Mastering Sliding Window Technique in Python

A powerful pattern to optimize problems involving subarrays and substrings.

What is Sliding Window?

Sliding window is a technique where we maintain a window (subarray) and move it step-by-step instead of recomputing values repeatedly.

Why Use It?

• Reduces time complexity
• Avoids nested loops
• Efficient for contiguous subarrays

Fixed Window Example

def max_sum_subarray(arr, k):
      window_sum = sum(arr[:k])
      max_sum = window_sum
  
      for i in range(k, len(arr)):
          window_sum += arr[i]
          window_sum -= arr[i - k]
          max_sum = max(max_sum, window_sum)
  
      return max_sum

Variable Window Example

def longest_substring(s):
      seen = set()
      left = 0
      max_len = 0
  
      for right in range(len(s)):
          while s[right] in seen:
              seen.remove(s[left])
              left += 1
  
          seen.add(s[right])
          max_len = max(max_len, right - left + 1)
  
      return max_len

Common Patterns

• Fixed window size (k)
• Variable window size
• Substring problems
• Maximum / minimum window

When to Use

• Contiguous subarrays
• Strings and substrings
• Optimization problems