Find All Anagrams In A String Leetcode Problem 438 [Python Solution]

Are you ready to tackle a coding challenge?

Today, we're going to dive into the Find All Anagrams In A String problem, a LeetCode challenge.

This problem falls under the category of Arrays & Hashing and is categorized as a medium difficulty problem.

It's an interesting problem that can be solved efficiently using Python.

Problem Overview

The problem statement is as follows: Given two strings s and p, your task is to return an array containing all the starting indices of p's anagrams in s.

An anagram is a word or phrase formed by rearranging the letters of another word or phrase, typically using all the original letters exactly once.

Let's take a look at an example to understand the problem better:

Example 1:

• Input: s = "cbaebabacd", p = "abc"
• Output: [0, 6]
• Explanation: In this case, the substring starting at index 0, "cba," is an anagram of "abc." Similarly, the substring starting at index 6, "bac," is also an anagram of "abc."

Example 2:

• Input: s = "abab", p = "ab"
• Output: [0, 1, 2]
• Explanation: Here, we find anagrams of "ab" at indices 0, 1, and 2 in the string s.

Constraints:

• 1 <= s.length, p.length <= 3 * 10^4
• Both s and p consist of lowercase English letters.

Now, let's dive into the problem and explore how to efficiently solve it.

Understanding the Constraints

Before we dive into the code, it's essential to understand the constraints mentioned in the problem.

These constraints are crucial as they help us identify potential edge cases and fine-tune our solution.

1. The lengths of s and p can be relatively large, up to 30,000 characters.

This means that a brute force approach may not be efficient, and we need to find an optimized solution.

1. Both s and p consist of lowercase English letters.

This constraint limits the characters that can appear in the input strings.

It's valuable information for our solution.

Efficient Python Code Solution

Now, let's move on to the efficient Python solution for this problem.

We will utilize a sliding window approach to find anagrams efficiently.

Here's the Python code solution:

def findAnagrams(s: str, p: str):
    # Initialize the start index, pMap, sMap, and the result list.

startIndex = 0
    pMap, sMap = {}, {}
    res = []

    # Count the occurrences of each character in string p.

for char in p:
        pMap[char] = 1 + pMap.get(char, 0)

    # Iterate through string s.

for i in range(len(s)):
        # Count the occurrences of each character in the current window of s.

sMap[s[i]] = 1 + sMap.get(s[i], 0)

        # Check if the current window size is equal to the length of p.

if i >= len(p) - 1:
            # If the current window is an anagram of p, add its start index to the result.

if sMap == pMap:
                res.append(startIndex)

            # If the character at the start index is in sMap, remove it and update the map.

if s[startIndex] in sMap:
                sMap[s[startIndex]] -= 1
                if sMap[s[startIndex]] == 0:
                    del sMap[s[startIndex]]

            # Increment the start index.

startIndex += 1

    return res

In this code, we initialize two dictionaries, pMap and sMap, to count the occurrences of characters in the strings p and s.

We then use a sliding window approach to efficiently find anagrams.

This solution has a time complexity of O(s), where s is the length of the string s.

Now that we have the code, you might wonder how this approach works.

Let's break it down step by step.

1. Initialize Variables and Maps

We start by initializing the startIndex, pMap, and sMap. startIndex keeps track of the start of the current window in s, while pMap and sMap are dictionaries used to count the occurrences of characters in strings p and s.

2. Count Characters in String p

We iterate through the characters in string p and populate the pMap dictionary.

This dictionary will help us determine what an anagram of p should look like.

3. Sliding Window Approach

Now comes the heart of the solution—the sliding window approach.

We iterate through string s, and for each character, we update the sMap to reflect the character count within the current window.

We also check if the current window size is equal to the length of p.

4. Checking for Anagrams

When the window size matches the length of p, we compare sMap with pMap.

If they are equal, it means we have found an anagram of p, and we add the startIndex to our result list.

5. Shifting the Window

To continue the sliding window approach, we need to shift the window.

We remove the character at the startIndex from sMap and update it accordingly.

We then increment the startIndex.

6. Repeat and Collect Results

We continue this process until we have checked all possible windows in the string s.

The result list contains the starting indices of all substrings that are anagrams of p.

Time and Space Complexity

The time complexity of this solution is O(s), where s is the length of string s.

This is achieved by iterating through the string once while maintaining a sliding window with constant-time operations.

The space complexity is O(1) for the hash maps pMap and sMap because they store a fixed number of unique characters (26 in this case).

The result list res has a space complexity of O(s) in the worst case, as it can potentially store all starting indices.

Reasoning Behind Our Approach

The efficient solution to this problem relies on the sliding window approach and the use of hash maps to count character occurrences.

The sliding window technique allows us to avoid redundant counting of characters, which significantly improves the efficiency of the algorithm.

By maintaining separate hash maps for string p and the current window in string s, we can quickly check if we have found an anagram.

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Conclusion

In this blog post, we explored the LeetCode problem Find All Anagrams In A String We learned how to efficiently solve this problem using a sliding window approach and hash maps to count character occurrences.

The time complexity of our solution is O(s), making it an efficient way to find anagrams in a given string s.

Remember that understanding the problem constraints and leveraging appropriate data structures and techniques are essential in solving coding challenges

efficiently.

Feel free to try out the solution and explore other LeetCode problems to sharpen your coding skills.

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If you have any questions, suggestions, or feedback, don't hesitate to leave a comment.

Happy coding!

Question Link

Now, it's your turn to dive into the code, experiment with it, and explore more coding challenges.

If you have any questions, feel free to ask, share your thoughts, or suggest additional topics you'd like to see covered in future posts.

Happy coding!