# 5 Best Ways to Sort Elements of an Array in Ascending Order in Python

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π‘ Problem Formulation: This article aims to guide programmers on how to sort the elements of an array (or a list in Python terms) in ascending order. For instance, given the input array `[3, 1, 4, 1, 5]`, the desired output after sorting is `[1, 1, 3, 4, 5]`.

## Method 1: The Built-in `sorted()` Function

The built-in `sorted()` function in Python is a simple and efficient method to sort an array. It returns a new sorted list from the elements of any iterable, not changing the original iterable. It is stable, and can take a key parameter for custom sorting.

Here’s an example:

```array = [3, 1, 4, 1, 5]
sorted_array = sorted(array)
print(sorted_array)```

Output: `[1, 1, 3, 4, 5]`

This snippet shows the usage of `sorted()` which takes ‘array’ as an argument and returns a new list ‘sorted_array’ containing all elements from ‘array’ in ascending order.

## Method 2: The List `sort()` Method

Unlike `sorted()`, the list `sort()` method sorts the list in-place, meaning it modifies the original list. It is also stable and allows custom sorting using a key function.

Here’s an example:

```array = [3, 1, 4, 1, 5]
array.sort()
print(array)```

Output: `[1, 1, 3, 4, 5]`

The above code sorts the ‘array’ in-place using the `sort()` method which mutates the list and sorts it in ascending order.

## Method 3: Using a Loop and Swap

This traditional method uses nested loops to go through the list elements and swap them if they are out of order. Itβs a direct implementation of the bubble sort algorithm.

Here’s an example:

```array = [3, 1, 4, 1, 5]
for i in range(len(array)):
for j in range(i + 1, len(array)):
if array[i] > array[j]:
array[i], array[j] = array[j], array[i]
print(array)```

Output: `[1, 1, 3, 4, 5]`

In this code snippet, we’re manually implementing the sorting logic. We iterate over the list with two nested loops and swap elements if they are in the wrong order until the entire list is sorted.

## Method 4: Using List Comprehensions and the `min()` Function

List comprehensions coupled with the `min()` function can be used to repeatedly find and remove the smallest element from the list, appending it to a new list until the original list is empty.

Here’s an example:

```original = [3, 1, 4, 1, 5]
sorted_array = []

while original:
minimum = min(original)
sorted_array.append(minimum)
original.remove(minimum)

print(sorted_array)```

Output: `[1, 1, 3, 4, 5]`

This code continuously finds the smallest element in ‘original’, appends it to ‘sorted_array’, and removes it from ‘original’ until all elements are transferred in ascending order.

## Bonus One-Liner Method 5: Using `lambda` and `reduce()`

A more functional programming approach using `lambda` and `reduce()` to perform a custom sorting algorithm in a more condensed form. Not suitable for large arrays or production, but fun to explore.

Here’s an example:

```from functools import reduce
array = [3, 1, 4, 1, 5]
sorted_array = reduce(lambda acc, x: acc + [x] if x >= acc[-1] else [x] + acc, array, [float('-inf')])
print(sorted_array[1:])```

Output: `[1, 1, 3, 4, 5]`

This one-liner uses `reduce()` to build a sorted array by inserting each number either at the end if it’s larger than the last element, or at the beginning if not. The initial value is a list containing negative infinity to handle the first insertion.

## Summary/Discussion

• Method 1: Built-in `sorted()` Function. Simplest and recommended for most cases. Does not modify the original list. It is not the most performant for very large lists.
• Method 2: List `sort()` Method. Best for when the original list can be altered. Slightly more efficient than sorted() because it doesn’t create a copy of the list.
• Method 3: Using a Loop and Swap. Educative implementation, mimicking classic sorting algorithms. It is less efficient than Python’s built-in methods.
• Method 4: Using List Comprehensions and `min()`. Creative use of list comprehensions and min function. Inefficient for large lists due to O(n^2) complexity.
• Bonus Method 5: Using `lambda` and `reduce()`. One-liner that provides a functional programming twist. It can be hard to read and inefficient for sorting.