Day 10 Recursion Part II

Recursion VS Iteration

Below is an example of counting the depth of a binary tree using both iteration and recursion.

#Implementation using iteration:
def depth(tree):
  result = 0
  # our "queue" will store nodes at each level
  queue = [tree]
  # loop as long as there are nodes to explore
  while queue:
    # count the number of child nodes
    level_count = len(queue)
    for child_count in range(0, level_count):
      # loop through each child
      child = queue.pop(0)
     # add its children if they exist
      if child["left_child"]:
        queue.append(child["left_child"])
      if child["right_child"]:
        queue.append(child["right_child"])
    # count the level
    result += 1
  return result
 
two_level_tree = {
"data": 6, 
"left_child":
  {"data": 2}
}
 
four_level_tree = {
"data": 54,
"right_child":
  {"data": 93,
   "left_child":
     {"data": 63,
      "left_child":
        {"data": 59}
      }
   }
}
 
 
depth(two_level_tree)
# 2
depth(four_level_tree)
# 4


#Implementation using recursion:
def depth(tree):
  if not tree:
    return 0

  left_depth = depth(tree["left_child"])
  right_depth = depth(tree["right_child"])

  if left_depth > right_depth:
    return left_depth + 1
  else:
    return right_depth + 1

# HELPER FUNCTION TO BUILD TREES
def build_bst(my_list):
  if len(my_list) == 0:
    return None

  mid_idx = len(my_list) // 2
  mid_val = my_list[mid_idx]

  tree_node = {"data": mid_val}
  tree_node["left_child"] = build_bst(my_list[ : mid_idx])
  tree_node["right_child"] = build_bst(my_list[mid_idx + 1 : ])

  return tree_node

# HELPER VARIABLES
tree_level_1 = build_bst([1])
tree_level_2 = build_bst([1, 2, 3])
tree_level_4 = build_bst([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]) 

# test cases
print(depth(tree_level_1) == 1)
print(depth(tree_level_2) == 2)
print(depth(tree_level_4) == 4)