def solve(self): # Phase 1: Solve centers (all same color on each face) self._solve_centers() self._verify_centers_solved() # Phase 2: Pair edges self._pair_edges() self._verify_edges_paired() # Phase 3: Solve as 3x3 (use existing verified 3x3 solver) self._solve_as_3x3() assert self.is_solved() import unittest class TestNxNxNVerification(unittest.TestCase): def test_solve_2x2(self): cube = NxNxNCube(2) cube.randomize(seed=42) cube.solve() self.assertTrue(cube.is_solved())
Every stage's move set is proven to reduce the cube to the next subgroup (G1 → G2 → G3 → solved). The code checks that after each phase, the cube belongs to the correct subgroup using invariant scanning. Writing Your Own Verified NxNxN Solver: A Step-by-Step Template If you can't find the perfect repo, here's how to build a verified NxNxN solver in Python, using ideas from the verified projects above. Step 1: Data Structure Represent the cube as a dictionary of (N, N, N) positions to colors. Use numpy for performance. nxnxn rubik 39scube algorithm github python verified
from rubikscubennnsolver.RubiksCubeNNNEven import RubiksCubeNNNEven from rubikscubennnsolver.RubiksCubeNNNOdd import RubiksCubeNNNOdd cube = RubiksCubeNNNOdd(5, 'URFDLB') cube.randomize() cube.solve() assert cube.solved() def solve(self): # Phase 1: Solve centers (all