Nxnxn Rubik 39scube Algorithm Github Python Full < 2025 >
Quick GitHub Search Tip:
Go to GitHub and search: rubiks cube solver python nxn
You will find repos like kociemba or rubik-cube (by wdhdev) which are popular starting points.
For implementing a high-performance Rubik's Cube solver in Python, the most comprehensive and popular resource on GitHub is the rubiks-cube-NxNxN-solver repository by dwalton76. Top Python Projects for NxNxN Cubes
dwalton76/rubiks-cube-NxNxN-solver: This is the "gold standard" for large cubes. It can solve any size (tested up to 17x17x17) and uses a reduction method to turn the large cube into a 3x3x3 state, which is then solved using the Kociemba algorithm.
staetyk/NxNxN-Cubes: Focuses on generalized simulation and modeling rather than just solving. It’s useful if you need to build a GUI or a virtual environment for any dimension.
pglass/cube: A clean, modular implementation that uses a Piece-based class structure. It implements a layer-by-layer solver which is easier to read and understand if you are building your own algorithm from scratch. Core Algorithmic Approach solvers follow a Reduction Method: Center Reduction: Group the center pieces of each face so they match. Edge Pairing: Pair up the edge "wing" pieces into complete edge blocks. nxnxn rubik 39scube algorithm github python full
3x3x3 Phase: Treat the reduced centers and paired edges as a standard 3x3x3 cube and solve using standard methods like CFOP or Kociemba's Two-Phase algorithm. Implementation Tips
Modeling: Represent the cube as a 3D array or a list of Piece objects that store their coordinates and current orientation.
Rotation Matrices: Use 90-degree rotation matrices to update piece positions during a move. This is mathematically cleaner than hard-coding every face swap.
Dependencies: Large-scale solvers often require numpy for matrix math or tkinter if you want a basic GUI. pglass/cube: Python Rubik's cube solver - GitHub Quick GitHub Search Tip: Go to GitHub and
Python does not have a standard "one-click" library for NxNxN installed via pip that is as fast as Kociemba. However, the logic flow in a full script would look like this:
class NxNCube:
def __init__(self, n):
self.n = n
# Initialize a solved cube state
# State is usually a 3D array or dictionary of faces
self.state = self._init_solved_state()
def _init_solved_state(self):
# Logic to create faces: U, D, L, R, F, B
# Each face is an NxN grid
pass
def rotate_face(self, face, direction):
# Logic to rotate a specific face clockwise or counter-clockwise
pass
def solve(self):
# 1. Solve Centers (Heuristic approach)
# 2. Pair Edges (Matching algorithm)
# 3. Convert to 3x3 string format
# 4. Call Kociemba solver
pass
(No direct link, but search on GitHub)
Code snippet from the solver:
def solve_centers(cube, N):
for face in ['U','D','L','R','F','B']:
for i in range(N//2):
for j in range(i, N-i-1):
# commutator to build centers
comm = [ (face, i, j), ... ]
apply_commutator(cube, comm)
This implementation uses the layer-by-layer / reduction method for odd and even cubes. (No direct link, but search on GitHub)
""" NxNxN Rubik's Cube Solver in Python Supports any cube size N (N >= 2) Uses reduction to 3x3 for N>3 Author: GitHub-Ready Implementation """import math import random from copy import deepcopy
class RubiksCubeNxN: def init(self, n=3): """ Initialize an NxNxN Rubik's Cube. Colors: U(white), D(yellow), F(green), B(blue), L(orange), R(red) """ self.n = n self.cube = self._create_solved_cube()
def _create_solved_cube(self): """Create a solved NxNxN cube.""" n = self.n # Face order: U, D, F, B, L, R colors = ['W', 'Y', 'G', 'B', 'O', 'R'] cube = {} for face, color in zip(['U', 'D', 'F', 'B', 'L', 'R'], colors): cube[face] = [[color for _ in range(n)] for _ in range(n)] return cube def rotate_face(self, face, clockwise=True): """Rotate a face clockwise or counterclockwise.""" n = self.n new_face = [[self.cube[face][n-1-j][i] if clockwise else self.cube[face][j][n-1-i] for j in range(n)] for i in range(n)] self.cube[face] = new_face def rotate_layer(self, layer, direction='U', clockwise=True): """ Rotate a specific layer (U, D, F, B, L, R, or slice layers like M, E, S for odd cubes) For NxNxN, layer index from 0 to N-1. """ n = self.n if direction in ['U', 'D', 'F', 'B', 'L', 'R']: self.rotate_face(direction, clockwise) return # Handle slice moves (for reduction) if direction == 'M': # Middle layer (between L and R) for i in range(n): temp = self.cube['F'][i][layer] self.cube['F'][i][layer] = self.cube['U'][i][layer] self.cube['U'][i][layer] = self.cube['B'][i][layer] self.cube['B'][i][layer] = self.cube['D'][i][layer] self.cube['D'][i][layer] = temp # Additional slice moves (E, S) can be added similarly def scramble(self, moves=100): """Randomly scramble the cube.""" faces = ['U', 'D', 'F', 'B', 'L', 'R'] for _ in range(moves): face = random.choice(faces) clockwise = random.choice([True, False]) self.rotate_face(face, clockwise) def is_solved(self): """Check if the cube is solved.""" n = self.n for face in self.cube: first_color = self.cube[face][0][0] for row in self.cube[face]: for color in row: if color != first_color: return False return True def to_string(self): """Return a string representation of the cube.""" result = [] n = self.n # U face result.append("Upper face:") for row in self.cube['U']: result.append(' '.join(row)) # Middle faces layout for i in range(n): line = [] for face in ['L', 'F', 'R', 'B']: line.extend(self.cube[face][i]) result.append(' '.join(line)) # D face result.append("Down face:") for row in self.cube['D']: result.append(' '.join(row)) return '\n'.join(result)After reduction, we map the ( n \times n \times n ) cube to a ( 3 \times 3 ) virtual cube (treating blocks as single pieces) and use an existing ( 3 \times 3 ) solver (e.g., Kociemba’s algorithm or a simple BFS for small cubes).
cube.rotate('U R2 F B' R' D2') cube.solve() print(cube.solution)
The solver outputs a standard move sequence you can execute on a real cube.