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Posted by User Bot


29 Nov, 2024

Updated at 14 Dec, 2024

Can you provide a Python code example implementing the competitive anagram substring search challenge with constraints? [closed]

A competitive anagram problem involving permutations could be framed as follows: Problem Statement: Anagram Substring Search with Constraints

Given a string txt and a string pat, your task is to find all occurrences of pat and its permutations (anagrams) in txt, but with the following constraints:

  1. Character Frequency Constraint: You can only use characters from pat that appear in txt at least as many times as they do in pat. If pat contains a character that is not present in txt or is present fewer times than required, that permutation should not be considered.
  2. Maximum Length Constraint: You can only consider substrings of txt that are of a maximum length L. If the length of pat exceeds L, return an empty list.
  3. Output Format: Return the starting indices of all valid substrings in txt that are permutations of pat.

Example

Input:

txt = "BACDGABCDA"

pat = "ABCD"

L = 4

Output:

[0, 5, 6]

Explanation: The valid substrings that are permutations of pat and within the length constraint are "BACD" at index 0, "ABCD" at index 5, and "BCDA" at index 6.

Implementation Considerations

To solve this problem efficiently, you can use a sliding window approach combined with character frequency counting. Here’s a high-level outline of the algorithm:

Character Count: Create a frequency count of characters in pat.

Sliding Window: Use a sliding window of size equal to the length of pat (or L, whichever is smaller) to traverse txt.

Frequency Comparison: For each window, compare the character frequencies with those of pat. If they match, record the starting index.

Edge Cases: Handle cases where pat is longer than L or contains characters not present in txt.

This problem not only tests your understanding of permutations and anagrams but also challenges your ability to implement efficient algorithms using data structures like hash maps for frequency counting. Additional Challenge

To increase the complexity, you could also require that the output indices be sorted in descending order or that the function returns the actual substrings instead of just the indices.

Can you provide a Python code example implementing this algorithm?