5 Best Ways to Check Whether the Average Character of the String is Present in Python

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💡 Problem Formulation: In Python, determining if the average character (based on ASCII value) of a string exists within the string itself can be a unique problem to solve. For instance, given the string “abcde”, the average character would be ‘c’. This article explores five different methods to check whether this average character is indeed a part of the original string.

Method 1: Using ASCII Values and the chr() Function

This method revolves around calculating the average ASCII value of all characters in the string and then converting this average back into a character using the chr() function. The presence of this character in the original string is then checked.

Here’s an example:

def average_char_present(s):
    avg_ascii = int(round(sum(map(ord, s)) / len(s)))
    avg_char = chr(avg_ascii)
    return avg_char in s

string = "abcde"
print(average_char_present(string))

Output:

True

This snippet defines a function average_char_present that first calculates the average of the ASCII values of the characters in the string, rounds it to the nearest whole number, converts that average ASCII value to a character, and finally checks if this character is present in the original string.

Method 2: Using the statistics Module

The statistics Python module includes a mean() function that can be used to find the average of a list of numbers. We use it to compute the average of the ASCII values and check for the character’s presence as done in the first method.

Here’s an example:

import statistics

def average_char_present(s):
    avg_ascii = round(statistics.mean(map(ord, s)))
    avg_char = chr(avg_ascii)
    return avg_char in s

string = "hello"
print(average_char_present(string))

Output:

False

In this code, the average_char_present function is defined using the statistics.mean() function to compute the average ASCII value, followed by similar steps of converting it to a character and checking if it’s in the string as outlined in Method 1.

Method 3: Using List Comprehension and the in Operator

This method simplifies the process by using a list comprehension to calculate the sum and subsequently the average character, combining the steps into a one-liner within the return statement.

Here’s an example:

def average_char_present(s):
    return chr(round(sum([ord(char) for char in s]) / len(s))) in s

string = "world"
print(average_char_present(string))

Output:

True

The function average_char_present here makes use of list comprehension within the sum() call to calculate the average ASCII value and immediately checks for the character’s presence in the string, thus succinctly accomplishing the task.

Method 4: Using the reduce() Function from functools

The reduce() function from functools can be used to accumulate the ASCII values, computing the average character in a functional programming style. This method is more efficient for longer strings.

Here’s an example:

from functools import reduce

def average_char_present(s):
    avg_ascii = round(reduce(lambda x, y: x + y, map(ord, s)) / len(s))
    avg_char = chr(avg_ascii)
    return avg_char in s

string = "function"
print(average_char_present(string))

Output:

True

The code defines average_char_present using reduce() to sum the ASCII values, then calculates the average and checks for the character’s presence. This approach may be preferred for its functional programming style and efficiency with long strings.

Bonus One-Liner Method 5: Using a Lambda and the all() Function

A compact one-liner method can be achieved by using a lambda function inside the all() function to evaluate the average character presence directly in the return statement.

Here’s an example:

string = "syntax"
print((lambda s: chr(round(sum(map(ord, s)) / len(s))) in s)(string))

Output:

False

This one-liner lambda function directly calculates the sum, finds the average ASCII value, converts it to a character, and checks its presence in the original string. This method is concise but may sacrifice readability for brevity.

Summary/Discussion

  • Method 1: ASCII Values and chr(). Strengths: Straightforward and easy to understand. Weaknesses: Requires manual implementation of the average calculation.
  • Method 2: Using statistics Module. Strengths: Utilizes built-in functions for cleaner code. Weaknesses: Overhead of importing an additional module.
  • Method 3: List Comprehension. Strengths: More Pythonic with concise syntax. Weaknesses: Might be less readable to beginners.
  • Method 4: reduce() Function. Strengths: Efficient and functional programming approach. Weaknesses: Can be less intuitive than other methods.
  • Method 5: Lambda One-Liner. Strengths: Extremely concise. Weaknesses: Readability can suffer, making it hard to debug or maintain.