I am trying to solve sliding-tile problem using Hill climbing algorithm in python where in I want to print the each intermediate step but my code isn't showing any output. I don't think so that any infinite loop is present in my code. Please review my code and suggest me any solution to it.

from copy import deepcopy

class State:def init(self, state, parent):self.parent = parentself.state = state

def is_goal(self):    return self.state == [[1, 2, 3], [8, 0, 4], [7, 6, 5]]def generate_neighbors(self):    neighbors = []    for i in range(3):        for j in range(3):            if self.state[i][j] == 0:                if i >= 0 and i != 2:   #move down                    new_state = deepcopy(self.state)                    new_state[i][j], new_state[i+1][j] = new_state[i+1][j], new_state[i][j]                    neighbors.append(State(new_state, self))                if i <=2 and i != 0:    #move up                    new_state = deepcopy(self.state)                    new_state[i][j], new_state[i-1][j] = new_state[i-1][j], new_state[i][j]                    neighbors.append(State(new_state, self))                if j >= 0 and j != 2: # move right                    new_state = deepcopy(self.state)                    new_state[i][j], new_state[i][j+1] = new_state[i][j+1], new_state[i][j]                    neighbors.append(State(new_state, self))                if j <= 2 and j != 0:   # move left                    new_state = deepcopy(self.state)                    new_state[i][j], new_state[i][j-1] = new_state[i][j-1], new_state[i][j]                    neighbors.append(State(new_state, self))    return neighbors

def heuristic(state):goal_state = [[1, 2, 3], [8, 0, 4], [7, 6, 5]]cost = 0for i in range(3):for j in range(3):if state.state[i][j] != goal_state[i][j]:cost += 1

return cost

def hill_climbing(initial_state, heuristic):

current_state = initial_statewhile not current_state.is_goal():    neighbors = current_state.generate_neighbors()    best_neighbor = neighbors[0]    for neighbor in neighbors:        if heuristic(neighbor) < heuristic(best_neighbor):            best_neighbor = neighbor    current_state = best_neighborpath = []while current_state is not None:    path.append(current_state.state)    current_state = current_state.parentreturn path[::-1]

initial_state = State([[2, 0, 3], [1, 8, 4], [7, 6, 5]], None)

path = hill_climbing(initial_state, heuristic)

Print the solution path

for state in path:print(state)