Lesson 4/25 · 📋 Linear Structures
📋 Linear StructuresLesson 4/25
Phase 1 · Linear Structures18 min

Two Pointers Technique

Turn O(n²) brute force into elegant O(n) solutions

The two pointers technique uses two variables that traverse a data structure, often from opposite ends, to solve problems that would otherwise need nested loops.
It's one of the most powerful patterns in coding interviews. Master it and you'll solve dozens of problems.
Two Sum on a sorted array, O(n)python
def two_sum_sorted(nums, target):
    """Find two numbers that sum to target. nums is sorted."""
    left, right = 0, len(nums) - 1

    while left < right:
        current_sum = nums[left] + nums[right]
        if current_sum == target:
            return [left, right]
        elif current_sum < target:
            left += 1   # Need bigger sum → move left pointer right
        else:
            right -= 1  # Need smaller sum → move right pointer left
    return []

print(two_sum_sorted([1, 2, 3, 4, 6], 6))  # → [1, 3]

"racecar", compare r↔r, a↔a, c↔c, all match → palindrome

🔀In the Real World...

Merging two sorted arrays in merge sort uses two pointers, one for each array, advancing the pointer for whichever element is smaller. This is what makes merge sort O(n log n) instead of O(n²).

🤔Quick Check

When is the two-pointer technique applicable?

Practice Exercises

0/2 solved
Exercise 1 of 2medium
⏱ 00:00

Palindrome Check

Use two pointers to check if a string is a palindrome (ignoring non-alphanumeric characters and case).
Expected output:TrueFalse
solution.py
1 / 2
Exercise 2 of 2medium
⏱ 00:00

Container With Most Water

Given heights of walls, find two walls that form a container with maximum water area.Area = min(height[left], height[right]) × (right - left)
Expected output: 49
solution.py
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