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""" |
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Basic graph-analytics helpers (pure CPU, no heavy maths): |
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• build_nx – convert agraph nodes/edges → NetworkX graph |
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• get_top_hubs – return top-k nodes by degree-centrality |
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• get_density – overall graph density |
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""" |
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from typing import List, Dict, Tuple |
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import networkx as nx |
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def build_nx(nodes: List[Dict], edges: List[Dict]) -> nx.Graph: |
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G = nx.Graph() |
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for n in nodes: |
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G.add_node(n["id"], label=n.get("label", n["id"])) |
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for e in edges: |
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G.add_edge(e["source"], e["target"]) |
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return G |
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def get_top_hubs(G: nx.Graph, k: int = 5) -> List[Tuple[str, float]]: |
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""" |
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Return [(node_id, centrality)] sorted desc. |
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""" |
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dc = nx.degree_centrality(G) |
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return sorted(dc.items(), key=lambda x: x[1], reverse=True)[:k] |
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def get_density(G: nx.Graph) -> float: |
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return nx.density(G) |
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