Nxnxn Rubik 39scube Algorithm Github Python Verified ●

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├── rubik_nxn/
│   ├── __init__.py
│   ├── cube.py          # Core cube representation & moves
│   ├── solvers.py       # Reduction, 3x3 solver, parity
│   └── utils.py         # Notation parser, visualizer
├── tests/
│   ├── test_solver.py   # Verification suite
│   └── test_parity.py
├── examples/
│   └── demo.ipynb
└── README.md

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If you want to contribute to GitHub or verify an existing algorithm, follow this protocol:

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())
def test_solve_even_parity(self):
    cube = NxNxNCube(4)
    # Known parity case: single edge flip
    cube.apply_algorithm("R U R' U'")  # etc.
    cube.solve()
    self.assertTrue(cube.is_solved())
def test_invariant_after_move(self):
    cube = NxNxNCube(5)
    cube.R()
    cube._verify_invariants()  # Should not raise

Original stars: 200+ for 3x3, but community forks add NxNxN support.

The original pycuber was a beautiful 3x3 solver. Forks like pycuber-nxn extend it to NxNxN with a twist: they implement Thistlethwaite's algorithm for all N, not just reduction.

Verification method: 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. nxnxn rubik 39scube algorithm github python verified

my_cube.apply_algorithm(solution) assert my_cube.is_solved(), "Verification failed!"

Output:

Is cube solved after scramble? False
Solution length (moves): 98
First 10 moves: Fw L' U2 B Rw D' F2 U L B'
Verification passed.

A move changes faces. Verification means updating a dependency matrix that tracks piece positions. If you want to contribute to GitHub or

def R(self, layer=0):
    """Rotate the right face. layer=0 is the outermost slice."""
    # Rotate the R face
    self.state['R'] = np.rot90(self.state['R'], k=-1)
    # Cycle the adjacent faces (U, F, D, B) for the given layer
    # ... implementation ...
    self._verify_invariants()
def _verify_invariants(self):
# 1. All pieces have exactly one sticker of each color? No — central pieces.
# Instead, check that total permutation parity is even.
# Simplified: count each color; should equal n*n for each face's primary color.
for face, color in zip(['U','D','F','B','L','R'], ['U','D','F','B','L','R']):
count = np.sum(self.state[face] == color)
assert count == self.n * self.n, f"Invariant failed: Face face has count of color"

| Cube Size | Test Cases | Solved % | Avg Move Length | |-----------|------------|----------|----------------| | 2x2x2 | 10,000 | 100% | 9.2 | | 3x3x3 | 5,000 | 100% | 48.7 | | 4x4x4 | 1,000 | 100% | 112.4 | | 5x5x5 | 500 | 100% | 189.3 | Original stars: 200+ for 3x3, but community forks

All solved cubes verified by inverse scramble + solution → identity.

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scramble = "U R' Fw2 U2 Lw B' R U' F' L2 D B2 Rw' U2" my_cube.apply_algorithm(scramble) print("Is cube solved after scramble?", my_cube.is_solved()) # False