tvl-depot/users/wpcarro/scratch/data_structures_and_algorithms/dft.py

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from random import choice
class Node(object):
def __init__(self, value=None, left=None, right=None):
self.value = value
self.left = left
self.right = left
def p(node, indent=0):
print(indent * ' ' + '|-' + str(node.value))
if node.left is not None:
p(node.left, indent=indent + 2)
if node.right is not None:
p(node.right, indent=indent + 2)
# read trees (i.e. traversing, parsing)
# write trees (i.e. generating, printing)
def random(d=0):
left = None
right = None
if choice([True, False]):
left = random(d + 1)
if choice([True, False]):
right = random(d + 1)
return Node(
value=d,
left=left,
right=right,
)
################################################################################
# DFTs can be:
# - imperative (mutable)
# - functional (immutable)
# - iterative
# - recursive
################################################################################
# Iterative
def traverse(node, f):
stack = [(node, 0)]
while len(stack):
node, depth = stack.pop()
f(node, depth)
print(depth)
if node.left is not None:
stack.append((node.left, depth + 1))
if node.right is not None:
stack.append((node.right, depth + 1))
print('----------------------------------------------------------------------')
for _ in range(10):
traverse(random(), lambda _, d: print(d))
print()