def bfs(start,goal):
# dimension of the square puzzle
n = len(start)
# offsets for movements in the list
offsets = {
"right": 1,
"left": -1,
"up": -n,
"down": n
}
# converting matrix to string
start_state = "".join(matrix_to_lst(start))
goal_state = "".join(matrix_to_lst(goal))
queue = Queue()
queue.enqueue(start_state)
predecessors = {start_state: None}
while not queue.is_empty():
# pop off first state in the queue
current_state = queue.dequeue()
# check if it is the goal itself
if current_state == goal_state:
return get_path(predecessors, start_state, goal_state)
current_state_lst = list(current_state) # convert string to list, because swap is not possible on strings(immutable)
blank_pos = current_state_lst.index('A') # find position of blank tile
for direction in ["up", "right", "down", "left"]:
current_copy = copy.deepcopy(current_state_lst) # deepcopy to protect current_state_lst itself from modification
new_blank_pos = blank_pos + offsets[direction]
if new_blank_pos >= 0 and new_blank_pos < n**2 : # check for valid location before swapping tile
current_copy[blank_pos], current_copy[new_blank_pos] = current_copy[new_blank_pos], current_copy[blank_pos] # swap operation
neighbour = "".join(current_copy) # convert to string
else:
continue # if invalid location, continue to next direction
if neighbour not in predecessors:
queue.enqueue(neighbour) # add neighbour to exploration queue
predecessors[neighbour] = current_state # add neighbour to the parent-child dictionary for backtracking
return None
def bfs(maze, start, goal):
q = Queue()
q.enqueue(start)
pred = {start: None}
while (not q.is_empty()):
cc = q.dequeue()
if cc == goal:
return get_path(pred, start, goal)
else:
for key, value in offsets.items():
newpos = tuple(cc[i] + value[i] for i in range(len(cc)))
if is_legal_pos(maze, newpos) and newpos not in pred:
q.enqueue(newpos)
pred[newpos] = cc
def bfs(maze, start, goal):
queue = Queue()
queue.enqueue(start)
predecessors = {start: None}
while not queue.is_empty():
current_cell = queue.dequeue()
if current_cell == goal:
return get_path(predecessors, start, goal)
for direction in ["up", "right", "down", "left"]:
row_offset, col_offset = offsets[direction]
neighbor = (current_cell[0] + row_offset, current_cell[1] + col_offset)
if is_legal_pos(maze, neighbor) and neighbor not in predecessors:
queue.enqueue(neighbor)
predecessors[neighbor] = current_cell
return None
def __init__(self):
self.cats = Queue()
self.dogs = Queue()
class AnimalShelter():
"""A place for animals to be cared for until they're adopted."""
def __init__(self):
self.cats = Queue()
self.dogs = Queue()
def take_in(self, animal):
"""Take a pet in until it's adopted."""
# Is there a better way to handle the timing?
if type(animal) == Cat:
self.cats.enqueue((animal, datetime.datetime.now()))
elif type(animal) == Dog:
self.dogs.enqueue((animal, datetime.datetime.now()))
self.dogs.peek()
else:
print("We don't take that kind of animal here, sorry!")
def introduce_next_pet(self):
"""Show an interested owner the next pet up for adoption."""
next_cat = self.cats.peek()
next_dog = self.dogs.peek()
if next_cat[1] < next_dog[1]:
return next_cat[0]
else:
return next_dog[0]
def release_animal_to_owner(self, species=None):
"""Let a person adopt a pet."""
if species is not None:
if species.lower() == "cat":
return self.cats.dequeue()[0]
elif species.lower() == "dog":
return self.dogs.dequeue()[0]
else:
next_cat = self.cats.peek()
next_dog = self.dogs.peek()
if next_cat[1] < next_dog[1]:
return self.cats.dequeue()[0]
else:
return self.dogs.dequeue()[0]
# Boolean to check if user wishes to continue with app
start = True
# List of possible selection for category
categories = ['G', 'I', 'U', 'P', 'B']
"""
Start of App
"""
print()
print("\tWelcome to abcnews Web Scrapper App!\n")
# Initialize Queues
story_queue = Queue()
old_queue = Queue()
# Iteration counter
i = 0
while start:
selection = input(
'\tPlease select a category (Type Letter): \nGeneral (G) U.S. (U) International (I) Business (B) Politics (P)\n\nCategory: '
).upper()
print()
# Create scrapper object
section_headlines = Abcnews_scrapper()