Trees
BST Search
Search a binary search tree for one present and one absent value.
Algorithm
The canonical tree is 4(2(1,3),6(5,7)), so this Python DSA
implementation can be compared directly with the rest of the DSA track.
search path
A comparison chooses one subtree at each step, so whole branches are skipped.
Visual walkthrough
Basic Implementation
basic.py
class Node:
def __init__(self, value, left=None, right=None):
self.value = value
self.left = left
self.right = right
def render(node):
if node is None:
return "_"
if node.left is None and node.right is None:
return str(node.value)
return f"{node.value}({render(node.left)},{render(node.right)})"
def sample_tree():
n1 = Node(1)
n3 = Node(3)
n2 = Node(2, n1, n3)
n5 = Node(5)
n7 = Node(7)
n6 = Node(6, n5, n7)
return Node(4, n2, n6)
root = sample_tree()
def search(root, target):
node = root
while node is not None:
if target == node.value:
return True
node = node.left if target < node.value else node.right
return False
print("5 found" if search(root, 5) else "5 not found")
print("8 found" if search(root, 8) else "8 not found")
Complexity
- Time: O(h) per search
- Space: O(1) iterative
Implementation notes
- Python represents each node as a
Nodeobject withvalue,left, andrightattributes.root = sample_tree()keeps a reference to the top node of the checked-in tree. - Search is iterative, not recursive:
node = rootcreates a cursor reference,while node is not Noneguards every attribute read, andnode = node.left if target < node.value else node.rightmoves that cursor without mutating the tree. - The function returns the boolean singletons
TrueorFalse; no search-time nodes are allocated, and Python manages tree objects while they remain reachable fromroot. The replay shows5taking right-left-match and8taking right-right-right toNone.