unigraph

Graph data structures and classic graph algorithms for Python, backed by the native UniGraph engine written in Nim.

unigraph provides a compact, concrete graph for signed 64-bit vertex labels and float64 edge weights. Graphs may be directed or undirected; the Python surface uses simple-graph semantics, so self-loops and parallel edges are rejected. Traversals, shortest paths, spanning forests, strongly connected components, TSP solvers, and DOT/ASCII rendering all run in the native core.

Install

pip install unigraph

Prebuilt wheels include the native UniGraph library for Linux, macOS, and Windows on CPython 3.9–3.14. Installing a wheel needs neither Nim nor a C compiler.

Quick start

import unigraph

g = unigraph.Graph(directed=False)
paris = g.add_vertex(75)
lyon = g.add_vertex(69)
marseille = g.add_vertex(13)

g.add_edge(paris, lyon, 465.0)
g.add_edge(lyon, marseille, 315.0)
g.add_edge(paris, marseille, 775.0)

g.bfs(paris)                         # [paris, lyon, marseille]
g.dijkstra(paris)[marseille]         # 775.0
g.shortest_path(paris, marseille)    # ([paris, marseille], 775.0)
g.kruskal()                          # two edges, total weight 780.0
print(g.to_dot())                    # Graphviz DOT

Vertex IDs are stable handles returned by add_vertex; labels remain available through get_vertex_data. Algorithms consume IDs, not labels, so duplicate labels are allowed without making vertices ambiguous.

What's included

Category	Python API
Graph construction	`Graph`, `add_vertex`, `add_edge`, `remove_edge`, `vertex_count`, `edge_count`
Inspection	`vertices`, `edges`, `neighbors`, `in_neighbors`, `out_neighbors`, `get_vertex_data`, `get_edge_weight`, `has_edge`
Traversal	`bfs`, `dfs`, `reachable`, `is_connected`
Shortest paths	`dijkstra`, `shortest_path`, `a_star`, `bellman_ford`
Spanning forest	`prim`, `kruskal` on undirected graphs
Components	`strongly_connected_components`, `kosaraju`, `articulation_points`
Traveling salesperson	`tsp_naive`, `tsp_nearest`, `tsp_2opt`
Presentation	`to_ascii`, `to_dot`, `degree_distribution`

shortest_path returns None when the goal is unreachable. Bellman–Ford returns (distances, has_negative_cycle); when the flag is true, do not treat the partial distances as shortest paths. Prim, Kruskal, and articulation points reject directed graphs with ValueError. Exact TSP is intentionally limited to at most ten vertices; the nearest-neighbor and 2-opt methods are heuristics and do not promise the optimum.

The full Nim API is generic over vertex data, edge data, and four storage kernels. Python deliberately exposes one stable ABI specialization; use the Nim API when custom payload types, multigraphs, or kernel selection are required.

Development

Building from source requires Nim 2.2, Nimble, a C compiler, Cython, and Python development headers.

nimble install -y
nimble pyLib
cd py
python3 -m pip install -e .
python3 -m pytest -q

On Windows, run the commands from a Developer Command Prompt and use python if python3 is not available.

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unigraph 1.0.0

unigraph

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