

from random import randint, random







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase = False    ,     _UpperCAmelCase = False    ,     _UpperCAmelCase = 5    ,     ):
						SCREAMING_SNAKE_CASE_:			int  		=	[[-1] * number_of_cells]  # Create a highway without any car
						SCREAMING_SNAKE_CASE_:			Tuple  		=	0
						SCREAMING_SNAKE_CASE_:			Dict  		=	max(_lowerCAmelCase    ,     0   )
						while i < number_of_cells:
												SCREAMING_SNAKE_CASE_:			Tuple  		=	(
												    randint(0    ,     _lowerCAmelCase   ) if random_speed else initial_speed
												)  # Place the cars
												i += (
												    randint(1    ,     max_speed * 2   ) if random_frequency else frequency
												)  # Arbitrary number, may need tuning
						return highway







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Any  		=	0
						SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	highway_now[car_index + 1 :]
						for cell in range(len(_lowerCAmelCase   )   ):  # May need a better name for this
												if cells[cell] != -1:  # If the cell is not empty then
																		return distance  # we have the distance we wanted
												distance += 1
						# Here if the car is near the end of the highway
						return distance + get_distance(_lowerCAmelCase    ,     -1   )







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Any  		=	len(_lowerCAmelCase   )
						# Beforce calculations, the highway is empty
						SCREAMING_SNAKE_CASE_:			Tuple  		=	[-1] * number_of_cells

						for car_index in range(_lowerCAmelCase   ):
												if highway_now[car_index] != -1:
																		# Add 1 to the current speed of the car and cap the speed
																		SCREAMING_SNAKE_CASE_:			List[str]  		=	min(highway_now[car_index] + 1    ,     _lowerCAmelCase   )
																		# Number of empty cell before the next car
																		SCREAMING_SNAKE_CASE_:			int  		=	get_distance(_lowerCAmelCase    ,     _lowerCAmelCase   ) - 1
																		# We can't have the car causing an accident
																		SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	min(next_highway[car_index]    ,     _lowerCAmelCase   )
																		if random() < probability:
																								# Randomly, a driver will slow down
																								SCREAMING_SNAKE_CASE_:			Any  		=	max(next_highway[car_index] - 1    ,     0   )
						return next_highway







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			str  		=	len(highway[0]   )

						for i in range(_lowerCAmelCase   ):
												SCREAMING_SNAKE_CASE_:			Tuple  		=	update(highway[i]    ,     _lowerCAmelCase    ,     _lowerCAmelCase   )
												SCREAMING_SNAKE_CASE_:			Dict  		=	[-1] * number_of_cells

												for car_index in range(_lowerCAmelCase   ):
																		SCREAMING_SNAKE_CASE_:			Tuple  		=	next_speeds_calculated[car_index]
																		if speed != -1:
																								# Change the position based on the speed (with % to create the loop)
																								SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	(car_index + speed) % number_of_cells
																								# Commit the change of position
																								SCREAMING_SNAKE_CASE_:			Optional[int]  		=	speed
												highway.append(_lowerCAmelCase   )

						return highway


if __name__ == "__main__":
						import doctest

						doctest.testmod()








from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass



@dataclass
class   __lowercase    :




			"""simple docstring"""







			_UpperCAmelCase       :							int
			_UpperCAmelCase       :							int







class   __lowercase    :




			"""simple docstring"""







			def __init__(			self  :					Any       ,						lowerCAmelCase__  :					int):
									SCREAMING_SNAKE_CASE_:			list[list[Edge]]  		=	[[] for _ in range(lowerCAmelCase__)]
									SCREAMING_SNAKE_CASE_:			Dict  		=	size



			def __getitem__(			self  :					Dict       ,						lowerCAmelCase__  :					int):
									return iter(self._graph[vertex])



			@property
			def 	_SCREAMING_SNAKE_CASE      (			self  :					Tuple):
									return self._size



			def 	_SCREAMING_SNAKE_CASE      (			self  :					Dict       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int):
									if weight not in (0, 1):
															raise ValueError("Edge weight must be either 0 or 1.")

									if to_vertex < 0 or to_vertex >= self.size:
															raise ValueError("Vertex indexes must be in [0; size).")

									self._graph[from_vertex].append(Edge(lowerCAmelCase__       ,						lowerCAmelCase__))




			def 	_SCREAMING_SNAKE_CASE      (			self  :					List[Any]       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int):
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	deque([start_vertex])
									SCREAMING_SNAKE_CASE_:			list[int | None]  		=	[None] * self.size
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	0

									while queue:
															SCREAMING_SNAKE_CASE_:			int  		=	queue.popleft()
															SCREAMING_SNAKE_CASE_:			str  		=	distances[current_vertex]
															if current_distance is None:
																					continue

															for edge in self[current_vertex]:
																					SCREAMING_SNAKE_CASE_:			Optional[int]  		=	current_distance + edge.weight
																					SCREAMING_SNAKE_CASE_:			str  		=	distances[edge.destination_vertex]
																					if (
																					    isinstance(lowerCAmelCase__       ,						lowerCAmelCase__)
																					    and new_distance >= dest_vertex_distance
																					):
																											continue
																					SCREAMING_SNAKE_CASE_:			Any  		=	new_distance
																					if edge.weight == 0:
																											queue.appendleft(edge.destination_vertex)
																					else:
																											queue.append(edge.destination_vertex)

									if distances[finish_vertex] is None:
															raise ValueError("No path from start_vertex to finish_vertex.")

									return distances[finish_vertex]


if __name__ == "__main__":
						import doctest

						doctest.testmod()






