def generate() -> BinaryTree:
tree = BinaryTree()
tree.root = Node(randint(1, 1000))
generate_helper(tree.root, 0.7, 0.7)
# suggestion: don't use higher values for probability, it will lead to recursion
# error
return tree
def create_trees(n: int) -> List[BinaryTree]:
tree_arr = []
if n == 0:
return tree_arr
tree = BinaryTree()
tree.root = Node(0)
tree_arr.append(tree)
create_trees_helper(tree_arr, n - 1)
return tree_arr
def deserialize(string: str) -> BinaryTree:
# the string needs to have the same format as the binary tree serialization
# eg: data is padded with single quotes (') and comma (,) is used as a delimiter
data = string.split(",")
queue = Queue()
for node in data:
queue.enqueue(node)
tree = BinaryTree()
tree.root = Node(queue.dequeue().strip("'"))
deserialize_helper(tree.root, queue)
return tree
def merge_trees(tree1: BinaryTree, tree2: BinaryTree) -> BinaryTree:
tree = BinaryTree()
if not tree1.root and not tree2.root:
return tree
# root generation
r1, r2 = 0, 0
if tree1.root:
r1 = tree1.root.val
if tree2.root:
r2 = tree2.root.val
tree.root = Node(r1 + r2)
# generating rest of the tree
merge_trees_helper(tree.root, tree1.root, tree2.root)
return tree
def generate_tree(preorder: List[int], inorder: List[int]) -> BinaryTree:
length = len(preorder)
if length != len(inorder):
raise RuntimeError
if length == 0:
return BinaryTree()
# generating the root
root = preorder[0]
tree = BinaryTree()
tree.root = Node(root)
# generating the rest of the tree
if length > 1:
i = inorder.index(root)
# partitioning the nodes as per the branch
inorder_left, preorder_left = (inorder[:i], preorder[1 : i + 1])
inorder_right, preorder_right = (inorder[i + 1 :], preorder[i + 1 :])
# creating a tree for each branch
tree_left = generate_tree(preorder_left, inorder_left)
tree_right = generate_tree(preorder_right, inorder_right)
# attaching the sub-tree to their respective branch
tree.root.left = tree_left.root
tree.root.right = tree_right.root
return tree
get_bottom_view_helper(node.left, depth + 1, hd - 1, accumulator)
if node.right:
get_bottom_view_helper(node.right, depth + 1, hd + 1, accumulator)
return accumulator
def get_bottom_view(tree: BinaryTree) -> List[int]:
data = get_bottom_view_helper(tree.root, 0, 0, {})
res_arr = [(hd, data[hd][1]) for hd in data]
res_arr.sort(key=lambda elem: elem[0])
return [elem for _, elem in res_arr]
if __name__ == "__main__":
tree = BinaryTree()
tree.root = Node(5)
tree.root.left = Node(3)
tree.root.right = Node(7)
tree.root.left.left = Node(1)
tree.root.left.right = Node(4)
tree.root.right.left = Node(6)
tree.root.right.right = Node(9)
tree.root.left.left.left = Node(0)
tree.root.right.right.left = Node(8)
print(tree)
l_max_sum + node.val,
r_max_sum + node.val,
l_max_sum + node.val + r_max_sum,
)
# overall max sum is updated as per requirement
overall_max_sum = max(current_max_sum, overall_max_sum)
return overall_max_sum
def get_max_path_sum(tree: BinaryTree) -> int:
return get_max_path_sum_helper(tree.root)
if __name__ == "__main__":
tree = BinaryTree()
tree.root = Node(1)
print(tree)
print(get_max_path_sum(tree))
tree.root.left = Node(2)
print(tree)
print(get_max_path_sum(tree))
tree.root.right = Node(3)
print(tree)
print(get_max_path_sum(tree))
tree.root.val = -1
print(tree)
print(get_max_path_sum(tree))
tree1 = BinarySearchTree()
tree1.add(5)
tree1.add(9)
tree1.add(1)
tree1.add(4)
tree1.add(10)
tree1.add(3)
tree1.add(2)
tree1.add(10)
tree1.add(7)
print(is_binary_search_tree(tree1))
tree2 = BinaryTree()
tree2.root = Node(5)
tree2.root.left = Node(4)
tree2.root.right = Node(6)
print(is_binary_search_tree(tree2))
tree3 = BinaryTree()
tree3.root = Node(5)
tree3.root.left = Node(6)
tree3.root.right = Node(4)
print(is_binary_search_tree(tree3))
"""
SPECS:
self.right.calculate_helper())
return self.val
def calculate_expression_tree(tree: BinaryTree) -> Union[int, float]:
root = tree.root
if root:
root.transform_helper()
return root.calculate_helper()
return None
if __name__ == "__main__":
tree = BinaryTree()
tree.root = ExpressionTreeNode("*")
tree.root.left = ExpressionTreeNode("+")
tree.root.right = ExpressionTreeNode("+")
tree.root.left.left = ExpressionTreeNode(3)
tree.root.left.right = ExpressionTreeNode(2)
tree.root.right.left = ExpressionTreeNode(4)
tree.root.right.right = ExpressionTreeNode(5)
print(calculate_expression_tree(tree))
"""
SPECS:
TIME COMPLEXITY: O(n)
SPACE COMPLEXITY: O(log(n))
return tree
# root generation
r1, r2 = 0, 0
if tree1.root:
r1 = tree1.root.val
if tree2.root:
r2 = tree2.root.val
tree.root = Node(r1 + r2)
# generating rest of the tree
merge_trees_helper(tree.root, tree1.root, tree2.root)
return tree
if __name__ == "__main__":
tree1 = BinaryTree()
tree1.root = Node(1)
tree1.root.left = Node(2)
tree1.root.right = Node(3)
tree1.root.left.right = Node(4)
print(tree1)
tree2 = BinaryTree()
tree2.root = Node(2)
tree2.root.right = Node(-3)
tree2.root.right.right = Node(10)
print(tree2)
print(merge_trees(tree1, tree2))
"""
SPECS:
return True
if self.left:
left = self.left._is_any_descendant_unlocked()
else:
left = False
if self.right:
right = self.right._is_any_descendant_unlocked()
else:
right = False
return left or right
if __name__ == "__main__":
tree = BinaryTree()
tree.root = NodeWithLock(5)
tree.root.left = NodeWithLock(3)
tree.root.left.parent = tree.root
tree.root.right = NodeWithLock(18)
tree.root.right.parent = tree.root
tree.root.left.left = NodeWithLock(0)
tree.root.left.left.parent = tree.root.left
print(tree)
print()
print(tree.root.left.left.lock())
print(tree.root.left.lock())
print(tree.root.lock())
node.left = node.right.left
node.right = node.right.right
create_full_bin_tree_helper(node)
elif node.left is not None and node.right is not None:
create_full_bin_tree_helper(node.left)
create_full_bin_tree_helper(node.right)
def create_full_bin_tree(tree: BinaryTree) -> None:
if tree.root:
create_full_bin_tree_helper(tree.root)
if __name__ == "__main__":
tree = BinaryTree()
tree.root = Node("a")
tree.root.left = Node("b")
tree.root.right = Node("c")
tree.root.left.left = Node("d")
tree.root.left.left.right = Node("f")
tree.root.right.right = Node("e")
tree.root.right.right.left = Node("g")
tree.root.right.right.right = Node("h")
print(tree)
create_full_bin_tree(tree)
# the string needs to have the same format as the binary tree serialization
# eg: data is padded with single quotes (') and comma (,) is used as a delimiter
data = string.split(",")
queue = Queue()
for node in data:
queue.enqueue(node)
tree = BinaryTree()
tree.root = Node(queue.dequeue().strip("'"))
deserialize_helper(tree.root, queue)
return tree
if __name__ == "__main__":
tree = BinaryTree()
tree.root = Node("root")
tree.root.left = Node("left")
tree.root.right = Node("right")
tree.root.left.left = Node("left.left")
print(serialize(tree))
generated_tree = deserialize(
"'root','left','left.left','None','None','None','right','None','None'"
)
print(serialize(generated_tree))
if sub_tree1.left and find_helper(sub_tree1.left, sub_tree2):
return True
if sub_tree1.right and find_helper(sub_tree1.right, sub_tree2):
return True
return False
def get_match(s: BinaryTree, t: BinaryTree) -> bool:
if s.root and t.root:
return find_helper(s.root, t.root)
return False
if __name__ == "__main__":
tree1 = BinaryTree()
tree1.root = Node(0)
tree1.root.left = Node(1)
tree1.root.right = Node(2)
tree1.root.right.left = Node(3)
tree1.root.right.right = Node(4)
tree2 = BinaryTree()
tree2.root = Node(2)
tree2.root.left = Node(3)
tree2.root.right = Node(4)
tree3 = BinaryTree()
tree3.root = Node(2)
tree3.root.left = Node(3)
tree3.root.right = Node(5)
g = Node(700)
h = Node(800)
a.left = b
a.right = c
b.left = d
b.right = e
c.left = f
c.right = g
d.right = h
tree = BinaryTree()
tree.root = a
print(tree)
print(get_level_min_sum(tree))
a.val = 1000
print(tree)
print(get_level_min_sum(tree))
b.val = 1500
print(tree)
print(get_level_min_sum(tree))
h.val = 2000
print(tree)
print(get_level_min_sum(tree))
"""
SPECS:
current_balance = -1 <= (right_height - left_height) <= 1
height = max(left_height, right_height) + 1
return height, balance and current_balance
def check_balance(tree: BinaryTree) -> bool:
if tree.root is None:
return True
_, balance = height_helper(tree.root)
return balance
if __name__ == "__main__":
tree = BinaryTree()
tree.root = Node(0)
tree.root.left = Node(1)
tree.root.right = Node(2)
tree.root.left.left = Node(3)
tree.root.left.right = Node(4)
print(check_balance(tree))
tree.root.left.right.left = Node(5)
print(check_balance(tree))
"""
SPECS:
def generate_cartesian_tree(sequence: List[int]) -> BinaryTree:
tree = BinaryTree()
tree.root = generate_cartesian_tree_helper(sequence)
return tree