**π‘ Problem Formulation:** Python programmers often need to manipulate numerical data. A common task could be replacing specific digits in a number – for instance, replacing all occurrences of the digit ‘0’ with ‘5’ in a given integer. For example, transforming the integer 1050 should result in 1555.

## Method 1: Using Sting Conversion

This method leverages Python’s ability to convert numbers to strings for easy manipulation. The `str.replace()`

function is then utilized to substitute ‘0’ with ‘5’, followed by a conversion back to an integer.

Here’s an example:

number = 1050 replaced_number = int(str(number).replace('0', '5')) print(replaced_number)

Output: `1555`

This method is straightforward and takes advantage of Python’s dynamic type conversion. First, the integer is converted to a string allowing the replace function to change all ‘0’s to ‘5’s. The string is then converted back into a integer for the final result.

## Method 2: Using Mathematical Manipulation

By decomposing a number mathematically, digits can be examined and replaced logically. This involves digit extraction, comparison, and construction of the new number.

Here’s an example:

def replace_zero_with_five(number): result_num = 0 decimal_place = 1 while (number > 0): digit = number % 10 if digit == 0: digit = 5 result_num += digit * decimal_place number //= 10 decimal_place *= 10 return result_num print(replace_zero_with_five(1050))

Output: `1555`

This mathematical approach inspects each digit and conditionally replaces zeros. It builds the new number from the rightmost digit, shifting it correctly according to its original place value. This method is efficient but might be less intuitive for those unfamiliar with numeric algorithms.

## Method 3: Using List Comprehension and Join

Python’s list comprehension provides a concise way to iterate over elements. In this method, a list of single characters is created from the original number, each character is replaced if needed, and then concatenated back into a string.

Here’s an example:

number = 1050 replaced_number = int(''.join(['5' if digit=='0' else digit for digit in str(number)])) print(replaced_number)

Output: `1555`

This method uses Python’s powerful list comprehension to create a list of characters, replacing ‘0’ with ‘5’. The `join()`

method then merges these into a new string, which is converted back to an integer. This is a more Pythonic approach and maintains readability.

## Method 4: Using Recursion

Recursion is a way to break down a problem into smaller instances of itself. It’s a more elegant solution where the function calls itself with a simpler version of the original problem until it arrives at a simple base case.

Here’s an example:

def replace_zero_with_five_recursive(number): if number == 0: return 0 digit = number % 10 if digit == 0: digit = 5 return replace_zero_with_five_recursive(number // 10) * 10 + digit print(replace_zero_with_five_recursive(1050))

Output: `1555`

The recursive method works by reducing the number by a factor of ten each time and dealing with the last digit. If the digit is zero, it is replaced by five; otherwise, it remains unchanged. This method keeps the stack depth proportional to the number of digits in the number, which could be a limitation for very large numbers.

## Bonus One-Liner Method 5: Using Regular Expressions

Regular expressions are a powerful tool for pattern matching and string manipulation. Python’s `re`

library can be used to replace characters in a string following a certain pattern, in this case, zeros.

Here’s an example:

import re number = 1050 replaced_number = int(re.sub('0', '5', str(number))) print(replaced_number)

Output: `1555`

This one-liner uses the `re.sub()`

method from Python’s regular expression library to replace all zeros in a string representation of the number directly. It’s a compact and efficient method but understanding regular expressions can be challenging for new programmers.

## Summary/Discussion

**Method 1: String Conversion.**Simple and intuitive. Can be slow for very large numbers due to string manipulation overhead.**Method 2: Mathematical Manipulation.**Fast and doesn’t depend on string conversion. Less readable and could be complex for some users.**Method 3: List Comprehension and Join.**Pythonic and readable. It’s a middle ground between string and mathematical approaches.**Method 4: Recursion.**Elegant and divides the problem into subproblems. Not suitable for very large numbers due to stack overflow risks.**Method 5: Regular Expressions.**Compact one-liner approach. Requires understanding of regex patterns and might have performance considerations.