Tutorial: How to Use List sort() in Python

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Welcome to our tutorial on using the list sort() function in Python. Lists are a fundamental data structure in Python and often require sorting to make the data more organized and meaningful. In this article, we will provide an overview of the list sort() function and explain its uses and benefits. Additionally, we will discuss various techniques for sorting lists and provide examples of sorting in both alphabetical and numerical order. Let’s dive in and explore the world of list sorting techniques.

Understanding the List sort() Function

Now that we have introduced the list sort() function, let’s dive deeper into its inner workings. At its core, the list sort() function sorts the elements of a list in ascending order. However, it can also be customized to sort in descending order or based on other criteria.

How does the list sort() function work?

The list sort() function uses a default sorting algorithm called Timsort. This algorithm is efficient and fast, making it a popular choice for Python developers. Timsort works by first dividing the list into small sublists, sorting them individually, and then merging them to produce a fully sorted list.

It’s important to note that the list sort() function modifies the original list in place, meaning that the order of the elements in the list will be permanently changed.

Choosing the right algorithm for your needs

While Timsort is the default algorithm used by the list sort() function, Python also offers alternative sorting algorithms that can be used depending on your specific needs.

The sorted() function, for instance, uses the Merge Sort algorithm, which may be more suitable for larger lists. If you’re working with highly specialized data, such as text data that requires case-insensitive sorting, you may want to consider using the natsort package, which offers a natural sorting algorithm.

When selecting an algorithm, it’s important to consider factors such as the size of your list, the type of data you’re working with, and the desired outcome of your sorting operation.


By understanding the inner workings of the list sort() function and the various sorting algorithms available in Python, you can optimize your sorting operations to achieve the desired outcome efficiently and effectively. With this knowledge, you can choose the most appropriate sorting technique for your specific needs and improve the performance of your Python programs.

Sorting Lists in Ascending Order

Sorting a list in ascending order can be useful in a variety of applications. Fortunately, Python makes this task easy with the list sort() function. To use it, simply call the function on your list variable and the elements will be automatically sorted in ascending order.

Here’s an example:

numbers = [5, 3, 8, 2, 1]

This will output:

[1, 2, 3, 5, 8]

Notice that the function modifies the original list in place and returns None. If you want to keep the original list and create a sorted copy, you can use the sorted() function:

numbers = [5, 3, 8, 2, 1]
sorted_numbers = sorted(numbers)

This will output:

[5, 3, 8, 2, 1]
[1, 2, 3, 5, 8]

Keep in mind that the list sort() function can also be used to sort other data types, such as strings:

words = ['apple', 'banana', 'cherry', 'date', 'elderberry']

This will output:

['apple', 'banana', 'cherry', 'date', 'elderberry']

Sorting Numeric Lists with Different Data Types

When sorting a list with multiple data types, it’s important to pay attention to the order in which the elements are sorted. Python sorts strings in alphabetical order, while numeric values are sorted in ascending order. To ensure consistent sorting, you may need to convert your data types before sorting.

For example, let’s say you have a list of strings and integers:

mixed = ['5', 3, '8', 2, '1']

If you try to sort this list as is, you’ll run into an error:


This will produce the error message:

TypeError: '<' not supported between instances of 'int' and 'str'

To fix this, you can convert all the elements to the same data type before sorting:

mixed = ['5', 3, '8', 2, '1']
mixed = [int(i) if i.isdigit() else i for i in mixed]

This will output:

[2, 3, '1', '5', '8']

As you can see, the integers are sorted in ascending order while the strings are sorted in alphabetical order based on their ASCII values.

With these techniques in mind, you now have the tools to sort lists in ascending order using Python’s list sort() function.

Sorting Lists in Descending Order

Sorting lists in descending order is a common task when dealing with data. Luckily, Python also provides a simple method to sort lists in reverse alphabetical or numerical order using the list sort() function.

Reverse Order with list sort() Function

To sort a list in descending order, we can modify the list sort() function by adding the parameter reverse=True as shown in the following example:

fruits = ['apple', 'banana', 'cherry']

In this example, the output will be:

['cherry', 'banana', 'apple']

Sorting Lists with Different Data Types

When sorting lists in descending order with different data types, we may encounter some challenges. For instance, sorting a list containing both strings and numbers will result in a TypeError message.

To avoid this issue, we can use the sorted() function and define a custom key to sort the list. We can create a function that first checks the length of the input element and then defines the sorting key.

For example:

mixed_list = ['apple', 10, 'banana', 20, 'cherry', 30]
def custom_sort(elem):
    if isinstance(elem, str):
        return len(elem)
    return elem
mixed_list.sort(reverse=True, key=custom_sort)

The output will be:

[30, 20, 'cherry', 10, 'banana', 'apple']

By using the sorted() function and defining a custom sorting key, we can easily sort lists in descending order, even when dealing with different data types.


In conclusion, understanding the list sort() function in Python is essential for efficient data manipulation. We have discussed the various techniques for sorting lists, including sorting in ascending and descending order, as well as the different sorting algorithms used by Python.

Importance of List Sorting

Sorting lists can have a significant impact on the efficiency of a program, especially when dealing with large amounts of data. Being able to sort data in a specific order allows for easier and faster access to the desired information.

Further Exploration

For those interested in further exploring list sorting techniques, we recommend referring to the official Python documentation, as well as other reliable resources such as online tutorials or textbooks.

We hope that this article has provided a comprehensive introduction to list sorting in Python and has been informative for readers.

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