=1)

内容的提问来源于stack exchange，提问作者Alex Nikitin