




'''simple docstring'''


import random
import sys

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap

_snake_case   :   Optional[int]     							=	'Usage of script: script_name <size_of_canvas:int>'

_snake_case   :   Any     							=	[0] * 100 + [1] * 10
random.shuffle(choice)
def 	snake_case_					(UpperCamelCase :						int   ):





							'''simple docstring'''


							_a			  =       [[False for i in range(UpperCamelCase   )] for j in range(UpperCamelCase   )]
							return canvas
def 	snake_case_					(UpperCamelCase :						list[list[bool]]   ):





							'''simple docstring'''


							for i, row in enumerate(UpperCamelCase   ):
														for j, _ in enumerate(UpperCamelCase   ):
																					_a			  =       bool(random.getrandbits(1   )   )
def 	snake_case_					(UpperCamelCase :						list[list[bool]]   ):





							'''simple docstring'''


							_a			  =       np.array(UpperCamelCase   )
							_a			  =       np.array(create_canvas(current_canvas.shape[0]   )   )
							for r, row in enumerate(UpperCamelCase   ):
														for c, pt in enumerate(UpperCamelCase   ):
																					_a			  =       __judge_point(
																					    UpperCamelCase				,		current_canvas[r - 1 : r + 2, c - 1 : c + 2]   )

							_a			  =       next_gen_canvas
							del next_gen_canvas  # cleaning memory as we move on.
							_a			  =       current_canvas.tolist()
							return return_canvas
def 	snake_case_					(UpperCamelCase :						bool				,		UpperCamelCase :						list[list[bool]]   ):





							'''simple docstring'''


							_a			  =       0
							_a			  =       0
							# finding dead or alive neighbours count.
							for i in neighbours:
														for status in i:
																					if status:
																												alive += 1
																					else:
																												dead += 1

    # handling duplicate entry for focus pt.
							if pt:
														alive -= 1
							else:
														dead -= 1

							# running the rules of game here.
							_a			  =       pt
							if pt:
														if alive < 2:
																					_a			  =       False
														elif alive == 2 or alive == 3:
																					_a			  =       True
														elif alive > 3:
																					_a			  =       False
							else:
														if alive == 3:
																					_a			  =       True

							return state


if __name__ == "__main__":
				if len(sys.argv) != 2:
								raise Exception(usage_doc)

				_snake_case   :   Tuple     							=	int(sys.argv[1])
				# main working structure of this module.
				_snake_case   :   int     							=	create_canvas(canvas_size)
				seed(c)
				_snake_case   :   str     							=	plt.subplots()
				fig.show()
				_snake_case   :   List[Any]     							=	ListedColormap(['w', 'k'])
				try:
								while True:
												_snake_case   :   Any     							=	run(c)
												ax.matshow(c, cmap=cmap)
												fig.canvas.draw()
												ax.cla()
				except KeyboardInterrupt:
								# do nothing.
								pass







'''simple docstring'''


_snake_case   :   Any     							=	{
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}
def 	snake_case_					(UpperCamelCase :						dict				,		UpperCamelCase :						Dict				,		UpperCamelCase :						Optional[int]   ):





							'''simple docstring'''


							_a			  =       set()
							# keep track of all the paths to be checked
							_a			  =       [[start]]

							# return path if start is goal
							if start == goal:
														return [start]

							# keeps looping until all possible paths have been checked
							while queue:
														# pop the first path from the queue
														_a			  =       queue.pop(0   )
														# get the last node from the path
														_a			  =       path[-1]
														if node not in explored:
																					_a			  =       graph[node]
																					# go through all neighbour nodes, construct a new path and
																					# push it into the queue
																					for neighbour in neighbours:
																												_a			  =       list(UpperCamelCase   )
																												new_path.append(UpperCamelCase   )
																												queue.append(UpperCamelCase   )
																												# return path if neighbour is goal
																												if neighbour == goal:
																																			return new_path

            # mark node as explored
																					explored.add(UpperCamelCase   )

    # in case there's no path between the 2 nodes
							return []
def 	snake_case_					(UpperCamelCase :						dict				,		UpperCamelCase :						Optional[int]				,		UpperCamelCase :						Dict   ):





							'''simple docstring'''


							if not graph or start not in graph or target not in graph:
														return -1
							if start == target:
														return 0
							_a			  =       [start]
							_a			  =       set(UpperCamelCase   )
							# Keep tab on distances from `start` node.
							_a			  =       {start: 0, target: -1}
							while queue:
														_a			  =       queue.pop(0   )
														if node == target:
																					_a			  =       (
																					    dist[node] if dist[target] == -1 else min(dist[target]				,		dist[node]   )
																					)
														for adjacent in graph[node]:
																					if adjacent not in visited:
																												visited.add(UpperCamelCase   )
																												queue.append(UpperCamelCase   )
																												_a			  =       dist[node] + 1
							return dist[target]


if __name__ == "__main__":
				print(bfs_shortest_path(demo_graph, 'G', 'D'))  # returns ['G', 'C', 'A', 'B', 'D']
				print(bfs_shortest_path_distance(demo_graph, 'G', 'D'))  # returns 4

