def __init__(self, length: int = DEFAULT_CAPACITY):
"""
complexity: O(n)
"""
Queue.__init__(self)
self.front = 0
self.rear = 0
self.array = [None] * length
def remove_all(queue: Queue) -> None:
"""Remove all items from the given queue.
>>> queue = Queue()
>>> queue.enqueue(1)
>>> queue.enqueue(2)
>>> queue.enqueue(3)
>>> remove_all(queue)
>>> queue.is_empty()
True
"""
while not queue.is_empty():
queue.dequeue()
def test_remove_all_but_one_doctest2() -> None:
"""Test is the doctest given in remove_all_but_one."""
queue = Queue()
queue.enqueue(2)
queue.enqueue(2)
queue.enqueue(3)
remove_all_but_one(queue)
assert queue.is_empty() is False
assert queue.dequeue() == 3
assert queue.is_empty()
def solve(self,
puzzle: Puzzle,
seen: Optional[Set[str]] = None) -> List[Puzzle]:
"""
Return a list of puzzle states representing a path to a solution of
<puzzle>. The first element in the list should be <puzzle>, the
second element should be a puzzle that is in <puzzle>.extensions(),
and so on. The last puzzle in the list should be such that it is in a
solved state.
In other words, each subsequent item of the returned list should take
the puzzle one step closer to a solution, which is represented by the
last item in the list.
Return an empty list if the puzzle has no solution.
<seen> is either None (default) or a set of puzzle states' string
representations, whose puzzle states can't be any part of the path to
the solution.
"""
if puzzle.is_solved():
return [puzzle]
puzzle_copy = puzzle.extensions()
path_options = Queue()
path_options.enqueue(puzzle_copy)
path = []
seen = []
while not path_options.is_empty():
path.extend(path_options.dequeue())
puzzle_copy = []
for states in path:
if any(str(states) in fails for fails in seen):
path.remove(states)
elif states.fail_fast():
seen.append(str(path.remove(states)))
else:
puzzle_copy.extend(states.extensions())
if not puzzle_copy:
path_options = Queue()
if path[-1].is_solved:
return path
else:
path_options.enqueue(puzzle_copy)
def _check_extensions(p: Puzzle,
q: Queue,
path: List[Puzzle],
seen: Optional[Set[str]] = None) -> Queue:
"""
Checks the extensions of the inputted puzzle and returns a new queue
with all the extensions that do not fail fast and are not in seen.
Also modifies the path list so that it contains the new extension as a
path or removes all paths that led to the extension that fails fast.
"""
for p2 in p.extensions():
if not p2.fail_fast() and not p2.__str__() in seen:
q.enqueue(path + [p2])
seen.add(p2.__str__())
else:
seen.add(p2.__str__())
return q
def test_remove_all_doctest() -> None:
"""This is the doctest given in remove_all."""
queue = Queue()
queue.enqueue(1)
queue.enqueue(2)
queue.enqueue(3)
remove_all(queue)
assert queue.is_empty()
def filter_queue(q: Queue, min: int) -> None:
"""Remove all items from <q> that are less than <minimum>.
>>> q = Queue()
>>> q.enqueue(2)
>>> q.enqueue(21)
>>> q.enqueue(5)
>>> q.enqueue(1)
>>> filter_queue(q, 10)
>>> q.dequeue()
21
>>> q.is_empty()
True
"""
temp_queue = Queue()
while not q.is_empty():
value = q.dequeue()
if value >= min:
temp_queue.enqueue(value)
while not temp_queue.is_empty():
q.enqueue(temp_queue.dequeue())
def remove_all_but_one(queue: Queue) -> None:
"""Remove all items from the given queue except the last one.
Precondition: <queue> contains at least one item.
or: not queue.is_empty()
>>> queue = Queue()
>>> queue.enqueue(1)
>>> queue.enqueue(2)
>>> queue.enqueue(3)
>>> remove_all_but_one(queue)
>>> queue.is_empty()
False
>>> queue.dequeue()
3
>>> queue.is_empty()
True
"""
while not queue.is_empty():
b1 = queue.dequeue()
queue.enqueue(b1)
def simulate_one_server(input_file):
"""
Server simulator
:param input_file: (File) - Request inputs file.
:return: (Float) - Average wait time for a request
"""
www = Server()
req_queue = Queue()
try:
with open(input_file, 'rb') as infile:
req_data = csv.reader(infile)
w_times = []
for row in req_data:
req_queue.enqueue(Request(row))
if not www.busy() and not req_queue.is_empty():
curr = req_queue.dequeue()
www.start_next(curr)
curr_time = curr.get_stamp()
w_times.append(curr.wait_time(curr_time))
www.tick()
avg_wait = float(sum(w_times)) / len(w_times)
return 'Average wait: {:.2f} seconds\n' \
'\t Tasks remaining {}' \
.format(avg_wait, req_queue.size())
except IOError:
print 'Could not open {}'.format(input_file)
def solve(self, puzzle: Puzzle,
seen: Optional[Set[str]] = None) -> List[Puzzle]:
"""
Return a list of puzzle states representing a path to a solution of
<puzzle>. The first element in the list should be <puzzle>, the
second element should be a puzzle that is in <puzzle>.extensions(),
and so on. The last puzzle in the list should be such that it is in a
solved state.
In other words, each subsequent item of the returned list should take
the puzzle one step closer to a solution, which is represented by the
last item in the list.
Return an empty list if the puzzle has no solution.
<seen> is either None (default) or a set of puzzle states' string
representations, whose puzzle states can't be any part of the path to
the solution.
"""
if puzzle.fail_fast():
return []
if seen is not None:
if str(puzzle) in seen:
return []
if puzzle.is_solved():
return [puzzle]
if seen is None:
seen = {str(puzzle)}
else:
seen.add(str(puzzle))
queue = Queue()
for extension in puzzle.extensions():
queue.enqueue([puzzle, extension])
while not queue.is_empty():
curr_path = queue.dequeue()
examine = curr_path[-1]
if examine.is_solved():
if seen is None or str(examine) not in seen:
return curr_path
if not (examine.fail_fast() or (str(examine) in seen)):
seen.add(str(examine))
for extension in examine.extensions():
new_path = curr_path + [extension]
queue.enqueue(new_path)
return []
def construct_from_list(values: List[List[Union[str, int]]]) -> ExprTree:
"""
Construct an expression tree from <values>.
See the handout for a detailed explanation of how <values>
encodes the expression tree.
Hint: We have provided you with the helper method ExprTree.append
You will likely want to use this method.
Precondition:
<values> encodes a valid expression tree
>>> example = [[5]]
>>> exp_t = construct_from_list(example)
>>> exp_t == ExprTree(5, [])
True
>>> print(exp_t)
5
>>> print(ExprTree(5, []))
5
>>> example = [['+'], [3, 'a']]
>>> exp_t = construct_from_list(example)
>>> subtrees = [ExprTree(3, []), ExprTree('a', [])]
>>> exp_t == ExprTree('+', subtrees)
True
"""
if not values:
return ExprTree(None, [])
copy = values[:]
current_level = Queue()
first = copy.pop(0)[0]
if first not in OPERATORS:
return ExprTree(first, [])
else:
result = ExprTree(first, [])
current_level.enqueue(result)
while copy:
lst = copy.pop(0)
tree = current_level.dequeue()
for element in lst:
subtree = ExprTree(element, [])
tree.append(subtree)
if element in OPERATORS:
current_level.enqueue(subtree)
return result
def solve(self, puzzle: Puzzle,
seen: Optional[Set[str]] = None) -> List[Puzzle]:
"""
Return a list of puzzle states representing a path to a solution of
<puzzle>. The first element in the list should be <puzzle>, the
second element should be a puzzle that is in <puzzle>.extensions(),
and so on. The last puzzle in the list should be such that it is in a
solved state.
In other words, each subsequent item of the returned list should take
the puzzle one step closer to a solution, which is represented by the
last item in the list.
Return an empty list if the puzzle has no solution.
<seen> is either None (default) or a set of puzzle states' string
representations, whose puzzle states can't be any part of the path to
the solution.
"""
queue = Queue()
if seen is None:
seen = set()
queue.enqueue([puzzle])
while not queue.is_empty():
lst = queue.dequeue()
p = lst[-1]
if p.fail_fast() or str(p) in seen:
if str(p) not in seen:
seen.add(str(p))
elif p.is_solved():
return lst
else:
for puz in p.extensions():
sublst = lst + [puz]
queue.enqueue(sublst)
return []
def construct_from_list(values: List[List[Union[str, int]]]) -> ExprTree:
"""
Construct an expression tree from <values>.
See the handout for a detailed explanation of how <values>
encodes the expression tree.
Hint: We have provided you with the helper method ExprTree.append
You will likely want to use this method.
Precondition:
<values> encodes a valid expression tree
>>> example = [[5]]
>>> exp_t = construct_from_list(example)
>>> exp_t == ExprTree(5, [])
True
>>> print(exp_t)
5
>>> print(ExprTree(5, []))
5
>>> example = [['+'], [3, 'a']]
>>> exp_t = construct_from_list(example)
>>> subtrees = [ExprTree(3, []), ExprTree('a', [])]
>>> exp_t == ExprTree('+', subtrees)
True
"""
solution = ExprTree(values[0][0], [])
temp = Queue()
temp.enqueue(solution)
lst = values
lst.remove(values[0])
for value in values:
v = temp.dequeue()
for i in value:
if i in ["*", "+"]:
tree = ExprTree(i, [])
temp.enqueue(tree)
v.append(tree)
else:
v.append(ExprTree(i, []))
return solution
def construct_from_list(values: List[List[Union[str, int]]]) -> ExprTree:
"""
Construct an expression tree from <values>.
See the handout for a detailed explanation of how <values>
encodes the expression tree.
Hint: We have provided you with the helper method ExprTree.append
You will likely want to use this method.
Precondition:
<values> encodes a valid expression tree
>>> example = [[5]]
>>> exp_t = construct_from_list(example)
>>> exp_t == ExprTree(5, [])
True
>>> print(exp_t)
5
>>> print(ExprTree(5, []))
5
>>> example = [['+'], [3, 'a']]
>>> exp_t = construct_from_list(example)
>>> subtrees = [ExprTree(3, []), ExprTree('a', [])]
>>> exp_t == ExprTree('+', subtrees)
True
"""
queue = Queue()
a = ExprTree(values.pop(0)[-1], [])
queue.enqueue(a)
for lst in values:
gen = queue.dequeue()
for i in lst:
root = ExprTree(i, [])
if i in OPERATORS:
queue.enqueue(root)
gen.append(root)
else:
gen.append(root)
return a
def solve(self,
puzzle: Puzzle,
seen: Optional[Set[str]] = None) -> List[Puzzle]:
"""
Return a list of puzzle states representing a path to a solution of
<puzzle>. The first element in the list should be <puzzle>, the
second element should be a puzzle that is in <puzzle>.extensions(),
and so on. The last puzzle in the list should be such that it is in a
solved state.
In other words, each subsequent item of the returned list should take
the puzzle one step closer to a solution, which is represented by the
last item in the list.
Return an empty list if the puzzle has no solution.
<seen> is either None (default) or a set of puzzle states' string
representations, whose puzzle states can't be any part of the path to
the solution.
"""
if seen is None:
seen = set()
if puzzle.fail_fast():
return []
else:
lst = puzzle.extensions()
potentials = Queue()
for i in lst:
if not i.fail_fast() and not i.__str__() in seen:
potentials.enqueue([puzzle] + [i])
while not potentials.is_empty():
path = potentials.dequeue()
if path[-1].is_solved():
return path
potentials = _check_extensions(path[-1], potentials, path,
seen)
return []
def list_nestedness(lst: List[int], q: Queue) -> List[List[int]]:
"""
Return a list of elements of lst in each level of nestedness using q.
Precondition: q is empty.
lst contains only ints.
>>> lst = [1, [[[2], 3]], [4, [5]]]
>>> list_nestedness(lst, Queue())
[[1], [4], [3, 5], [2]]
"""
# Step 1. Add all of the items from lst into c
for item in lst:
q.add(item)
# LIST_NESTEDNESS - 2. Add "END" to the Queue
q.add("END")
# LIST_NESTEDNESS - 3. Create an empty list called level
level = []
# LIST_NESTEDNESS - 4. Create an empty list called all_levels
all_levels = []
# Step 2. Repeat the following until c is empty
while not q.is_empty():
# Step 2a. Remove an item from the container
removed_item = q.remove()
# Step 2b. If that item is not a list, print it out
if not isinstance(removed_item, list):
# LIST_NESTEDNESS - 5B. If removed_item is "END" append level to
# all_levels and set level to an empty list.
if removed_item == "END":
all_levels.append(level)
level = []
# LIST_NESTEDNESS - 5BI. If the Queue is not empty, add "END"
# to the Queue
if not q.is_empty():
q.add("END")
else:
# LIST_NESTEDNESS - 5C. If removed_item is not a list or "END",
# add it to the list 'level'
level.append(removed_item)
else:
# Step 2c. If it is a list, add all of its items into c
for item in removed_item:
q.add(item)
# Return all_levels when we're done.
return all_levels
def __init__(self, length: int = DEFAULT_CAPACITY):
Queue.__init__(self)
self.front = 0
self.rear = 0
self.array = [None] * length
def clear(self) -> None:
Queue.clear(self)
self.front = 0
self.rear = 0