**π‘ Problem Formulation:** Converting a string to a matrix with a specific number of characters per row is a common task for text processing or displaying data in a structured format. Here, we aim to transform an input string into a matrix where each row contains exactly *k* characters, ensuring the last row is filled correspondingly. For example, given the string “PythonIsAmazing” and *k* equal to 4, the desired output is a matrix with the rows [‘Pyth’, ‘onIs’, ‘Amaz’, ‘ing’].

## Method 1: Using Loops

The loop method involves iterating over the string with a step of size *k* and slicing the string into substrings. This is a straightforward approach and gives a clear picture of how the string is being divided into rows for the matrix.

Here’s an example:

def string_to_matrix(s, k): return [s[i:i+k] for i in range(0, len(s), k)] # Example usage matrix = string_to_matrix('PythonIsAmazing', 4) print(matrix)

Output:

['Pyth', 'onIs', 'Amaz', 'ing']

This code snippet defines a function `string_to_matrix`

that takes a string `s`

and an integer `k`

as arguments. It uses a list comprehension to iterate through the string, slicing it into chunks of size `k`

. The resulting list of strings represents the matrix rows.

## Method 2: Using the `textwrap`

Module

The `textwrap`

module provides a convenient way to split a string into lines of specific width, which is essentially what you’re doing when you create a matrix with *k* characters per row. It’s part of Python’s standard library, which means no extra installation is necessary.

Here’s an example:

import textwrap def string_to_matrix(s, k): return textwrap.wrap(s, k) # Example usage matrix = string_to_matrix('PythonIsAmazing', 4) print(matrix)

Output:

['Pyth', 'onIs', 'Amaz', 'ing']

This code snippet utilizes the `textwrap.wrap()`

function to achieve the required task. The function automatically splits the string `s`

into a list of lines, each having a maximum width of `k`

characters, effectively giving us our matrix rows.

## Method 3: Using Regular Expressions

The regular expressions method uses the `re`

module to find all substrings of length *k*. This is a powerful technique that can be adapted for more complex string processing tasks.

Here’s an example:

import re def string_to_matrix(s, k): return re.findall('.{{1,{}}}'.format(k), s) # Example usage matrix = string_to_matrix('PythonIsAmazing', 4) print(matrix)

Output:

['Pyth', 'onIs', 'Amaz', 'ing']

In this code snippet, we define a function `string_to_matrix`

that uses the `re.findall()`

function from the `re`

module. The pattern ‘.{{1,{}}}’ is a dynamic regular expression where `{}`

is formatted to be `k`

. It matches any string of length up to `k`

, thus dividing the string into the desired matrix.

## Method 4: Using NumPy

For those dealing with scientific computing, NumPy’s array manipulation capabilities provide a robust way to convert a string to a matrix. This method is especially useful when the resulting matrix will be used for further numerical computations.

Here’s an example:

import numpy as np def string_to_matrix(s, k): arr = np.array(list(s)) return arr.reshape(-1, k) # Example usage matrix = string_to_matrix('PythonIsAmazing', 4) print(matrix)

Output:

[['P' 'y' 't' 'h'] ['o' 'n' 'I' 's'] ['A' 'm' 'a' 'z'] ['i' 'n' 'g' ' ']]

This snippet uses NumPy’s function `reshape()`

to transform a flat array of characters into a 2D array with `k`

characters in each sub-array. The `-1`

passed to the reshape function asks NumPy to infer the correct number of rows for the given column size.

## Bonus One-Liner Method 5: Using a Generator Expression

The generator expression is a concise, memory-efficient way to perform the task in a lazy evaluation context. It should be used when you want to generate rows on-the-fly, one at a time, without storing the entire conversion in memory.

Here’s an example:

def string_to_matrix(s, k): return (s[i:i+k] for i in range(0, len(s), k)) # Example usage matrix_generator = string_to_matrix('PythonIsAmazing', 4) for row in matrix_generator: print(row)

Output:

Pyth onIs Amaz ing

This efficient one-liner defines a generator expression that yields substrings of `s`

with a length of `k`

. The matrix is not stored in memory entirely at any point, making this solution very memory efficient, especially for large strings.

## Summary/Discussion

**Method 1: Using Loops.**Simple and straightforward. Loops provide a clear understanding of the process. May not be the most Pythonic or fastest approach for large datasets.**Method 2: Using the**Utilizes built-in Python libraries, offering a clean, readable syntax. May not offer the same level of control or customization as other methods.`textwrap`

Module.**Method 3: Using Regular Expressions.**Highly versatile and can be adapted for more complex patterns. However, it might be overkill for simple tasks and can be less readable or maintainable.**Method 4: Using NumPy.**Ideal for numerical computations and matrix manipulations. Requires NumPy installation and can be inefficient if used solely for the purpose of string to matrix conversion.**Method 5: Using a Generator Expression.**Memory efficient and suitable for large datasets or streaming data. However, it lacks the simplicity of direct access to all matrix rows at once.