@urbdyn/petgraph-wasm
v0.0.1
Published
WASM port of petgraph, a graph data structure library providing graph types and algorithms.
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Readme
petgraph-wasm
A work in progress, selective WASM wrapper around the fantastic petgraph library in Rust.
This project aims to provide a direct port of the petgraph library to an NPM packages which preserves as much of the original API structure and design as possible. For more details please check out the thoroughly documented petgraph API.
Example
// Typescript example
import {DiGraph, toposort} from 'petgraph-wasm'
// Create new directional graph
const g = new DiGraph()
// Add nodes to directional graph
const kno_index = g.addNode("Knoxville")
const vil_index = g.addNode("Vilnius")
const tai_index = g.addNode("Taipei")
// Connect them with edges
g.addEdge(kno_index,vil_index)
g.addEdge(kno_index,tai_index)
g.addEdge(vil_index,tai_index)
// Sort them
const sorted_g = toposort(g)
// Detect cycles
g.addEdge(tai_index,kno_index)
// Will throw error!
toposort(g)
Performance
You should always measure you're exact needs to know how this library will work for you. But here's a few order of magnitude examples as run on a GCP VM with a 2.25GHz AMD EPYC CPU. There are probably overly "optomistic" in design as compared to real world needs.
| Action | Nodes | Edges | Time |
|------------|-----------|------------|---------------|
| toposort
| 10,000 | 9,000 | ~2ms |
| toposort
| 10,000 | 90,000 | ~5ms |
| toposort
| 10,000 | 900,000 | ~20ms |
| toposort
| 100,000 | 99,000 | ~20ms |
| toposort
| 100,000 | 990,000 | ~70ms |
| toposort
| 100,000 | 900,000 | ~600ms |
| toposort
| 1,000,000 | 999,000 | ~350ms |
| toposort
| 1,000,000 | 9,990,000 | ~750ms |
| toposort
| 1,000,000 | 99,900,000 | out-of-memory |
Development
To work on this you will need to install rust-up and wasm-pack.
# Build the npm package
wasm-pack build --target nodejs
# Test on node
wasm-pack test --node
# Create release build
./bin/ci.sh
# Try out benchmark of 100,000 nodes each with 15 edges
time ./example_js/benchmark.js 100000 15