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Leaf nodes from Preorder of a Binary Search Tree

Theory

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Leaf nodes from Preorder of a Binary Search Tree

Don’t start Leaf nodes from Preorder of a Binary Search Tree with jargon. Start with folder on disk. That is the whole point.

Do Leaf nodes from Preorder of a Binary Search Tree once by hand. left < root < right. Change one input. Say the new result out loud.

Without Leaf nodes from Preorder of a Binary Search Tree, a file explorer gets messy and folder on disk is hard to trust.

Leaf nodes from Preorder of a Binary Search Tree shows up in a file explorer. Name folder on disk, not “a real-world scenario”.

Don’t do this with Leaf nodes from Preorder of a Binary Search Tree: unbalanced BST becoming a list. Interviewers spot it in ten seconds.

Leaf nodes from Preorder of a Binary Search Tree is not a lonely heading. Neha ties it to folder on disk.

Close Leaf nodes from Preorder of a Binary Search Tree with: “If I skip it, folder on disk goes wrong like this: unbalanced BST becoming a list.”

Diagram

Exam tip

For Leaf nodes from Preorder of a Binary Search Tree: definition + a file explorer + one failure.

Example

def binary_search(arr, target):
    lo, hi = 0, len(arr) - 1
    while lo <= hi:
        mid = (lo + hi) // 2
        if arr[mid] == target:
            return mid
        if arr[mid] < target:
            lo = mid + 1
        else:
            hi = mid - 1
    return -1

print(binary_search([1, 3, 5, 7, 9], 7))

Leaf nodes from Preorder of a Binary Search Tree — binary search halves a sorted array each step — O(log n).

Short notes

DefLeaf nodes from Preorder of a Binary Search Tree — Neha uses it for folder on disk in a file explorer.
RuleLeaf nodes from Preorder of a Binary Search Tree → left < root < right.
RememberLeaf nodes from Preorder of a Binary Search Tree + Big-O (a file explorer).
UseLeaf nodes from Preorder of a Binary Search Tree in a file explorer (folder on disk).
TrapLeaf nodes from Preorder of a Binary Search Tree — unbalanced BST becoming a list.
ExLeaf nodes from Preorder of a Binary Search Tree → folder on disk.

def binary_search(arr, target): lo, hi = 0, len(arr) - 1 while lo <= hi: mid = (lo + hi) // 2 if arr[mid] == target: return mid if arr[mid] < target: lo = mid + 1 else: hi = mid - 1 return -1 print(binary_search([1, 3, 5, 7, 9], 7))

Leaf nodes from Preorder of a Binary Search Tree

Example

Short notes

Questions

Leaf nodes from Preorder of a Binary Search Tree

Example

Short notes

Questions