Maxcut For Mac Direct

brew install coin-or/coin/or-tools # SDP solver backend pip install cvxpy networkx numpy

Now a GW implementation in a few lines:

import networkx as nx
import cvxpy as cp
import numpy as np

(Apple Silicon) Install Rosetta only if necessary for Intel-only binaries:
softwareupdate --install-rosetta
For Julia:
brew install julia
julia> import Pkg; Pkg.add(["LightGraphs","JuMP","Gurobi","SCS"])

import networkx as nx
import random
def random_partition(G):
    return v: random.choice([0,1]) for v in G
def cut_value(G, part):
    return sum(w.get('weight',1) for u,v,w in ((u,v,G[u][v]) for u,v in G.edges()) if part[u]!=part[v])
def local_search(G, part):
    improved=True
    while improved:
        improved=False
        for v in G:
            delta = 0
            for u in G.neighbors(v):
                w = G[v][u].get('weight',1)
                delta += w if part[u]==part[v] else -w
            if delta>0:
                part[v] = 1-part[v]
                improved=True
    return part
G = nx.gnp_random_graph(50, 0.1)
for u,v in G.edges():
    G[u][v]['weight']=random.random()
part = random_partition(G)
part = local_search(G, part)
print("Cut value:", cut_value(G, part))

Built for hobbyists and pros alike, SCAL Pro runs natively on macOS and supports true shape nesting plus cutting to most USB/Bluetooth cutters. maxcut for mac