utils.py

import math
from collections import Counter

def shannon_entropy(data: str) -> float:
    """
    The following function calculates the Shannon entropy of a given string.

    Entropy is a measure of randomness or unpredictability in data. The higher the entropy, the more likley the randomness -
    a key characteristic of secrets such as API keys, tokens, database URLs, etc.,.

    Args:
        data (str): the input string for calculating entropy.
    
    Returns:
        float: the Shannon entropy value (higher value -> more random).
    
    sources consulted:
        - https://www.sciencedirect.com/topics/engineering/shannon-entropy
        - https://www.reddit.com/r/learnpython/comments/g1sdkh/python_programming_challenge_calculating_shannon/
    """


    #returns 0 if the input is empty
    if not data:
        return 0
    #counts frequency of each character in the given string
    counter = Counter(data)
    length = len(data)
    #application of the shannon entropy formula
    entropy = -sum(count / length * math.log2(count / length) for count in counter.values())

    return entropy