5 Best Ways to Check if a String Can Be Rearranged to Form a Special Palindrome in Python

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πŸ’‘ Problem Formulation: A special palindrome in the context of this article refers to a string that can be rearranged to form a palindrome where characters are the same in any continuous sequence of the same characters. For example, the input string “aabbcc” can be rearranged to “acbca” or “baccab” to meet this criterion. We aim to explore methods to ascertain if such a rearrangement is possible.

Method 1: Frequency Counter with Even-Odd Logic

This method involves creating a frequency counter of all characters in the string and ensuring that at most one character has an odd count, which is a requirement for a string to be rearrangeable into a special palindrome.

Here’s an example:

from collections import Counter

def can_form_special_palindrome(s):
    frequency = Counter(s)
    odd_count = sum(1 for char_count in frequency.values() if char_count % 2 != 0)
    return odd_count <= 1


Output: True

This code snippet uses collections.Counter to record the count of each character in the string. It then checks the condition that there can be at most one character with an odd count, else it’s not possible to arrange it into a special palindrome.

Method 2: Sorting and Pairing

By sorting the string and then ensuring that characters can be paired up (with a possible single middle character), we can verify if the string is rearrangeable into a special palindrome.

Here’s an example:

def can_be_special_palindrome(s):
    sorted_str = sorted(s)
    mid_found = False
    i = 0

    while i < len(sorted_str):
        if i == len(sorted_str) - 1 or sorted_str[i] != sorted_str[i + 1]:
            if mid_found: 
                return False  
            mid_found = True
            i += 1
            i += 2
    return True


Output: True

This method involves sorting the string first and then iterating through it to check if characters can form pairs, allowing for a single unpaired character which would sit in the center of a special palindrome.

Method 3: Using Python Sets

By leveraging the properties of sets in Python to find unique characters and comparing their counts, we can deduce the ability to form a special palindrome.

Here’s an example:

def can_form_special_palindrome_v3(s):
    unique_chars = set(s)
    odd_count = 0
    for char in unique_chars:
        if s.count(char) % 2 != 0:
            odd_count += 1
            if odd_count > 1:
                return False
    return True


Output: True

This method uses the uniqueness attribute of sets to iterate over each character only once and check for the odd occurrences of characters, allowing for a maximum of one to fit the special palindrome requirement.

Method 4: Greedy Approach

A greedy approach assumes that if two adjacent letters are the same, they can form a part of a palindrome, and if not, checks if rearrangement possibilities exhausted.

Here’s an example:

def can_form_special_palindrome_v4(s):
    for char in set(s):
        if s.count(char) == 1:
            return False
        half_count = s.count(char) // 2
        s = s.replace(char, '', half_count * 2)
    return len(s) <= 1


Output: True

This code attempts to greedily remove pairs of matching characters from the string, assessing the feasibility of forming a special palindrome based on the residual characters. If more than one character is left unpaired, it returns false.

Bonus One-Liner Method 5: Using List Comprehensions

Python list comprehensions can provide a concise way of determining special palindrome viability based on character counts, by checking the length of the list of odd-occurring characters.

Here’s an example:

def can_form_special_palindrome_oneliner(s):
    return len([char for char in set(s) if s.count(char) % 2]) <= 1


Output: True

This single-line function expresses the logic coherently in one line by creating a list of characters with odd counts and ensuring said list does not exceed one character.


  • Method 1: Frequency Counter with Even-Odd Logic. Strengths: Efficient and straightforward logic. Weaknesses: Requires additional space for the frequency counter.
  • Method 2: Sorting and Pairing. Strengths: Intuitive and works well with sorted data. Weaknesses: Time complexity increases due to sorting operation.
  • Method 3: Using Python Sets. Strengths: Single-pass solution, utilizing the uniqueness of set elements. Weaknesses: Multiple count operations increase the time complexity.
  • Method 4: Greedy Approach. Strengths: Directly attempts to reduce the string to a potential palindrome. Weaknesses: Repeated string operations may be costly.
  • Method 5: One-Liner using List Comprehensions. Strengths: Elegant and simple. Weaknesses: Same as Method 3 regarding time complexity due to multiple counts.