Longest Repeating Character Replacement
Detailed guide and Python implementation for the 'Longest Repeating Character Replacement' problem.
1. Concept Overview
The 'Longest Repeating Character Replacement' problem is a key challenge in the Sliding Window section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Longest Repeating Character Replacement.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Longest Repeating Character Replacement carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Problem Statement
You are given a string s and an integer k. You can choose any character of the string and change it to any other uppercase English letter. You can perform this operation at most k times.
Return the length of the longest substring containing the same letter you can get after performing the above operations.
Write a function characterReplacement(s: str, k: int) -> int.
- •1 <= len(s) <= 10^5
- •s consists of only uppercase English letters
- •0 <= k <= len(s)
Examples
s = "ABAB", k = 2
4
Replace the two 'A's with 'B's or vice versa to get "BBBB" or "AAAA". The longest substring is 4.
s = "AABABBA", k = 1
4
Replace the 'B' at index 3 with 'A' to get "AAAAABA". The longest substring of same characters starting from index 0 is "AAAA" with length 4.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Ready to Solve?
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Interview Insights & Variations
Complexity Analysis Breakdown
Why Time: Directly evaluates all possibilities.
Why Space: Uses standard local memory.
Why Time: Optimized paths reduce total operations.
Why Space: May trade memory for speed.
Optimized Solution Python Code
Optimized Solution Python Code
def character_replacement_opt(s, k):
count = {}
res = 0
l = 0
maxf = 0
for r in range(len(s)):
count[s[r]] = 1 + count.get(s[r], 0)
maxf = max(maxf, count[s[r]])
if (r - l + 1) - maxf > k:
count[s[l]] -= 1
l += 1
res = max(res, r - l + 1)
return resBrute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def character_replacement_brute(s, k):
res = 0
for i in range(len(s)):
counts = {}
max_f = 0
for j in range(i, len(s)):
counts[s[j]] = 1 + counts.get(s[j], 0)
max_f = max(max_f, counts[s[j]])
if (j - i + 1) - max_f <= k:
res = max(res, j - i + 1)
return resAlgorithm Pattern Checklist
When dealing with Sliding Window data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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