π‘ **Problem Formulation**: Working with datasets often involves sorting lists, and it can become tricky when a list contains strings with numbers.

For instance, you might have a list like `["item2", "item12", "item1"]`

and want it sorted so that the numerical part of the strings dictates the order, resulting in `["item1", "item2", "item12"]`

.

How can you achieve this in Python, considering the default sort would treat the numbers lexicographically, yielding an unintuitive `["item1", "item12", "item2"]`

?

Here are five methods to solve this sorting problem.

## Method 1: Using a Custom Key Function

In Python, the `sort()`

method of lists accepts a `key`

argument that allows you to specify a function to be called on each list item before making comparisons. The `key`

function can be crafted to extract numerical values from strings and use them for sorting.

**Here’s an example:**

import re def numerical_key(s): return int(re.search(r'\d+', s).group()) items = ["apple10", "apple2", "banana1"] items.sort(key=numerical_key) print(items)

Output:

`['banana1', 'apple2', 'apple10']`

This code defines a `numerical_key`

function that uses the `re`

module to find the first sequence of digits in each string and converts it to an integer. When passed as the `key`

argument to `sort()`

, it ensures the numbers within the strings are compared numerically, not lexicographically.

## Method 2: Using the `natsort`

Library

`natsort`

is a third-party library designed to sort lists “naturally,” handling the insertion of numbers within strings seamlessly. It’s especially useful for lists that cannot be easily handled with custom key functions.

**Here’s an example:**

from natsort import natsorted items = ["version_1.9.1", "version_1.10.0", "version_1.9.2"] sorted_items = natsorted(items) print(sorted_items)

By simply calling `natsorted()`

from the `natsort`

library, our list is sorted with the numerical values interpreted correctly, keeping the versions in the anticipated incremental order.

## Method 3: Parsing Numbers Manually π NO LIBRARY!

If you want to avoid external dependencies and prefer handling number parsing manually, you can create a function that splits strings into segments of numbers and non-numbers, then sorts by converting numeric segments to integers.

**Here’s an example:**

def parse_num(s): return [int(text) if text.isdigit() else text.lower() for text in re.split(r'(\d+)', s)] items = ["x10y", "x2y", "x1y"] items.sort(key=parse_num) print(items)

The `parse_num`

function divides each string into a list of numbers and text, converting recognizable numbers into integers. This list can then be used as a sorting key.

## Method 4: Using functools.cmp_to_key

The `functools`

module provides a `cmp_to_key`

utility that converts an old-style comparison function (one that returns -1, 0, or 1) to a key function. This is useful when upgrading legacy code or when comparison logic is complex.

**Here’s an example:**

from functools import cmp_to_key import re def compare_items(a, b): a_num = int(re.search(r'\d+', a).group()) b_num = int(re.search(r'\d+', b).group()) return (a_num > b_num) - (a_num < b_num) items = ["item202", "item20", "item3"] items.sort(key=cmp_to_key(compare_items)) print(items)

By defining a comparison function, `compare_items`

, which extracts numbers and compares them directly, you can use `cmp_to_key`

to transform this function into a key function for sorting.

Also check out my article on this:

π Python List Sort Key

## Bonus One-Liner Method 5: Using List Comprehension with sort()

Sometimes, the simplest methods are the most satisfying. If you know that every string in your list starts with non-digits followed by digits, a one-liner can do the trick with `sort()`

.

**Here’s an example:**

items = ["stage3", "stage11", "stage1"] items.sort(key=lambda x: (x.rstrip('0123456789'), int(re.search(r'\d+$', x).group()))) print(items)

The `lambda`

function strips away trailing digits and isolates the numeric suffix of each string. The `sort()`

method then sorts items first by their non-numeric prefix and then by the numeric value of the suffix.

## Summary/Discussion

**Method 1**uses a custom key function; it’s built-in and efficient for simple cases.**Method 2**leverages`natsort`

, an external library; very powerful and handles complex cases but requires an external dependency.**Method 3**requires manual parsing; it’s flexible for diverse string structures but is more complex to implement and maintain.**Method 4**takes advantage of`functools.cmp_to_key`

; useful for adapting comparison functions but may be overkill for simpler cases.**Method 5**is a compact one-liner using list comprehension; it’s clean and succinct but might not be as readable for those unfamiliar with lambdas or regex.

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